jgrd16372.pdf (4.87 MB)
Snow scattering signals in ground-based passive microwave radiometer measurements
journal contributionposted on 2012-10-24, 09:08 authored by S. Kneifel, U. Löhnert, S. Crewell, A. Battaglia, D. Siebler
 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.