# Multi-Sensor Precipitation Estimation from Space: Data Sources, Methods and Validation
## 5 Satellite Precipitation Products
### Precipitation Products with High Spatiotemporal Resolution  
The TMPA comprises the TRMM 3B42 RT (0.25\({}^{\circ}\)/3 h) and 3B43 (0.25\({}^{\circ}\)/monthly) products. The TMPA algorithm integrates IR estimates and PMW retrievals through a series of adjustments and combinations, including calibration of IR brightness temperatures using PMW retrievals (via PMM), merging of PMW and IR estimates to generate TRMM 3B42 RT, and rescaling the results to monthly totals for unadjusted TRMM 3B43 [25]. To optimize accuracy, both TRMM 3B42 and 3B43 datasets are corrected using global monthly rain gauge data. The PMW data primarily originated from sensors such as TMI (GMI after the retirement of TRMM), SSM/I/SSMIS, AMSR-E (AMSR2 after 2012), AMSU-B, and MHS. The Precipitation Process System within NASA's Earth Observing System Science and Data Information System was responsible for producing the TMPA dataset at [[ftp://trmmopen.gsfc.nasa.gov/pub/merged](ftp://trmmopen.gsfc.nasa.gov/pub/merged)]([ftp://trmmopen.gsfc.nasa.gov/pub/merged](ftp://trmmopen.gsfc.nasa.gov/pub/merged)) (accessed on 28 October 2020). Notably, the TMPA was retired at the end of 2019. The IMERG currently comprises a 0.1\({}^{\circ}\)/0.5 h product. The GPM IMERG algorithm aims to intercalibrate, merge, and interpolate satellite PMW precipitation estimates with PMW-calibrated IR estimates, gauge data, and potentially other precipitation estima  
Figure 3: Summary of major global satellite precipitation products currently available. tors [30]. This algorithm incorporates various methods employed in global precipitation estimation algorithms such as the cloud-classification method in PERSIANN-CCS [28], the KF-based CMORPH algorithm [111], and the PMM-based method. While the core algorithm is based on KF-based CMORPH, additional methods are utilized to enhance and adjust the IR and PMW estimates. The production of the GPM dataset is overseen by PPS in EOSSDIS at NASA (available at [[https://pmm.nasa.gov/data-access/downloads/gpm](https://pmm.nasa.gov/data-access/downloads/gpm)]([https://pmm.nasa.gov/data-access/downloads/gpm](https://pmm.nasa.gov/data-access/downloads/gpm)), accessed on 1 December 2024). Notably, the GPM IMERG extends its temporal coverage to include the TRMM era and now offers a 20-year-long data series spanning from 2000 to the present [139]. The CMORPH comprises products with spatial resolutions of 0.25\({}^{\circ}\)/3 h, 0.07\({}^{\circ}\)/0.5 h, and CDR (0.07\({}^{\circ}\)/daily). The CMORPH algorithm integrates passive microwave (PMW) and infrared (IR) data through a cloud-motion-based approach [26], which is further enhanced using a Kalman filter model [111]. PMW observations are obtained from diverse sources including SSM/I, SSM/S, AMSU-B, AMSR-E, and GMI sensors. Cloud vectors are corrected using radar data from the U.S. Next-Generation Weather Radar (NEXRAD) stage-II product. [PERSON] et al. [108] reprocessed the satellite-based CMORPH precipitation estimates and rectified biases by incorporating gauge data via the Precipitation Measurement Mission (PMM), resulting in the creation of the CMORPH CDR dataset. The Climate Prediction Center (CPC) of the NOAA is responsible for generating the CMORPH datasets. The GSMaP comprises 0.1\({}^{\circ}\)/1 h near-real-time products (GSMaP_NRT, GSMaP_Gauge_NRT), 0.1\({}^{\circ}\)/1 y standard products (GSMaP_MVK, GSMaP_Gauge), and a 0.1\({}^{\circ}\)/0.5 h real-time satellite precipitation product (GSMaP-NOW). GSMaP_NRT is derived from the MW-IR merged data (GSMaP_MVK), excluding backward propagation to provide near-real-time information, while GSMaP_Gauge_NRT represents the corresponding gauge-based adjusted product [86; 140]. The GSMaP_MVK algorithm applies a Kalman filter model to refine the PMW estimates obtained through cloud-motion-based methods [110]. Additionally, GSMaP_Gauge is a rain-gauge-adjusted product based on GSMAP_MVK [141]. The GSMaP-NOW, produced using the GSMaP V06 algorithm, has been available for the whole globe since June 2019 [110; 142].