CPTECINPE - Cachoeira Paulista, Brazil

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					               LBA-HydroNET
               Workshop Report

                   DECEMBER 4 – 6, 2000


      CPTEC/INPE - Cachoeira Paulista, Brazil




                                     Hosted by:

         Centro de Previsao de Tempo e Estudos Climaticos (CPTEC)
                        University of New Hampshire (UNH)


                               With support from:

               National Aeronautics and Space Administration (NASA)
    United Nations Educational, Scientific and Cultural Organization (UNESCO)
Water Center for the Humid Tropics of Latin America and the Caribbean (CATHALAC)
               International Geosphere-Biosphere Programme (IGBP)
                               LBA-HydroNET Workshop Report

                                            Table of Contents


Agenda     .   .   .   .   .    .   .   .     .   .   .   .   .   .   .   .   .   .   .   .   .   .    1

LBA-HydroNET Base Map – Hydrometeorological Station Holdings .                        .   .   .   .    5

Navigation Map from LBA-HydroNET                  .   .   .   .   .   .   .   .   .   .   .   .   .    6

Example of WWWeb-based Data Entry                 .   .   .   .   .   .   .   .   .   .   .   .   .    6

Table 1: LBA HydroNET version 1.0 Data Table                  .   .   .   .   .   .   .   .   .   .    7

Workshop Meeting Notes . . . . . . . . . . . . .                                      .   .   .   .   10
  Plenary Presentations and Discussion . . . . . . . . .                              .   .   .   .   10
     Introductions and General Framework Presentations . . . . .                      .   .   .   .   10
     Listing of LBA Hydrometeorology Investigations . . . . .                         .   .   .   .   14
     Summaries of Individual Participant Presentations . . . . .                      .   .   .   .   15
  Demonstrations, Hands-on Activities, and Working Group Sessions                     .   .   .   .   20
     Beija-flor Demonstration . . . . . . . . . . . .                                 .   .   .   .   20
     EOS-Webster Demonstration . . . . . . . . . . .                                  .   .   .   .   21
     LBA-HydroNET System Demonstration . . . . . . . .                                .   .   .   .   21
  Table 2: Discussion: Working Group Designations . . . . .                           .   .   .   .   22
  Table 3: Guidelines for Break-Out-Data Working Group . . .                          .   .   .   .   22
  Plenary Sessions with Working Group Key Findings Reports . .                        .   .   .   .   24
     Coupled Models Group (linking water, carbon, nutrients) . . .                    .   .   .   .   24
     Water Balance Closure Group . . . . . . . . . .                                  .   .   .   .   26
     Precipitation Group . . . . . . . . . . . . .                                    .   .   .   .   27
     Operational Hydrometeorology Group . . . . . . . .                               .   .   .   .   28
  Concluding Discussion . . . . . . . . . . . . .                                     .   .   .   .   30

Participant List . .       .    .   .   .     .   .   .   .   .   .   .   .   .   .   .   .   .   .   31
Participant Abstracts      .    .   .   .     .   .   .   .   .   .   .   .   .   .   .   .   .   .   34

   Lelys Bravo de Guenni        .   .   .     .   .   .   .   .   .   .   .   .   .   .   .   .   .   35
   Applications of downscaling and disaggregation techniques on studies of the variability of
   the components of the water cycle. Case study: The LBA domain

   Manoel Cardoso .        .    .   .   .     .   .   .   .   .   .   .   .   .   .   .   .   .   .   36
   Importance of the cooperation between LBA Ecology and LBA Hydrology for predictions of
   fire behavior

   Sin Chan Chou, Clemente A.S. Tanajura, Yongkang Xue, and Carlos Nobre                  .   .   .   37
   Simulations with the coupled Eta/SSiB model over South America
                                 Table of Contents (Continued)


Cassiano D’Almeida, Charles Vörösmarty, Balazs Fekete, Lelys Bravo de Guenni, Jose
Marengo, and Cort Willmott . . . . . . . . . . . . . . . . 38
Water budget closure system for South America and the LBA domain

Balazs Fekete, Charles Vörösmarty, Cassiano D’Almeida .                 .   .   .   .   .   .   .   39
LBA-HydroNET data archive: Development and application

George C. Hurtt     .   .   .   .   .   .    .   .      .   .   .   .   .   .   .   .   .   .   .   40
Linking ecological and hydrological models of the Amazon

John M. Melack .        .   .   .   .   .    .   .      .   .   .   .   .   .   .   .   .   .   .   41
Multi-scale analysis of inundation with microwave and optical remote sensing in the Amazon
Basin: Applications to biogeochemical measurements and modeling

Leandro Della Vedova de Oliveira Pinto .         .      .   .   .   .   .   .   .   .   .   .   .   44
Turbulent fluxes of energy over a tropical forest in the Amazonia

Juan Julio Ordonez Galvez       .   .   .    .   .      .   .   .   .   .   .   .   .   .   .   .   45
Cuenca Amazonica Peruana: Red hidrometeorologica, analyses de informacion y trabajos
de investigacion

Michael Routhier and Annette Schloss         .   .      .   .   .   .   .   .   .   .   .   .   .   47
Earth Science Information Partners Project

Eric A. Smith .     .   .   .   .   .   .    .   .      .   .   .   .   .   .   .   .   .   .   .   48
Controls on large-scale Amazonian wet and dry season carbon flux variability by
biophysical, surface meteorological, and cloudiness factors

Brian Staab     .   .   .   .   .   .   .    .   .      .   .   .   .   .   .   .   .   .   .   .   49
Terrestrial water balance of the Amazon and a model for its interpretation

Gilberto A. Vicente     .   .   .   .   .    .   .      .   .   .   .   .   .   .   .   .   .   .   50
Real time satellite rainfall estimation over Amazonia

Charles J. Vörösmarty.      .   .   .   .    .   .      .   .   .   .   .   .   .   .   .   .   .   51
University of New Hampshire Water Systems Analysis Group - Activities and support to LBA

Ellen White     .   .   .   .   .   .   .    .   .      .   .   .   .   .   .   .   .   .   .   .   53
Overview of LBA-Hydrometeorology
                           LBA-HydroNET Workshop
                    CPTEC/INPE - Cachoeira Paulista - Brazil


                                AGENDA



MONDAY - DECEMBER 4, 2000     (CPTEC AUDITORIUM)


 9:00 – 9:30       Welcoming Remarks (Nobre/Donoso)
 9:30 – 9:50       Introduction and Logistics (Knapp/White)
 9:50 – 10:20      Scope of Workshop (Vörösmarty/Marengo)
10:20 – 10:30      LBA-Ecology (Hurtt)


10:30 – 10:50      COFFEE BREAK


10:50 – 12:30      Individual Presentations (5-10 minutes each)

                       -    Jose Cortez Medinacelli (SENAMHI)
                       -    Marco Antonio Davila (IDEAM)
                       -    Jose Diaz (MARN)
                       -    Juan Julio Ordonez Galvez (SENAMHI)
                       -    Mauro Leonardo Rosas (INAMHI)
                       -    Gerard Cocheao (ANEEL)
                       -    Valdemar Santos Guimaraes (ANEEL)
                       -    Eurides de Oliveira (ANEEL)
                       -    Leandro Della Vedova de Oliveira Pinto (USP)
                       -    Azeneth Eufrausino Schuler (CENA/USP)


12:30 – 2:00       LUNCH


 2:00 - 3:30       Individual Presentations (5-10 minutes each)

                       -    Jose Marengo (CPTEC/INPE)
                       -    J. Tomasella (CPTEC/INPE)
                       -    Sin Chan Chou (CPTEC/INPE)
                       -    Merilyn Gentry (ORNL/LBA-Ecology)
                       -    Eurides de Oliveira (ANEEL)


 3:30 - 3:50       COFFEE BREAK




                                           1
MONDAY – DECEMBER 4, 2000 (continued)


3:50 - 5:30           Individual Presentations (5-10 minutes each)

                          -   Charles Vorosmarty (UNH)
                          -   Lelys Bravo de Guenni (UNH)
                          -   Manoel Cardoso (UNH)
                          -   Cassiano D’Almeida (UNH)
                          -   Balazs Fekete (UNH)
                          -   George Hurtt (UNH)
                          -   Eric Smith (FSU)
                          -   Brian Staab (UCSB)
                          -   Gilberto Vicente (QSS Group)
                          -   Maarten Waterloo (Alterra)


5:30 - 6:00           Open discussion


6:00                  ADJOURN FOR DAY




                                          2
TUESDAY - DECEMBER 5, 2000      (CPTEC AUDITORIUM)


 9:00 - 9:10        Day 2 Welcome (Vörösmarty)
 9:10 – 9:50        Beija-Flor Demonstration (Gentry)
 9:50 – 10:30       EOS Webster Demonstration (Schloss/Routhier)


10:30 – 11:00       COFFEE BREAK

                    (Move to CPTEC COMPUTER LAB)

11:00 – 12:30       LBA-HydroNET Demonstration and Application (Fekete/D’Almeida)


12:30 – 2:00        LUNCH


 2:00 - 3:30        Hands-on use of LBA-HydroNET system


 4:00 - 4:15        COFFEE BREAK

 4:15 - 6:00        General Discussion and First Impressions of LBA-HydroNET:

                       -     Functionality
                       -     Problems
                       -     Suggestions for improvements
                       -     New data sets and applications

                    Data sets from each participant uploaded to the system, and Working Groups
                    determined.


 6:00               ADJOURN FOR DAY




                                            3
WEDNESDAY - DECEMBER 6, 2000      (CPTEC AUDITORIUM)


 9:00 – 9:30       Plenary Session
                       - Choose Applications and Issues for Breakout Groups



 9:30 – 10:00      Breakout discussions and participant input on the current and future design of
                   LBA-HydroNET.

                   (Choose Chair and Rapporteur from each group; to be members of Steering
                   Committee)

                   Please discuss following issues with respect to R-HydroNET:
                       - Functionality
                       - Problems
                       - Suggestions for improvements
                       - New data sets and applications

10:45 – 11:00      COFFEE BREAK


11:00 – 1:00       Plenary Session
                       - Rapporteur reports (10-minutes each)
                       - General discussion on reports
                       - Coordination with other LBA activities
                       - Next meeting(s) and workshop(s)
                       - Other issues


  1:00             ADJOURN




                                          4
LBA-HydroNET Base Map – Hydrometeorological Station Holdings




                             5
Navigation Map from LBA-HydroNET




Example of WWWeb-based Data Entry




                6
                 Table 1: Available Data Sets for Inclusion in LBA-HydroNET
                         with Spatial Coverage over Full LBA Domain

                                           (Data Availability as of March 2001)



                                                             Time Series - Station Data

                                             Original                 Series        Data     Spatial     Time      Available                                 Current
Number       Data Set         Reference                      Type                                                                        Location
                                            Resolution                Span         Source    Extent      Step       Format                                  Availability
         GHCN* Air                         Point Data      Station
                            Vose et al,                              Varying                                                      /solo/data1/cd/
  1      Temperature                       N=342           Time                Raingage     Global      Monthly Ascii - ArcInfo                                YES
                            1992                                     Years                                                        GHCN
         Data                              stations        Series
         GHCN                              Point Data      Station
                            Vose et al,                              Varying                                                      /solo/data1/cd/
  2      Precipitation                     N=1392          Time                Raingage     Global      Monthly Ascii - ArcInfo                                YES
                            1992                                     Years                                                        GHCN
         Data                              stations        Series
         WMO*                              Point Data      Station
                                                                     Varying                                                      /solo/data1/cd/
  3      Precipitation      Wernsted, F.   N=6433          Time                Raingage     Global      Monthly Ascii - ArcInfo                                YES
                                                                     Years                                                        WMO
         Data                              stations        Series
                            Dunne, T.
         ANEEL*                            Point Data      Station
                            (EOS-                                    Varying                Amazon                                /solo/data1/cd/
  4      Precipitation                     N=1300          Time                Raingage                 Monthly Ascii - ArcInfo                                YES
                            Amazon                                   Years                  Basin                                 ANEEL
         Data                              stations        Series
                            Project)
                                                           Station
         UNESCO*            Vorosmarty et Point Data                 Varying   Discharge    South                                 /solo/data1/cd/
  5                                                        Time                                         Monthly Ascii - ArcInfo                                YES
         Discharge Data     al, 1998b     N=85 stations              Years     Gage         America                               UNESCO
                                                           Series
                                           Point Data      Station
         INA* Discharge                                              Varying   Discharge                                          /solo/data1/cd/
  6                                        N=301           Time                             Argentina   Monthly Ascii - ArcInfo                                YES
         Data                                                        Years     Gage                                               INA
                                           stations        Series
                                                                                                                                  /solo/data1/cd/bolivia/
                                                           Station                                              Microsoft
         SENAMHI*                          Point Data                Varying   Discharge                                          Hidrologia/
  7                                                        Time                             Bolivia     Monthly Excel                                           NO
         Discharge Data                    N=18 stations             Years     Gage                                               Caudales Medios
                                                           Series                                               spreadsheet
                                                                                                                                  Mensuales.XLS
                                                           Station                                              Microsoft         /solo/data1/cd/bolivia/
         SENAMHI*                          Point Data                Varying   Discharge
  8                                                        Time                             Bolivia     Monthly Excel             Hidrologia/                   NO
         River Stage Data                  N=18 stations             Years     Gage
                                                           Series                                               spreadsheet       Alturas de Rio.XLS
         SENAMHI                                           Station                                              Microsoft         /solo/data1/cd/bolivia/
                                           Point Data                Varying
  9      Precipitation                                     Time                Raingage     Bolivia     Monthly Excel             Meteorologia_II               NO
                                           N=24 stations             Years
         Data                                              Series                                               spreadsheet       Precipitacion.xls
                                                                                                                                  /solo/data1/cd/bolivia/
                                                           Station                                              Microsoft
         SENAMHI Air                       Point Data                Varying                                                      Meteorologia_II
  10                                                       Time                Raingage     Bolivia     Monthly Excel                                           NO
         Pressure Data                     N=23 stations             Years                                                        Presion Media del
                                                           Series                                               spreadsheet
                                                                                                                                  Aire.XLS
                                                                                                                                  /solo/data1/cd/bolivia/
                                                                                                                                  Meteorologia_I
                                                                                                                                  Temperatura Media
                                                                                                                                  Ambiente.xls
         SENAMHI Air                                       Station                                              Microsoft
                                           Point Data                Varying                                                      and Meteorologia_II
  11     Temperature                                       Time                Raingage     Bolivia     Monthly Excel                                           NO
                                           N=24 stations             Years                                                        Temperatura Minima
         Data                                              Series                                               spreadsheet
                                                                                                                                  Media.xls
                                                                                                                                  and Meteorologia_II
                                                                                                                                  Temperatura Maxima
                                                                                                                                  Media.xls
         SENAMHI                                           Station                                              Microsoft         /solo/data1/cd/bolivia/
                                           Point Data                Varying
  12     Relative                                          Time                Raingage     Bolivia     Monthly Excel             Meteorologia_I                NO
                                           N=23 stations             Years
         Humidity Data                                     Series                                               spreadsheet       Humedad Relativa.XLS




