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Tuning an Analysis and Incremental Analysis Updating (IAU) Assimilation for an Efficient High Resolution Forecast System Keith A. Brewster1 kbrewster@ou.edu.

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Presentation on theme: "Tuning an Analysis and Incremental Analysis Updating (IAU) Assimilation for an Efficient High Resolution Forecast System Keith A. Brewster1 kbrewster@ou.edu."— Presentation transcript:

1 Tuning an Analysis and Incremental Analysis Updating (IAU) Assimilation for an Efficient High Resolution Forecast System Keith A. Brewster1 Derek R. Stratman1,2 1Center for Analysis and Prediction of Storms 2School of Meteorology University of Oklahoma IOAS-AOLS New Orleans, LA January, 2016 Keith Brewster Senior Research Scientist & Associate Director Center for Analysis and Prediction of Storms University of Oklahoma OU-NJU Symposium May, 2015

2 Dallas-Fort Worth Urban Testbed
Population ~ 6.5 million (4th largest city in U.S.) Severe weather – Floods, tornadoes, hail, severe winds, droughts Weather sensitive industries – transportation hubs (ground, air, rail), sporting venues Network of Networks approach Primary focus is urban flooding & severe weather

3 Observation Summary Conventional Observations
Non-Conventional Observations ASOS EarthNetworks (WxBug) AWOS CWOP GST MoPED Oklahoma & W Texas Mesonets S-band WSR-88D Radars X-band Radars C-band TDWR Radars Radiosondes SODARs Radiometers

4 Surface Observations AWOS & ASOS WxBUG & CWOP

5 Building the Radar Network Dual-Doppler Angle Analysis
Combined Network NEXRAD: KFWS TDWR: TDAL, TDFW X-Band Network: 8 Radars Avg Beam Height: 600 m

6 2015 Operational Configuration
OSCER Boomer Xeon64 Oct-core SandyBridge 2.0 GHz Analyses at 400 m Resolution Dedicated Queue 3DVAR and Cloud Analysis Sfc, Profilers, VAD, Radar Wind and Reflectivity 5-minute Interval 400-m grid spacing Grid Size 448 x 456 x 28 Processors: 8 x 24 = 192 Obs Processing & Analysis Wallclock ~8 min Assimilation/Forecasts On-Demand 3DVAR and ARPS with 10-min IAU Sfc, Profilers, VAD, Radar Wind and Reflectivity Assimilation 2-hour Forward Forecast 15 minute interval 1-km grid spacing Grid Size 363 x 323 x 53 Processors: 12 x 16 = 192 Obs Processing + Analysis + Forecast Wallclock ~20-25 min

7 400-m Analyses 26 Dec 2015 0000 UTC 0005 UTC 0010 UTC 0015 UTC

8 Recent Improvements Updated the cloud analyses handling of reflectivity to be exactly reversible to reflectivity plotting algorithms for all microphysics options in ARPS and WRF. Updated IAU process to better handle multi-moment microphysics. Recently added SODAR and MoPED automated processing to realtime system. Tuning scripts to further reduce latency.

9 Updated IAU Scheme Variable-Dependent IAU Timing
Typical Triangular Timing Variable-Dependent Timing Variable-Dependent Timing

10 April 24, Hail Case Test Using Milbrant & Yau Single-Moment Microphysics

11 Variable-Dependent Timing “B”

12 Variable-Dependent Timing “C”

13 After 10 Minutes IAU Variable Anx IAU-Orig IAU-B IAU-C Snow 14.3 g/kg
4.0 5.3 10.0 Graupel 6.0 2.1 2.0 Hail 0.3 0.6 W 8.4 m/s 6.2 7.5 7.9 A B C

14 December, 2015 Operational Configuration

15 D/FW Metro Tornado Tracks, 26 Dec 2015
Blue Ridge EF-1 UTC Farmersville EF-1 UTC Copeville EF-2 UTC Garland-Rowlett EF-4 UTC Rockwall County Ovilla UTC Dallas County Preliminary Data NOAA Damage Survey Viewer

16 1-km Forecast Initialized 2330 UTC 26-Dec-2015

17 Conclusions/Future Plans
Realtime Data Analyses and Forecasts Operating with Low Latency Updated Hydrometeor Retrieval for Multiple Microphysics Schemes Developed new IAU with Variable-Dependent Timing New OSCER Schooner Coming Online Soon. Faster processors 2x10 cores per chip. Should allow update to 2-moment microphysics Thanks to CASA Colleagues from UMass, CSU, NCTCoG, OSCER Staff Thanks to National Mesonet Program, NOAA OS&T CAPS Forecasts Online Contact Info:


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