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					Using LAPS in the Forecast
         Office


                  By
                  Steve Albers

                  May 2002
                   LAPS
A system designed to:

• Exploit all available data sources
• Create analyzed and forecast grids
• Build products for specific forecast
  applications
• Use advanced display technology

…All within the local weather office
Why do analysis in the local office?
   “THE CONCEPT OF THE LOCAL DATA BASE
   IS CENTRAL TO FUTURE OPERATIONS…THE
   MOST COMPLETE DATA SETS WILL ONLY
   BE AVAILABLE TO THE LOCAL WFO. THE
   NEW OBSERVING SYSTEMS ARE DESIGNED
   TO PROVIDE INTEGRATED 3-D DEPICTIONS
   OF THE RAPIDLY CHANGING STATE OF THE
   ENVIRONMENT.”

-Strategic plan for the modernization and associated restructuring of the
National Weather Service
                 LAPS Grid
• LAPS Grid (in AWIPS)
  –   Hourly Time Cycle
  –   Horizontal Resolution = 10 km
  –   Vertical Resolution = 50 mb
  –   Size: 61 x 61 x 21
Data Acquisition and
  Quality Control
                        LAPS Data Sources




The blue colored data are currently used in AWIPS LAPS. The other data are used in
the "full-blown" LAPS and can potentially be added to AWIPS/LAPS if the data
becomes available.
             Local Surface Data
  Local Data may be defined as that data not entering into the
  National Database
• Sources
   – Highway Departments
      • Many States with full or partial networks
   – Agricultural Networks
      • State run, sometimes private
   – Universities and Other Schools
      • Experimental observations
   – Private Industry
      • Environmental monitoring
   – State and Federal Agencies
      • RAWS
     Problems with Local Data
• Poor Maintenance

• Poor Communications

• Poor Calibration

Result ----------------> Inaccurate,
                           Irregular,
                               Observations
 Multi-layered Quality Control
• Gross Error Checks
  – Rough Climatological Estimates
• Station Blacklist
• Dynamical Models
  – Use of meso-beta models
  – Standard Deviation Check
• Statistical Models (Kalman Filter)
  – Buddy Checking
    Standard Deviation Check
• Compute Standard Deviation of observations-
  background

• Remove outliers

• Now adjustable via namelist
        Kalman QC Scheme
FUTURE Upgrade to AWIPS/LAPS QC
• Adaptable to small workstations
• Accommodates models of varying
  complexity
• Model error is a dynamic quantity within
  the filter, thus the scheme adjusts as model
  skill varies
Kalman
 Flow
 Chart
         AWIPS 5.1.2 LAPS
          Improvements:
• Wind Profiler Ingest restored
  – QC threshold tightened
• Surface Stations
  – More local (LDAD) station data
  – Improved QC of MSLP
         AWIPS 5.2.1 LAPS
          Improvements:
• Surface Analysis
  – Improved Successive Correction considers
     instrument and background errors
  – Works with uneven station spacing and terrain
  – Reduction of bulls-eye effects (that had
    occurred even with valid stations)
• Improved Surface Pressure Consistency
  – MSLP
  – Reduced
  – Unreduced (terrain following)
           AWIPS 5.2.2 LAPS
            Improvements:
• Additional Backgrounds such as AVN
   – Supports LAPS in Alaska, Pacific
   – Domain Relocatability
• Surface Analysis
   – Improved fit between obs and analysis
   – Corrected “theta check” for temperature analysis at
     high elevation sites
• Stability Indices added
   – Wet Bulb Zero, K, TT, Showalter, LCL
      Candidate Future Improvements:

• GUI
  – Domain Resizability
  – Graphical Product Monitor
• Surface Obs QC
  –   Turning on Kalman Filter QC (sfc_qc.exe)
  –   Tighten T, Td QC checks
  –   Allow namelist adjustment of QC checks
  –   Handling of surface stations with known bias
Candidate Future Improvements (cont):
• Surface Analysis
   – Land/Sea weighting to help with coastline effects
   – Adjustment of reduced pressure height
• Other Background Models
   – Hi-res Eta?
• Improved use of radar data
   –   Multiple radars?
   –   Wideband Level-II data?
   –   Sub-cloud evaporation
   –   Doppler radial velocities
Candidate Future Improvements (cont.)