                                                                               7
                                   Table 1: Available Data Sets for Inclusion in LBA-HydroNET (continued)




                                                                  Time Series - Gridded Data

                                                     Original                    Series                      Spatial    Time     Available                                  Current
Number      Data Set             Reference                           Type                    Data Source                                              Location
                                                    Resolution                   Span                        Extent     Step      Format                                   Availability
                                                                                                                                              /net/nfs/solo/data1/
         GSFC GOES-8                                2.28 arc
                                                               Gridded Time 4/98-                           South                             cd/goes/
  13     IR Auto-    Vicente et al, 1998            min x 2.16                             Infrared                 Daily        GrADS*                                        NO
                                                               Series       present                         America                           1998
         Estimator                                  arc min
                                                                                                                                              1999
         NASA/NASDA                                                                                                              Hierachical
         TRMM*         /daac.gsfc.nasa.gov/         0.50 x 0.50   Gridded Time             Microwave                             Data        /net/nfs/solo/data1/cd/
  14                                                                           2/98-5/00                   Tropics     Daily                                                   NO
         Precipitation CAMPAIGN_DOCS/               0.10 x 0.10   Series                   Radar/Microwave                       Format      TRMM
         Data                                                                                                                    (HDF)
                                                                               1/99-2/99;
         ETA/CPTEC                                                Gridded Time                              South                             /solo/data1/cd/eta/
  15                                                0.40 x 0.40                9/00-      GCM outputs               Daily        GrADS                                         NO
         Outputs                                                  Series                                    America                           /solo/data1/cd/eta/010303
                                                                               present
         East Anglia
                                                                  Gridded Time                              South           GHAAS*            /balazs/projects/lba/
  16     Precipitation   New et al, 1999            0.50 x 0.50                1960/90     Raingage                 Monthly                                                   YES
                                                                  Series                                    America         RiverGIS          RGIS/Precip
         Data
         East Anglia
                                                                  Gridded Time                              South           GHAAS             /balazs/projects/lba/
  17     Vapor Pressure New et al, 1999             0.50 x 0.50                1960/90     Raingage                 Monthly                                                   YES
                                                                  Series                                    America         RiverGIS          RGIS/VaporPressure
         Data
         East Anglia Air
                                                                  Gridded Time                              South           GHAAS             /balazs/projects/lba/
  18     Temperature     New et al, 1999            0.50 x 0.50                1960/90     Raingage                 Monthly                                                   YES
                                                                  Series                                    America         RiverGIS          RGIS/AirTemp
         Data
         East Anglia
                                                                  Gridded Time                              South           GHAAS             /balazs/projects/lba/
  19     Cloud Cover     New et al, 1999            0.50 x 0.50                1960-90     Raingage                 Monthly                                                   YES
                                                                  Series                                    America         RiverGIS          RGIS/CloudCover
         Data
         GPCC*           GPCC, 1992 & 1993;
                                                                  Gridded Time                                                   GHAAS        solo/data3/localdb20/grid/
  20     Precipitation   Rudolph, 1993            1.00 x 1.00                  1986-99     Raingage/Infrared Global    Monthly                                                YES
                                                                  Series                                                         RiverGIS     precip/global/RGIS
         Data            www.dwd.de/research/gpcc
         GPCP*
                         WMO/ICSU, 1990;                          Gridded Time                                                   GHAAS        solo/data3/localdb20/grid/
  21     Precipitation                              1.00 x 1.00                1986-99     Raingage/Infrared Global    Monthly                                                YES
                         Janowiak and Arkin, 1991                 Series                                                         RiverGIS     precip/global/RGIS
         Data
         NCEP/NCAR                                                Gridded Time                                                   GHAAS        solo/data3/localdb20/grid/
  22                     Kalnay et al, 1996         1.90 x 1.90                1958-97     GCM outputs      Global     Monthly                                                YES
         Reanalysis                                               Series                                                         RiverGIS     precip/global/RGIS

                                                    12                                                                     Microsoft
         Wetland                                                  Gridded Time                              Amazon                     /solo/data1/cd/
  23                     Sippel et al, 1998         Mainstem                   12/78-8/87 Microwave                Monthly Excel                                               NO
         Flooding Data                                            Series                                    Basin                      flood/
                                                    Reaches                                                                spreadsheet



                                                                   Climatology - Station Data

                                                     Original                    Series                      Spatial    Time     Available                                  Current
Number      Data Set             Reference                           Type                    Data Source                                              Location
                                                    Resolution                   Span                        Extent     Step      Format                                   Availability
         Legates &
                                                    Point Data
         Willmott                                              Station         Varying                      South           Ascii -           /solo/data1/cd/
  24                     Legates & Willmott, 1990   N=1702                                 Raingage                 Monthly                                                   YES
         Precipitation                                         Climatology     Years                        America         ArcInfo           LEGATES_WILLMOTT/
                                                    stations
         Data
         Legates &
                                                    Point Data
         Willmott Air                                          Station         Varying                      South           Ascii -           /solo/data1/cd/
  25                     Legates & Willmott, 1990   N=1210                                 Raingage                 Monthly                                                   YES
         Temperature                                           Climatology     Years                        America         ArcInfo           LEGATES_WILLMOTT/
                                                    stations
         Data




                                                                                      8
                                Table 1: Available Data Sets for Inclusion in LBA-HydroNET (continued)




                                                               Climatology - Gridded Data

                                                                                                                                                                 Current
                                                       Original                  Series                     Spatial    Time   Available
Number       Data Set              Reference                          Type                  Data Source                                           Location       Availabil
                                                      Resolution                 Span                       Extent     Step    Format
                                                                                                                                                                   ity
         Cramer &
                                                                    Gridded                                                               /solo/data1/cd/
  26     Leemans Precip.   Leemans & Cramer, 1991     0.50 x 0.50               1930-60   Raingage         Global     Monthly Ascii                                YES
                                                                    Climatology                                                           craleegrid/
         (v2.1)
         Cramer &
                                                                    Gridded                                                               /solo/data1/cd/
  27     Leemans Air       Leemans & Cramer, 1991     0.50 x 0.50               1930-60   Raingage         Global     Monthly Ascii>                               YES
                                                                    Climatology                                                           craleegrid/
         Temp. (v2.1)
         Willmott,
                           Willmott & Matsuura,                     Gridded                                                               /solo/data1/cd/
  28     Matsuura &                                   0.50 x 0.50               1950-96   Raingage         Global     Monthly Ascii                                NO
                           1995                                     Climatology                                                           willmats/
         Legates (v2.01)
         Willmott &                                                 Gridded                                South                          /solo/data1/cd/
  29                       Willmott & Webber, 1998    0.50 x 0.50               1960/90   Raingage                 Monthly GrADS                                   YES
         Webber (v1.02)                                             Climatology                            America                        willwebbgrid/
         East Anglia                                                                                               Annual
                                                                    Gridded                                South           GHAAS /balazs/projects/lba/
  30     Precipitation     New et al, 1999            0.50 x 0.50               1960/90   Raingage                 -                                               YES
                                                                    Climatology                            America         RiverGIS RGIS/Precip
         Data                                                                                                      Monthly
         East Anglia                                                                                               Annual
                                                                    Gridded                                South           GHAAS /balazs/projects/lba/
  31     Vapor Pressure    New et al, 1999            0.50 x 0.50               1960/90   Raingage                 -                                               YES
                                                                    Climatology                            America         RiverGIS RGIS/VaporPressure
         Data                                                                                                      Monthly
         East Anglia Air                                                                                           Annual
                                                                    Gridded                                South           GHAAS /balazs/projects/lba/
  32     Temperature       New et al, 1999            0.50 x 0.50               1960/90   Raingage                 -                                               YES
                                                                    Climatology                            America         RiverGIS RGIS/AirTemp
         Data                                                                                                      Monthly
         East Anglia                                                                                               Annual
                                                                    Gridded                                South           GHAAS /balazs/projects/lba/
  33     Cloud Cover       New et al, 1999            0.50 x 0.50               1960/90   Raingage                 -                                               YES
                                                                    Climatology                            America         RiverGIS RGIS/CloudCover
         Data                                                                                                      Monthly
         GPCC              GPCC, 1992 & 1993;                                                                         Annual
                                                                    Gridded                                                   GHAAS solo/data3/localdb20/grid/
  34     Precipitation     Rudolph, 1993            1.00 x 1.00                 1986-99   Raingage/Infrared Global    -                                            YES
                                                                    Climatology                                               RiverGIS precip/global/RGIS
         Data              www.dwd.de/research/gpcc                                                                   Monthly
         GPCP                                                                                                         Annual
                           WMO/ICSU, 1990;                          Gridded                                                   GHAAS solo/data3/localdb20/grid/
  35     Precipitation                                1.00 x 1.00               1986-99   Raingage/Infrared Global    -                                            YES
                           Janowiak and Arkin, 1991                 Climatology                                               RiverGIS precip/global/RGIS
         Data                                                                                                         Monthly



                                                                    Climatology - Static Data

                                                                                                                                                                 Current
                                                       Original                  Series                     Spatial    Time   Available
Number       Data Set              Reference                          Type                  Data Source                                           Location       Availabil
                                                      Resolution                 Span                       Extent     Step    Format
                                                                                                                                                                   ity
         ETOPO5                                       5 arc min x                                                             Ascii -     /solo/data1/cd/
  36                       NOAA, 1988                                 Static       -                       Global        -                                         YES
         Elevation Data                               5 arc min                                                               ArcInfo     elevation/
                                                      28.8 arc
         GTOPO30                                                                                                              Ascii -     /solo/data1/cd/
  37                       USGS, 1996                 sec x 28.8      Static       -                       Global        -                                         NO
         Elevation Data                                                                                                       ArcInfo     elevation/
                                                      arc sec
                                                      30 arc sec
         EROS U.S.G.S.     UNESCO(1987) through                                                                               Ascii -     /solo/data1/cd/
  38                                                  x 30 arc        Static       -                       Brazil        -                                         YES
         Soil Data         GRID                                                                                               ArcInfo     soil/
                                                      sec
                                                      30 arc sec
         IGBP-DIS Land                                                                                                        Ascii -     /solo/data1/cd/
  39                       Belward, 1996              x 30 arc        Static       -                       Global        -                                         YES
         Cover Data                                                                                                           ArcInfo     land_cover/
                                                      sec
         Simulated
                                                                                                           South              GHAAS /balazs/projects/lba/
  40     Topological    Fekete et al, 2001            0.10 x 0.10     Static       -                                     -                                         YES
                                                                                                           America            RiverGIS RGIS/Network
         Network(STN06)




                                                                                    9
                                  LBA-HydroNET Workshop
                                            Meeting Notes

                                          CPTEC/INPE
                                  Cachoeira Paulista – SP, Brazil
                                      4 – 6 December 2000


Monday, December 4: Plenary Presentations and Discussion

Introductions and General Framework Presentations

Charles Vörösmarty and Jose Marengo welcomed participants on behalf of the two host institutions,
CPTEC and the University of New Hampshire, and gave a preview of the agenda for the three-day
workshop: one day of research presentations, and two days of practical use of the HydroNET system,
including hands-on instruction and working group discussions.

Marengo requested that everyone give short presentations that would emphasize the significance of their
research within the context of LBA and the Amazon region’s hydrometeorology.


Carlos Nobre

Carlos Nobre welcomed the group and gave a brief overview of the LBA program, its current status, and
CPTEC’s role.

Most of the workshop participants are active within LBA. However, it bears repeating that LBA began as
an ambitious idea: an all-encompassing experiment across many disciplines for understanding the
Amazon region’s natural ecosystems and how humans interact with the natural setting (biologically,
physically, etc.) in one of the world’s most important biomes. Similar projects are now beginning in
Southeast Asia and Africa. This workshop clearly depicts the spirit of Earth Systems Science and multi-
disciplinary investigations, bringing together a mix of hydrologists, ecosystem modelers, ecologists, and
hydrometeorologists. Such collaboration puts LBA a step forward in science.

LBA had been planned for many years, but after research started in 1998, the program “took off” and is
now producing significant results. More important experiments are still to come. As there is much work
left, this workshop plays a key role in highlighting hydrometeorological questions and what we need to do
in order to accomplish our goals. In Rondônia, for example, we still have much to learn, and are seeing
ongoing research building on knowledge being gained. There have already been decades of
hydrometeorological data collection in South America, but typically not very much interpretation of that
data. It is time to begin extracting a deeper scientific understanding based on these data.

The new INPE/CPTEC center was inaugurated in 1994. It has grown alongside LBA, playing an
important role in its planning and implementation. It also houses the LBA Central Office and contributes
much to the program’s modeling efforts, especially meteorological modeling, by running a mesoscale
numerical weather prediction model and housing one of the data systems. CPTEC provides a test bed for
a lot of new knowledge being gained.

There remains an identifiable gap: from the inception of LBA, there should have been more studies in
mesoscale hydrology. There is a broad array of studies, especially in Rondônia and Santarém,
emphasizing other key research areas (e.g., land-atmosphere exchanges, ecology), but we have never been
able to reach the same level regarding hydrological process studies. LBA has focused more on large-

                                                   10
scale issues using remote sensing, but it might be beneficial for this community to discuss that at some
point in the workshop and consider what is being missed.           This workshop is a very worthwhile
opportunity; perhaps we should have held it several years ago.


David Knapp

David Knapp offered some logistical information concerning the morning’s schedule, lunch plans,
computers available (17, each with a CD-ROM reader and internet access), restaurant suggestions, and his
own contact information. He added that any printouts that would need to be made during the workshop
could be done through him.


