A regime-based diagnosis of transition probabilities and changes in frequency and intensity of Indian Summer Monsoon rainfall

Abstract

We present a diagnostic framework of daily rainfall regimes during the Indian Summer Monsoon (ISM) for June–September 1961–2018. Using high-resolution (0.25°) daily rainfall and unsupervised k-means clustering, eleven objectively defined spatial rainfall patterns were identified and linked with characteristic low-level winds, sea-level pressure and moisture fields, separating different synoptic patterns of ISM rainfall. The dataset provides (i) centroid rainfall patterns of each regime and (ii) daily cluster IDs, enabling reconstruction of the full temporal sequence of rainfall regimes and calculation of transition probabilities between states. Transition analysis confirms that break phases are the most persistent while monsoon depressions are more transient, mirroring observed synoptic life cycles. A decomposition of rainfall change between 1961–1989 and 1990–2018 shows that drying in Northeast India (∼ 9 %) is driven by a reduction in frequency of break clusters associated with localized rainfall over the region (Cluster 2), whereas Gangetic Plain drying (∼ 7 %) is linked to reduction in both rainfall intensity and frequency (Clusters 2 and 8). Over the western India, the increasing rainfall (∼ 15 %) is mainly driven by increasing remnants of depressions and mid-tropospheric cyclones (Cluster 9). This regime-based approach provides a powerful diagnostic tool to examine synoptic drivers, longterm changes in rainfall intensity and frequency, regime transition dynamics, and can be useful to evaluate model representation of ISM variability, teleconnections and trend attribution.