TY - JOUR
T1 - Collaboration of the weather and climate communities to advance subseasonal-to-seasonal prediction
AU - Brunet, Gilbert
AU - Shapiro, Melvyn
AU - Hoskins, Brian
AU - Moncrieff, Mitch
AU - Dole, Randall
AU - Kiladis, George N.
AU - Kirtman, Ben
AU - Lorenc, Andrew
AU - Mills, Brian
AU - Morss, Rebecca
AU - Polavarapu, Saroja
AU - Rogers, David
AU - Schaake, John
AU - Shukla, Jagadish
PY - 2010/10
Y1 - 2010/10
N2 - Progress in long-range prediction depends on coordination of research in multimodel ensembles, in tropical convection and its interaction with the global circulation, in data assimilation, and in socio-economic applications. The four main areas of the World Weather Research Program-World Climate Research Program (WWRP-WCRP) collaboration includes seamless weather/climate prediction, including ensemble prediction systems (EPSs), multiscale organization of tropical convection and its two-way interaction with the global circulation, data assimilation for coupled models, and utilization of sub-seasonal and seasonal predictions for social and economic benefits. Data assimilation allows the diagnosis of errors while they are still small, before they interact significantly with other fields. The success of this endeavor will depend on the collaboration, commitment, excellence, and strength of the weather, climate, Earth system, and social science research communities.
AB - Progress in long-range prediction depends on coordination of research in multimodel ensembles, in tropical convection and its interaction with the global circulation, in data assimilation, and in socio-economic applications. The four main areas of the World Weather Research Program-World Climate Research Program (WWRP-WCRP) collaboration includes seamless weather/climate prediction, including ensemble prediction systems (EPSs), multiscale organization of tropical convection and its two-way interaction with the global circulation, data assimilation for coupled models, and utilization of sub-seasonal and seasonal predictions for social and economic benefits. Data assimilation allows the diagnosis of errors while they are still small, before they interact significantly with other fields. The success of this endeavor will depend on the collaboration, commitment, excellence, and strength of the weather, climate, Earth system, and social science research communities.
UR - https://www.scopus.com/pages/publications/78649314548
U2 - 10.1175/2010BAMS3013.1
DO - 10.1175/2010BAMS3013.1
M3 - Article
AN - SCOPUS:78649314548
SN - 0003-0007
VL - 91
SP - 1397
EP - 1406
JO - Bulletin of the American Meteorological Society
JF - Bulletin of the American Meteorological Society
IS - 10
ER -