Ellen White

Ellen White gave an overview presentation of the LBA-Hydrometeorology Project, defining it as a NASA
LSHP-funded program supporting GEWEX of the World Climate Research Program as well as within the
broader LBA experiment.          She then briefly summarized the eleven LBA-Hydrometeorology
investigations, each of which represents a joint collaboration between Brazilian and US investigator
teams. The investigations are listed at the end of this section on page 14.


Charles Vörösmarty

Vörösmarty spoke concerning the scope of the workshop, expressing eagerness to see how the workshop
would facilitate collaboration among regional partners sharing hydrometeorological data, and recognizing
the various sources of funding support for the workshop. The majority of support came from NASA’s
Land Surface Hydrology Program (LSHP), but with support from UNESCO, CATHALAC, and IGBP as
well.

Overall goals of the LBA-HydroNET project are (a) to construct a GIS-based Web site to serve as a
repository of hydrometeorological information for use by LBA researchers; and (b) to develop a basin-
scale water budget closure system for Amazonia using observations and simulation outputs. Vörösmarty
and CPTEC colleagues have been especially interested in seeing this happen for several years.

There is great concern about the global phenomenon of decline in hydrometeorological monitoring
capability due to loss of ground stations in what used to be well-monitored parts of the Earth. A time
series of this decline has been compiled and documented by UNH in collaboration with the World
Meteorological Organization’s Global Runoff Data Center. The number of reporting stations shows an
exponential increase until the mid-1980s, then a sharp decline. The apparent reason for this was the
habitual delay in making data available from the time of collection, loss of networks, and strict
restrictions on data availability and use. The UNH group has been active in working against this trend on
a global scale. For the Arctic region, they gathered colleagues from Canada and USGS, pooled existing
archives, mounted data in easy-to-use formats, and multiplied usable data by a factor of 25, to
approximately 3700 active meteorological stations.

R-HydroNET—the continental-scale counterpart to LBA-HydroNET—was begun three years ago.
Original funding from the U.S. State Department and UNESCO was secured in summer 1997, the Web
site was established and operational by spring 1998, and a workshop for R-HydroNET was held in
Panama City in summer 1998. In that same year, the LBA-HydroNET proposal was submitted and
accepted for funding under the NASA research announcement. At this point, the LBA-HydroNET v1.0
framework has been created, and this workshop marks the beginning of the next phase of project
development.

                                                   11
Some decisions will need to be made concerning the direction of the organization and data management
of LBA-HydroNET. Should data be limited in spatial scale to Amazonia alone, or include more/all of
South America? In order to meet needs and desires of data providers and users, data is currently
categorized in a tiered fashion, with Level 1 being publicly accessible archives, Level 2 having password
protection, and Level 3 consisting of completely restricted data sets. (Vörösmarty showed examples of the
Web site’s data presentation, what is included, how it is organized, and how value-added data products
are incorporated.) Will we want to continue this “security” system, or make changes, realizing as well
the general data policy guidelines of LBA more generally? The time domain is currently 1980 to present,
and the spatial domain includes the full Amazon Basin.

The workshop should concentrate on specific products and activities. By considering concrete examples
of important variables, it becomes easier to determine what would be the preferred spatial resolutions,
temporal resolutions, and data sources. Potentially, using the HydroNET system, a researcher could
assemble data sets and compare them to see where they do and do not agree in order to improve the
accuracy of data and value-added products, to learn how to debug programs more effectively, etc. This
workshop may be a good opportunity to brainstorm other applications. The team working on the water
budget closure system, for example, is seeking to identify several conceptual domains for viewing key
water balance elements. Using the HydroNET system, investigators could take various data sets, plug
them into equations, and quickly evaluate the quality of the data sets. Often problems with data can be
perceived only in combination with other data.

The goals of this workshop are:

    •   to announce the creation of the Web-based data bank (LBA-HydroNET v1.0)
    •   to demonstrate the system’s current capabilities
    •   to create an initial steering committee composed of regional data partners who will assist in
        design and implementation of forthcoming versions of the LBA-HydroNET, develop research and
        applied scientific applications for the system, and lead future regional data gathering,
        assimilation, and production efforts using the system
    •   to provide initial training in the use of the HydroNET
    •   to test the system using regional hydrometeorological data: import a first set of input data
        provided by LBA-HydroNET partners, process into value-added hydromet products, and mount
        on WWW site for use by data partners.


Jose Marengo

Jose Marengo spoke briefly about applications of the HydroNET system over the LBA domain. In
Amazonia we have a place where we can carry out our research, and there are several neighboring regions
that are closely linked in terms of hydrometeorological processes, events, and their effects. If we can map
precipitation in an area and avoid flooding catastrophes, clearly this should be a priority. One of the
requirements of LBA is the free availability of data. Conceived as such, this project can have major
impacts. A long vision is clearly necessary and possible.




                                                    12
George Hurtt

George Hurtt presented an overview of LBA-Ecology and its scientific relationship to LBA-
Hydrometeorology. Most ecological modeling proceeds by assuming that atmospheric and hydrological
data can be specified as exogenous inputs. Hydrologists seem to take the opposite tack, using biospheric
measurements as inputs for land-atmosphere models. It is, however, more appropriate to consider it as a
coupled system.

Important progress can be and has been made by studying these systems in isolation. Research must be
done in this way to understand the component systems: their responses, mechanisms, scaling issues, etc.
The central LBA questions, however, are of the coupled system, which is important because of potential
feedbacks across the components.

Feedbacks can dramatically amplify responses (e.g., water vapor feedback on a climate system), and they
can fundamentally alter systems. Land use change, for example, initiates a process where temperature
and precipitation may be altered, which will in turn affect natural vegetation, potentially to an even
greater degree than the initial land use change that affected it.

LBA-Ecology and Hydrometeorology need to work together. The practical benefits are that Hydromet
gets relevant details about land surface, and Ecology gets weather, climate, and hydrological information.
The “big picture” strategy of these two groups working together should be to move toward coupled
models that would simultaneously conserve carbon, water, energy, and nutrients, and to develop the
ability to identify, assess, and better predict feedbacks between systems.


Eric Smith

Eric Smith briefed the group on another potential front for collaboration and data sharing, the Global
Precipitation Mission (GPM), an endeavor planned by NASA on which he will serve as Mission Scientist.

Official participants of the GPM program currently include the U.S. (NASA) and Japan (NASDA), with
additional participation expected from Italy and possibly a number of other countries, including China,
Brazil, Canada, and Korea, as well as sister agencies such as NOAA. The mission is intended to build on
the work of TRMM, involving a core satellite carrying active and passive instruments as well as nine
member satellites with passive sensors. The goal is to produce a nearly global (within the 60 degree
latitude) precipitation measurement with a sampling interval of 3 hours or less (the sampling frequency
given as a minimum by hydrologists). There will be a need for very good validation capabilities, which is
a key point of potential participation by LBA investigations.

The targeted year for commencement of the mission is 2007, viewed as the first phase of an ongoing
series of satellite launches, building into an international-scale venture. Hardware should be selected by
2003, and the satellite constellation should be operational by 2007, but some instruments are expected to
fail and/or wear out, etc., as time continues.

GPM is poised to become a centerpiece for Global Water Cycle science. The advanced dual frequency
radar system of NASDA-CRL will lead to improved rain retrievals through the capacity of its
measurements to be sensitive to precipitation variability, and improved precipitation data is extremely
valuable for many areas of research, particularly crossover areas of interdisciplinary interest. GPM offers
a program for blending scientific research and applications, which can enable the advance of space
technology and the attainment of new levels of international cooperation in science. Using flexible
mission architecture and international partnering, GPM presents a path for the development of an
operational and space-based global rainfall measuring system.



                                                    13
                      LBA-HYDROMETEOROLOGY INVESTIGATIONS


PC-02: Pinker/Ceballos
       “Surface Radiation Budgets for LBA”

PC-03: Xue/Chou
       “Influence of Land Surface Processes/Land Cover Changes in Amazon on Regional
       Hydrometeorology”

PC-04: Dirmeyer/Marengo/Rocha
       “Coupled High-Resolution Ocean-Land-Atmosphere Simulation of Seasonal-Inter-annual
       Climate Variability over Amazonia”

PC-05: Avissar/Dias
       “The Impacts of Land-Use/Land-Cover in Amazonia on Hydrometeorological Processes at
       Different Spatial and Temporal Scales”

PC-06: Betts/Dias/Dias
       “LBA Land-Surface Atmosphere Studies Directed to Forecast Model Improvement”

PC-07: Ferreira/Ambrizzi
       “Role of Land-Surface Processes and Regional and Global Interactions in the Seasonal to
       Inter-annual Variability of the Atmosphere in the Amazon Region”

PC-08: Shuttleworth/Marengo
       “Influences of Subgrid-Scale Heterogeneity on Remotely Sensed Estimates of the Amazonian
       Surface Energy Balance”

PC-09: Vicente/Costa
       “High Resolution, Multi-Spectral, Automatic Satellite Rainfall Estimation Over Amazonia in
       Real Time”

SH-01: Birkett/Jasinski/Costa
       “Altimetric Remote Sensing of the Amazon: Contribution to Surface Water Dynamics”

SH-02: Dunne/Martinelli
       “Mesoscale Effects of Climate and Land-cover Change on River-basin Hydrology on
       Amazonia”

SH-03: Vörösmarty/Marengo
       “A Water Budget Closure System to Support LBA Hydrometeorology and Ecology Studies”




                                             14
Summaries of Individual Participant Presentations:

Lelys Bravo de Guenni
Applications of downscaling and disaggregation techniques on studies of the variability of the
components of the water cycle. Case study—the LBA domain

Bravo’s recent research includes stochastic rainfall models, rainfall parameterization procedures in time
and space, rainfall modeling using a Bayesian approach, disaggregation techniques, downscaling
techniques, and large scale climatic influence on local rainfall, with projects both within Venezuela and
across the Amazon Basin.

Venezuela’s LBA contribution, SIG-CANAIMA, is the motivation for de Guenni to be spending a year at
UNH. She is working with the UNH Water Systems Analysis Group on a project entitled, “Applications
of downscaling and disaggregation techniques on studies of the variability of the components of the water
cycle in the LBA domain.” Currently she is incorporating rainfall data (monthly and daily) into forecast
models. The “Red Hidrometeorológica,” which supplies the majority of hydroelectric power within
Venezuela, has offered some very important data sets. A second source has been a monthly set of
accumulated data corresponding to a group of 39 stations in Nebraska, and a third has consisted of output
from a dynamic regional climate model in a 4x7 grid over the same area, where grid cells are 40x50 km.
Principal objectives of the research are to improve gridded regional climate model predictions, to improve
pointwise statistical predictions, and to estimate areal and point rainfall.


Manoel Cardoso
Importance of the cooperation between LBA Ecology and LBA Hydrology for predictions of fire behavior

Cardoso discussed his work on an Amazonian model that deals with fire’s effects, including changes in
albedo, evapotranspiration, and landcover, and consequent changes for hydrometeorology, including
cloud formation, rainfall, and runoff. He showed the average precipitation in 1995 from the entire
Amazon region and then from areas where the number of fires was quantified and found to be numerous.
The latter were remarkably drier, and in fact in the very wettest areas, virtually no fires occurred.

He plotted fire risk against climate change, and noted that as fire feedback is significant, there are a few
possibilities concerning curve shape, which will be the focus of his Ph.D. research. The two variables
may have an exponential relationship, but fire risk may tend toward a maximum. Cardoso expressed
interest in coupling fire models with ecosystem models, and also in exchanging data with hydrologists in
order to augment knowledge in both disciplines.


Sin Chan Chou, Clemente A.S. Tanajura, Yongkang Xue, and Carlos Nobre
Simulations with the coupled Eta/SSiB model over South America

Chou described the LBA investigation with Yongkang Xue, which uses the CPTEC operational model. A
newer version has recently been completed, with slight modifications that she described. She explained
the investigation, emphasizing the coupling of the Eta/SSiB model, vegetation map, validations with
precipitation observations, and temperature reanalysis. These seem to have the correct temporal pattern
for temperature, although peaks are a bit high in the highest temperature locations, but values themselves
do not match observations very well. It seems that there should be more cloud cover in the model, and
also, there is a very large presence of shortwave radiation that does not appear in the model at all.
Because the team wants to run this model inter-annually, it is very important to know the lateral boundary
and the physics of the model, because their effects will be amplified.


                                                    15
Cassiano D’Almeida, Charles Vörösmarty, Balazs Fekete, Lelys Bravo de Guenni, Jose Antonio
Marengo, and Cort Willmott
Water budget closure system for South America and the LBA domain

Cassiano D’Almeida is working with Vörösmarty at UNH’s Water Systems Analysis Group on a water
budget closure system for South America and the LBA domain. Key water balance elements are
represented by a set of equations focusing on the categories of atmosphere, soil, ground water, and river,
all from an aerological approach. They envision LBA-HydroNET as a tool for improved model
validation and assurance of data accuracy. D’Almeida gave an expanded presentation on the LBA-
HydroNET system the following day during this workshop.


Balazs Fekete, Charles Vörösmarty, and Cassiano D’Almeida
LBA-HydroNET data archive: Development and application

Fekete showed an important organizing database for LBA-HydroNET, the Potential Simulated
Topological Networks at 30-minute resolution (STN30p). A higher resolution will be required for
application to LBA, targeted now at 6-minute or about 10km. He demonstrated the identification of inter-
station regions in the Danube basin, which can be used to compare observed and simulated sub-basin
runoff. In some cases the model shows more runoff than precipitation. He showed a comparison among
different rainfall data sets for the Tropics, which were very similar in seasonality but which he believes
gives estimates that are generally too low. He views runoff and discharge data to be more trustworthy
than rainfall data, and the UNH group is developing methods to use runoff to correct precipitation fields
in areas of the globe where rivers are uninfluenced by hydraulic engineering (e.g., Amazonia). This work
is collaborative with the WMO Global Precipitation Climatology Center and Global Runoff Data Center.


