Utilizing Spaceborne Radars to Retrieve Dry Snowfall

Abstract

A dataset consisting of one year of CloudSat Cloud Profiling Radar (CPR) near-surface radar reflectivity Z associated with dry snowfall is examined in this study. The CPR observations are converted to snowfall rates S using derived Z e -S relationships, which were created from backscatter cross sections of various nonspherical and spherical ice particle models. The CPR reflectivity histograms show that the dominant mode of global near-surface dry snowfall has extremely light reflectivity values (;3-4 dBZ e ), and an estimated 94% of all CPR dry snowfall observations are less than 10 dBZ e . The average conditional global snowfall rate is calculated to be about 0.28 mm h 21 , but is regionally highly variable as well as strongly sensitive to the ice particle model chosen. Further, ground clutter contamination is found in regions of complex terrain even when a vertical reflectivity continuity threshold is utilized. The potential of future multifrequency spaceborne radars is evaluated using proxy 35-13.6-GHz reflectivities and sensor specifications of the proposed Global Precipitation Measurement dual-frequency precipitation radar (DPR). It is estimated that because of its higher detectability threshold, only about 7%-1% of the near-surface radar reflectivity values and about 17%-4% of the total accumulation associated with global dry snowfall would be detected by a DPR-like instrument, but these results are very sensitive to the chosen ice particle model. These potential detection shortcomings can be partially mitigated by using snowfall-rate distributions derived by the CPR or other similar high-frequency active sensors.

Improved Micro Rain Radar snow measurements using Doppler spectra post-processing

“…They found sufficient agreement between a MRR and a pulsed MIRA36 35.5 GHz cloud radar, if reflectivities exceed 3 dBz. However, Kulie and Bennartz (2009) showed that approximately half of the global snow events occur at reflectivities below 3 dBz, thus MRRs are only of limited use for snow climatologies. KN attributed the poor performance of the MRR below 3 dBz to the real time signal processing algorithm.…”

G band atmospheric radars: new frontiers in cloud physics

“…CloudSat (Stephens et al, 2008) offers one of the most sophisticated possibilities for deriving the distribution of global snowfall (Liu, 2008b). The advantage of CloudSat's cloud profiling radar is that one can derive information on the vertical distribution of snow as well as small cloud ice particles and thus estimate the surface snowfall rate even during relatively light precipitation cases (Liu, 2008b;Matrosov et al, 2008;Kulie and Bennartz, 2009). However, radar-based algorithms rely on statistical relations between the equivalent radar reflectivity factor Z e and snowfall rate S, which are in turn a function of particle fall velocity, particle habit (Petty and Huang, 2010;Kulie et al, 2010) and particle size distribution (PSD).…”

Detecting snowfall over land by satellite high‐frequency microwave observations: The lack of scattering signature and a statistical approach

“…The high sensitivity of the CPR (-25 dBZ) enables investigators to study the snowfall frequency and intensity based on measured radar reflectivity [e.g., Liu, 2008a;Matrosov et al, 2008;Kulie and Bennartz, 2009;Turk et al, 2011;Wood, 2011]. However, because CPR does not scan, it only measures a 1.5 km-wide strip on the Earth surface by each satellite pass, which largely limits its utility for weather monitoring and climate data collection.…”