• Use of visible & 3.9u satellite in cloud analysis
• LI/CAPE/CIN with different parcels in boundary
  layer
• New (Bunkers) method for computing storm
  motions feeding to helicity determination
• Wind profiler
  – Include obs from just outside the domain
  – Implies restructuring wind analysis
• ACARS
• Forecast Model (Hot-Start MM5)
      Sources of LAPS Information

• The LAPS homepage http://laps.fsl.noaa.gov
 provides access to many links including:

• What is in AWIPS LAPS?
http://laps.fsl.noaa.gov/LAPB/AWIPS_WFO_page.htm
             Analysis Information
LAPS analysis discussions are near the bottom of:
http://laps.fsl.noaa.gov/presentations/presentations.html

Especially noteworthy are the links for

•   Satellite Meteorology
•   Analyses: Temperature, Wind, and Clouds/Precip.
•   Modeling and Visualization
    –   A Collection of Case Studies
            3-D Temperature
• Interpolate from model (RUC)
• Insert RAOB, RASS, and ACARS if available
  – 3-Dimensional weighting used
• Insert surface temperature and blend upward
  – depending on stability and elevation
     • Surface temperature analysis depends on
        – METARS, Buoys, and LDAD
        – Gradients adjusted by IR temperature
               3-D Clouds

• Preliminary analysis from vertical “soundings”
  derived from METARS and PIREPS
• IR used to determine cloud top (using
  temperature field)
• Radar data inserted (3-D if available)
• Visible satellite can be used
3-D Cloud Analysis
LAPS Snow Cover and Precip. Type
          LAPS 3-D Water Vapor
        (Specific Humidity) Analysis
• Interpolates background field from synoptic-scale model forecast
• QCs against LAPS temperature field (eliminates possible
  supersaturation)
• Assimilates RAOB data
• Assimilates boundary layer moisture from LAPS Sfc Td analysis
• Scales moisture profile (entire profile excluding boundary layer)
  to agree with derived GOES TPW (processed at NESDIS)
• Scales moisture profile at two levels to agree with GOES
  sounder radiances (channels 10, 11, 12). The levels are 700-500
  hPa, and above 500
• Saturates where there are analyzed clouds
• Performs final QC against supersaturation
Products Derived from Wind Analysis
            Case Study Example

An example of the use of LAPS in convective event

                  14 May 1999

           Location: DEN-BOU WFO
             Quote from the Field
"...for the hourly LAPS soundings, you can go to
  interactive skew-T, and loop the editable soundings
  from one hour to the next, and get a more accurate
  idea of how various parameters are changing on an
  hourly basis...nice. We continue to find
  considerable use of the LAPS data (including
  soundings) for short-term convective forecasting."
               Case Study Example
• On 14 May, moisture is in place. A line of storms
  develops along the foothills around noon LT (1800 UTC)
  and moves east. LAPS used to diagnose potential for
  severe development. A Tornado Watch issued by ~1900
  UTC for portions of eastern CO and nearby areas.

• A brief tornado did form in far eastern CO west of GLD
  around 0000 UTC the 15th. Other tornadoes occurred later
  near GLD.
NOWRAD
and
METARS
with LAPS
surface
CAPE
2100 UTC
NOWRAD
and
METARS
with LAPS
surface
CIN
2100 UTC
Dewpoint
max
appears
near CAPE
max, but
between
METARS
2100 UTC
Examine
soundings
near
CAPE
max at
points B,
E and F
2100 UTC
Soundings
near
CAPE
max at B,
E and F
2100 UTC
RUC also
has
dewpoint
max near
point E
2100 UTC
LAPS &
RUC
sounding
comparison
at point E
(CAPE
Max)
2100 UTC
CAPE
Maximum
persists in
same area
2200 UTC
CIN
minimum
in area of
CAPE
max
2200 UTC
Point E,
CAPE has
increased to
2674 J/kg
2200 UTC
Convergence
and
Equivalent
Potential
Temperature
are co-located
2100 UTC
How does
LAPS sfc
divergence
compare to
that of the
RUC?
Similar over
the plains.
2100 UTC
LAPS winds
every 10 km,
RUC winds
every 80 km
2100 UTC
         Case Study Example (cont.)