George C. Hurtt
Linking ecological and hydrological models of the Amazon

Hurtt presented the Ecosystem Demography (ED) model. ED addresses the specific need for tracking
fine-scale heterogeneity in ecosystem structure and fluxes in large-scale studies. The model is designed
to represent much of the land-cover heterogeneity that is currently being observed, and retains landscape
demography, since forest succession takes time. Causes of heterogeneity may be weather/climate, soils,
topography, natural disturbances, or human land use. The core of the ED model is a new scaling method
for stochastic point processes. It is essentially a physiologically-based “gap model” integrated with other
key ecosystem processes including decomposition and nutrient fluxes, as well as disturbance processes
such as tree falls, fires, land use and abandonment. The resulting form is a system of partial differential
equations for each grid cell. Spatial scales extend from patch to region, and temporal scales from hours to
centuries. The model is being developed to utilize data from several scales for model testing or
initialization. These data include regional scale data sets, data from state of the art remote sensing
sensors, including 1m IKONOS optical data, Lidar structural data on vegetation heights, and GOES fire
data, as well as ground based information such as eddy flux, inventories, and experiments from key LBA
study sites. ED is also in the process of being coupled to the MM5 meso-scale climate model and a new
global climate model for studies of land-atmosphere coupling. Hurtt’s presentation emphasized the need
for better coupling between hydrologic studies and ecosystem studies because of the potential for
important feedbacks.




                                                    16
Leandro Della Vedova de Oliveira Pinto
Turbulent fluxes of energy over a tropical forest in Amazonia

Oliveira has been working with Humberto Ribeiro da Rocha at the Universidade de São Paulo (USP) on a
project entitled “Turbulent Fluxes of Energy over a Tropical Forest in Amazônia,” which constitutes part
of the LBA-Ecology project “Measuring the Effects of Logging on the CO2 and Energy Exchange of
Primary Forest in Tapajós National Forest.” Objectives of the research are:
    •   to study the biosphere-atmosphere relationship over a tropical forest area through the balance of
        momentum, sensible heat, and latent heat fluxes, and
    •   to collect and analyze the turbulent fluxes and investigate their daily and annual variability.

The experimental site is located in the Tapajós National Forest (TNF), where measurements of wind
components, temperature, and water vapor are collected at a height of 65m. Soil data is also collected for
temperature (five levels), moisture (five levels), and efflux. These data are being processed using an eddy
covariance system (Moncrieff et al., 1997) in order to estimate mean turbulent fluxes of momentum,
sensible heat, and latent heat.

The field experimental data collected will be used to calibrate surface parameters in the Simple-Biosphere
model (SiB2) to validate the efficiency of this model over the study area.


Eric A. Smith
Controls on Large-Scale Amazonian Wet & Dry Season Carbon Flux Variability by Biophysical, Surface
Meteorological, and Cloudiness Factors

Smith discussed his study of controls on Amazonian wet-dry season net carbon flux variability by
meteorological, downwelling radiation, hydrological, and biophysical factors. He has coupled a hierarchy
of carbon assimilation models to a hydrometeorological model, running at various levels of time and
space. The critical forcing parameters of incoming radiation and precipitation are estimated from GOES
satellite data.

The main objective of the research is to understand the space-time variability of the carbon budget and
carbon sequestration and how the underlying variabilities are controlled by feedback on the environment.

The project seeks to compare and contrast wet and dry season carbon production; to determine how
variations of carbon fluxes are partitioned; to understand the sensitivity of carbon fluxes and net carbon
flux variations at large scales to different radiative transfer parameterizations; and to quantify space-time
sampling requirements in the context of four main sets of control factors associated with meteorology,
downwelling radiation, hydrology, and biophysics. The methodology involves acquisition of three recent
years of high resolution GOES-8 imager measurements (March 1998 through February 2001) as well as
additional required remotely sensed and in situ measurements, examination of three pairs of wet-dry
season runs, validation of model output from other LBA investigations, and then analysis of the output in
order to understand the sampling issue.

Smith showed the gridded starting-point imagery from GOES. His group has estimated the mainstream
surface radiation budget comparing downwelling shortwave and longwave flux, as well as PAR flux.
Estimates have also been made on precipitation. He is running the carbon assimilation model using the
AVHRR-based Pennsylvania State University land classification system, to be updated sometime in 2001.
He will examine photosynthetic activity, respiration, and primary biomass production at various time
(diurnal, seasonal, inter-annual) and spatial scales, with special emphasis on wet-dry season inter-
comparisons.




                                                     17
The proposed contribution to LBA-HydroNET from this research is the GOES data that Florida State
University has collected as well as an expanded set of model-derived products, including radiation and
rainfall retrievals, plus budgets for surface radiation, energy, water, and carbon. He pointed out the need
for careful validation of these products.


Brian Staab
Terrestrial water balance of the Amazon and a model for its interpretation

Staab presented his study with Tom Dunne, “Terrestrial Water Balance of the Amazon River Basin and a
Model for its Interpretation.” The study’s objectives are to determine spatial and temporal patterns of
precipitation, evapotranspiration, and runoff in Amazonia, along with their responsible mechanisms, and
to determine factors that control routing and runoff along the channel network and valley floors. His key
science questions are:

    •   What role does the basin’s climatology and size play in determining its runoff response?
    •   How do El Nino events affect patterns of runoff and evapotranspiration?
    •   What is the magnitude of subterranean moisture carryover between wet or dry years and average
        years?

Additional questions concern forest hydrology (importance of deep roots and direct impacts of
deforestation on evapotranspiration and runoff) and model and data issues (e.g., comparisons of simulated
water balance results across differing time steps, and examination of fine-scale rainfall and radiation
effects on runoff and evapotranspiration).

His approach is to map rainfall and runoff fields and compute evapotranspiration with a regression model,
compute monthly runoff and evapotranspiration fields with a simple, spatially variable water balance
model, and route computed runoff through the channel network.


Gilberto Vicente and Marcos Heil Costa
Real time satellite rainfall estimation over Amazonia

Vicente has been working on real-time satellite rainfall estimation over Amazonia for more than five
years. He developed this interest while at NOAA through work with flash flood information, when he
noticed that no one was providing that information for South America. The objective of his work with
Costa is to provide continuous, real time satellite rainfall estimation over Amazonia with a resolution of
4x4km, easily accessible and free of charge.

The auto estimator used is the NOAA/NESDIS Operational Algorithm for Flash Flood Applications,
which accounts for cloud top temperature, cloud top growth rate, cloud top temperature gradient,
precipitable water, relative humidity, wind speed and direction, and orographic correction. The algorithm
links radar rainfall and cloud top temperature.

Vicente discussed the use of parallax correction, which concerns cloud position error due to satellite
position, and mentioned more work in progress: assimilation of wind and orographic information,
validation efforts, technique calibration, data dissemination, and comparative study. Data is available in
real time on the internet at http://orbit-net.nesdis.noaa.gov/arad/ht/ff/gilberto.htm.




                                                    18
Charles J. Vörösmarty, Cassiano D’Almeida, and Balazs Fekete
University of New Hampshire Water Systems Analysis Group - Activities and support to LBA

Vörösmarty noted that several of the presentations to immediately follow would concern potential
applications of the LBA-HydroNET data sets. This archive for Amazonia exists within the framework of
the UNH Global Hydrological Archive and Analysis System (UNH-GHAAS), which makes a variety of
hydrographic data sets from around the world available online. LBA-HydroNET releases both point and
gridded data sets, with the latter generated by remote sensing, spatial interpolation of station-based data,
or modeled outputs.

As one example of the utility of assembling hydrometeorological data sets within a common framework,
he presented an example based on an inter-comparison of precipitation fields and their eventual impact on
spatially-distributed runoff. For South America, there is a complex pattern of over- and under-estimations
based on the existing precipitation data sets. Using a system like LBA-HydroNET, a researcher can
evaluate such data sets through comparison, and gain insight if seeking to develop new methods for
ensuring greater accuracy. Earlier work by the UNH group focused on creating coherent time series of
water budgets over Amazonia to explore the issue of inter-annual variability. Time series of observed and
modeled river discharge were analyzed in the context of use of Nimbus-7 37 GHz passive microwave
polarization temperature differences to remotely infer discharge along the mainstem Amazon. Follow-up
work with C. Birkett (GSFC; Greenbelt MD) and J. Melack (UC, Santa Barbara CA) explores the use of
radar altimetry to drive water transport models across the Amazonian region.

Part of the broader goal of the UNH Water Systems Analysis Group has been to articulate the impact of
humans on the terrestrial water cycle. Recent work has included the documentation of the "aging" of
continental runoff due to artificial impoundment as well as the changing nature of demand for water
resources. By and large, the Amazon provides a unique environment for exploring more natural forces
such as climate variability, since most of the basin is uninfluenced by water engineering works. Recent
assessment by the UNH group demonstrated, however, that much of the inhabited portion of the basin
will show increasing signs of water stress, with a more than 20% increase in relative water use by
humans, arising mainly from population growth and economic development. Further, the influence of
land cover change on the hydrography of the region bears more careful study.

In addition to studies of the hydrography of the Amazon region, nutrient chemistry information could be
supported through the LBA-HydroNET context. Recent analysis by the UNH team has shown that
nitrogen loads have increased in the basin due to human activities including those from atmospheric N
deposition associated with industrial development. The capacity to monitor these changes may also
show-up in the spatial and temporal patterns of river plumes, such as those monitored through the
SeaWiFS sensor.




                                                    19
Tuesday, December 5: Demonstrations, Hands-On Activities, Working Group
Sessions
Vörösmarty welcomed the group back, asked for submission of missing abstracts, data for uploading into
the system, and presentation slides for inclusion in the report of the workshop. He suggested that
breakout groups for the following day be defined according to applications of the HydroNET system, and
gave some thoughts on issues that would need to be addressed:

    •    precipitation
    •    data policy (raw data vs. value-added products, delays in mounting of data in order to protect
         products provided by operational science partners)
    •    data rescue (potential need to digitize tabular data and/or maps)
    •    coupled water, energy, carbon models
    •    real-time vs. time-series analysis
    •    links to other LBA activities (fire, LC/LUC, C budgeting)
    •    use of runoff to “condition” precipitation
    •    regions of interest, like Andes or Amazon floodplain
    •    extreme events/ENSO


Discussion

Smith:           The day’s presenters should give attention to what data sets are in (or expected to be in)
                 the systems they would be demonstrating, rather than merely discussing the data systems
                 themselves.

Tomasella:       What is the group’s intent concerning international scientific interaction: Will South
                 American participants just be seen as data providers, or as full participants?

Vörösmarty:      This issue was part of the very motivation for the workshop, its location, and the active
                 solicitation of participation by individuals from Brazil and other South American
                 countries. HydroNET coordinators are themselves an international group, and are
                 seeking to know what the international scientific community wants and needs in terms of
                 HydroNET services.

Smith:           The group should certainly make an effort to mold general mindsets and expectations, but
                 should also set out some manageable goals to take away as action items from this
                 workshop. I doubt that we will solve any large, systemic problems in such a limited
                 context, but am confident that we can accomplish some small steps (e.g., two or three key
                 papers written).


Gentry: Beija-flor demonstration

Gentry discussed several elements of the Beija-flor system. She began by describing the Metadata Editor,
explained harvesting and the reasons for simultaneous harvest at ORNL and CPTEC. She emphasized
that if a provider stipulates in the data set that he/she does not want it to be harvested, it will not appear in
the index.

In the event that metadata is entered incorrectly, the provider can enter and fix it, whether it is located at
ORNL or at CPTEC, or the coordinator at that site can do it. If someone else notices the error, the best
thing to do is to contact either the data contact or the provider.


                                                       20
Smith:          An advisory should be circulated to that effect, since metadata errors are common
                problems.

Gentry showed a slide of the Beija-flor search page, which is currently in English with a draft version in
Portuguese, as is also the case with the user’s guide. Files are in XML, and users can link to other search
engines from within Beija-flor. Also, if IAI-DIS, ESIPs, or other members of the data archiving
community wish to submit metadata files, the capability exists for searching those indexes as well.
Gentry explained how to perform searches, including using a map for spatial searches. She listed data
sets that are currently held in the archive at ORNL, and concluded by demonstrating the processes of
performing a search and entering metadata, noting that soon the Metadata Editor will include two file type
options: data set and poster (where presently the only option is “metadata”).

Vicente:        Can data files be submitted in different formats?

Gentry:         That is no problem, since there is no official LBA format. Under the field for providing
                the data address in the Metadata Editor is a label, in which a provider can specify format.


Schloss: EOS-Webster demonstration

Annette Schloss explained the concept of the NASA ESIPs, their types, and the structure of the
federation. She discussed the LBA Cluster and the ESIP role in developing and/or providing products
and services. Products already available are satellite imagery, their derived products, GIS products, and
land cover data. The products should be listed in Beija-flor, but the effort to accomplish this has not been
very successful. Services that ESIPs provide include data warehousing, creating custom products,
cataloguing of data and products, and data brokering. She listed LBA Cluster participants (the various
ESIPs involved as well as representatives of LBA-Ecology, LBA-Hydrometeorology, and LBA-DIS), and
mentioned the Web site, http://lba-ecology.gsfc.nasa.gov/lbaecoesip/.

EOS-Webster is a participant member of the ESIP/LBA Cluster. It constitutes a digital library that
provides model products and GOES and IKONOS products, as well as services such as creating spatial
and temporal subsets and reformatting data, offering the user a choice of media. Spatially explicit model
data include ED, NOAA/NASA Pathfinder, and Amazonian vegetation and soil maps from WHRC.
Schloss demonstrated how to access data documentation, showed the page listing data collections, and
showed the search and retrieval tool.

Smith:          Concerning the transfer of real-time GOES data into EOS-Webster, in view of the need
                for extra funding for this endeavor, if it is viewed as a valuable product by participants of
                this workshop, the group should advocate continuation of that support. Currently, the
                initiative exists under LBA-Ecology, but perhaps it should be expanded to LBA-
                Hydrometeorology, and possibly other projects as well.

Schloss:        As it presently stands, users must be affiliated with NASA to access data, but if a
                potential user is interested and has no such affiliation, a registration with that person can
                be worked out.


Fekete/D’Almeida: LBA-HydroNET system demonstration

Fekete and D’Almeida led the group in a demonstration and hands-on practice session with the LBA-
HydroNET system in the CPTEC computer lab. They demonstrated several of the capabilities and system
interfaces, answered several specific questions, and gave a tour of the archive holdings.



                                                    21
                      TABLE 2: Discussion: Working Group Designations



Four groups were formed, around

     1)   precipitation issues
     2)   coupled models
     3)   water budget closure
     4)   operational hydrometeorology


Groups were to meet independently the following morning, to discuss key scientific questions,
operational objectives, data needs, important tools to be provided by LBA-HydroNET, and
“governance” issues. Two volunteers from each group became working group coordinators, to
communicate expectations, to track post-workshop progress toward goals, and to serve as an
ad-hoc steering committee.




