# Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate
## 3 Satellite Measurement of Precipitation
### Scientific and Technological Challenges
#### 3.2.2 Observing Snow and Ice  
The retrieval of precipitation from space is still not effective in estimating the solid component both from radar and radiometers [168]; this is due to the difficulty of distinguishing between falling snow and snow/ice on the ground, and also to the sensitivity of active and passive sensors to snowfall below clouds. Note that the accuracy of ground measurements is not very high due to the technological limitations of sensors and to wind resuspension; intercomparison campaigns give some hope to improve over existing methods [169; 170]. The first step toward the creation of global spaceborne snowfall algorithms is the determination of detection thresholds for the various active and passive sensor channel configurations as outlined by Skofronick-Jackson et al. [171]. The study showed the importance of the radar frequency (W-band against Ku- and Ka-bands) in the retrieval, the influence of cloud structure macrophysics on PMW channel detection capability, and the effects of snowflake microphysics (shape and density) on active and passive measurements. Previously, Kulie and Bennartz [172] found that near surface dry snowfall is characterized globally by extremely light reflectivity values (3-4 dBZ\({}_{\rm e}\)). Liu [173] used CloudSat's CPR data to show that the CPR was indeed capable of detecting snow clouds and their vertical structure. The GPM Microwave Imager (GMI) has new capabilities for the detection of snowfall, the retrieval of snow water paths (SWPs) [174], and the detection of near surface snowfall using the DPR [175], and is able to provide maps of global snowfall properties [176] (see an example in Figure 8). A quantification of the differences between CPR and DPR products [177] recently showed that the average snowfall rate from CPR is 43% higher than that observed by DPR, thus indicating that retrieval assumptions (microphysics and snow scattering properties) are quite different between the two algorithms. This is the key point for designing future snowfall algorithms and more accurate databases of the scattering properties of non-spherical cloud ice particles [178]. The community around the International Workshop on Space-based Snowfall Measurement (IWSSM), together with the IPWG, is working on this very important subject. The Snowport portal is a very helpful discussion forum ([[http://snowport.meteo.uni-koeln.de](http://snowport.meteo.uni-koeln.de)]([http://snowport.meteo.uni-koeln.de](http://snowport.meteo.uni-koeln.de)), last accessed 9 August 2019). Future developments will concentrate on triple-frequency radar technology [179; 180; 181]. Figure 8: GPM Core Observatory view of the “Nor’easter” winter storm on 2 March, 2018 over the Eastern US. Rainfall rates are shown in warm colors and snow-bearing clouds and falling snow in bluish colors. Courtesy of NASA ([[https://pmm.nasa.gov/extreme-weather/gpm-examines-snow-destructive-noreaster](https://pmm.nasa.gov/extreme-weather/gpm-examines-snow-destructive-noreaster)]([https://pmm.nasa.gov/extreme-weather/gpm-examines-snow-destructive-noreaster](https://pmm.nasa.gov/extreme-weather/gpm-examines-snow-destructive-noreaster)), last accessed 24 September 2019). Deep neural networks (DNN) are also being adopted as a viable alternative to merge together data from passive and active sensors at high latitudes [182]. This is accompanied by significant progress being made towards using PMW bands around 183 GHz for snowfall detection in Arctic conditions [183]. A better quantification of snowfall at high latitudes [184] and on a global scale [176] will also contribute to unravelling the controversy around the impact of Arctic warming on increased rainfall/snowfall [185] and, more generally, to explaining the differences in model projections between the southern and northern hemispheres and wet and dry regions [186]. It will also help examine the impact of excluding precipitating ice on atmospheric radiative fluxes and heating rates in climate models [187] and estimate the cooling flux from snow melting in the ocean [188].