Revamping extended range forecast of Indian summer monsoon
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Revamping extended range forecast of Indian summer monsoon Pushpendra Raghav1 · Swatah Snigdha Borkotoky1 · Jisha Joseph1 · Rajib Chattopadhyay2 · A. K. Sahai2 · Subimal Ghosh1,3 Received: 4 March 2020 / Accepted: 31 August 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Forecast of the Indian summer monsoon on an extended range (beyond the conventional one-week lead time) is critical for an agronomic economy like India. Although dynamic models have been quite successful in capturing and representing monsoon circulation, they fail to sustain this skill beyond the standard weather time scale (7–10 days). As such, the present study is directed at developing a computationally feasible, yet reliable method of statistical downscaling that further improves the present skill of global dynamic models for extended range forecasting. We quantitatively demonstrate the feasibility of this post-processing statistical module for improving the predictability of the dynamic Extended Range Prediction System (ERPAS), which is developed by Indian Institute of Tropical Meteorology, Pune, India and now operational in the country. It first develops climate cluster(s) (rainfall states in the present case), then builds a statistical relationship between these clusters and a set of appropriate climate variables using a robust and advanced classification technique known as Extreme Gradient Boosting (XGboost), and eventually delivers the real-valued precipitation at individual grid cells via a non-parametric regression. The module is able to skilfully capture the active and break phases of the Indian summer monsoon, and also subsequently project them for the ensuing regression component of the module. This approach shows to significantly boost the prediction skill over the Core Monsoon Zone of Indian mainland up to a lead time of 4 weeks. Our statistical downscaled model is comparable in the week 1 lead time but outperforms global models for 2nd, 3rd, and 4th weeks lead time. Nonetheless, this performance is retained only in the northern and central region, and not ubiquitous over the rest of India. Keywords Extended range prediction · Multi-model ensemble · Indian summer monsoon · Statistical learning
1 Introduction Indian summer monsoon rainfall and its variability (both at intra-seasonal and inter-annual level) has a profound influence on the national economy and also on several key driving sectors of public interest like agriculture (Gadgil and Gadgil 2006) and water resources planning. As such, a reliable forecast of Indian summer monsoon rainfall Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00382-020-05454-5) contains supplementary material, which is available to authorized users. * Subimal Ghosh [email protected] 1
Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, India
2
Indian Institute of Tropical Meteorology, Pune, India
3
Interdisciplinary Program in Climate Studies, Indian Institute of Technology B
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