The Sensitivity of a Real-Time Four- Dimensional Data Assimilation Procedure to Weather Research and Forecast Model Simulations: A Case Study Hsiao-ming Hsu and Yubao Liu NCAR/RAP

Motivations WRF real-case initialization schemes:  SI – interpolation from other models  3DVAR – hopeful, but 3D, simplified balance  4DVAR – bright future Hereby, we look into a method to initialize WRF with a four-dimensional dynamically and physically consistent analysis, which incorporates all available synoptic and asynoptic observations. NCAR/ATEC MM5-based RT-FDDA system provides this kind of analysis to initialize WRF forecast.

NCAR/ATEC RTFDDA Built around MM5 (Jennifer et al. 2001, Liu et al. 2002) Continuous observation nudging (Stauffer and Seaman 1994) Multi-grids (1 km fine meshes) 3 hourly-cycling Operated at 5 ATEC ranges and support several special tasks (CO-fire, Olympics…) Cold start t Forecasts FDDA Day NDay 0

During Year-2002 Winter Olympics at SLC, RTFDDA was operational for 2 months. There was a snow storm event during March 13. A pair of contrast experiments of 12-hr WRF forecasts with different initial conditions were conducted, started at 00Z, March 13. CASE

EXP1- “Cold start” WRF WRF initial condition was generated by re- analysis of ETA forecast with available observations at 00Z, March 13. EXP2 - “Warm start” WRF WRF initial condition was obtained from the RTFDDA analysis which had been running continuously from a “cold start” 84 hours ago. EXP3 - “Warm start” MM5 Same as EXP2, but with MM5 (from op-RTFDDA). Experiment Design

Domain configuration 82 x 70 dx = 36 km 36 layers 12 levels in 1 km AGL Coarse mesh only

Hourly Precipitation of 1 – 12 Forecasts Cold startWarm start

Subjective verification of 1 hour precipitation at 3-h forecast A A A BB B B C C C C OBS IR OBS Radar Warm start Cold start

WRF Forecast at 03Z RTFDDA forecast at 03Z

Summary Significant differences were observed between the “cold start” and the “warm start” WRF forecasts. The “warm-start” WRF run compares more favorable to observations. The “Warm start” WRF results are very similar to those from RTFDDA (MM5) during the first few fours of forecasts. It is evident that reasonable benefit of reduced dynamical and cloud/precipitation “spin-up” during first few hours can be obtained by interfacing MM5 RTFDDA process to WRF initialization.

Future Work Comparison study on higher resolutions and severe weather cases. Ingesting RTFDDA cloud/precipitation analyses into “warm start” WRF. Implement “warm start” WRF in the same operational environment of RTFDDA MM5 Quantitative verification of “warm-start” WRF against various observations for a longer-term parallel tests with MM5.