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Using LAPS in the Forecast Office - PowerPoint PPT Presentation

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

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Using LAPS in the Forecast Office


Steve Albers

May 2002

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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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Why do analysis in the local office?

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-Strategic plan for the modernization and associated restructuring of the National Weather Service

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  • LAPS Grid (in AWIPS)

    • Hourly Time Cycle

    • Horizontal Resolution = 10 km

    • Vertical Resolution = 50 mb

    • Size: 61 x 61 x 21

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Data Acquisition and Quality Control

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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.

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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

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Problems with Local Data

  • Poor Maintenance

  • Poor Communications

  • Poor Calibration

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



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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

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Standard Deviation Check

  • Compute Standard Deviation of observations-background

  • Remove outliers

  • Now adjustable via namelist

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Kalman QC Scheme


  • 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

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Kalman Flow Chart

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AWIPS 5.1.2 LAPS Improvements:

  • Wind Profiler Ingest restored

    • QC threshold tightened

  • Surface Stations

    • More local (LDAD) station data

    • Improved QC of MSLP

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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)

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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

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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

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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

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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


  • Forecast Model (Hot-Start MM5)

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Sources of LAPS Information

  • The LAPS homepage

    provides access to many links including:

  • What is in AWIPS LAPS?

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Analysis Information

LAPS analysis discussions are near the bottom of:

Especially noteworthy are the links for

  • Satellite Meteorology

  • Analyses: Temperature, Wind, and Clouds/Precip.

  • Modeling and Visualization

    • A Collection of Case Studies

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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

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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

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3-D Cloud Analysis

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LAPS Snow Cover and Precip. Type

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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

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Products Derived from Wind Analysis

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Case Study Example

An example of the use of LAPS in convective event

14 May 1999

Location: DEN-BOU WFO

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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."

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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.

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NOWRAD and METARS with LAPS surface CAPE

2100 UTC

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NOWRAD and METARS with LAPS surface CIN

2100 UTC

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Dewpoint max appears near CAPE max, but between METARS

2100 UTC

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Examine soundings near CAPE max at points B, E and F

2100 UTC

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Soundings near CAPE max at B, E and F

2100 UTC

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RUC also has dewpoint max near point E

2100 UTC

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LAPS & RUC sounding comparison at point E (CAPE Max)

2100 UTC

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CAPE Maximum persists in same area

2200 UTC

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CIN minimum in area of CAPE max

2200 UTC

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Point E, CAPE has increased to 2674 J/kg

2200 UTC

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Convergence and Equivalent Potential Temperature are co-located

2100 UTC

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How does LAPS sfc divergence compare to that of the RUC?

Similar over the plains.

2100 UTC

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LAPS winds every 10 km, RUC winds every 80 km

2100 UTC

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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?

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LAPS sounding near LBF

1600 UTC

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LAPS sounding near LBF

1700 UTC

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LAPS sounding near LBF

1800 UTC

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LAPS sounding near LBF

2100 UTC

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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)

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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.

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LAPS Analysis at 1500 UTC, Generated with Volume Browser

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Visible image

1600 UTC

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Visible image

1700 UTC

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LAPS cross-section

1700 UTC

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LAPS cross-section

1800 UTC

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LAPS cross-section

1900 UTC

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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.

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Case Study Example (cont.)

  • Another field that can be monitored with LAPS is helicity. A description of LAPS helicity is at

  • 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.

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NOWRAD with METARS and LAPS surface helicity

1900 UTC

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NOWRAD with METARS and LAPS surface helicity

2000 UTC

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NOWRAD with METARS and LAPS surface helicity

2100 UTC

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NOWRAD with METARS and LAPS surface helicity

2200 UTC

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NOWRAD with METARS and LAPS surface helicity

2300 UTC

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Case Study Example (cont.)

  • Now we’ll show some other LAPS fields that might be useful (and some that might not…)

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Divergence compares favorably with the RUC

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The omega field has considerable detail (which is highly influenced by topography

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LAPS Topography

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Vorticity is a smooth field in LAPS

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Comparison with the Eta does show some differences.

Are they real?

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Stay Away from DivQ at 10 km

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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!

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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

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

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LAPS Summary

  • You can see more about our local modeling efforts at

  • What else in the future? (hopefully a more complete input data stream to AWIPS LAPS analysis)

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The End

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