Analysis of Himalayan summer monsoon rainfall characteristics using Indian High‐Resolution Regional Reanalysis

Abstract

AbstractThis study assesses the high‐resolution Indian Monsoon Data Assimilation and Analysis (IMDAA) dataset in representing the Indian summer monsoon (ISM) precipitation over the Himalayan region against ground‐based gridded (IMD), satellite‐based (TRMM, GPM‐IMERG and CHIRPS) and ERA5 reanalysis datasets at seasonal mean, trends, interannual and diurnal timescales. We first evaluate the relative performance of IMDAA rainfall using various statistical performance measures against the aforementioned datasets. Analysis suggests that IMDAA successfully captures the spatial distribution of ISM mean precipitation and seasonal cycle of daily rainfall over the Himalayas as in gridded, satellite and ERA5 reanalysis datasets, albeit with some overestimation in magnitude. Furthermore, statistical results show that IMDAA exhibits a wetter tendency, more RMSE, and higher precipitation variations over the foothills of the Himalayas. The results of the skill score determine that IMDAA diligently captured moderate and extreme precipitation events but was unable to detect heavy and low‐precipitation events. Our analysis further reveals that IMDAA shows a positive trend in mean ISM precipitation over the western Himalayan region, in line with CHIRPS, IMERG, IMD, ERA5 and TRMM datasets. Investigation of rainfall trends from station observations over the foothills of the Himalayas revealed mixed trends, with some stations (Tehri, Uttarkashi and Mukhim) showing an increasing trend and others (Dunta and Bhatwari) showing a decreasing trend. However, IMDAA reanalysis agrees well with all gauge station‐based trends. Additionally, the interannual variability of Himalayan precipitation is well represented in IMDAA as its principal component correlates well with its seasonal precipitation anomalies. It is found that the leading empirical orthogonal function mode of IMDAA accounts 24% of the total variance, demonstrating a single mode of variability. Furthermore, it is noticeable that strong convective activity during wet ISM years than in dry years, suggesting that the IMDAA can capture these variations successfully compared to ERA5. The interannual variability of ISM precipitation over the Himalayas is strongly associated with the El Niño–Southern Oscillation, which is well represented by IMDAA. In addition, IMDAA successfully replicated the diurnal cycle of precipitation over the central Himalayas, showing the presence of bimodal precipitation maxima: one in the afternoon and another one in the early morning, which is consistent with satellite observations. Thus, our results suggest that the IMDAA is a valuable dataset to understand the spatial–temporal pattern of summer precipitation over such a complex high mountain Asian region.