# Passive Microwave Imagers, Their Applications, and Benefits: A Review
## 2 PMWI Applications and Impact Areas
### Applications and Benefits of PMWIs
#### 2.1.6 Sea Surface  
PMWIs play a crucial role in estimating ocean surface wind speeds by measuring the roughness of the sea surface. They help in the accurate retrieval of wind speed data by detecting variations in the ocean's surface caused by wind, which is essential for climate monitoring and weather prediction [80]. Currently, data from SSM/I, TMI, GMI, AMSR-E, SSMIS, AMSR2, and GMI are aggregated to create a PMWI-derived ocean 10 m wind speed climate data record called the MultiSensor Advanced Climatology of Liquid Water Path (MAC-LWP) [23]. Additionally, as part of the NASA MEASURE project, the Cross-Calibrated Multi-Platform (CCMP) project combines inter-calibrated 10 m ocean surface wind retrievals from multiple satellite microwave sensors--including PMWIs such as TRMM TMI, DMSP-F8 SSM/I, DMSP-F10 SSM/I, DMSP-F11 SSM/I, DMSP-F13 SSM/I, DMSP-F14 SSM/I, DMSP-F15 SSM/I, DMSP-F16 SSMIS, DMSP-F17 SSMIS, Aqua AMSR-E, GCOM-W1 AMSR2, GPM GMI, and Coriolis WindSat. It also incorporates data from active sensors on Metop-A and Metop-B, along with a background field from ERA5 10 m Neutral Stability winds. The wind retrievals, produced by Remote Sensing Systems (RSSs), include data from most of the wind-sensing U.S., Japanese, and European satellites flown to date [81]. Figure 4 illustrates the monthly mean ocean surface wind for December 2024, derived by combining 10 m wind retrievals from satellite microwave sensors--including PMWIs such as DMSP-F16 SSMIS, DMSP-F17 SSMIS, DMSP-F18 SSMIS, GCOM-W1 AMSR-E, and GPM GMI. Building on these advancements in wind retrieval, it is also important to consider the role of ocean surface emissivity in remote sensing. Wind speed influences the emissivity of the ocean surface and horizontally polarized channels, while SST primarily affects vertically polarized channels [82]. Notably, PMWIs have been widely applied in studying SST, which is vital for climate monitoring--a task made feasible only through satellite remote sensing [83]. The first space-based microwave radiometer capable of measuring SST was the SMMR [84; 85], and the high-quality PMW SST record began in 1997 with the launch of TRMM TMI (10 GHz channel), followed by GMI [86; 87; 88; 89]. The first globally accurate PMW SST data, derived from the 6 GHz channels, became available in 2002 through the AMSR-E [90; 91], which was followed by AMSR2 on the GCOM-W1, launched in May 2012 [90]. A follow-up mission to AMSR2, known as AMSR3, is planned by JAXA, while the ESA is developing the CIMR, which includes radiometer channels at 1.4, 6.9, 10.7, 18.7, and  
Figure 4: The NASA Cross-Calibrated Multi-Platform (CCMP) project combined monthly mean 10 m ocean surface wind speeds for December 2024 from microwave imagers—including PMWIs such as DMSP SSMS, GCOM-W1 AMSR-E, and GPM GMI [81] (source: figure created by authors). 36.6 GHz. CIMR is a polar mission designed to provide all-weather, high-resolution, and high-accuracy sub-daily observations of SST as its primary variables [77; 92; 93]. PMW SST estimates obtained using the 6.9 and 10.7 GHz channels typically have a spatial sampling of approximately 10 km, a resolution ranging from 50 to 60 km, and an uncertainty of around 0.4 \({}^{\circ}\)C [80; 94; 95; 96] that is primarily due to mismatches in the timing and location of observations, variations in measurement depth, and errors in both satellite estimates and in situ observations [83]. Moreover, the spatial resolution of SST retrievals is limited, meaning that a larger antenna is necessary to achieve a higher spatial resolution. AMSR3 has capabilities nearly identical to those of AMSR2, but with the added inclusion of high-frequency channels at 166 and 183 GHz. Enhancing the spatial resolution of measurements from the 6.9 and 10.7 GHz channels and also identifying the role of different channel combinations could significantly improve PMW SST estimates and increase their information content in global products and regional analysis systems [83].