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Do Seasonal Forecasts of Indian Summer Monsoon Rainfall Show Better Skill with February Initial Conditions?

Rajendran, K and Surendran, S and Varghese, SJ and Chakraborty, A (2021) Do Seasonal Forecasts of Indian Summer Monsoon Rainfall Show Better Skill with February Initial Conditions? In: Current Science, 120 (12). pp. 1863-1874.

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Official URL: https://doi.org/10.18520/cs/v120/i12/1863-1874


Prediction for Indian summer monsoon rainfall (ISMR) is generated by integrating model from initial conditions (ICs) of weather at some time prior to sea- son. We examine the factors responsible for the widely reported highest ISMR forecast skill for February ICs in climate forecast system (CFSv2) model. Skill for February ICs is highest only based on correlation bet- ween observed and predicted year-to-year variation of ISMR, whereas other skill scores indicate highest skill for late-April/early-May ICs having shorter yet useful forecast lead-time. Higher correlation for February ICs arises from correct forecasting of 1983 ISMR excess, which is however due to wrong forecast of La Niña and correlation drops to lower value than that for late-April/early-May ICs if 1983 is excluded. Fore- cast skill for sea-surface temperature variation over equatorial central Pacific (ENSO) in Boreal summer is lowest for February ICs indicating role of dynamical drift induced by long forecast lead-time. Model defi- ciencies such as oversensitivity of ISMR to ENSO and unrealistic ENSO influence on variation of convection over equatorial Indian Ocean (EQUINOO) lead to errors in ISMR forecasting. In CFSv2, ISMR is mostly decided by ENSO whereas in observation it is influ- enced by ENSO and EQUINOO independently. © 2021. All Rights Reserved.

Item Type: Journal Article
Publication: Current Science
Publisher: Indian Academy of Sciences
Additional Information: The copyright for this article belongs to Indian Academy of Sciences
Department/Centre: Division of Mechanical Sciences > Divecha Centre for Climate Change
Date Deposited: 07 Oct 2021 15:53
Last Modified: 07 Oct 2021 15:53
URI: http://eprints.iisc.ac.in/id/eprint/69609

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