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Skilful seasonal predictions of Global Monsoon summer precipitation with DePreSys3

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Monerie, P.-A. orcid id iconORCID: https://orcid.org/0000-0002-5304-9559, Robson, J. I. orcid id iconORCID: https://orcid.org/0000-0002-3467-018X, Dunstone, N. J. and Turner, A. G. orcid id iconORCID: https://orcid.org/0000-0002-0642-6876 (2021) Skilful seasonal predictions of Global Monsoon summer precipitation with DePreSys3. Environmental Research Letters, 16 (10). ISSN 1748-9326 doi: 10.1088/1748-9326/ac2a65

Abstract/Summary

We assess skill of the Met Office’s DePreSys3 prediction system at forecasting summer global monsoon precipitation at the seasonal time scale (2-5 month forecast period). DePreSys3 has significant skill at predicting summer monsoon precipitation (r=0.68), but the skill varies by region and is higher in the northern (r=0.68) rather than in the southern hemisphere (r=0.44). To understand the sources of precipitation forecast skill, we decompose the precipitation into several dynamic and thermodynamic components and assess the skill in predicting each. While dynamical changes of the atmospheric circulation primarily contribute to global monsoon variability, skill at predicting shifts in the atmospheric circulation is relatively low. This lower skill partly relates to DePreSys3’s limited ability to accurately simulate changes in atmospheric circulation patterns in response to sea surface temperature forcing. Skill at predicting the thermodynamic component of precipitation is generally higher than for the dynamic component, but thermodynamic anomalies only contribute a small proportion of the total precipitation variability. Finally, we show that the use of a large ensemble improves skill for predicting monsoon precipitation, but skill does not increase beyond 20 members.

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/100481
Item Type Article
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher Institute of Physics
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