January 24, 2005 The LAPS “hot start” Initializing mesoscale forecast models with active cloud and precipitation processes Paul Schultz NOAA Forecast Systems Laboratory Local Analysis and Prediction Branch

January 24, 2005 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

January 24, 2005 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?

January 24, 2005 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

LAPS Three-Dimensional Cloud Analysis METAR Pilot reports Doppler radar Satellites

January 24, 2005 Cloud typing “stable” “unstable”

January 24, 2005 Example cloud type analysis

January 24, 2005 Cumulus vertical motions

January 24, 2005 LAPS Dynamic Balance Adjustment ( ) b are background quantities; (^) are solution increments from background; ( )’ are observation differences from background

January 24, 2005 LAPS Dynamic Balance Adjustment FHFLFHFL

January 24, 2005 Results 3D Simulated Clouds 00Hr Fcst, Valid 28 Mar 01/00Z01Hr Fcst, Valid 28 Mar 01/00Z

January 24, 2005 Example: first forecast hour, 5-min frames

January 24, 2005 MODEL NOISE |dp/dt| Balanced Unbalanced

January 24, 2005 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.

Model Initialization Comparisons Time-n Time MM5 Forecast LAPS Analyses MM5 NudgingMM5 Forecast Eta Eta LBC for all runs Dynamically balanced, Cloud-consistent LAPS LAPS II Cold start Warm start Hot start no LAPS analysis; interpolate from larger-scale model pre-forecast nudging to a series of LAPS analyses; sometimes called dynamic initialization diabatic initialization using the balanced LAPS analysis

Results of Initialization Comparisons

Results of Initialization Comparison

January 24, 2005 Example – 21 June 2001/0600 UTC Run GOES IR+NOWRAD, Valid 21/0600 UTC MM5 00 hr Forecast, Valid 21/0600 UTC

January 24, 2005 Example – 21 June 2001/0600 UTC Run GOES IR+NOWRAD, Valid 21/0700 UTC MM5 01 hr Forecast, Valid 21/0700 UTC

January 24, 2005 Example – 21 June 2001/0600 UTC Run GOES IR+NOWRAD, Valid 21/0800 UTC MM5 02 hr Forecast, Valid 21/0800 UTC

January 24, 2005 Example – 21 June 2001/0600 UTC Run GOES IR+NOWRAD, Valid 21/0900 UTC MM5 03 hr Forecast, Valid 21/0900 UTC

January 24, 2005 Example – 21 June 2001/0600 UTC Run GOES IR+NOWRAD, Valid 21/1000 UTC MM5 04 hr Forecast, Valid 21/1000 UTC

January 24, 2005 Example – 21 June 2001/0600 UTC Run GOES IR+NOWRAD, Valid 21/1100 UTC MM5 05 hr Forecast, Valid 21/1100 UTC