Snow scattering signals in ground‐based passive microwave radiometer measurements

Abstract

[1] This paper investigates the influence of snow microphysical parameters on the enhancement of ground-based passive microwave brightness temperature (TB) measurements. In addition to multispectral passive microwave observations between 20 and 150 GHz, a 35 GHz cloud radar and a 2-D video disdrometer for in situ measurements of snowfall were deployed as part of the "towards an optimal estimation-based snowfall characterization algorithm" campaign in the winter season of 2008-2009 at an Alpine environment located at 2650 m mean sea level. These observations are combined with nearby radiosonde ascents and surface standard meteorological measurements to reconstruct the atmospheric state (i.e., fields of temperature, humidity, snow, and liquid water contents) and are subsequently used as input for a microwave radiative transfer (RT) model. We investigate the sensitivity of the missing information about snow shape and snow particle size distribution (SSD) on the microwave TB measurements using the disdrometer data as a rough constraint. For an extended case study, we found that TBs at 90 and 150 GHz are significantly enhanced because of scattering of surface radiation at snow crystals and that this enhancement is clearly correlated with the radar derived snow water path (SWP < 0.2 kg m −2 ). RT simulations highlight the strong influence of the vertical distribution of cloud liquid water (liquid water path LWP < 0.1 kg m −2 ) on the TB, which in extreme cases, can fully obscure the snow scattering signal. TB variations of the same magnitude can also be caused by typical variations in SSD parameters and particle shape similar to results obtained by space-borne studies. Ground-based stations with their infrastructural capabilities in combining active and passive microwave observations have the potential to disentangle the influences of different snow shape, SSD, and SWP in snow retrievals, thus supporting current and future satellite missions.

G band atmospheric radars: new frontiers in cloud physics

“…In this context lidar and radar can provide useful complementary and synergetic information (Battaglia and Delanöe, 2013, and references therein). By combining multi-frequency measurements from active and passive microwave remote sensing instruments, essential assumptions on particle type and size distribution have been evaluated through consistency checks with radiative transfer modelling in snow clouds (Löhnert et al, 2011;Kneifel et al, 2010;Kulie et al, 2010). These assumptions can be constrained further by in situ measurements and continuous temperature and humidity profile information.…”

Uncertainties of ground-based microwave radiometer retrievals in zenith and off-zenith observations under snow conditions

“…The liquid water and snow both can produce noise signals in the microwave region, but in different ways. The liquid water affects the MWR measurements with the emission, but the snow produces a scattering signal and a higher-frequency, larger scattering signal produced by snow (Kneifel et al, 2010). As we all know, the temperature profile is retrieved with a brightness temperature of 51-59 GHz.…”

“…But the surface temperature at midlatitudes is not as low as that at high latitude and always higher than 0 • , so the snow falling near surface will partially convert to liquid water, and the liquid water affects the MWR measurements with the emission of microwave, especially at high frequencies. In snowfall conditions, the scattering of upwelling radiation and changing of the surface reflections and emissivity may also result in enhancement of brightness temperature, but it is significant at frequencies above 90 GHz (Kneifel et al, 2010). …”

“…As mentioned before, this is mainly because snowfall is easier to freeze on the radome top in heavy snowfall and the noise signals caused by snowfall increase, while on the sides of the radome the snowfall drops to the ground by gravity, so the MWR retrieval discrepancies are greater in heavy snowfall, and the discrepancies can be reduced in off-zenith observations. Furthermore, as discussed by Kneifel et al (2010), the measurements of brightness temperature will be affected by snow, and the depression is mainly caused by scattering of frozen hydrometeors. But the surface temperature at midlatitudes is not as low as that at high latitude and always higher than 0 • , so the snow falling near surface will partially convert to liquid water, and the liquid water affects the MWR measurements with the emission of microwave, especially at high frequencies.…”

“…Some methods are explored to investigate these characteristics and discuss their utilization in the snow measurements (Matrosov et al, 2008;Löhnert et al, 2011;Xie et al, 2012). The scattering signal of snow is highly dependent on the assumption of snow shape and snow size distribution (SSD), especially for large-sized parameters (Kneifel et al, 2010). Some studies have demonstrated that snowfall can significantly reduce the measurement accuracy of MWR (Knupp et al, 2009;Cimini et al, 2011;Ware et al, 2013).…”