The LAPS

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The LAPS hot startInitializing mesoscale
forecast models with active cloud and
precipitation processes

• Paul Schultz
• NOAA Forecast Systems Laboratory
• Local Analysis and Prediction Branch

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The LAPS team

• John McGinley, branch chief, variational methods
• Paul Schultz, project manager, modeler, your
  speaker today
• Brent Shaw, most recent lead modeler
• Steve Albers, cloud analysis, temp/wind analysis
• Dan Birkenheuer, humidity analysis
• John Smart, everything

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Goals

• Address NWP spin up problem
• Explicit short-range (0-6 h) QPFs and cloud
  forecasts
• Focus on a local modeling capability
• Must be computationally inexpensive
• Exploit all locally-available meteorological data
• High-resolution grids
• Robust data ingest, QC, and fusion
• Develop a flexible solution for easy technology
  transfer
• Hardware/OS independence
• Choice of mesoscale model
• Demonstrated in WRF, MM5, RAMS
• COAMPS, ARPS, NMM?

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Basis

• Scale analysis of thermodynamic energy equation
  appropriate for convective-scale motions strongly
  suggests latent heat release forces the action
• Put saturated updrafts where they belong
• Relax 3-D horizontal divergence to support
  updrafts

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LAPS Three-Dimensional Cloud Analysis
Satellites
Pilot reports
METAR
METAR
METAR
Doppler radar
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Cloud typing
stable
unstable
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Example cloud type analysis
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Cumulus vertical motions
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LAPS Dynamic Balance Adjustment
( ) b are background quantities () are
solution increments from background ( ) are
observation differences from background
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LAPS Dynamic Balance Adjustment
FH FL
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Results
3D Simulated Clouds
00Hr Fcst, Valid 28 Mar 01/00Z
01Hr Fcst, Valid 28 Mar 01/00Z
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Example first forecast hour, 5-min frames
hot start loop
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MODEL NOISE dp/dt
Unbalanced
Balanced
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Quantitative Assessment

• Comparison of parallel model runs using three
  kinds of initialization (hot, warm, cold)
  otherwise identical
• Objective verification of model performance using
  hot start vs. other initialization methods
• Approximately 40 forecast cycles during Jan 2001
• Gridded comparisons using LAPS analysis as truth
• Computed various threat scores, RMSE, etc.

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Model Initialization Comparisons
Time-n Time
Cold start
MM5 Forecast
no LAPS analysis interpolate from larger-scale
model
Eta
Warm start
LAPS Analyses
pre-forecast nudging to a series of LAPS
analyses sometimes called dynamic initialization
MM5 Nudging
MM5 Forecast
Hot start
MM5 Forecast
diabatic initialization using the balanced LAPS
analysis
LAPS II
Dynamically balanced, Cloud-consistent LAPS
Eta LBC for all runs
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Results of Initialization Comparisons
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Results of Initialization Comparison
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Example 21 June 2001/0600 UTC Run
MM5 00 hr Forecast, Valid 21/0600 UTC
GOES IRNOWRAD, Valid 21/0600 UTC
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Example 21 June 2001/0600 UTC Run
MM5 01 hr Forecast, Valid 21/0700 UTC
GOES IRNOWRAD, Valid 21/0700 UTC
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Example 21 June 2001/0600 UTC Run
MM5 02 hr Forecast, Valid 21/0800 UTC
GOES IRNOWRAD, Valid 21/0800 UTC
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Example 21 June 2001/0600 UTC Run
MM5 03 hr Forecast, Valid 21/0900 UTC
GOES IRNOWRAD, Valid 21/0900 UTC
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Example 21 June 2001/0600 UTC Run
MM5 04 hr Forecast, Valid 21/1000 UTC
GOES IRNOWRAD, Valid 21/1000 UTC
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Example 21 June 2001/0600 UTC Run
MM5 05 hr Forecast, Valid 21/1100 UTC
GOES IRNOWRAD, Valid 21/1100 UTC