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Combining regional moist static energy and ENSO for forecasting of early and late season Indian monsoon rainfall and its extremes
Author(s) -
Rajagopalan Balaji,
Molnar Peter
Publication year - 2014
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2014gl060429
Subject(s) - predictability , climatology , monsoon , environmental science , southern oscillation , wet season , agriculture , el niño southern oscillation , geography , geology , mathematics , archaeology , cartography , statistics
We exploit El Niño–Southern Oscillation (ENSO) indices and moist static energy of surface air over the Indian subcontinent and surroundings as predictors of monsoon rainfall over India during early and late seasons, defined here as 20 May to 15 June and 20 September to 15 October, respectively. Although these seasons contribute only ~22% of the entire seasonal rainfall, they clearly affect planning of agriculture and water resources. A simple, nonlinear, statistical model applied to these predictors accounts for ~40% and 45% of the observed variance of early and late season rainfall, respectively, and similar fractions for 3 day maximum rainfall intensity. Forecasted average and 3 day maximum rainfall at grid points covering India show greatest success over central India during the early season and over west central, northwestern, and northern India during the late season, regions where agriculture dominates land use. These predictors, however, offer virtually no predictability of peak season rainfall.