Probabilistic seasonal outlook for the rainy season over India by monitoring the onset dates using GPM IMERG satellite-based precipitation

Abstract. We utilized the Integrated Multi-Satellite Retrievals for Global Precipitation Mission version 6 (IMERG) rainfall observation (available in real time) over India to determine the onset and withdrawal of the rainy season. The annual mean climatology derived from IMERG observations over India aligned closely with the rain gauge-based India Meteorological Department observation. The IMERG rainfall time series was randomly perturbed to generate 101 ensemble members at every grid point of the rainfall analysis to obtain a corresponding ensemble of the onset and withdrawal dates of the rainy season. The perturbations were designed to sample the uncertainty due to random synoptic or mesoscale rain events influencing the diagnosis of the onset/withdrawal dates at the granularity of the IMERG observations (available at 10 km grid). Following earlier studies, we find from the IMERG dataset that seasons with an earlier onset date are strongly related to a lengthier and wetter season, whereas seasons with a later onset date correspond to a shorter and a drier season. In contrast, the connections between El Niño–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) with the onset, withdrawal, seasonal length, and rainfall of the rainy season were comparatively weaker over most of India. The generation of ensembles in this study underscores the potential for real-time application of generating reliable, probabilistic seasonal outlooks of the rainy season over India by leveraging the local links amongst onset date, seasonal length, and seasonal rainfall anomalies. This potential is further confirmed by the high probabilistic skill scores of the seasonal outlooks using the area under the relative operating characteristic curve method.