期刊
METEOROLOGICAL APPLICATIONS
卷 28, 期 4, 页码 -出版社
WILEY
DOI: 10.1002/met.2011
关键词
precipitation anomaly; PSA; S2S; SAM; South America; sub-seasonal predictions; teleconnections
资金
- Fundacao de Amparo a Pesquisa do Estado de Sao Paulo-CLIMAX-Belmont Forum [2015/50687-8]
- Proyectos de Investigacion Cientifica y Tecnologica [2018-03046]
- UBACyT Project [20020170100428BA]
This study aims to investigate the ability of two S2S project models to predict Southern Hemisphere teleconnections and anomalous precipitation over South America. The models showed good performance in forecasting the Southern Annular Mode and Pacific South America pattern, exhibiting the capability to predict extreme cases in advance by several weeks.
Precipitation predictions in the sub-seasonal timescale are very important for several sectors such as agriculture and energy in regions of South America that are very much affected by precipitation extremes, both excess and lack of rain. The aim of the present study is to investigate the ability of two S2S project models (ECMWF and NCEP) to detect the Southern Hemisphere teleconnections in model hindcasts and the associated anomalous precipitation over South America. The period of analyses is 1999-2010 for the austral summer season (December-January-February). Both models represented adequately the Southern Annular Mode (SAM) pattern in predictions up to 4 weeks ahead and the Pacific South America (PSA) pattern up to 3 weeks. Atmospheric variables of observed extreme cases of SAM were well predicted by the two models, 2 and 3 weeks in advance. The models predicted well atmospheric variables in observed extreme cases of PSA, 2 weeks in advance and with less intensity in the third week. Precipitation anomaly signals associated with these modes were well predicted 2 weeks in advance, although with different intensities. The good ability of the models hindcast in predicting teleconnection patterns and precipitation anomalies over South America provides more confidence to use predictions at sub-seasonal timescale.
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