Spatial multivariate selection of climate indices for precipitation over India

نویسندگان

چکیده

Abstract Large-scale interdependent teleconnections influence precipitation at various spatio-temporal scales. Selecting the relevant climate indices based on geographical location is important. Therefore, this study focuses spatial multivariate selection of influencing variability over India, using partial least square regression and variable importance projection technique. 17 gridded dataset (0.25 × 0.25°) from Indian Meteorological Department for 1951–2020 a monthly scale are considered. Results show that among all indices, Nino 4, 1 + 2, Trans Index, Atlantic Multidecadal Oscillation (AMO), quasi-biennial oscillation (QBO), Arctic (AO), North (NAO) have significant India. Further, within homogenous regions, it found Southern Index 3.4 selected majorly in South Peninsular compared to other regions. The NAO/AO similar pattern was be Northeast region (>89%). AMO mainly Northwest, West Central (>80%), QBO about 70% grid locations It noted number identified varies spatially across region. Overall, highlights identifying would aid developing improved predictive parsimonious models agriculture planning water resources management

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ژورنال

عنوان ژورنال: Environmental Research Letters

سال: 2022

ISSN: ['1748-9326']

DOI: https://doi.org/10.1088/1748-9326/ac8a06