![]() ![]() dBm to Watt converter Stripline Impedance calculator Microstrip line impedance Antenna G/T Noise temp.Retrievals of falling snow from space-based observations represent key inputs for understanding and linking Earth’s atmospheric, hydrological, and energy cycles. This work quantifies and investigates causes of differences among the first stable falling snow retrieval products from the Global precipitation Measurement (GPM) Core Observatory satellite and CloudSat’s Cloud Profiling Radar (CPR) falling snow product. An important part of this analysis details the challenges associated with comparing the various GPM and CloudSat snow estimates arising from different snow-rain classification methods, orbits, resolutions, sampling, instrument specifications, and algorithm assumptions. After equalizing snow-rain classification methodologies and limiting latitudinal extent, CPR observes nearly 10 (3) times the occurrence (accumulation) of falling snow as GPM’s Dual-Frequency Precipitation Radar (DPR). The occurrence disparity is substantially reduced if CloudSat pixels are averaged to simulate DPR radar pixels and CPR observations are truncated below the 8-dBZ reflectivity threshold. However, even though the truncated CPR- and DPR-based data have similar falling snow occurrences, average snowfall rate from the truncated CPR record remains significantly higher (43%) than the DPR, indicating that retrieval assumptions (microphysics and snow scattering properties) are quite different. ![]() ![]() Diagnostic reflectivity ( Z)-snow rate ( S) relationships were therefore developed at Ku and W band using the same snow scattering properties and particle size distributions in a final effort to minimize algorithm differences. CPR-DPR snowfall amount differences were reduced to ~16% after adopting this diagnostic Z– S approach. Observations of the global distributions of falling snow are needed for a wide variety of scientific and societal applications. For example, falling snow observations can be used to evaluate global change precipitation science predictions ( Karl et al. 2017 Harpold and Kohler 2017) and are needed for assessing inputs to snowpack water reserves ( Lettenmaier et al. While most of the societal needs for falling snow measurements are important over land surfaces, falling snow over oceans and lakes represents a loss to capturing that water for resources and can affect the water body characteristics by changing the salinity and/or water temperature ( Kattsov and Walsh 2000 Holland et al. Since it is difficult to measure global precipitation from ground-based observations ( Kidd et al. 2017), satellite observations are required (e.g., Levizzani et al. The Tropical Rainfall Measuring Mission (TRMM) and other satellite precipitation sensors have shown the value of satellite-based global rain observations ( Hou et al. Now there is great interest in hydrological investigations with global falling snow-rate products to help close the atmospheric inputs to the water cycle ( Field and Heymsfield 2015 Rodell et al. 2015) and to study snowpack patterns and growth ( Palerme et al. 2018).Ĭurrently there are two National Aeronautics and Space Administration (NASA) spaceborne platforms with instruments capable of observing falling snow: CloudSat ( Stephens et al.
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