*3.1. Satellite Precipitation Products*

The TRMM satellite was launched in 1997 through a joint space mission between the NASA of U.S. and the National Space Development Agency of Japan [30]. TRMM carries five instruments, including a suite of three rainfall sensors (Precipitation Radar (PR), TRMM Microwave Imager (TMI), Visible and Infrared Sensor (VIRS)) and two related instruments (Lightening Imaging Sensor (LIS) and Clouds and the Earth's Radiant Energy System (CERES)). The TRMM Multi-satellite Precipitation Analysis (TMPA) products combine infrared (IR) data from geostationary satellites, such as GOES-W, GOES-E, GMS, Meteosat-5, Meteosat-7, and NOAA-12, with microwave (MW) data from multiple satellites including TMI/TRMM (TRMM Microwave Imager), SSMI/DMSP (Special Sensor Microwave Imager/Defense Meteorological Satellite Program), AMSU/NOAA (Advanced Microwave Sounding Unit/National Oceanic and Atmospheric Administration), and AMSR-E (Advanced Microwave Scanning Radiometer-EOS) [31]. The TMPA products are produced in the following four stages. First, the MW precipitation estimates are calibrated and combined using algorithms such as sensor-specific versions of the Goddard Profiling Algorithm (GPROF). Secondly, IR precipitation estimates are created using the calibrated MW precipitation. Thirdly, the MW and IR precipitation estimates are combined. Finally, rain gauge data are incorporated. Detailed descriptions of the algorithms and steps for producing the TMPA products could be found in Huffman et al. (2007) [32] and Huffman et al. (2018) [33].

In May 2012, the TMPA was upgraded from version 6 (V6) to version 7 (V7) by implementing the latest version of re-calibration algorithm and using the new GPCC monthly precipitation products for bias correction. The TMPA 3B42 consists of two products: the near-real-time product (3B42RT) and the post-processed product (3B42). The 3B42RT product, which is released approximately 9 h after real-time, spans the latitude belt from 50◦ N to 50◦ S. In contrast, with a more extensive coverage from 60◦ N to 60◦ S, the 3B42 product is released 10–15 days after each month when the bias correction has been made based on ground gauge records.

As a global successor of TRMM, the GPM project is launched in 2014 to provide global precipitation observations. The GPM satellite is equipped with an advanced Dual-frequency Precipitation Radar (DRP) that observes the internal structure of storms within and under the clouds, and a GPM Microwave Imager (GMI) that measures the type, size, and intensity of precipitation. The DPR is more sensitive than its TRMM predecessor especially in the measurement of light rainfall and snowfall in high latitude regions.

In March 2014, NASA released its first GPM-era global precipitation product–IMERG (Integrated Multi-satellites Retrievals for GPM). The IMERG algorithm is designed to inter-calibrate, interpolate, and merge all available satellite MW precipitation estimates, MW-calibrated IR satellite estimates, gauge measurements, and other potential precipitation estimates at fine spatial and temporal resolution worldwide. Its inter-calibration of available MW data is similar to TMPA, but further interpolated and re-calibrated by the Climate Prediction Center (CPC) morphing Kalman Filter technique and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks—Cloud Classification System (PERSIANN-CCS) [34,35].

IMERG includes three products with different latencies: the near-real-time 'Early' (near real-time with a latency of 6 h) run (IMERG-E), the near-real-time 'Late' (reprocessed near real-time with a latency of 18 h) run (IMERG-L), and the post-real-time 'Final' (gauge-adjusted with a latency of four months) run (IMERG-F). The algorithm for the IMERG was upgraded from Version 5 (V5) to Version 6 (V6) to reduce bias and improve consistency among different IMERG runs in June 2019. For example, the 'displacement vectors' in V6 are computed using the Modern Era Retrospective Reanalysis 2 (MERRA-2) and Goddard Earth Observing System (GEOS) model Forward Processing (FP) data instead of the previously used infrared data, which helps ensure consistency in the vectors between the Final Run and the Early and Late Runs.

In this study, we aim to evaluate the performance of a total of five SPPs in the SRB, including the Early, Late, and Final runs of the IMERG V6 products (0.1◦ × 0.1◦ and 30-min interval), and the near-real-time and post-processed runs of the TMPA V7 products (0.25◦ × 0.25◦ and 3-hour interval). The SPPs datasets are all downloaded from the NASA website (https://disc.gsfc.nasa.gov/). After being downloaded, the SPPs datasets are adjusted to the local time, which is eight hours ahead of Coordinated Universal Time (UTC). Since the IMERG V6 and TMPA V7 products respectively contain 30-min and 3-h rainfall estimates, they need to be processed before being evaluated at different temporal scales. At the daily and monthly scale, both IMERG and TMPA data are directly aggregated to the corresponding levels for comparison with ground measurements. For evaluation at the hourly scale, the TMPA hourly rainfall estimates are obtained by assuming a constant rainfall intensity over the 3-hour period.