• The next images show a series of LAPS soundings
  from near LBF illustrating some dramatic changes
  in the moisture aloft. Why does this occur?
LAPS
sounding
near LBF
1600 UTC
LAPS
sounding
near LBF
1700 UTC
LAPS
sounding
near LBF
1800 UTC
LAPS
sounding
near LBF
2100 UTC
          Case Study Example (cont.)

• Now we will examine some LAPS cross-sections
  to investigate the changes in moisture, interspersed
  with a sequence of satellite images showing the
  location of the cross-section, C-C` (from WSW to
  ENE across DEN)
Visible image
with LAPS
700 mb temp
and wind and
METARS
1500 UTC


Note the
strong thermal
gradient aloft
from NW-S
(snowing in
southern WY)
and the LL
moisture
gradient
across eastern
CO.
LAPS Analysis at 1500 UTC, Generated with Volume Browser
Visible image
1600 UTC
Visible image
1700 UTC
LAPS
cross-
section
1700 UTC
LAPS
cross-
section
1800 UTC
LAPS
cross-
section
1900 UTC
          Case Study Example (cont.)

• The cross-sections show some fairly substantial
  changes in mid-level RH. Some of this is related to
  LAPS diagnosis of clouds, but the other changes
  must be caused by the satellite moisture analysis
  between cloudy areas. It is not clear how
  believable some of these are in this case.
             Case Study Example (cont.)
• Another field that can be monitored with LAPS is helicity. A
  description of LAPS helicity is at
   http://laps.fsl.noaa.gov/frd/laps/LAPB/AWIPS_WFO_page.htm

• A storm motion is derived from the mean wind (sfc-300 mb) with an
  off mean wind motion determined by a vector addition of 0.15 x
  Shear vector, set to perpendicular to the mean storm motion

• Next we’ll examine some helicity images for this case. Combining
  CAPE and minimum CIN with helicity agreed with the path of the
  supercell storm that produced the CO tornado.
NOWRAD
with
METARS
and LAPS
surface
helicity
1900 UTC
NOWRAD
with
METARS
and LAPS
surface
helicity
2000 UTC
NOWRAD
with
METARS
and LAPS
surface
helicity
2100 UTC
NOWRAD
with
METARS
and LAPS
surface
helicity
2200 UTC
NOWRAD
with
METARS
and LAPS
surface
helicity
2300 UTC
         Case Study Example (cont.)

• Now we’ll show some other LAPS fields that
  might be useful (and some that might not…)
Divergence
compares
favorably
with the
RUC
The omega
field has
considerable
detail (which
is highly
influenced
by
topography
LAPS
Topography
Vorticity is
a smooth
field in
LAPS
Comparison
with the
Eta does
show some
differences.
Are they
real?
Stay Away
from DivQ
at 10 km
Why Run Models in the Weather Office?

• Diagnose local weather features having
  mesoscale forcing
  – sea/mountain breezes
  – modulation of synoptic scale features
• Take advantage of high resolution terrain
  data to downscale national model forecasts
  – orography is a data source!
       Why Run Models in the
       Weather Office? (cont.)
• Take advantage of unique local data
  – radar
  – surface mesonets
• Have an NWP tool under local control for
  scheduled and special support
• Take advantage of powerful/cheap
  computers
SFM forecast
showing
details of the
orographic
precipitation,
as well as
capturing the
Longmont
anticyclone
flow on the
plains
              LAPS Summary
• You can see more about our local modeling
  efforts at
 http://laps.fsl.noaa.gov/szoke/lapsreview/start.html
• What else in the future? (hopefully a more
  complete input data stream to AWIPS
  LAPS analysis)
The End

				
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