4.7 Article

Skilful seasonal predictions of global monsoon summer precipitation with DePreSys3

Journal

ENVIRONMENTAL RESEARCH LETTERS
Volume 16, Issue 10, Pages -

Publisher

IOP Publishing Ltd
DOI: 10.1088/1748-9326/ac2a65

Keywords

DePreSys3; seasonal prediction; global monsoon; skill; summer monsoon precipitation; dynamic; thermodynamic

Funding

  1. EMERGENCE project under the Natural Environment Research Council (NERC) [NE/S004890/1]
  2. Natural Environment Research Council (NERC) via the National Centre for Atmospheric Science (NCAS)
  3. UK Governments Newton Fund
  4. Indian Ministry of Earth Sciences (MoES)
  5. UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund
  6. DOVE project
  7. NERC ACSIS program
  8. NERC [NE/S004890/1] Funding Source: UKRI

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The study evaluated the skill of the Met Office's DePreSys3 prediction system in forecasting summer global monsoon precipitation at the seasonal time scale, showing significant skill in predicting summer monsoon precipitation, with higher skill in the northern hemisphere compared to the southern hemisphere. Skill in predicting shifts in the atmospheric circulation is relatively low, with the dynamical component primarily contributing to global monsoon variability. The use of a large ensemble improves skill for predicting monsoon precipitation, but skill does not increase beyond 20 members.
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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