**1. Introduction**

The Tropical Rainfall Measuring Mission (TRMM) was launched in November 1997 [1], and its most frequently used product, TRMM-3B42 v7 (hereafter TRMM7), is expected to cease in December 2019 (https://pmm.nasa.gov/data-access/downloads/trmm). As an extension and enhancements on the TRMM data, the Global Precipitation Measurement (GPM) Core Satellite was launched in February 2014 [2]. After that, the satellite precipitation products (hereafter SPPs) of the GPM mission, including Integrated Multi-satellitE Retrievals for GPM (IMERG) [3] and Global Satellite Mapping of Precipitation for GPM (GSMaP) [4], were provided by the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA), respectively. In March 2019, NASA released the IMERG-Final v6 (hereafter IMERG6), which includes TRMM-era

data dating back to June 2000 and suggested that researchers use this for most research purposes (https://pmm.nasa.gov/data-access/downloads/trmm). However, the performance of these SPPs may depend heavily on location and season [5–12]. Thus, it is important to clarify which SPP (e.g., IMERG or GSMaP) is the most suitable product to replace TRMM7 for studies of precipitation changes over various regions and during various seasons [13–15]. A better understanding of the performance of SPPs [13–22] can benefit other studies where SPPs are required to examine issues that are related to precipitation (e.g., moisture budget, speed of the hydrological cycle, etc.).

Located in Asia, Taiwan (119.9◦E–122.1◦E, 21.8◦N–25.5◦N) is an island that is known for its complex terrain (Figure 1b). In view of earlier literature, few studies have evaluated the performance of IMERG6 [15] or other SPPs over Taiwan [15,23–26]. Recently, Huang et al. [24] showed that IMERG-Final v5 (hereafter IMERG5), which is the earlier version of IMERG6, can qualitatively illustrate the multiple timescale variations in precipitation over Taiwan in a similar manner to the local rain-gauge observations made during the period March 2014–February 2017, but the amount of the estimation is lower than that seen in the gauge observations. However, Huang et al. [24] did not compare IMERG5 with the other SPPs used to investigate the precipitation around Taiwan. In addition, it should be noted that a major change was made to the morphing scheme used in IMERG5 and IMERG6 [3]. In versions of IMERG up to and including v5, the vectors used to describe cloud motion were computed from geosynchronous infrared brightness temperatures. In contrast, the morphing algorithm used in IMERG6 is modified to derive cloud motion vectors from variables in the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis [27]. Tan and Huffman [28] examined the global precipitation for August 2017 to October 2017 from IMERG5 and IMERG6, and noticed that IMERG6 outperforms IMERG5. However, the possibility that IMERG6 outperforms IMERG5 or any other SPPs with regards to precipitation over Taiwan has not been examined by Tan and Huffman [28].

**Figure 1.** (**a**) Spatial distribution of summer mean precipitation over Taiwan, averaged during the summers (June, July, and August; JJA) of 2014–2017; from left to right is estimations made using Central Weather Bureau (CWB) data, Tropical Rainfall Measuring Mission-3B42 v7 (TRMM7), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement-Final v5 (IMERG5) and v6 (IMERG6), and Global Satellite Mapping of Precipitation for Global Precipitation Measurement-Gauge v7 (GSMaP7). (**b**) The geographic location and topography of Taiwan. (**c**) The spatial correlation (Scorr) and the root mean square error (RMSE) for the comparison between the satellite precipitation products (SPPs) and the CWB data in (**a**). Here, the sample size is 392 grid points for the land areas in (**a**). (**d**) The estimations of the precipitation in (**a**), averaged by area at different altitudes. The color legends of (**c**,**d**) are given in the right panel of (**d**).

The GSMaP project, which was sponsored by Japan Science and Technology Agency during 2002–2007 and extended by JAXA, aims to develop microwave radiometer algorithms for producing high resolution global precipitation maps [29]. After the GPM mission was launched, a new algorithm was developed for the GSMaP project which included the GPM satellite data, producing GSMaP-Gauge data from March 2014 [4]. Recently, Derin et al. [15] pointed out that GSMaP-Gauge v7 (hereafter GSMaP7) and IMERG5 performed better than IMERG6 in depicting the precipitation formation over multiple complex terrain regions, including western Taiwan, during the period 2014–2015. However, only 34 gauges in western Taiwan and only two years of data from 2014–2015 were used by Derin et al. [15] as the reference base for comparison. It should be noted that there are more than 400 rain gauges across the entirety of Taiwan [24] that can be used for a more detailed comparison of SPPs starting from 2000. As the performance of SPPs might be location dependent and timing dependent [24], it is important to examine the performance of SPPs over Taiwan using higher density of rain gauges and longer time periods.

The main objective of this study was to evaluate the performance of multiple SPPs (including TRMM7, IMERG5, IMERG6, and GSMaP7) in depicting the spatial-temporal variations of summer (June, July, and August; JJA) precipitation over whole Taiwan, using more than 400 local rain gauges as the reference base for comparison. The selection of GPM SPPs followed Derin et al. [15]. However, in contrast to Derin et al. [15], who only performed the evaluation at daily and annual timescales, we perform the evaluation of summer precipitation at mean status, daily, interannual and diurnal timescales. In addition, we examine the capabilities to apply SPPs in studying the activities of summer connective afternoon rainfall (CAR) event (Figure 7, explained later), which is the most frequently observed weather pattern in Taiwan [30]. The analysis mainly focuses on the time periods that overlap in all data investigated, that is, the summers of 2014–2017 (Table 1), with an additional comparison between TRMM7 and IMERG6 for the summers of 2000–2017.


**Coverage** 50◦S–50◦N 60◦S–60◦N 60◦S–60◦N 60◦S–60◦N **Period** 1998/1–2019/10 2014/3–2018/6 2000/6–present 2014/3–present

**Table 1.** Information about the satellite precipitation products (SPPs) used in this study.

The remainder of this manuscript is arranged as follows. Information about the data and the statistical methodology are introduced in Section 2. Section 3 documents the evaluation and application of SPPs in studying the multiple timescale variations of summer precipitation over Taiwan. Discussions are provided in Section 4. A summary is given in Section 5.
