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Ensemble Forecasting: Thorpex-Tigge and use in Applications Tom Hopson.

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Presentation on theme: "Ensemble Forecasting: Thorpex-Tigge and use in Applications Tom Hopson."— Presentation transcript:

1 Ensemble Forecasting: Thorpex-Tigge and use in Applications Tom Hopson

2 Outline I.Thorpex-Tigge data set II.Ensemble forecast examples: a)Southwestern African flooding

3 TIGGE, the THORPEX Interactive Grand Global Ensemble component of the World Weather Research Programme TIGGE archive consists of ensemble forecast data from ten global NWP centers designed to accelerate the improvements in the accuracy of 1- day to 2 week high-impact weather forecasts for the benefit of humanity. starting from October 2006 available for scientific research near-real time forecasts (some centers delayed) THORPEX Interactive Grand Global Ensemble

4 Archive Status and Monitoring, Data Receipt Archive Centre Current Data Provider NCAR NCEP CMC UKMO ECMWF MeteoFrance JMA KMA CMA BoM CPTEC IDD/LDM HTTP FTP Unidata IDD/LDM Internet Data Distribution / Local Data Manager Commodity internet application to send and receive data NCDC

5 Archive Status and Monitoring, Variability between providers

6 Archive Status and Monitoring, Archive Completeness PL = Pressure Level, PT = 320K θ Level, PV = ± 2 Potential Vorticity Level, SL = Single/Surface Level VariableLvLECWFUKMOJMANCEPCMACMCBOMMetFKMACPTC Geopotential ZPL Specific HPL T U-velocityPL V-velocityPL Potential VorPT Potential TPV U-velocityPV V-VelocityPV U 10mSL V 10mSL CAPESL Conv. Inhib.SL Land-seaSL Mean SLPSL Orog.SL Skin TSL Snow D. H20SL Snow F. H20SL

7 Archive Status and Monitoring, Archive Completeness VariableLvLECWFUKMOJMANCEPCMACMCBOMMetFKMACPTC Soil Moist.SL Soil TSL Sunshine D.SL Surf. DPTSL Surf. ATmaxSL Surf. ATminSL Surf. ATSL Surf. PSL LW Rad. OutSL LH fluxSL Net RadSL Net Therm. RadSL Sensible Rad.SL Cloud CovSL Column WaterSL PrecipitationSL Wilt. PointSL Field Cap.SL PL = Pressure Level, PT = 320K θ Level, PV = ± 2 Potential Vorticity Level, SL = Single/Surface Level

8 Outline I.Motivation for ensemble forecasting and post- processing a)Introduce Quantile Regression (QR; Kroenker and Bassett, 1978) post-processing procedure II.Ensemble forecast verification III.Thorpex-Tigge data set IV.Ensemble forecast examples: a)Southwestern African flooding b)African meningitis c)US Army test range weather forecasting d)Bangladesh flood forecasting

9 Early May 2011, floods in southwestern Africa

10 -- examine ens forecasts … ECMWF 24hr precip

11 Early May 2011, floods in southwestern Africa -- examine ens forecasts … NCEP GEFS 24hr precip

12 Early May 2011, floods in southwestern Africa -- examine ens forecasts … ECMWF 5-day precip

13 Early May 2011, floods in southwestern Africa -- examine ens forecasts … NCEP GEFS 5day precip


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