## 1 Introduction  
Precipitation is a vital component of the water cycle, and understanding the characteristics of precipitation is essential for hydro-meteorological applications [1; 2]. In mountainous regions, water resource management is further challenging due to the complex climate associated with topographic variance [3]. In these regions, the occurrences of hydrological hazards such as floods, landslides and soil erosion are very sensitive to precipitation amounts. Thus, reliable and precise estimates of precipitation are a prerequisite for hydro-meteorological and natural disaster studies [4; 5]. Nepal lies on the south-central part of the main Himalayan range, with more than 80% of the country covered by mountains; in this environment, there is a high probability of landslides and debris flows during the monsoon season. Precipitation in the country is extremely variable due to the complex topography. The seasonal cycle is predominantly governed by the monsoon system [6; 7] with maximum (~80%) precipitation occurring in summer. Rain gauge-based measurements provide relatively accurate measurements of precipitation on the ground surface [8; 9]. These observations developed by the Department of Hydrology and Meteorology (hereafter, DHM) in Nepal are relatively dense in the lowlands but sparse in high mountain areas [10; 11]. The scarcity of rain gauge observations is a major challenge in hydro-meteorological studies and for effective water and disaster management. This scarcity of measurements also limits knowledge of precipitation patterns across the country [12]. Fortunately, high-resolution satellite-based precipitation (hereafter, SBP) products provide potential alternatives for monitoring precipitation on regular high-resolution grids, yielding unprecedented levels of detail especially over remote areas and mountainous regions where stations are very sparse. However, these estimates are indirect measurements and must be verified and calibrated using gauge observations before further application [13; 14]. SBP estimates are based on various remotely sensed characteristics of clouds, such as cloud-top temperature (IR imagery), reflectivity (visible) or from the scattering effects of ice particles on passive microwave (PMW) radiation [15; 16; 17; 18]. In the post- Tropical Rainfall Measuring Mission (TRMM) era, the Global Precipitation Measurement (GPM) Core Observatory spacecraft, equipped with advanced sensors and channels, like the Dual-frequency Precipitation Radar (DPR) and the GPM Microwave Imager (GMI) which had capabilities to sense light rain and snowfall, was launched on 27 February 2014 in a collaboration between NASA and the Japan Aerospace Exploration Agency (JAXA) [16]. New SBP products were introduced after the GPM mission: the Integrated Multi-satellite Retrievals for GPM (IMERG) [19; 20]; meanwhile, JAXA updated to a newer version of the Global Satellite Mapping of Precipitation (GSMaP) product (GSMaP Version 07) with orographic rainfall correction [21]. Several studies have already evaluated SBP products around the globe for different hydro-meteorological applications [22; 23; 24; 25; 26; 27; 28]. They found that the new generation SBP products (GPM-Era) were improved than their previous version (TRMM-Era). For example, [29; 30; 31] found that the GPM-Era (IMERG-V3) precipitation product outperforms the TRMM-Era (TRMM 3B42V7, TMPA-RT) precipitation products. Meanwhile, studies conducted in Myanmar found the GSMaP-V07 product had the lowest accuracy when compared with the IMERG-05B product [32]. Similarly, [PERSON] and [PERSON] [33] also mentioned that IMERG-V05 performed better than GSMaP-V07, especially in high-elevation areas. A study conducted in Northwestern China did not found any significant difference in estimating the precipitation by IMERG-V06 and IMERG-V05 [34].