PROMISE Predictability and variability of monsoons and the by agl27658

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									                      PROMISE
   Predictability and variability of monsoons and the
agricultural and hydrological impacts of climate change




      A 3 year research project funded under Framework 5 of the
        European Union (grant number EVK2-CT-1999-00022)

      For more information see http://ugamp.nerc.ac.uk/promise
Talk outline
•Goals and structure of PROMISE
•Examples of PROMISE research
•International conference we are planning
for 2003
    World population prospects …




                                Source: United Nations Population Division 1998

 India predicted to be the most populated country by 2050
PROMISE Partners
                University of Reading
                CIRAD
                CNRM
                DMI
                ICTP
                CEH
                LMD
                MPI
                The Met Office
      Bologna
                ECMWF
                CRC
                CINECA
                IITM
Goals of PROMISE
PROMISE aims to improve understanding of:

    •The potential for seasonal prediction and the benefits
    that would accrue in terms of the management of
    water resources and agriculture


    •The impacts of climate change on tropical
    countries, in particular on the availability of water
    resources for human use and on the productivity of
    crops and the potential changes in natural
    vegetation
Links with end-users
•Development of a data archive
•Visits to CGIAR centres
•ICTP workshop (held in 2001)
•International conference to be held in 2003


For more information see:
http://ugamp.nerc.ac.uk/promise/research/endusers
PROMISE Research and Support
 Natural variability and        Assessment of       Impact of climate
predictability of current   anthropogenic climate   change on ground
  monsoon climates          changes for monsoon       hydrology and
                                   climates            agriculture


                                     +
    Development of a database               Establishment of
    of observed and simulated               active links with
    data on meteorology,                    climate scientists in
    hydrology and agriculture               monsoon affected countries
Main areas of PROMISE research
                                               ERA-40
Sensitivity of
monsoon variability
to sea surface        Seasonal
temperatures          predictability and            DEMETER
                      natural variability of
                      monsoon climates
                                                 Hydrological and
Sensitivity of                                   agricultural impacts
monsoon variability                              of climate change in
to land-surface                                  monsoon-affected
processes                                        countries

                      Assessment of
                      future monsoon
Impact of land-use    climates
changes on future                                            ERA-40
monsoon climates
Integrated climate modelling
Examples of PROMISE research

 •Development of a hydrological model that can be
 integrated with regional climate models (GWAVA)
 •Development of a crop model that can be
 integrated with seasonal forecast to produce yield
 estimates in Senegal (GCH4)
 •Development of a large scale crop model that
 can be combined with GCMs to produce long
 term forecasts of yields that can be used for
 planning (HAPPY)
     GWAVA
Global Water AVailability
       Assessment
         Jeremy Meigh
Centre for Ecology & Hydrology
    (Institute of Hydrology)
        Wallingford, UK
         in conjunction with
   British Geological Survey
            Overall objective
• Develop a methodology for the assessment of
  water resources in relation to water demands
  which can be applied globally
    GWAVA Detailed Objectives
• Consistent methodology at the global scale
• Representation of spatial variability in water
  availability and demands
• Representation of seasonal and year-to-year
  variability in water resources
• Accounting for the real properties of water
  resources systems
• Tackling problems of international basins
• Combined treatment of surface and groundwater
• Ability to take into account scenarios of
  population growth, urbanisation, economic
  development and climate change
                General approach
• 0.5 by 0.5 degree grid for both water availability and demands
• Linking grid cells to simulate river network

• Models to account for effects of:
      • lakes, reservoirs and wetlands
        • abstractions and return flows
        • inter-basin transfers

• Water demands based on current and projected population and
  livestock numbers, information on irrigation and industrial use

• Indices of water availability versus demand derived at the grid cell
  scale
        Inputs and data sources
• Physical and water resources data
      Elevation, River network
      Vegetation, Soil type
      Lakes, Reservoirs and Wetlands
      Aquifer properties

• Climate
    Rainfall - 30 year time series, Evaporation


• Demand related information
   Population, Livestock numbers, Industrial and
    Irrigation demands
River network and cell linkages




                          Indian Ocean
Change in annual water demand, 2050
Change in water availability index
                               2050, taking in to
                               account:
                                Supply changes due to
                               climate change

                              Demand changes due to:
                                 increasing population
              -2.00 to -1.90     population distribution
              -1.75 to -1.50     increasing per capita
              -1.00 to -0.50
                                    demands (improved
              -0.20 to 0.20
              0.50 to 1.00
                                  living
              1.50 to 1.75          standards and
              1.90 to 2.00          industrialisation)
Application of model to West Africa
River network    Density of trees




                            Soil type
Examples of PROMISE research

 •Development of a hydrological model that can be
 integrated with regional climate models (GWAVA)
 •Development of a crop model that can be
 integrated with seasonal forecast to produce yield
 estimates in Senegal (GCH4)
 •Development of a large scale crop model that
 can be combined with GCMs to produce long
 term forecasts of yields that can be used for
 planning (HAPPY)
             DHC_CP
      Diagnostic Hydrique des Cultures
           Champs Pluviométriques

      Crop Water Balance Calculation
   Using Satellite based Rainfall Estimates
                            Presented by :
                 Abdallah SAMBA, Agrometeorologist
             AGRHYMET Regional Centre at Niamey, NIGER
                          Trieste, June 2001
AGRHYMET                                                 CIRAD
              Introduction
• Need to forecast the yields of food
  crops in order to :
     • best manage the cereal stocks
     • control the distribution of food
     • start food aid in time

