Cross-validation of microwave snowfall products over the continental United States
- 1University of Leicester, National Centre for Earth Observation, Physics and Astronomy, United Kingdom of Great Britain – England, Scotland, Wales (kamil.mroz@le.ac.uk)
- 2Institute of Atmospheric Sciences and Climate (ISAC), National Research Council of Italy (CNR), Rome, Italy
- 3Department of Environmental, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Torino, Italy
- 4Earth Observation Science, Department of Physics and Astronomy, University of Leicester, Leicester, United Kingdom
- 5School of Meteorology and School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, Oklahoma
- 6NOAA/National Severe Storms Laboratory, Norman, Oklahoma
- 7Advanced Radar Research Center, University of Oklahoma, Norman, Oklahoma
In this talk, surface snowfall rate estimates from the Global Precipitation Measurement (GPM) mission’s Core Observatory sensors and the CloudSat radar are compared to those from the Multi-Radar Multi-Sensor (MRMS) radar composite product over the continental United States. The analysis spans a period between Nov. 2014 and Sept. 2020 and covers the following products: the Dual-Frequency Precipitation Radar product (2A.GPM.DPR) and its single frequency counterparts (2A.GPM.Ka, 2A.GPM.Ku); GPM Combined Radar Radiometer Algorithm (2B.GPM.DPRGMI.CORRA); the CloudSat Snow Profile product (2C-SNOW-PROFILE) and two passive microwave retrievals i.e. the Goddard PROFiling algorithm (2A.GPM.GMI.GPROF) and the Snow retrievaL ALgorithm fOr gMi (SLALOM).
The 2C-SNOW product has the highest Heidke Skill Score (HSS=75%) for detecting snowfall among all the analysed products. SLALOM ranks the second (60%) while the Ka-band products falls at the end of the spectrum, with the HSS of 10% only. Low detection capabilities of the DPR products are a result of its low sensitivity. All the GPM retrievals underestimate not only the snow occurances but also snowfall volumes. Underestimation by a factor of two is present for all the GPM products compared to MRMS data. Large discrepancies (RMSE of 0.7 to 1.5 mm/h) between space-borne and ground-based snowfall rate estimates can be attributed to the complexity of ice scattering properties and differences in the algorithms' assumptions.
How to cite: Mroz, K., Montopoli, M., Panegrossi, G., Baldini, L., Battaglia, A., and Kirstetter, P.: Cross-validation of microwave snowfall products over the continental United States, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9971, https://doi.org/10.5194/egusphere-egu21-9971, 2021.
