Development of a snowfall retrieval algorithm at high microwave frequencies

Abstract

[1] A snowfall retrieval algorithm based on Bayes' theorem is developed using high-frequency microwave satellite data. In this algorithm, observational data from both airborne and surface-based radars are used to construct an a priori database of snowfall profiles. These profiles are then used as input to a forward radiative transfer model to obtain brightness temperatures at high microwave frequencies. In the radiative transfer calculations, two size distributions for snowflakes and ten observed atmospheric sounding profiles are used with snowfall profiles from observations. In addition, the scattering properties of the snowflakes are calculated on the basis of realistic nonspherical shapes using discrete dipole approximation. The algorithm is first verified by airborne microwave and radar observations and then applied to the Advanced Microwave Sounding Unit-B (AMSU-B) satellite data. The retrieved snowfall rates using AMSU-B data from three snowfall cases in the vicinity of Japan show reasonable agreement with surface radar observations with correlation coefficients of about 0.8, 0.6, and 0.96 for the three cases, respectively. The comparison results also suggest the algorithm performs better for dry and heavy snow cases, but is less accurate for wet and weak snow cases.

Utilizing Spaceborne Radars to Retrieve Dry Snowfall

“…Unfortunately, routine surface measurements of snow are scarce in remote regions where snowfall frequently occurs, and these locales are also largely devoid of ground-based remote sensing observations that could provide useful information about frozen precipitation. Therefore, satellite-based microwave remote sensing remains the most viable option to obtain global snowfall information, and increasing attention is being dedicated to retrieve properties of snow via passive, active, and combined microwave observations (e.g., SkofronickJackson et al 2004;Noh et al 2006;Kim et al 2007;Liu 2008a;Grecu and Olson 2008). These recent research avenues are especially critical to prepare for the Global Precipitation Measurement (GPM) mission that is scheduled to launch early in the next decade and will include coincident active and passive measurements at higher latitudes.…”

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

“…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. Passive satellite sensors such as high-frequency (>80 GHz) microwave radiometers have also been used in detecting snowfall events [Liu and Curry, 1997;Chen and Staelin, 2003;Kongoli et al, 2003;Ferraro et al, 2005;Skofronick-Jackson et al, 2004;Noh et al, 2006Noh et al, , 2009. While most of these studies targeted moderate to heavy snowfall events under unfrozen or nonsnow-covered surfaces, the encouraging results from these studies offered a viable alternative to high-sensitivity space-borne radar for snowfall detection and retrieval.…”

Snowfall Detectability of Nasa's Cloudsat: The First Cross-Investigation of Its 2c-Snow-Profile Product and National Multi-Sensor Mosaic Qpe (Nmq) Snowfall Data

“…Many previous efforts have been put into the use of passive microwave sensors (e.g., AMSR-E, AMSU, and TMI) for detecting snowfall or snow cover and retrieving snow depth, snow water equivalent (SWE), or snowfall rate [8][9][10][11][12][13]. Active microwave sensors also have a great potential in measuring snow.…”