Abstract
The Indian Institute of Tropical Meteorology (IITM) has generated seasonal and extended range hindcast products for 1981–2008 and 2003–2016, respectively, using the IITM-Climate Forecast System (IITM-CFS) coupled model at various resolutions and configurations. Notably, our observational analysis suggests that for the 1981–2008 period, the tropical Indo-Pacific drivers, namely, the canonical El Niño-Southern Oscillation (ENSO), ENSO Modoki, and Indian Ocean Dipole (IOD). are significantly associated with the observed Kharif rice production (KRP) of various rice-growing Indian states. In this paper, using the available hindcasts, we evaluate whether these state-of-the-art retrospective forecasts capture the relationship of the KRP of multiple states with the local rainfall as well as the tropical Indo-Pacific drivers, namely, the canonical ENSO, ENSO Modoki, and the IOD. Using techniques of anomaly correlation, partial correlation, and pattern correlation, we surmise that the IITM-CFS successfully simulate the observed association of the tropical Indo-Pacific drivers with the local rainfall of many states during the summer monsoon. Significantly, the observed relationship of the local KRP with various climate drivers is predicted well for several Indian states such as United Andhra Pradesh, Karnataka, Odisha, and Bihar. The basis seems to be the model’s ability to capture the teleconnections from the tropical Indo-Pacific drivers such as the IOD, canonical and Modoki ENSOs to the local climate, and consequently, the Kharif rice production.
Highlights
The importance of the Indian summer monsoon rainfall (ISMR), which spans from June through September (JJAS), for the growth of the Indian agro-economy, is well-known (Gadgil et al, 2006)
The economy of most Indian states is governed by agricultural yield, which still largely depends on monsoon rainfall (e.g., Amat et al, 2018)
We explore the potential utility of the hindcasts from the state of the art Institute of Tropical Meteorology (IITM) dynamical seasonal and extended hindcast systems
Summary
The importance of the Indian summer monsoon rainfall (ISMR), which spans from June through September (JJAS), for the growth of the Indian agro-economy, is well-known (Gadgil et al, 2006). The importance of ERP has been used for determining the Monsoon Intraseasonal Oscillations (MISOs) (Sahai et al, 2013a; Sharmila et al, 2013) in term of active & break spells, which could be a crucial factor for farmers for agricultural scheduling These lead seasonal and extended range monsoon rainfall prediction skills motivate us to make an attempt to explore the usefulness of the climate prediction skills for the Kharif rice production forecast. We explore whether the extended-range and seasonal climate prediction skills of the IITMCFS hindcast data-sets can translate into tenable lead forecasts skills for the observed Kharif rice production (KRP) in the various Indian states.
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