                   TABLE 3: Guidelines for Break-Out-Data Working Group
                          (presented as a proposal to participants)


I.   Scientific Questions and Operational Objectives of LBA-HydroNET

     A. Identify key scientific questions that will be addressed by the sub-group.
     B. Identify:

          1. Two (2) scientific papers that should be published based on HydroNET data holdings;
             AND
          2. Two (2) key products that should be developed using LBA-HydroNET data holdings
             and tools, both within the next 18 months.


II. Data Needs

     A. Perform initial data inventory.

          1. What data are already included in LBA-HydroNET and ORNL data lists relevant to this
             area of study? (Consult hand-outs from Tuesday.)

     B. What are the principal data gaps remaining and which data sets are recommended for
        collection under LBA-HydroNET?

          1. Do we need operational data?
          2. Will a data rescue be necessary? (If so, identify these data explicitly.)



                                                  22
          TABLE 3: Guidelines for Break-Out-Data Working Group (continued)


II. Data Needs (continued)

       3. Are there paper products such as hydrographic yearbooks or maps that require digitizing?
          (If so, identify these data explicitly.)

   C. Domain of the data sets

       1. Spatial: all of South America, everything north of 400S, only Amazonia?
       2. Time: Start: 1960s, 70s, 80s (??). End: 2000 and beyond.

   D. Resolution of existing or recommended new data sets

       1. Specify the spatial resolution.
       2. Specify the temporal resolution.


III. What tools should LBA-HydroNET provide users to support these studies?

   Examples include:

   *   Visualization for rapid error identification
   *   GIS-based sub-setting
   *   Tools for rapid inter-comparisons
   *   Others, please specify
   *
   *


IV. “Governance” (how to manage the system)

   A. What strategies or mechanisms can be developed to:
      * Respect the interests of data providers, while also ensuring the delivery of timely
        and freely available LBA science data sets?
      * How should raw data be treated?
      * How should value-added products be treated?

   B. Should LBA-HydroNET be organized into three sub-archives, consisting of
      (1) Data sets that are public, cost-free, and unrestricted?
      (2) Partially restricted to designated users?
      (3) Fully restricted to data donors only?
      (4) Or some combination of these?

   C. What linkages should be made between LBA-HydroNET and:
      (1) Other LBA activities (LBA-DIS, Beija-flor, LBA-Ecology)
      (2) Other agencies (UNESCO, IGBP, WMO, AMAZON-HYCOS, WCRP GEWEX
          and CLIVAR initiatives), FAO?




                                                23
Wednesday, December 6: Plenary Sessions with Working Group Reports


WORKING GROUP KEY FINDINGS REPORTS:

Coupled Models Group (linking water, carbon, nutrients)

Participants:   Julio Tota da Silva, co-leader
                Eric Smith, co-leader/rapporteur
                Manoel Cardoso
                George Hurtt
                Leandro Della Vedova de Oliveira Pinto
                Marysol Schuler
                Javier Tomasella
                Maarten Waterloo

Philosophy:     To bring about coupled model capability for Amazonia

Task:           To write three papers:
                1) Overview of modeling issue on carbon-water cycles
                   •    What is our modeling capability?
                   •    How are we equipped to validate?
                   •    What are our metrics of success?
                   •    What do we need to/from LBA-HydroNET for success?
                        Authors: G. Hurtt, M. Cardoso, J. Silva, L. Pinto, M. Schuler

                2) Assessment of precipitation data
                   •  How well do we know the situation?
                   •  How well do we need to know it?
                   •  What do we need to close the gap?
                      Authors: J. Tomasella, B. Fekete, E. Smith

                3) Assessment of current PAR data sets
                   •  How well do we know the situation?
                   •  How well do we need to know it?
                   •  What do we need to close the gap?
                      Authors: J. Silva, J. Gu, R. Pinker, M. Waterloo, E. Smith

Data Needs:

    Domain:         Amazonia
    Regional focus: Rondonia
    Time period: For overview = not determined
                    For precipitation = 1960 to present
                    For PAR = 1998-2002
    Sampling:       For overview = not determined
                    For precipitation = varying
                    For PAR = 10 to 30 minutes




                                                   24
Long-term strategy:
                Conduct a model inter-comparison study of up to 10 models. The overview paper that
                the group will address should consider key new products needed for this purpose to be
                provided by LBA-HydroNET.

Data Governance:
               •   Data sets needed for the three initial studies either exist or will exist shortly under
                   stipulated LBA data policy, therefore this group does not have any current problems
                   (although Tomasella noted some potential problems in seeking to expand rainfall data
                   sets).
               •   In pursuing the model inter-comparison research in the future, we expect to confront
                   data policy issues. However, it is simply too early to understand specifics.
               •   Authorship policy: Lead authors will speak with data providers and respect their
                   wishes concerning authorship.




                                                  25
Water Balance Closure Group

Participants:   Jose Marengo, leader/rapporteur
                Cassiano D’Almeida
                Annette Schloss
                Brian Staab

Science Questions:
                •     How sensitive is the water budget accounting to different precipitation data sets (e.g.,
                      climatology and extreme events, hydrological and aerological closure)?
                •     What are the systematic errors in water budget closure in its space and time
                      components?
                •     What can be learned through inter-comparisons of water budget data, and what
                      applications exist?

Papers/Products:
                •   AGU announcement, BAMS paper.

Data Needs (adjusted to specifics of Water Budget Closure Group):
               •   Inventory of data sets per country, institution.
               •   Gridded discharge data set, 0.5 x 0.5 degrees, but likely higher.
               •   Should include ANEEL-HIBAM data sets in list.
               •   Domain: North of 40°S.
               •   Resolution: Time = 10 days or twice monthly; Space = 0.5 x 0.5 degrees and higher.

Tools Needed:
                •   Possibility for co-registration of data sets.
                •   Data and product inter-comparisons.
                •   GIS-ready.

Data Governance:
                •     LBA-DIS will ultimately have to develop strategies for dealing with raw data vs.
                      value-added products, and to respect the interests of data providers while still
                      ensuring delivery of timely and freely available data.
                •     It is premature to make decisions concerning specific levels of data restriction
                      without concrete products.
                •     Interaction with various LBA modules and other science agencies should be
                      maximized.




                                                        26
Precipitation Group

Participants:   Lelys Bravo de Guenni, leader/rapporteur
                Merilyn Gentry
                Eurides de Oliveira
                Claudia Cristina dos Santos
                Gilberto Vicente

Scientific Questions:
                •   How well does the inventory of hydrometeorological data match the information
                    needs for different applications?
                •   How much does water storage in the Andes (snow, rainfall) affect river outflow in the
                    Amazon?

Key Products:
                •     Produce a matrix of application needs vs. data availability (from the inventory).
                      Examples of applications might be:
                      - Human health (tropical diseases).
                      - City planning.
                      - Population distribution vs. rainfall variability.
                •     Data reanalysis for rainfall and temperature using historical data with state-of-the-art
                      technology.

Data Needs:
                •     Operational data is not currently needed.
                •     Good climatology would be very helpful: For instance, data maps covering whole
                      region.
                •     Mountain data is especially needed.
                •     Domain: Whole Amazon region, including all countries.
                •     Resolution: Wide range of time and space resolutions.

Tools:
                •   Ability to distribute large data files.
                •   Ability to compress and standardize format.
                •   Identification of a user-friendly format for reading and using data.

Governance:     Data restriction levels should be more rigorously defined. Possibilities might include a
                time delay in release of data, publishing of monthly data instead of daily, or other
                frequencies (daily vs. hourly, etc.). Best to leave this question open for now.




                                                      27
Operational Hydrometeorology Group

Participants:     Juan Julio Ordonez Galvez, co-leader
                  Valdemar Guimarães, co-leader
                  Jose Diaz
                  Balazs Fekete, rapporteur
                  Jose Cortez Medinacelli
                  Marco Antonio da Vila Paz

Key Objectives:
                  •     Assemble an inventory of the existing data (e.g., observation stations, time series,
                        maps).
                  •     Import data to a common data bank (standardized format and tools).
                  •     Identify key stations and parameters that need to be measured and distributed
                        operationally.

Key Products:
                  •   The inventory itself.
                  •   A database of archive data.
                  •   Operational near real time data.

Data Needs:
                  A) Initial data inventory of monitoring stations in the Amazon region.
                     •    Bolivia: 30 discharge gauging stations, 70 meteorological stations, and 5
                          telemetered meteorological stations operating in the past 7 years.
                     •    Brazil: 250 discharge gauging stations, 400 meteorological stations, and 36
                          telemetered stations; observational records extend over the past 30 years.
                     •    Colombia: 3 discharge gauging stations and 25 meteorological stations.
                     •    Equador: Not yet determined.
                     •    Peru: 26 discharge gauging stations and 286 meteorological stations.
                     •    Venezuela: 68 discharge gauging stations, 669 meteorological stations, and 6
                          telemetered stations; observational records extend over the past 30 years.

                  B) Principal data gaps:
                     •   We need not only operational data but an archive of historical data as well.
                     •   Data rescue is necessary to transform the historic information from paper to
                         electronic media.
                     •   Maps and hydrographs must be digitized. Maps from different countries have to
                         be made uniform both in projection and classification.

                  C) We should focus on Amazonia first and consider expanding later to non-Amazon
                     regions.

                  D) Resolution: A uniform mapping of the Amazon region at 1:1M scale will be
                     necessary (gridded 1km resolution), as well as the establishment of new monitoring
                     stations.




                                                         28
Tools and Support:
               •     Support is needed to install new monitoring stations with automated sensors and
                     equipment for telemetry.
               •     Participating countries will need help to set up compatible hardware and software
                     systems for processing archived and operational data.
               •     There should be an inventory of the equipment, software, and networks used in the
                     participating countries.
               •     Participating countries typically use PCs with Pentium II and III processors running
                     MS Windows and Linux operating systems. Support is needed for obtaining software
                     licenses. All countries have internet access, which can be used as an efficient
                     mechanism for sharing data.
               •     Participating countries will need more training in the use of modern hardware and
                     software.

Governance:    In general, the free sharing of observational data is not a problem if the financing of the
               operation of the monitoring network is secured. Countries might be forced to charge for
               their data when they do not have the necessary funding to collect those data, and in such
               cases, the LBA-HydroNET could potentially help to find funding for the monitoring
               networks. An important consensus was reached: The group wholly rejected the
               concept of releasing restricted data, however agreed that agencies could process
               restricted data according to LBA recommendations and release value-added data
               products derived from the restricted data. In addition to previously suggested
               agencies, linkage should be made with HIBAM, AARAM, and SIVAM.




                                                   29
Concluding Discussion

Workshop participants were especially interested in the notion of a data/applications matrix publication,
as suggested by the precipitation working group. The coupled model group saw that this could inform
their overview publication and the “needs” aspect of their precipitation data assessment publication.

A term of 18 months was set for completion of these initial publications and products.

Vörösmarty led a discussion of anticipated activities (“momentum”) to follow from the Workshop:

    •   Meeting notes, abstracts, and working group conclusions will be posted on the Web site.
    •   Current and planned work will be publicly announced (EOS-AGU/BAMS).
    •   The steering committee composed of Bravo, Galvez, Guimarães, Marengo, Silva, Smith, and
        Vörösmarty will evaluate workshop, coordinate subgroup activities, and interact through email,
        meetings, and conference calls.
    •   Papers and products will be generated within 18 months.
    •   Progress will be posted on the LBA-HydroNET Web site.
        - Sub-group “areas”
        - News
        - Suggestion box
        - User metrics
    •   Training sessions and short visits are sought to be made
        - Colleagues from ANEEL offer a short course on operational hydrometeorology, and invited
            members of the LBA-HydroNET operational hydrometeorology group to participate.
            Funding will be an issue.
    •   Another LBA-HydroNET workshop will be scheduled.
        - Location: possibly Manaus, but since it is not easily accessible on international flights,
            perhaps Miami.
        - Date: September 2001?
        - Length: 5 days? (3 days general and breakout sessions and 2 days for paper writing? Extra
            days for activities such as inter-comparisons?)




                                                   30
                                LBA-HYDRONET WORKSHOP
                                             Participant List


MARCELO CID de AMORIM                                   MARCO ANTONIO da VILA PAZ
Instituto Nacional de Pesquisa Especial/CPTEC           Instituto del Ambiente (IDEAM)
Rodovia Presidente Dutra, km 40                         Diagonal 97 No 17-60 piso 7
12630-000 Cachoeira Paulista SP BRAZIL                  Apartado Aereo 18633, Bogota COLOMBIA
Tel:     55-12-560-8518                                 Tel:      571-635-4943/635-6056
                                                        Fax:      571-635-6218
Fax: 55-12-561-2835
                                                        marcodav@ideam.gov.co
amorim@cptec.inpe.br
                                                        CASSIANO D’ALMEIDA
LELYS BRAVO de GUENNI                                   Complex Systems Research Center
Complex Systems Research Center                         University of New Hampshire
University of New Hampshire                             Morse Hall, 39 College Road
Morse Hall, 39 College Road                             Durham NH 03824 USA
Durham NH 03824 USA                                     Tel:     603-862-0815
Tel:     603-862-0847                                   Fax:     603-862-0188
Fax:     603-862-0188                                   cassiano@eos.sr.unh.edu
lbravo@eos.sr.unh.edu
                                                        JOSE DIAZ
HELIO CAMARGO JR                                        Ministerio del Ambiente y de los Recursos Naturales
CPTEC/INPE                                              (MARN)
Rodovia Presidente Dutra, km 40                         Direccion de Hidrologia, Meteorologia y
12630-000 Cachoeira Paulista SP BRAZIL                  Oceanologia
Tel:    55-12-560-8429                                  Centro Simon Bolivar
Fax:    55-12-561-2835                                  Torre Sur, piso 6 of 606 Caracas VENEZUELA
helio@cptec.inpe.br                                     Tel:     582-408-1343
                                                        Fax:     582-481-1947
MANOEL CARDOSO                                          jose_diaz10@hotmail.com
Complex Systems Research Center                         cfermin@marnr.gov.ve
University of New Hampshire
Morse Hall, 39 College Road                             MARIA DONOSO
Durham NH 03824 USA                                     CATHALAC
Tel:     603-862-0819                                   4600 Ricknbacker Causeway, MSC 114
Fax:     603-862-0188                                   Miami FL 33149 USA
mcardoso@eos.sr.unh.edu                                 Tel:    305-361-4076
                                                        Fax:    305-361-4981
GERARD COCHONNEAU                                       cathalac@rsmas.mimi.edu
Superintendencia de Estudos e Informacoes
Hidrologicas                                            BALAZS FEKETE
Agencia Nacional de Energia Electrica (ANEEL)           Complex Systems Research Center
SGAN – Quadra 603 – Anexo J – 1 Andar                   University of New Hampshire
70830-030 Brasilia DF BRAZIL                            Morse Hall, 39 College Road
Tel:    55-61-426-5855                                  Durham NH 03824 USA
Fax:    55-61-426-5615                                  Tel:     603-862-0270
gerard@aneel.gov.br                                     Fax:     603-862-0587
                                                        balazs.fekete@unh.edu
JOSE CORTEZ MEDINACELLI
Servicio Nacional de Meteorologia e Hidrologia          MERILYN GENTRY
Calle Reyes Ortiz No 41                                 ORNL/LBA-Ecology Project Office
Casilla 10993, La Paz BOLIVIA                           PO Box 976
Tel:     591-232-6165/235-5824/235-9737                 Rockwood TN 37854
Fax:     591-239-2413                                   Tel:    865-354-1902
dirmet@mail.megalink.com                                Fax:    865-376-2655
                                                        mgentry2@utk.edu

