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Skill of South Asian Precipitation Forecasts in Multiple Seasonal Prediction Systems

Authors: Stacey, Jessica; Bett, Philip; Colledge, Francis; Colman, Andrew; Daron, Joseph; Graham, Richard; Janes, Tamara; +2 Authors

Skill of South Asian Precipitation Forecasts in Multiple Seasonal Prediction Systems

Abstract

The South Asia Seasonal Climate Outlook Forum (SASCOF) issues seasonal tercile precipitation forecasts to provide advance warning of anomalously dry or wet monsoon seasons in South Asia. To increase objectivity of the SASCOF seasonal outlook, the World Meteorological Organisation recommends using a multi-model ensemble combining the most skilful dynamical seasonal models for the region. We assess the skill of 12 seasonal climate models at forecasting seasonal precipitation totals for 1993-2016 for the southwest (July-September) and northeast (October-December) monsoon seasons at both regional and national levels for Afghanistan, Bangladesh, Nepal, and Pakistan. Unlike other skill assessments, we use the same forecast periods, hindcast initialisation months and domain used at the SASCOF. All models demonstrate positive skill when regionally averaged, especially for the southwest monsoon season, noting considerable spatial differences. Models demonstrate highest skill in areas with strong ENSO teleconnections in the observations, e.g., central/north India and Nepal during the southwest monsoon, and Afghanistan and north Pakistan during the northeast monsoon. Model skill is especially low in northwest India and northeast of the region during the southwest monsoon, e.g., Bangladesh (despite high precipitation totals) coinciding with a weak ENSO teleconnection. The IOD teleconnection is less pronounced in the SW monsoon season, whereas the spatial pattern for the NE monsoon season, closely resembles that of ENSO. Due to the high variability in model skill, we recommend including all models in the multi-model ensemble for the basis of the SASCOF regional outlook but discounting poorly performing models at the national level.

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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