Coupled Model Intercomparison Project phase 5 (Fifth Assessment Report of Intergovernmental Panel on Climate Change) coupled global climate model Representative Concentration Pathway 8.5 simulations are analyzed to derive robust signals of projected changes in Indian summer monsoon rainfall (ISMR) and its variability. Models project clear future temperature increase but diverse changes in ISMR with substantial intermodel spread. Objective measures of interannual variability (IAV) yields nearly equal chance for future increase or decrease. This leads to discrepancy in quantifying changes in ISMR and variability. However, based primarily on the physical association between mean changes in ISMR and its IAV, and objective methods such as k‐means clustering with Dunn's validity index, mean seasonal cycle, and reliability ensemble averaging, projections fall into distinct groups. Physically consistent groups of models with the highest reliability project future reduction in the frequency of light rainfall but increase in high to extreme rainfall and thereby future increase in ISMR by 0.74 ± 0.36 mm d−1, along with increased future IAV. These robust estimates of future changes are important for useful impact assessments.

An efficient, reliable very high resolution dynamical downscaling model, a regional climate model (Weather Research and Forecasting‐Advanced Research Weather Research and Forecasting) one‐way nested into skillful general circulation model (National Center for Atmospheric Research‐Community Climate System Model version 4), is configured and implemented for ecologically sensitive, densely populated west coast of India encompassing Western Ghats (WG) having complex, meridionally oriented orography and wide biodiversity. This model with 3 km resolution resolves orographic features enabling realistic simulation of physical and dynamical characteristics of present‐day Indian summer monsoon (ISM) and extreme events, particularly recent trends in ISM rainfall over WG as observed. Marked skill of this model provides confidence in its future climate projection at regional scale. Future ISM rainfall projection shows significant increase (reduction) over 50.7% (5.8%) of Indian grid points. Significant reduction (10–20% of mean) over WG is due to upper‐tropospheric warming effect that stabilizes the atmosphere. Projected changes in extreme events show overall increase in warm days and warm nights over India with maximum increase over South India. Projected changes show widespread increase in wet days over most of India and reduction over WG. Projection of consecutive dry days implies wetter future for most parts of India but strengthened drought conditions for WG. Wind extreme projection shows strengthened (weakened) low (high) winds probability over WG and increase (decrease) in very high (low) winds over central India. This study establishes the importance of (i) employing sufficiently high‐resolution model, (ii) using bias‐corrected boundary data, and (iii) configuring model for realistic present‐day climate over complex topographic coastlines such as the west coast, in order to obtain useful climate change information for adaptation measures.

Florida has a distinct wet season, which serves the annual water needs of the State and beyond. Our earlier studies have indicated that in addition to the seasonal rainfall anomalies, the variations of the length of the season also contribute significantly to variability of the wet season over Florida. Furthermore, the variations of the onset date of the rainy season relate significantly to the seasonal anomalies of length of the season and rainfall. In this study, we have used the National Aeronautics and Space Administration's (NASA's) Integrated Multi-Satellite Retrievals for Global Precipitation Mission version 6 (IMERG) rainfall dataset to monitor the rainy season over the five Water Management Districts (WMDs) of Florida for 2021. This effort was complimented by analyzing and verifying the variations of the rainy season over the preceding 20 wet seasons from the IMERG datasets. IMERG produces rainfall datasets at various latencies, with the final product having a 3.5-month latency since the satellite measurements of radiance are made. However, in this study, we find that an intermediate 12-h latency product of rainfall analysis from IMERG is reasonable to use for near real-time monitoring of the wet season over Florida. The operational monitoring of the 2021 wet season using the 12-h latency dataset from IMERG was also supplemented with the extended weather 6- to 10-day and 8- to 14-day forecasts of precipitation probability issued by the NOAA's Climate Prediction Center. Our study suggests that the current methodology of monitoring the onset date variations of the rainy season provides a viable alternative to assess and anticipate the seasonal variations amidst the moderate to insignificant weather and climate prediction skill of the numerical forecast models of the wet season of Florida.