The rain drop size distribution (DSD) at Cherrapunji, Northeast India was observed by a laser optical disdrometer Parsivel ${}^2$ from May to October 2017; this town is known for the world’s heaviest orographic rainfall recorded. The disdrometer showed a 30% underestimation of the rainfall amount, compared with a collocated rain gauge. The observed DSD had a number of drops with a mean normalized intercept log ${}_{10}{N}_{\mathrm{w}}>4.0$ for all rain rate categories, ranging from 80 mm h ${}^{-1}$ , comparable to tropical oceanic DSDs. These results differ from those of tropical oceanic DSDs, in that data with a larger $N_{\mathrm{w}}$ were confined to the stratiform side of a stratiform/convective separation line proposed by Bringi et al. (2009). A large number of small drops is important for quantitative precipitation estimates by in-situ radar and satellites, because it tends to miss or underestimate precipitation amounts. The large number of small drops, as defined by the second principal component (>+1.5) while using the principal component analysis approach of Dolan et al. (2018), was rare for the pre-monsoon season, but was prevalent during the monsoon season, accounting for 16% (19%) of the accumulated rainfall (precipitation period); it tended to appear over weak active spells or the beginning of active spells of intraseasonal variation during the monsoon season.

The characteristics of active rainfall spells (ARSs) at Cherrapunji, northeast India, where extreme high rainfall is experienced, and their relationships with large-scale dynamics were studied using daily rainfall data from 1902 to 2005 and Japanese 55-Year Reanalysis from 1958 to 2005. Extreme high daily rainfalls occur in association with ARSs. The extremely large amounts of rainfall in the monsoon season are determined by the cumulative rainfall during ARSs. ARSs start when anomalous anticyclonic circulation (AAC) at 850 hPa propagates westward from the South China Sea and western North Pacific, and covers the northern Bay of Bengal. The AAC propagates farther westward and suppresses convection over central India during ARSs at Cherrapunji, and continues for 3 to 14 days. Consequently, a northward shift of the monsoon trough during the “break” in the Indian core region occurs. The westerly wind, which prevails in the northern portion of the AAC, transports moisture toward northeast India and enhances moisture convergence over northeast India with southerly moisture transport from the Bay of Bengal, and greatly intensifies the orographic rainfall. In the upper troposphere, the Tibetan high tends to extend southward with the onset of ARSs. A linear relationship can be seen between the length and total rainfall of an ARS. Longer ARSs tend to result in greater total rainfall. AACs with a greater zonal scale tend to produce longer and more intense ARSs. This study provides evidence for the effect of western North Pacific AACs on the Indian summer monsoon.

Near-surface rain rate datasets derived from the Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR) and Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR) and near-surface raindrop size distribution (DSD) parameters derived from the GPM DPR were validated using 43 tipping-bucket rain gauges installed over the northeastern Indian subcontinent and two Parsivel² disdrometers installed on the Meghalaya Plateau, India. Both TRMM PR version 7 and version 8 products significantly underestimated the rainfall over the Indian subcontinent during the monsoon season (June–September). The GPM DPR version 06A product also significantly underestimated the rainfall at stations on the Meghalaya Plateau, India. The heavy rainfall area (HRA) of the Meghalaya Plateau in the TRMM PR climatology showed lighter rainfall on the plateau, whereas heavier rainfall was detected in adjacent valleys. Intense surface rainfall over the HRA may be detectable, because such intense rainfalls tended to occur from deeper convections, that were less affected by the ground clutter interferences. A comparison of the statistical features of the DSD parameters between the disdrometers and GPM DPR retrievals around the Meghalaya Plateau confirmed that an adequate assumption of the adjustment factor $\epsilon$ is important for improving the DSD parameters in GPM DPR retrievals.