                                                   31
LBA-HydroNET Participant List
Page 2


VALDEMAR GUIMARAES                                   EURIDES de OLIVEIRA
Superintendencia de Estudos e Informacoes            Superintendencia de Estudos e Informacoes
Hidrologicas                                         Hidrologicas
Agencia Nacional de Energia Electrica (ANEEL)        Agencia Nacional de Energia Electrica (ANEEL)
SGAN – Quadra 603 – Anexo J – 1 Andar                SGAN – Quadra 603 – Anexo J – 1 Andar
70830-030 Brasilia DF BRAZIL                         70830-030 Brasilia DF BRAZIL
Tel:    55-61-426-5855                               Tel:    55-61-426-5854
Fax:    55-61-426-5615                               Fax:    55-61-426-5615
valdemar@aneel.gov.br                                eurides@aneel.gov.br

LUIZ CARLOS HORTA                                    JUAN JULIO ORDONEZ GALVEZ
Manager, LBA Data and Information Systems            Servicio Nacional de Meteorologia e Hidrologia
CPTEC/INPE                                           Jiron Cahuide N 795
Rodovia Presidente Dutra, km 39                      Lima 11 PERU
12560-8542 Cachoeira Paulista SP BRAZIL              Tel:     51-14-472-4459
Tel:    55-12-560-8536                               Fax:     51-14-851-4539
Fax:    55-12-560-8542                               19990505@lamolina.edu.pe; dghapli@mixmail.com
horta@cptec.inpe.br
                                                     MAURO LEONARDO ROSAS
GEORGE C. HURTT                                      Instituto Nacional de Meteorologia e Hidrologia
Complex Systems Research Center                      Inaquito 700 y Corea
University of New Hampshire                          Quito ECUADOR
Morse Hall, 39 College Road                          Tel:      59-03-246-4421
Durham NH 03824 USA                                  Fax:      59-03-294-0575
Tel:     603-862-4185                                leonardo@inamhi.gov.ec
Fax:     603-862-0188
george.hurtt@unh.edu                                 MICHAEL ROUTHIER
                                                     Complex Systems Research Center
DAVID KNAPP                                          University of New Hampshire
Brazil Liaison Officer                               Morse Hall, 39 College Road
CPTEC/INPE                                           Durham NH 03824 USA
Rodovia Presidente Dutra, km 39                      Tel:     603-862-0819
12630-000 Cachoeira Paulista SP BRAZIL               Fax:     603-862-0188
Tel:    55-12-560-8525                               mike.routhier@unh.edu
Fax:    55-12-560-8542
knapp@cptec.inpe.br                                  CLAUDIA CRISTINA dos SANTOS
                                                     INPE/University of Sao Paulo
JOSE MARENGO                                         Av dos Astrounatas No 1758,
CPTEC/INPE                                           Caixa Postal 515
Rodovia Presidente Dutra, km 39                      12201-970 Sao Jose dos Campos SP BRAZIL
12630-000 Cachoeira Paulista SP BRASIL               Tel:     55-12-345-6643
Tel:    55-12-560-8464                               Fax:     55-12-341-1762
Fax:    55-12-560-8542                               claudia.santos@poli.usp.br
marengo@cptec.inpe.br
                                                     ANNETTE SCHLOSS
DAVID MENDES                                         Complex Systems Research Center
CPTEC/INPE                                           University of New Hampshire
Rod Pres Dutra km 40                                 Morse Hall, 39 College Road
12630-000 Cachoeira Paulista SP BRAZIL               Durham NH 03824 USA
Tel:    55-12-560-8429                               Tel:     603-862-0348
Fax:    55-12-561-2835                               Fax:     603-862-0188
david@cptec.inpe.br                                  annette.schloss@unh.edu



                                                32
LBA-HydroNET Participant List
Page 3


AZENETH EUFRAUSINO SCHULER                      LEANDRO DELLA VEDOVA
Laboratory of Isotopic Ecology                  de OLIVEIRA PINTO
Centro de Energia Nuclear na Agricultura        Departmento de Ciencias Atmosfericas (IAG)
Universidade de Sao Paulo                       Universidade de Sao Paulo
Av Centenario, 303                              Rua do Matao, 1226
13416-000 Piracicaba SP BRAZIL                  05508-900 Sao Paulo SP BRAZIL
Tel:    55-19-429-4600/4678                     Tel:    55-13-818-4772
Fax:    55-19-429-4610                          Fax:    55-13-818-4714
schuler@cena.usp.br                             leandro@model.iag.usp.br

CHOU SIN CHAN                                   GILBERTO A. VICENTE
CPTEC/INPE                                      QSS Group, Inc.
Rodovia Presidente Dutra, km 39                 NASA/GSFC/DAAC Code 902
12630-000 Cachoeira Paulista SP BRAZIL          Greenbelt MD 20771 USA
Tel:    55-12-560-8424                          Tel:    301-867-0078
Fax:    55-12-561-2835                          Fax:    301-867-0089
chou@cptec.inpe.br                              gvicente@qssmeds.com

ERIC A. SMITH
Department of Meteorology                       CHARLES J. VÖRÖSMARTY
Florida State University                        Water Systems Analysis Group
Tallahassee FL 32306-4520                       Institute for the Study of Earth, Oceans, and Space
Tel:     850-644-4253                           University of New Hampshire
Fax:     850-644-9639                           Morse Hall, 39 College Road
esmith@metsat.met.fsu.edu                       Durham NH 03824 USA
                                                Tel:      603-862-1792
SOLANDE SILVA de SOUZA                          Fax:      603-862-0188
CPTEC/INPE                                      charles.vorosmarty@unh.edu
Rodovia Presidente Dutra, km 40
12630-000 Cachoeira Paulista SP BRAZIL          MAARTEN J. WATERLOO
Tel:    55-12-560-8522                          Alterra
Fax:    55-12-561-2835                          PO Box 47
solange@cptec.inpe.br                           6700 AA
                                                Wageningen, The Netherlands
BRIAN STAAB                                     Tel:    3-131-747-4778
Stanford University/UCSB                        Fax:    3-131-742-4812
318 Emerson Street #1                           m.j.waterloo@alterra.wag-ur.nl
Palo Alto CA 94301 USA
Tel:     650-326-5755                           ELLEN WHITE
Fax:     650-324-2444                           LBA-Hydromet Project Office
bstaab@stanford.edu                             NASA/Goddard Space Flight Center
                                                Mailstop 923.4, Bldg 22, Rm 122
JULIO TOTA da SILVA                             Greenbelt MD 20771 USA
CPTEC/INPE                                      Tel:    301-286-2624
Rodovia Presidente Dutra, km 39                 Fax:    301-286-0239
12630-000 Cachoeira Paulista SP BRAZIL          ewhite@pop900.gsfc.nasa.gov
Tel:    55-12-560-8400
Fax:    55-12-561-2835
tota@cptec.inpe.br




                                           33
ABSTRACTS




   34
    Applications of downscaling and disaggregation techniques on studies of the
                  variability of the components of the water cycle

                                 Case study: The LBA domain


                                       Lelys Bravo de Guenni1
1
     Centro de Estadistica y Software Matematico (CESMa), Universidad Simon Bolivar, APDO. 89.000
     Caracas 1080-A Venezuela



Understanding the seasonal and inter-annual variability of the key elements of the water cycle (rainfall,
evapotranspiration, soil water and runoff) is paramount in the assessment of water resources availability
for human consumption, hydropower generation, agriculture and other water human needs. Land use and
land cover changes and increasing fresh water human appropriation may also significantly contribute to
alterations in the water cycle components. For most parts of the world including South America, climate
data availability for these studies is usually not adequate in spatial coverage and length of records since
many years of data at a fine spatial and temporal resolution (usually at a few km and a daily time step) are
required in order to understand the complex interactions between, for example large scale atmospheric
phenomena as El Nino/ La Nina and surface water availability for hydropower generation at the local
scale. Downscaling and disaggregation techniques can ameliorate these data limitation problems.
Downscaling methods can be defined as a suite of methodologies to generate high resolution
meteorological data from large scale atmospheric variables. The linking strategies between large scale
climate information and local climate can be classified mainly in two approaches: dynamic downscaling
techniques and stochastic downscaling techniques. Disaggregation techniques allow the simulation of an
unobserved high resolution climate variable in time, space or both from an observed value at a coarser
resolution by preserving important characteristics of the climate variable at the finer spatial and/or
temporal scale. A cooperative research effort between CPTEC and CESMa, recently funded by IAI
PESCA program, has been initiated. This effort is directed to the establishment of downscaling activities
in all Amazonian countries. By using these methodologies with their own data for applications at regional
and local scales and the experience of centers like CPTEC in dynamic downscaling and the scientific
expertise of CESMa in statistical modeling of climate data, specifically on rainfall, they will be able to
develop their own methods depending on their needs as users. Another cooperative research effort has
been initiated between the Water System Research group of the University of New Hampshire and
CESMa, in order to couple downscaling and disaggregation algorithms with a daily version of the UNH
Water Balance Model for multiple years, in order to produce time-varying components of the water cycle
elements. Both initiatives are also connected with the Venezuelan contribution to the LBA project which
has been funded by the Venezuelan National Council of Scientific Research (CONICIT). We envision
that all these research efforts can significantly contribute to the LBA HydroNET objectives.




                                                    35
Importance of the cooperation between LBA Ecology and LBA Hydrology for
                        predictions of fire behavior


                                           Manoel Cardoso1
1
    Complex Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of
    New Hampshire, Durham NH 03824 USA



The dynamics of the Amazonian ecosystems are strongly influenced by fire. Fires affect carbon and
nutrient cycling, vegetation succession, and are responsible for large emissions of aerossols and reactive
gases into the atmosphere. By changing ecosystems structure, fire also affects terms that are directly
important for hydrologic studies. For example evapotranspiration, albedo, and surface roughness are all
affected by fires. To a similar degree hydrologic factors such as precipitation are important influences on
fire dynamics. For example, other things being equal, extremely wet areas are less likely to burn than
dryer areas. In this talk, I will emphasize the need for cooperation between the Hydrology and Ecology
components of LBA to understand these complex feedbacks.




                                                    36
        Simulations with the coupled Eta/SSiB model over South America


     Sin Chan Chou1, Clemente A.S. Tanajura2, Yongkang Xue3, and Carlos A. Nobre1
1
    Centro de Previsao de Tempo e Estudos Climaticos, 12630-000 Cachoeira Paulista SP Brasil
2
    Laboratório Nacional de Computação Científica, Departamento de Mecânica Computacional,
    Petrópolis RJ Brasil
3
    University of California at Los Angeles, Department of Geography, Los Angeles CA 90095 USA



Two one-month integrations were performed with the regional Eta model coupled with the Simplified
Simple Biosphere model (SSiB) over South America. The goal of the present work is to validate the
model, and to investigate its biases and skill on the simulations of South American climate. This is an
initial step on the use of this model for climate research.

The Eta model was set up with 80-km horizontal resolution and 38 vertical layers over South American
continent and part of adjacent oceans. Analyses from the National Centers for Environmental Prediction
were used as initial and lateral boundary conditions. The selected months were August 1997 and
November 1997, which are in opposite phases of the precipitation annual cycle observed in the central
part of South America. The model was integrated continuously for each one-month period.

Monthly means and daily variations of simulated precipitation and surface temperature compare well with
observations. The patterns of simulated outgoing longwave radiation are also similar to the observed ones,
however, a positive bias is verified in the simulations. The model shows a positive bias in latent and
sensible heat surface fluxes, due to an excessive shortwave incoming radiation at the surface.
Comparisons with a version of the Eta model coupled with the bucket model shows that Eta/SSiB version
improves surface temperature and increases precipitation in the interior of the continent during wet
months.




                                                   37
       Water budget closure system for South America and the LBA domain


    Cassiano D’Almeida1, C.J. Vörösmarty1, B. Fekete1, L. Bravo de Guenni2, J.A. Marengo3,
                                    and C.J. Willmott4
1
      Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham NH
      03824 USA
2
      Centro de Estadistica y Software Matematico (CESMa), Universidad Simon Bolivar, Caracas 1080-A
      Venezuela
3
      Centro de Previsao de Tempo e Estudos Climaticos, 12630-000 Cachoeira Paulista SP Brasil
4
      Department of Geography, University of Delaware, Newark DE 19716 USA



The LBA Experiment is fundamentally multidisciplinary and it thus accomplishes individual studies of
terrestrial and floodplain ecology, meteorology, hydrology, terrestrial and aquatic biogeochemistry, trace
gas chemistry and the geography of land use and cover change. These studies, in turn, require accurate
water budget determinations since the inherent dynamics of the humid tropical ecosystem from Amazonia
are dictated by the fluxes and pools of water. In order to cope with these issues, the development of a
water budget scheme based on an aerological approach for the LBA domain is proposed. This approach
couples the water balance of the atmospheric component with the soil, ground and river components taken
from the standard approach that is usually applied to the water budget scheme. This method also enables
an intercomparison between input data sets taken from different sources, evaluating the suitability of any
available data sets into the context of the ecosystem from Amazonia.




