TY - GEN
AU - Y-Y. Park
AU - Roberto Buizza
AU - Martin Leutbecher
AB - TIGGE, the THORPEX Interactive Grand Global Ensemble, is a World Weather Research Programme to accelerate the improvements in the accuracy of 1-day to 2 week high-impact weather forecasts. This report reviews the status of the TIGGE archive, and discusses some preliminary results from predictability studies that would not have been possible without TIGGE. First, the key characteristics of the eight ensemble systems available in the TIGGE database at the time of writing (December 2007) are compared, and the strengths and weaknesses of each system are highlighted. Then, issues related to the generation of multi-model/multi-analysis ensemble products are discussed, and the potential value of combining different ensembles to generate medium-range products with a grand multi-model/multi-analysis global ensemble is investigated. Results should help developers of the different ensemble systems to better understand the characteristics of their ensemble, and should provide valuable information on how to improve their performance. This work proves the value of the TIGGE initiative, and illustrates some of the issues that could be addressed with the TIGGE data.
BT - ECMWF Technical Memoranda
DA - 01/2008
DO - 10.21957/64xzq5urj
LA - eng
M1 - 548
N2 - TIGGE, the THORPEX Interactive Grand Global Ensemble, is a World Weather Research Programme to accelerate the improvements in the accuracy of 1-day to 2 week high-impact weather forecasts. This report reviews the status of the TIGGE archive, and discusses some preliminary results from predictability studies that would not have been possible without TIGGE. First, the key characteristics of the eight ensemble systems available in the TIGGE database at the time of writing (December 2007) are compared, and the strengths and weaknesses of each system are highlighted. Then, issues related to the generation of multi-model/multi-analysis ensemble products are discussed, and the potential value of combining different ensembles to generate medium-range products with a grand multi-model/multi-analysis global ensemble is investigated. Results should help developers of the different ensemble systems to better understand the characteristics of their ensemble, and should provide valuable information on how to improve their performance. This work proves the value of the TIGGE initiative, and illustrates some of the issues that could be addressed with the TIGGE data.
PB - ECMWF
PY - 2008
EP - 43
T2 - ECMWF Technical Memoranda
TI - TIGGE: preliminary results on comparing and combining ensembles
UR - https://www.ecmwf.int/node/11602
ER -