**2. Data and Methods**

### *2.1. Data*

Following Huang et al. [24], the gridded hourly precipitation data produced from 436 rain-gauge observations provided by the Central Weather Bureau (hereafter CWB data) in Taiwan was used as the reference base for comparison. The Cressman scheme [31] was used to generate the gridded CWB data, following the procedures described by Hong and Cao [32].

Table 1 documents the basic information about SPPs used in this study. To compare with hourly CWB data, the 3-hourly TRMM7 were linearly interoperated into the hourly precipitation with a spatial resolution of 0.1◦ <sup>×</sup> 0.1◦. Also, the two half-hourly IMERG estimations (unit: mm·h<sup>−</sup>1) were averaged to obtain hourly data [24]. All the hourly data were then converted into the local timescale in Taiwan, that is, universal time (UTC) + 8 hours.

The algorithms used by the four SPPs are briefly summarized below. According to Huffman et al. [1], four stages are implemented for the production of TRMM7: (1) precipitation estimates from the microwave sensor are calibrated and combined; (2) the infrared precipitation estimates are produced to extend the spatial coverage that the microwave observations do not cover; (3) the microwave and infrared precipitation estimates are combined; and (4) the monthly Global Precipitation Climatology Center (GPCC) gauge analysis product is used to climatologically adjust TRMM7 [1,5]. No gauge adjustment is required over the oceans. The TRMM7 data can be obtained from https: //pmm.nasa.gov/data-access/downloads/trmm.

According to Huffman et al. [33], the precipitation estimates of IMERG5 are produced using the following steps: (1) the individual satellite sensor data are gridded and calibrated to the combined microwave-radar estimates; (2) the precipitation estimates are propagated forwards and backwards in time using cloud motion vectors derived from infrared data; (3) the propagated precipitation estimates, along with the infrared estimates, are merged based on Kalman weighting factors; and (4) a bias correction is conducted using the monthly GPCC gauge analysis product. Unlike IMERG5, the cloud motion vectors of IMERG6 are derived from MERRA-2 variables [3]. The data of IMERG5 and IMERG6 are available at https://pmm.nasa.gov/data-access/downloads/gpm.

According to Mega et al. [4], several steps are followed for the production of GSMaP7: (1) a simplified and near real-time version of precipitation estimation is generated using fewer passive microwave input streams and a forward-only cloud advection scheme [34]; (2) an improved version of precipitation estimation is generated by applying the Kalman filter to assimilate and refine the visible/infrared-based precipitation rates [29]; (3) both forwards and backwards morphing is applied on the improved version of precipitation estimation to the area observed by the passive microwave radiometer to be affected by precipitation; and (4) a bias correction is conducted using the CPC unified gauge-based analysis of daily precipitation. The GSMaP7 data can be downloaded from https://sharaku.eorc.jaxa.jp/GSMaP/.