                                                   38
           LBA-HydroNET data archive: Development and application


                Balazs Fekete1, Charles Vörösmarty 1, and Cassiano D’Almeida1
1
    Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham NH
    03824 USA



The LBA-HydroNET Data archive under development at the University of New Hampshire is planned to
be the focal depository of hydrology related information of the LBA domain. The purpose of the archive
is to provide raw and processed data in an easy to use fashion primarily for scientists participating in LBA
research. The system will offer data upload and download capabilities. The main purpose of the LBA-
HydroNET archive is to streamline the data processing from the uploading of raw data to the generation
of value added data products (e.g. gridded fields of meteorological variables, processed satellite images,
etc.). LBA-HydroNET will offer high level processed data products such as blended observed and
simulated runoff and gridded discharge. The design of the system allows semi real-time processing if the
streamlining and the steady supply of the raw data input can be solved.

The present prototype system contains mostly subsets of coarse resolution data sets, but some of the core
data sets are already available at finer resolution which will be suitable for regional analysis. One of the
core data sets is a 6-minute simulated topological network derived from HYDRO1k 1km resolution
gridded network by using a grid rescaling algorithm recently developed at UNH. The re-gridded 6-
minute network derived from HYDRO1k was carefully edited manually using RiverGIS, a specialized
GIS tool also developed at UNH. The manual editing resulted in significant improvement in quality over
the original HYDRO1k network and provides a routing framework, which can be the basis of developing
different routing schemes.

LBA-HydroNET currently contains numerous dynamic and static data sets such as monthly gridded fields
of meteorological variables from various sources (e.g., GPCC and GPCP precipitation time series from
1987-present, Climate Research Unit, University of East Anglia precipitation, air temperature, air
temperature range, vapor pressure, cloud cover, etc.), EROS/USGS Soil data, IGBP-DIS land-cover data.
Beside observed data, LBA-HydroNET contains modeled data such as ETA/CPTEC atmospheric model
outputs and a NCEP/NCAR reanalysis product.

The LBA-HydroNET data holding will not only provide the necessary input data for various modeling
efforts in the LBA experiment, but will allow the intercomparison of the various related data sets and
identify inconsistencies among different data sets as part of the budget closure system proposed by
Vorosmarty. As a result of these intercomparisons, we expect a better understanding of the error
characteristics of the data sets available for large scale experiments like LBA.




                                                    39
             Linking ecological and hydrological models of the Amazon


                                            George C. Hurtt1
1
    Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham NH
    03824 USA



Regional terrestrial ecosystem models of the Amazon predict biogeochemical, biophysical, and
hydrological aspects of the land surface over a range of time and space scales. These models are typically
run “off-line” and consider climate and precipitation as inputs and do not explicitly address river routing
and changes in water storage. In contrast, regional climate and hydrological models predict climate and
water fluxes across a range of time and space scales, but typically consider details of the land surface such
as LAI, rooting depth, and surface roughness as inputs. While some coupled studies are under
development, research is mainly proceeding by investigating parts of the coupled system separately. As
progress in ecology, hydrology, and climate studies of the Amazon is made, the potential for coupled
model investigations grows. In this talk review some of the progress in ecosystem modeling studies,
identify some of the potential feedbacks in the coupled system, and try to encourage the development of
coupled studies by arguing for close collaborations between ecological, hydrological, and climatological
investigations.




                                                     40
Multi-scale analysis of inundation with microwave and optical remote sensing
 in the Amazon Basin: applications to biogeochemical measurements and
                                   modeling


                                           John M. Melack1
1
    Institute for Computational Earth System Science, University of California, Santa Barbara CA 93106
    USA



Our LBA investigation being conducted by personnel at UCSB, INPE and INPA has continued its multi-
scale analysis of inundation and wetland vegetation using optical and microwave remote sensing

Synthetic aperture radar analyses - A methodology was developed and demonstrated for classifying
Amazonian wetlands using JERS-1 radar mosaics. The 100-m JERS-1 basin-wide data set is large (2.5
Gb), and has radiometric problems; some wetland and non-wetland features are not distinguishable using
the L-band, HH-polarized JERS-1 returns. Pixel-based classifiers previously applied successfully to 12.5-
m, multi-band, multi-polarization SIR-C data were not suited to classification of the JERS-1 mosaics.
Therefore, a hybrid machine-based and human-interpreted method was developed using polygons rather
than pixels as classification units.

In collaboration with Claudio Barbosa, an image segmentation approach using INPE’s SPRING software
was optimized for wetlands and for the JERS-1 mosaics. The SPRING segmentation algorithm
automatically generates spectrally distinct polygons. Polygons generated by the image segmentation are
clustered in an unsupervised classification of wetland vs. non-wetland, generating a preliminary wetlands
mask. The mask is then edited interactively to eliminate non-wetlands features such as hilly terrain which
are spectrally similar to wetlands on the mosaics but can be correctly identified by an interpreter based on
geographical context, spatial pattern, and cross-referencing with Landsat scenes and scanned topographic
maps. Unlike pixels, polygons or groups of polygons can quickly be selected and re-assigned to the
correct class. Mask generation is being performed on 4 by 6 degree tiles. For the Manaus tile, 31% of the
total area was found to be occupied by wetlands, a much higher percentage than assumed by current
biogeochemical and hydrological models. After masking of non-wetlands features, the wetland portion of
the co-registered high- and low-water mosaics is re-segmented using a smaller minimum polygon area,
and the polygons are assigned to vegetative-hydrologic classes using a rules-based classifier. The
classification system employs five vegetation structure classes (non-vegetated, herbaceous, shrub,
woodland, forest) and two hydrologic classes (flooded, non-flooded).

Radar interferometry - We have found that interferometric synthetic aperture radar (SAR) data are
capable of measuring subtle water level changes within flooded vegetation. During the past year, we have
used L-HH band radar data acquired over the central Amazon by the Shuttle Imaging Radar (SIR-C)
mission and by the Japanese SAR, JERS-1. Interferometric phase is temporally incoherent over open-
water. However, flooded forests and floodplain lakes with emergent shrubs permit radar double-bounce
returns from water and vegetation surfaces, thus coherency is maintained. Interferometric phase
observations show 7-11 cm one-day water-level decreases in tributaries and lakes within ~20 km of the
mainstem and 2-5 cm drops at ~80 km. Proximal observations are in close agreement with mainstem
gauge records, indicating rapid evacuation of the proximal floodplain to decreases in river stage.



                                                    41
John M. Melack
Multi-scale analysis of inundation with microwave and optical remote sensing in the Amazon Basin: applications to
biogeochemical measurements and modeling (continued)



Modeling floodplain flow using open-channel hydraulics is made difficult by a lack of defining
geometrical constraints. For example, our classification work using decision tree methods applied to
SAR data has demonstrated that nearly 50% of the floodplain can be covered with water or flooded
vegetation during mid-recessional flow. The lack of high-resolution digital elevation data combined with
the vast size of the Amazon floodplain limits our ability to measure flowpaths across the floodplain.
Instead, we have adopted a linear diffusion model to characterize the discharge from the Amazon
floodplain. This model does not require constraints regarding channel geometries including widths,
depths, and slopes. Using interferometric SAR data, we have measured volumetric-water loss for about
50 Amazon floodplain lakes and channels. The total discharge from the floodplain is in agreement with
estimates from Muskingum modeling of main channel flow.

Passive microwave - Our activities using passive microwave remote sensing have focused on analysis of
the inundation patterns in three seasonally flooded savannas, and on comparative analyses of hydrological
patterns in the major wetlands in South America. We are completing our data processing for passive
microwave remote sensing of hydrology in three savanna floodplains: Roraima, Bananal, and the flooded
area north of the mouth of the Rio Negro and Rio Branco. Our algorithms calculate the area inundated
monthly over the 9 years of observations by the Scanning Multisensor Microwave Radiometer (SMMR).
For each floodplain region, we delineate hydrogeomorphic subregions and quantify open-water area in
each subregion. We then establish test areas for estimation of algorithm parameters, the most important
of which is the microwave emission signal of flooded land with emergent vegetation. Finally, our
algorithms are validated against independent measures of flood intensity, such as river stage records in
areas of floodplain where inundation is known to be controlled by a large river.

Landsat analyses - Analysis of the mainstem Amazon floodplain in Brazil, based on Landsat Thematic
Mapper images, is nearing completion and will be submitted for publication by December 2000. The
upstream reaches are characterized by forest (>60%) with sparse macrophytes. Moving downstream, the
cover changes gradually to a mixture of forest (~30%) and macrophyte (10-20%) with large spatial
heterogeneity in cover type. Furthest downstream, forest cover is sparse (<20%) and macrophytes and
pasture cover up to 30% of the floodplain The diversity of river, water, and floodplain types that cover
the basin is a reflection of the geologic, hydrologic, and geomorphic characteristics of each sub-basin.

Additional activity is designed to make the Landsat data for river corridors and wetlands more accessible
by developing a web-accessible database of the available images. The web site is nearly complete and
includes data for approximately 200 Landsat images (www.geog.ucsb.edu/~rivers). From these 200
images a selection has now been made of representative sites that will provide information on the
variability of the wetland cover and water quality around the basin.

Airborne videography - Videography from 1995, 1996, 1997, and 1999 overflights of Amazonian
wetlands is being used to train classifiers and to build an independent, geocoded validation data set for
wetlands. Flight log files from the 1999 mission required extensive processing. A series of programs was
written to filter degraded portions of the data stream, reformat, relabel, and generate cleaned files labeled
by time code and subdivided into mappable units; vector and database files were then created to allow
colocation of the entire video data set with image data. We worked with University of Massachusetts
colleagues on these analyses.




                                                       42
John M. Melack
Multi-scale analysis of inundation with microwave and optical remote sensing in the Amazon Basin: applications to
biogeochemical measurements and modeling (continued)



Publications:

Alsdorf, D.E., J.M. Melack, T. Dunne, L.A.K. Mertes, L.L. Hess and L.C. Smith, 2000a. Interferometric
radar measurements of water level changes on the Amazon floodplain, Nature, 404:174-177.

Alsdorf, D.E., L.C. Smith, and J.M. Melack, 2000b. Amazon water level changes measured with
interferometric SIR-C radar, IEEE Transactions on Geoscience and Remote Sensing, in press.

Barbosa. C., L. Hess, J. Melack, E. Novo, Segmentation of JERS-1 radar mosaics for Amazonian
wetlands mapping. Proceedings of SELPER conference, October 2000.

Costa, M.P.F., O. Niemann, E. Novo, F. Ahern and J. Mantovani. 2000. Biophysical properties and
mapping of aquatic vegetation during the hydrological cycle of the Amazon floodplain using JERS-1 and
RADARSAT. International Journal of Remote Sensing, in press.

Shimabukuro, Y.E., E.M. Novo and L.K. Mertes. 2000. Amazon River mainstem floodplain TM Landsat
digital mosaic. International Journal of Remote Sensing, in press.

Siqueira, P., S. Hensley, S. Shaffer, L. Hess, G. McGarragh, B. Chapman, and A. Freeman, 2000. A
continental-scale mosaic of the Amazon Basin using JERS-1 SAR. IEEE Transactions on Geoscience
and Remote Sensing, in press.




                                                       43
        Turbulent fluxes of energy over a tropical forest in the Amazonia


        Leandro Della Vedova de Oliveira Pinto1 and Humberto Ribeiro da Rocha1

1
    Departamento de Ciências Atmosféricas, Instituto Astronômico e Geofísico, Universidade de São
    Paulo, São Paulo SP Brasil



This work is part of the “Measuring the effects of logging on the CO2 and energy exchange of
primary forest in Tapajós National forest” project founded by LBA-Ecology program (NRA –
1997-MTPE 02).

Measurements of wind components, temperature, and humidity at 65 m over land will be used to
calculate hourly, daily and annual turbulent fluxes of momentum, latent and sensible heat
through eddy covariance system over a tropical forest area in Amazônia (Tapajós National
Forest, Santarém - Brazil). The system is composed of a sonic anemometer (Campbell-CSAT 3-
D) and infrared gas analyzer (LICOR-6262). Ancillary data is composed of CO2 and H2O profile,
soil temperature, five levels of soil moisture profile, and so on.

The field experimental data collected will be used to calibrate surface parameters in the Simple-
Biosphere model (SiB2) to validate the efficiency of this model over the study area.




                                               44
                         Cuenca Amazonica Peruana:
    Red hidrometeorologica, analisis de informacion y trabajos de investigacion


                                    Juan Julio Ordonez Galvez1
1
     Servico Nacional de Meteorologia e Hidrologia, Lima 11 Peru



Es conocido que la cuenca amazónica peruana; la cual abarca una superficie total de 965 678 Km², valor
que representa el 74% del territorio nacional, se caracteriza por presentar una rica biodiversidad en su
superficie, que es necesario evaluarlo y cuantificarlo en función de sus principales parámetros
hidrometeorológicos, permitiendo con ello conocer la disponibilidad del recurso hídrico.

La cuenca Amazónica cuenta con una red hidrometeorológica básica operativa de 235 estaciones
distribuidas en su superficie, permitiendo llevar acabo una serie de análisis de la información, y
contribuyendo de esta manera al mejor conocimiento del comportamiento hidrometeorlógico de la
amazonía.

Dentro de los trabajos realizados y que se viene realizando, tenemos:

     -      Comportamiento, distribución y variabilidad espacial y temporal de la precipitación.
     -      Modelo regional de incrementos y descensos de niveles.
     -      Variabilidad y Tendencia de la precipitación en los años de EL Niño.
     -      Boletines hidrometeorológicos
     -      Proyecto AARAM:

Estos trabajos han permitido saber de cierta manera cual es la respuesta de la cuenca ante las ocurrencia
de algunos fenómenos extremos como el caso de Niño o la Niña, la variación de sus niveles extremos
durante el año, los cuales alcanzan valores de 9.94 metros de incremento y 8.17 metros de descenso en el
río amazonas, para el río marañon un incremento medio de 7.77 metros y un descenso medio de 7.46
metros y para el río ucayali un incremento medio de 9.63 metros y un descenso medio de 9.94 metros.

En lo referente al aporte pluviométrico, la distribución de la precipitación total anual varia entre 1500
mm. y 4500 mm., obteniéndose una media areal de 2419.48 mm, una mínima de 1309.04 mm y una
máxima de 3955.36 mm.

