The reliability of satellite precipitation products is important in climatic and hydro-meteorological studies, which is especially true in mountainous regions because of the lack of observations in these areas. Two recent satellite rainfall estimates (SREs) from Global Precipitation Measurement (GPM)-era—Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG-V06) and gauge calibrated Global Satellite Mapping of Precipitation (GSMaP-V07) are evaluated for their spatiotemporal accuracy and ability to capture extreme precipitation events using 279 gauge stations from southern slope of central Himalaya, Nepal, between 2014 and 2019. The overall result suggests that both SREs can capture the spatiotemporal precipitation variability, although they both underestimated the observed precipitation amount. Between the two, the IMERG product shows a more consistent performance with a higher correlation coefficient (0.52) and smaller bias (−2.49 mm/day) than the GSMaP product. It is worth mentioning that the monthly gauge-calibrated IMERG product yields better detection capability (higher probability of detection (POD) values) of daily precipitation events than the daily gauge calibrated GSMaP product; however, they both show similar performance in terms of false alarm ratio (FAR) and critical success index (CSI). Assessment based on extreme precipitation indices revealed that the IMERG product outperforms GSMaP in capturing daily precipitation extremes (RX1Day and RX5Day). In contrast, the GSMaP product tends to be more consistent in capturing the duration and threshold-based precipitation extremes (consecutive dry days (CDD), consecutive wet days (CWD), number of heavy precipitation days (R10mm), and number of extreme precipitation days (R25mm)). Therefore, it is suggested that the IMERG product can be a good alternative for monitoring daily extremes; meanwhile, GSMaP could be a better option for duration-based extremes in the mountainous region.

The southern Himalayan slopes are increasingly experiencing dry winters, posing significant challenges to water resources and agriculture. These conditions have intensified forest fires in Nepal, mainly driven by human activities such as unattended campfires, discarded cigarettes, and arson. A warmer and drier climate exacerbates the spread of these fires, causing severe air pollution and accelerating snow and glacier melt due to black carbon deposition in the Himalayas. Recent forest fire events, particularly in 2021 and 2024, were ten times higher than the long-term average, fueled by extended post-monsoon droughts. Climate models (CMIP3, CMIP5, and CMIP6) project worsening winter droughts, leading to an increased frequency and intensity of forest fires throughout the 21st century. Our study, based on observational, remote sensing, and climate model data, highlights climate variability and climate change-induced droughts as primary drivers of these fires. Projections indicate that persistent droughts will elevate wildfire risks and degrade air quality, posing severe threats to public health, ecosystems, and the economy. This presentation will discuss historical trends and future projections of forest fires, emphasizing their impact on regional air quality, as fire smoke can travel hundreds of kilometers.