MJO Prediction Skill of the Subseasonal-to-Seasonal Prediction Models
نویسندگان
چکیده
منابع مشابه
Subseasonal to Seasonal Prediction
The subseasonal to seasonal timescale provides a unique opportunity to capitalise on the expertise of the weather and climate research communities, and to bring them together to improve predictions on a timescale of particular relevance to the Global Framework for Climate Services (GFCS). A planning group which included representatives from WWRP/THORPEX, WCRP, CBS and CCl drafted the implementa...
متن کاملSubseasonal to Seasonal Prediction
The subseasonal to seasonal timescale provides a unique opportunity to capitalise on the expertise of the weather and climate research communities, and to bring them together to improve predictions on a timescale of particular relevance to the Global Framework for Climate Services (GFCS). A planning group which included representatives from WWRP/THORPEX, WCRP, CBS and CCl drafted the implementa...
متن کاملSUBSEASONAL TO SEASONAL PREDICTION RESEARCH IMPLEMENTATION PLAN 22 June 2012
The subseasonal to seasonal timescale provides a unique opportunity to capitalise on the expertise of the weather and climate research communities, and to bring them together to improve predictions on a timescale of particular relevance to the Global Framework for Climate Services (GFCS). A planning group which included representatives from WWRP/THORPEX, WCRP, CBS and CCl drafted the implementa...
متن کاملThe Experimental MJO Prediction Project
AMERICAN METEOROLOGICAL SOCIETY | 425 W eather prediction is typically concerned with lead times of hours to days, while seasonal-tointerannual climate prediction is concerned with lead times of months to seasons. Recently, there has been growing interest in “subseasonal” forecasts—those that have lead times on the order of weeks (e.g., Schubert et al. 2002; Waliser et al. 2003; Waliser et al. ...
متن کاملTracking Seasonal Prediction Models
A machine learning algorithm for combining predictions is applied to seasonal predictions of the NINO3.4 index from six coupled atmosphere-ocean models. The algorithm adaptively tracks a dynamic sequence of “best experts” and produces a probability that a particular expert is best. Averaging based on this probability effectively yields a multi-model prediction. The algorithm gives seasonal pred...
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ژورنال
عنوان ژورنال: Journal of Climate
سال: 2018
ISSN: 0894-8755,1520-0442
DOI: 10.1175/jcli-d-17-0545.1