El presente análisis realizado, nos permite conocer la variabilidad del régimen pluviométrico e hídricos
para la zona en estudio, lo que ha permitido determinar que durante los años de El Niño, la zona media de
la cuenca ha registrado las mayores precipitaciones durante el año 1982/83, obteniéndose con ello dos
períodos bien definidos: uno desde 19960/61 - 1982/83, cuya tendencia media es creciente y el otro
1982/83 - 1997/98, con una tendencia media decreciente.

Los niveles medios anuales del río Amazonas, durante los años de El Niño, registran una tendencia
media decreciente en su distribución espacial y temporal, determinándose un descenso medio de 2 metros
en el período analizado.




                                                   45
Juan Julio Ordonez Galvez
Cuenca Amazonica Peruana: Red Hidrometeorologica, Analisis de Informacion y Trabajos de Investigacion
(continued)



En lo referente al Proyecto AARAM, que se viene ejecutando conjuntamente con el SENAMHI, la
Universidad Agraria La Molina y la Universidad Internacional de Florida, tiene como objetivo la
búsqueda y desarrollo de métodos, técnicas y modelos que permitan cuantificar todo el potencial de la
cuencas amazónicas andinas, así como desarrollar un Balance Hídrico, con el fin de parametrizar las
principales variables que intervienen en el llamado ciclo hidrológico.

Para ello se ha seleccionado como cuenca piloto, la cuenca del río Pachitea la cual cuenta con un área
total; de 28 000 Km², y dividida en 13 subcuencas; en las cuales se vienen realizando las campañas de
aforo y muestreo de calidad de agua y de sedimentos. Además, en la cuenca del río San Alberto en
Oxapampa se tiene instalado un Laboratorio de Calidad de Agua donde se viene realizando los análisis
respectivos y al mismo tiempo se viene llevando trabajos de investigación en la parte de bioquímica y
geoquímica, en cuencas deforestada y forestales.

Actualmente, se viene desarrollando trabajos de investigación conducentes a la obtención de títulos de
Pregrado y Postgrado de estudiantes nacionales y extranjeros en las universidades de Agraria La Molina y
la Internacional de Florida.




                                                  46
                      Earth Science Information Partners Project


                             Annette Schloss1 and Michael Routhier1
1
    Earth Science Information Partners Project, Complex Systems Research Center, University of New
    Hampshire, Durham, NH 03824 USA



EOS-WEBSTER is a World Wide Web based interface to the University of New Hampshire's (UNH)
Earth Science Information Partner (ESIP) digital library which contains data, information, and services
concerning the earth system science community. It is designed to proved single-source access to a rich
selection of geographically based information including model output, satellite imagery and vector data.

EOS-WEBSTER is a member of NASA's Earth Science Enterprise (ESE) Earth Science Information
Partner (ESIP) Federation. The goal of NASA's ESE is to develop an understanding of the total earth
system and the effects of natural and human-induced changes on the global environment. The ESE
Federation of Earth Science Information Partners (ESIPs) provides a framework to enable optimum ways
to develop, produce, and distribute environmental information and to provide associated services to
science and society.

In support of these efforts and goals, EOS-WEBSTER provides regional scale remote sensing data and
ecosystem model predictions for science applications for the LBA-Ecology component of the Large Scale
Biosphere Atmosphere Experiment in Amazonia (LBA). Some of the current data sets presently housed
within EOS-WEBSTER which support LBA research include MODIS, GOES, IKONOS and Pathfinder
AVHRR NDVI satellite imagery for the Amazonian region. Additional data sets include AVHRR
satellite derived vegetation data for all of South America and IBGE vegetation and EMPRAPA derived
soil layers for Brazil. EOS-WEBSTER also provides a set of Brazilian state and Amazonian region level
gazetteer polygons for use with EOS-WEBSTER's "Search and Retrieve" tools to allow for the cookie-
cutting of specific geographic regions from constituent data sets.




                                                  47
Controls on large-scale Amazonian wet and dry season carbon flux variability
       by biophysical, surface meteorological, and cloudiness factors


                                             Eric A. Smith1
1
    Dept. of Meteorology, Florida State University, Tallahassee FL 32306-4520 USA



A major research focus for the LBA Ecology Program has been an assessment of the carbon budget and
the carbon sequestering capacity of the large scale forest-pasture system that dominates the Amazônia
landscape, and its time-space heterogeneity manifest in carbon fluxes across the entire Amazon Basin
ecosystem. Quantification of these processes requires a combination of in situ measurements, remotely
sensed measurements from space, and some type of realistically forced hydrometeorological model
coupled to a carbon assimilation model, capable of simulating details within the surface energy and water
budgets, along with the principle modes of photosynthesis and respiration.

In my group's research project we are developing and testing a carbon-water-energy budget retrieval
system, based on a coupled carbon-hydrometeorological model forced by both in situ meteorological
measurements and remotely sensed incoming radiation flux and precipitation retrievals, applied to the
large scale Amazônia study area. The coupled model includes three types of carbon assimilation
modules, all Farquahr-type models but with varying formulations for light use efficiency and the
relationship between photosynthesis and transpiration, and uses high time/space resolution GOES satellite
measurements to determine the spatial-temporal distribution of shortwave/longwave surface radiation
fluxes and rainfall. These satellite-based parameters are the main forcing parameters for the surface
energy and water budgets and thus major controls on carbon budget processes, and represent the
parameters least well represented by in situ surface measurements.

The major focus areas in our research are: (1) comparing and contrasting wet and dry season carbon
production-carbon release fluxes; (2) assessing how the variability of these fluxes is partitioned between
stomatal control (ecosystem variability), surface meteorological control (temperature, moisture, wind
variability), and cloud control (radiation & precipitation variability); (3) examining the sensitivity of the
carbon fluxes and flux variability to radiative parameterizations; and (4) understanding how sensitive the
carbon fluxes and flux variability are to various published schemes for formulating the carbon
assimilation process. Analysis-wise, we seek to understand how both accumulated and net biomass
production rates are varied at the diurnal, daily, and seasonal time scales as the model parameterization
schemes are altered.




                                                     48
    Terrestrial water balance of the Amazon and a model for its interpretation


                                             Brian Staab1
1
     Environmental Fluid Mechanics and Hydrology Program, Stanford University, Palo Alto CA 94301
     USA



A more complete understanding of the spatial and temporal patterns of precipitation, evapotranspiration
(ET), and runoff (RO) in the Amazon Basin and the mechanisms responsible for these patterns would
benefit the hydrologic, climate, and ecological research communities. We are investigating these patterns
and processes using a regression model, a simple spatially-variable water balance model, and a channel
routing model. Specifically, we are evaluating the role of the basin's climatology and size in determining
runoff response, the effect of El Nino events on patterns of ET and RO, and the magnitude of
subterranean moisture carryover between wet and dry years. The potential role of deep roots in
controlling rates of regional-scale ET and RO is being explored as well as the potential effects of events
which might alter the rainfall-runoff response (e.g., deforestation). We are also examining a variety of
model and data issues, including the effects of timestep and the influence of fine-scale rainfall and
radiation patterns.

The regression model was developed based on mapped rainfall and RO. ET is computed as the difference
between annual rainfall and RO, using the common
assumption that change in subsurface storage is small compared to this difference. The water balance
model uses an energy budget approach to compute fields of ET, RO, and soil moisture from input data
based on field and remotely-sensed measurements. These input data include rainfall, temperature,
radiation, available water content of soils, and rooting depth.
Runoff and ET predictions from the water balance model will be validated against annual empirical
results from the regression model, observed monthly discharge hydrographs from meso and macro-scale
and basins, and daily micrometeorology measurements. Validated RO estimates will then be used as
input to the channel routing model, allowing an assessment of the relative
roles of factors controlling the hydrograph over a broad range of drainage areas.




                                                   49
                  Real time satellite rainfall estimation over Amazonia


                            Gilberto A. Vicente1 and Marcos Heil Costa2
1
    QSS Group, Inc., NASA Goddard Space Flight Center, Distributed Active Archive Center, Greenbelt
    MD 20771 USA
2
    Federal University of Vicosa, Vicosa MG Brasil



This project deals with the problem of providing high resolution, real time satellite rainfall rate estimation
over the Amazon region during the LBA-Hydrology project. The rainfall rates are available every half-
hour as 1-hour mean, 3- and 6-hour totals and once a day 24-hours totals. These products are available in
GIF and digital GRADS format on the NOAA/NESDIS web site
 http://orbit-net.nesdis.noaa.gov/arad/ht/ff.

The satellite technique used in this project is similar to the current NWS operational technique, Auto-
Estimator, developed and implemented in the US by the PI for flash flood applications. It consists of
computing rainfall rates based on infrared (IR) GOES derived data, model derived precipitable water and
relative humidity and considerations regarding to the spatial and temporal evolution of convective cloud
systems.

During the presentation we will provide up to date information in the recent development, implementation
and validation of the technique for the Amazonia.




                                                     50
                 University of New Hampshire Water Systems Analysis Group
                                 Activities and support to LBA


                    Charles J. Vörösmarty1, Cassiano D’Almeida1, and Balazs Fekete1
1
        Institute for The Study of Earth, Oceans and Space, University of New Hampshire, Durham NH
        03824 USA



    The fundamental goal of the Water Systems Analysis Group (WSAG) at the University of New
    Hampshire is to act as a formal, active research and advanced training unit within the Institute for the
    Study of Earth, Oceans, and Space. The Group is dedicated to analysis of the critical global change issue
    of water systems and their alteration by anthropogenic activities. Creation of the WSAG reflects a rapidly
    emerging scientific field which pursues integrative studies of hydrology, biogeochemistry, and human-
    water interactions that is necessary to analyze the full dimension of anthropogenic change at local,
    regional, and global scales.

    The structure of the Water Systems Analysis Group is built around a set of “pillars” or research and
    training initiatives. There are four pillars defining the thematic content of the Water Systems Analysis
    Group:

           •   Humans and Their Direct Role in the Global Water Cycle
           •   Monitoring the Status of Inland and Coastal Waters
           •   Land-River-Coastal Systems (LaRCS)
           •   International Training Program for Water Studies & Summer Institute

    The LBA Science Plan articulates similar objectives and our LBA NASA Land Surface Hydrology
    project described below supports in particular the monitoring and international training aspects of the
    WSAG initiative.

    The goal of this LBA project is to establish a water budget closure system (WBC-LBA) for computing
    high-resolution water balance elements in support of the LBA campaign. The system being developed
    integrates several existing scientific tools including algorithms that produce high-resolution climatology
    fields, water balance and river transport models, and a recently-established GIS-based WWW-site that
    serves as a data repository for participating hydrometeorological agencies in South America, Central
    America, and the Caribbean (R-HydroNET v1.0; http://www.R-hydronet.sr.unh.edu/). The LBA-version
    resides on the WWWeb site: http://www.lba-hydronet.sr.unh.edu/.

    Our aim in developing the WBC-LBA is to produce gridded fields of precipitation, temperature and other
    climatic variables, evapotranspiration, soil water, drainage basin storage, runoff, and river discharge that
    are consistent with the observational record of data collected at hydrometeorological monitoring
    stations. We will also test runoff and convergence field predictions made by an atmospheric model (ie.
    the CPTEC/COLA GCM with coupled 4DDA ETA model) applied over the experimental domain. Both
    retrospective (1960-present) and LBA-contemporary time frames will be analyzed and the results made
    available to the LBA research community through the LBA-Data Information System.




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Charles J. Vörösmarty
University of New Hampshire Water System Analysis Group Activities and Support to LBA (continued)




Five supporting tasks are being pursued to ensure that the goal set forth above can be attained: (a) to
develop a coherent software system to error-check, visualize, and assimilate hydrometeorological data
sets, (b) to assimilate all relevant hydrometeorological data sets, (c) to combine these data sets with
models that compute key elements of the land-based water cycle of the Amazon basin, (d) to validate
results and identify existing gaps in our quantitative understanding of water cycle elements across
Amazonia, and (e) to archive at the LBA-DIS and LBA-HydroNET the associated data sets for
distribution to the research community. The software system constitutes a regional version of an existing
GIS-based river basin analysis tool, the UNH-Global Hydrological Archive and Analysis System
(GHAAS). Improvements to our climate field interpolations, water budgeting and fluvial transport models
are currently under development.

The convening of this Workshop and demonstration of various state-of-the-art hydromet data
management systems supports the broad WSAG education goals. In addition to its educational mission,
this Workshop also seeks to provide a mechanism for community-based consensus on how to populate the
LBA-HydroNET data repository with science-relevant information contributed by both LBA researchers
and regional hydrometeorological agency partners.




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                            Overview of LBA-Hydrometeorology


                                              Ellen White1
1
    LBA-Hydromet Project Office, NASA Goddard Space Flight Center, Greenbelt MD 20771 USA



The Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) was conceived in response to
the 1992 Rio Climate Convention with a vision to conduct new research combining field measurements,
satellite data, and models of atmospheric processes in order to expand empirical knowledge, to inform the
international debate, and to advance the pursuit of a basis for sustainable land use in the tropics. It is a
Brazil-led program, with participation by scientists from South America, the U.S., and Europe. Questions
concerning biological, chemical, and physical functioning of the Amazon Basin inform LBA research,
which necessarily includes atmospheric and hydrological investigation. The region is globally anomalous
in its convective characteristics and hydrology, as a place where clouds accumulate, generating
precipitation and releasing heat that affects both regional and global climate through tropical circulation.

The LBA-Hydrometeorology module was thus created, to be closely linked to all LBA science themes but
specifically focusing on seasonal-to-interannual hydrometeorological prediction and the effects of land
cover change on hydrology and climate. It is one of several international GEWEX projects within the
World Climate Research Program (WCRP), and is managed in the U.S. by NASA’s Land Surface
Hydrology Program (LSHP). Eleven research teams are involved, using modeling techniques and
satellite and ground data to study water and radiation fluxes, convection and precipitation patterns,
weather prediction, and surface dynamics. The LBA program promotes scientific collaboration and data
exchange among participants, offering a synergistic effect to research efforts.

Official LBA status is pending approval of the project’s Implementing Arrangement, but once it is
established, Hydromet investigators will be permitted to engage in field campaigns within Brazil. As
ground data become more complete, model accuracy can be evaluated and improved and conclusions can
be drawn about the relationships among land cover, water cycle, and regional and global climate. At the
present stage, data sets and products are being compiled for Amazonia that include shortwave radiation
budgets, photosynthetic activity, stomatal resistance, soil water content, vegetation, convection patterns,
precipitation rates, surface energy and water balances, sea surface temperatures, river stage and discharge
values, streamflow, runoff, and drainage basin storage.




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