# Multi-Sensor Precipitation Estimation from Space: Data Sources, Methods and Validation
## 2 Satellites and Sensors  
Since the 1960s, satellite observations have been utilized to obtain atmospheric parameters. The World Weather Watch (WWW) program, initiated by the World Meteorological Organization (WMO) in 1963, effectively coordinates surface and satellite observational capabilities through the Global Observing System (GOS), encompassing a network of GEO and polar-orbiting satellites. The satellites are utilized for observing, recording, and reporting information pertaining to weather, climate, and the natural environment in order to facilitate forecasting and warning services. Subsequent to the initiation of this program, there has been a notable increase in the number of launched satellites. Consequently, these platforms along with their onboard payloads have emerged as the primary sources of data for global precipitation estimation. MPEs primarily utilize high-resolution GEO IR images and highly precipitation-sensitive LEO PMW images (Table 2). The provision of GEO satellite data dates back to late 1974 when the National Aeronautics and Space Administration (NASA) launched the Synchronous Meteorological Satellites-1. With more satellites in the 1970s, daily global coverage GEO data became available, except for in polar regions [52]. Typically, IR images have a spatial resolution of between 1 and 4 km and a temporal resolution of between 10 and 30 min. The high spatiotemporal resolution facilitates the detection of cloud evolution and motion, thereby enhancing algorithm development (e.g., [69; 70]). The provision of temporally continuous PMW data dates back to 1987 with the Defense Meteorological Satellite Program (DMSP). Numerous algorithms have been developed since then as more satellites have been launched [71; 72]. Note that most PMW instruments have a spatial resolution of less than 5 km, particularly at lower frequencies. \begin{table}
\begin{tabular}{l l l} \hline
**Theme** & **References** \\ \hline VIS/IR, PMW, AMW, MPE & [38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51] \\ \hline Products & [52; 53; 54] \\ \hline Validation & [55; 56; 57; 58] \\ \hline Applications & [15; 59] \\ \hline Programs/Projects & [60; 61; 62; 63; 64; 65] \\ \hline Books & [66; 67; 68] \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._  
\begin{table}
\begin{tabular}{l l l l l l l} \hline
**Satellite** & **Sensor** & **IFOV at** & **Revisit** & **Agency** & **Temporal** & **Source** \\  & & **Nadir (km)** & **Time** & **ASAS** & 1975–present & **1975–present \\ \hline GOES & VISSR, VAS, & 2–6.9 & 15–30 & NOAA/ & & [[https://www.goes-rgov/products/samples.html](https://www.goes-rgov/products/samples.html)]([https://www.goes-rgov/products/samples.html](https://www.goes-rgov/products/samples.html)) \\  & 1–19 & Imager, ABI & (IR) & min & NASA & & (accessed on 1 December 2024) \\ \hline Meteosat 1–11 & & & & & & \\ (MOP/ & & & & & & \\ (MSO/MTG) & & & & & & \\ (MSO/ & &  
Launched in 1997, the TRMM primarily focused on quantifying atmospheric parameters over tropical and subtropical oceans based on the onboard microwave imager (TMI) and PR at 13.8 GHz [73]. The TRMM officially concluded its mission on 15 April 2015. The GPMCO, launched in 2014 as an extension of TRMM [20], represents a significant advancement in the field. It offers enhanced capabilities for measuring light rain (<0.5 mm/h), solid precipitation, and the microphysical properties of precipitating particles. The onboard Ka-band (35.5 GHz) and Ku-band (13.6 GHz) PR enable a three-dimensional measurement of precipitation structures. The Ka/Ku-band DPR can offer novel insights into particle drop size distributions during moderate precipitation [74]. Thus, it establishes the current standard for spaceborne precipitation estimation. The GPM mission conducts high-precision global precipitation measurements every 0.5-3 h [20]. It consists of a constellation of satellites equipped with PMW sensors from the space agencies of the USA, Japan, Europe, and India (Figure 2).