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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.

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using laps in the forecast office
Using LAPS in the Forecast Office

By

Steve Albers

May 2002

slide2
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

strategic plan for the modernization and associated restructuring of the national weather service

“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
  • LAPS Grid (in AWIPS)
    • Hourly Time Cycle
    • Horizontal Resolution = 10 km
    • Vertical Resolution = 50 mb
    • Size: 61 x 61 x 21
laps data sources
LAPSDataSources

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 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
Problems with Local Data
  • Poor Maintenance
  • Poor Communications
  • Poor Calibration

Result ----------------> Inaccurate,

Irregular,

Observations

multi layered quality control
Multi-layered Quality Control
  • Gross Error Checks
    • RoughClimatologicalEstimates
  • Station Blacklist
  • Dynamical Models
    • Use of meso-beta models
    • Standard Deviation Check
  • Statistical Models (Kalman Filter)
    • Buddy Checking
standard deviation check
Standard Deviation Check
  • Compute Standard Deviation of observations-background
  • Remove outliers
  • Now adjustable via namelist
kalman qc scheme
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
awips 5 1 2 laps improvements
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
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
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
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
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 cont22
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
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
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
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
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
laps 3 d water vapor specific humidity analysis
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
case study example
Case Study Example

An example of the use of LAPS in convective event

14 May 1999

Location: DEN-BOU WFO

quote from the field
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 example35
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.
case study example cont
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?
case study example cont54
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)
slide55

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.

case study example cont62
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 cont63
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.
case study example cont69
Case Study Example (cont.)
  • Now we’ll show some other LAPS fields that might be useful (and some that might not…)
why run models in the weather office
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
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
slide80

SFM forecast showing details of the orographic precipitation, as well as capturing the Longmont anticyclone flow on the plains

laps summary
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)
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