## 1 Introduction  
Precipitation is regarded as an essential component of global energy and water cycles, and it plays a significant role in the interactions between atmosphere, biosphere and hydrosphere [1]. The measurement of precipitation not only provides essential information to weather forecasters and climate scientists but also to a wide range of decision-makers, including agriculturalists, hydrologists, industrialists and emergency managers [2]. Therefore, accurate estimation and prediction of precipitation is important for a wide range of applications, such as agricultural crop forecasting, monitoring freshwater resources and numerical weather prediction. In the last three decades, satellite measurement of precipitation has grown to be an uninterrupted, reliable and cost-effective source over large data-void areas [3]. In 1997, NASA sent the first dedicated meteorological precipitation satellite--the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA)--with the National Space Development Agency (NASDA) to measure energy and precipitation exchange across tropical and subtropical areas of the world for 17 years (1997-2014) [4, 5]. Motivated by the splendid success of the TRMM satellite, on 27 February 2014, its successor, the GPM Core Observatory (GPMCO) was launched by Japan Aerospace Exploration Agency (JAXA) and NASA to continue and improve satellite-based precipitation observations on a global scale [6]. Thanks to the other satellites, the Core satellite is possible to guarantee a covering region between 65\({}^{\circ}\) N and 65\({}^{\circ}\) S.  
The GPM mission includes a constellation of nine satellites unified by the GPMCO as a reference standard for the other partner satellites [7]. The GPMCO contains an advanced 13-channel passive microwave radiometer, and a GPM Microwave Imager (GMI) combined with a Ka/Ku-band Dual-frequency Precipitation Radar (DPR). Since this radar has two frequencies that provides more accurate corrections for microwave rain attenuation, it unifies precipitation estimates as a benchmark [8]. Compared to the TRMM Precipitation Radar (PR), the DPR Ka-band is more sensitive for high-latitude snowfull and light rainfall (sensitivity of PR and Ka-band is 0.5 mm/h and 0.2 mm/h, respectively) [9]. Therefore, GPM DPR can more accurately detect extreme precipitation and estimate its impact on global climate models, which is essential for exploring and understanding the global water cycle [10]. In late 2014, precipitation from Integrated Multi-satellite Retrievals for GPM (IMERG) were released to the public; this especially high-resolution precipitation product is now available at the 30 min and 0.1\({}^{\circ}\) resolution in early mode (with a 4 h latency), late mode (with a 12 h latency) and final mode (with a 2.5 months latency), which run based on accuracy and latency [11]. The early and late products are multi-satellite data. The final run is, instead, obtained taking advantage of a combination of information acquired from satellite and monthly rain gauges data. [PERSON] et al. [12] suggested that this product can be regarded as the next generation of multi-sensor precipitation data and utilized for near real-time flood risk monitoring applications. Currently, some studies have utilized the IMERG products to estimate snowfall [11; 13]. The potential of data from IMERG for real-time short-term rainfall nowcasting and forecasting are less unexplored due to the lack of reliable ground rain gauge observations. Therefore, the rainfall nowcasting and forecasting by IMERG data should be investigated with a view to improving the forecasting of extreme rainfall events and assessing the potential of feeding this information into hydrological models, especially in regions where high-resolution precipitation data is not available. [PERSON] and [PERSON] [14] suggested that precipitation nowcasting is the generation of short-term (0-3 h) future precipitation distributions from a sequence of radar images, while [PERSON] et al.