• Using water balance simulation to
  obtain parameters which enable
  estimation of yields.
Water fluxes and their effects   (        )
on agricultural hydrosystem (         )

                                                   Agricultural
                                                   production


     Precipitation
                          Soil
                       evaporation

                                                                  Crop
                                                              transpiration


                                                        Runoff



                                     Drainage                                 Erosion
     Capillary rise


                                                Lixiviation
Ground water
Simplification for Water Balance simulation
             (The DHC4 model )
                                         Agricultural
                                         production


   Precipitation

                                                            Crop
                                                        transpiration

                              Soil
                           evaporation




                                                 Drainage



Ground water
          METEOSAT
           Satellite            WATER BALANCE
                                  SIMULATION


                                                  n years
                                                 x stations      File
                                                                 Screen
                                                                 GIS
             Rainfall data
                                               n stations        Spreadsheet
                                                                 Printer
                                                                    RESULTS
              Stochastic Rainfall Generation
                  Parameter Calibration




DATA BASES                                     Agrometeorological
 PET                                          Stations
 Historical rainfall data


 AGRHYMET                                                                  CIRAD
Examples of PROMISE research

 •Development of a hydrological model that can be
 integrated with regional climate models (GWAVA)
 •Development of a crop model that can be
 integrated with seasonal forecast to produce yield
 estimates in Senegal (GCH4)
 •Development of a large scale crop model that
 can be combined with GCMs to produce long
 term forecasts of yields that can be used for
 planning (HAPPY)
 Combined weather/crop
     forecasting for
   groundnut in India

Andy Challinor, Tim Wheeler and Julia Slingo
           University of Reading
Weather




                    Farm
                     - management
                    - decisions




          
              Crop
Soil                 Genotype
           Country +     district   field

                       Spatial scale
annual +

           T
           i
seasonal   m
           e   GCM
           s
           c                            Crop
           a                           models
monthly    l
           e
daily
           Country +        district   field
                       Spatial scale
annual +

           T
           i
seasonal   m  rainfall
           e
           s  groundnut
           c
           a
monthly    l
           e
daily
           Country +          district   field

                       Spatial scale
annual +

           T
           i
seasonal   m  rainfall
           e
           s  groundnut
           c
           a             Large area
monthly    l               model
           e
daily
Huge Area Potential Peanut Yield
      (HAPPY!!) model

                Pod yield              Biomass


                                                      transpiration
                                                       efficiency
                        Leaf canopy
  Development                         Transpiration
     stage                                                            temperature
                                                                      rainfall
                        Root system                                   RH




                                       Soil water
Calibrating and testing HAPPY
• Calibrate using field/district data.
• Test in hindcast mode using ERA-40
  data to drive HAPPY.
• Compare predicted crop yields with
  observed crop yields.
• Re-calibrate HAPPY?
                                                      weather
                        General Circulation Model
                                                      forecast




                                                         Probabilistic outputs
                     spatial
                   parameters
Large area model




                                        Crop model

                   Crop model            (HAPPY)
                   uncertainties

                                           output      crop
                                         processing   forecast
        International PROMISE
              conference
                         24th – 28th March 2003
                             ICTP in Trieste
                         currently sponsored by
                       EU PROMISE, ICTP, WCRP,
                            START/CLIMAG


Monsoon environments: Agricultural and hydrological
impacts of seasonal variability and climate change
 Monsoon environments: Agricultural and hydrological
 impacts of seasonal variability and climate change

 Conference topics

•The impacts of anthropogenic climate change on hydrology, agriculture
and natural vegetation in monsoon-affected countries
•Seasonal predictability of monsoon climates and the management of
water resources and agriculture
•Data provision for scientists from monsoon-affected countries using the
PROMISE data archive as an example.
•Use of seasonal forecasts as an operational tool
•Applications of crop and hydrological model output to decision-making
processes in developing countries
•Future of integrated climate/impacts modelling
Monsoon environments: Agricultural and hydrological
impacts of seasonal variability and climate change

Planned sessions

1. Seasonal predictability and natural variability of
   monsoon climates
2. Assessment of future monsoon climates in
   response to anthropogenic climate change
3. Sensitivity of monsoon variability to land-surface
   processes
4. Agricultural impacts of climate change
5. Hydrological impacts of climate change
6. Bringing together scientists and end users
Monsoon environments: Agricultural and hydrological
impacts of seasonal variability and climate change

Participants


•PROMISE partners
•Representatives from aid agencies
•Climate scientists from developing countries
•Policy makers / people involved with long term
planning
•European and American scientists working on
PROMISE-related topics
Summary
•PROMISE is an interdisciplinary project which aims to
improve understanding of the impacts of climate
change on monsoon environments
•An international conference is planned for March 2003
which we hope will involve both researchers and end-
users of research
•FAO’s involvement in PROMISE and particularly the
conference would provide an exciting opportunity for
collaboration
Further information
Find out more about PROMISE:
•web site: http://ugamp.nerc.ac.uk/promise
•brochure – a few copies here also download from the
web site
•E-mail or phone me: emily@met.rdg.ac.uk
+44 118 9316608
•attend the next annual PROMISE meeting in mid-May
in Paris

								
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