The sensitivity of satellite microwave observations to liquid water in the Antarctic snowpack

Surface melting on the Antarctic Ice Sheet has been monitored by satellite microwave radiometry for over 40 years. Despite this long perspective, our understanding of the microwave emission from wet snow is still limited, preventing the full exploitation of these observations to study supraglacial hydrology. Using the Snow Microwave Radiative Transfer (SMRT) model, this study investigates the sensitivity of microwave brightness temperature to snow liquid water content at frequencies from 1.4 to 37 GHz. We first determine the snowpack properties for eight selected coastal sites by retrieving profiles of density, grain size and ice layers from microwave observations when the snowpack is dry during wintertime. Second, a series of brightness temperature simulations is run with added water. The results show that (i) a small quantity of liquid water (≈0.5 kg m−2) can be detected, but the actual quantity cannot be retrieved out of the full range of possible water quantities; (ii) the detection of a buried wet layer is possible up to a maximum depth of 1 to 6 m depending on the frequency (6–37 GHz) and on the snow properties (grain size, density) at each site; (iii) surface ponds and water-saturated areas may prevent melt detection, but the current coverage of these waterbodies in the large satellite field of view is presently too small in Antarctica to have noticeable effects; and (iv) at 1.4 GHz, while the simulations are less reliable, we found a weaker sensitivity to liquid water and the maximal depth of detection is relatively shallow (&lt;10 m) compared to the typical radiation penetration depth in dry firn (≈1000 m) at this low frequency. These numerical results pave the way for the development of improved multi-frequency algorithms to detect melt intensity and the depth of liquid water below the surface in the Antarctic snowpack.</p

Snow Wetness Retrieved from L-Band Radiometry

The present study demonstrates the successful use of the high sensitivity of L-band brightness temperatures to snow liquid water in the retrieval of snow liquid water from multi-angular L-band brightness temperatures. The emission model employed was developed from parts of the “microwave emission model of layered snowpacks” (MEMLS), coupled with components adopted from the “L-band microwave emission of the biosphere” (L-MEB) model. Two types of snow liquid water retrievals were performed based on L-band brightness temperatures measured over (i) areas with a metal reflector placed on the ground (“reflector area”— T B , R ), and (ii) natural snow-covered ground (“natural area”— T B , N ). The reliable representation of temporal variations of snow liquid water is demonstrated for both types of the aforementioned quasi-simultaneous retrievals. This is verified by the fact that both types of snow liquid water retrievals indicate a dry snowpack throughout the “cold winter period” with frozen ground and air temperatures well below freezing, and synchronously respond to snowpack moisture variations during the “early spring period”. The robust and reliable performance of snow liquid water retrieved from T B , R , together with their level of detail, suggest the use of these retrievals as “references” to assess the meaningfulness of the snow liquid water retrievals based on T B , N . It is noteworthy that the latter retrievals are achieved in a two-step retrieval procedure using exclusively L-band brightness temperatures, without the need for in-situ measurements, such as ground permittivity ε G and snow mass-density ρ S . The latter two are estimated in the first retrieval-step employing the well-established two-parameter ( ρ S , ε G ) retrieval scheme designed for dry snow conditions and explored in the companion paper that is included in this special issue in terms of its sensitivity with respect to disturbative melting effects. The two-step retrieval approach proposed and investigated here, opens up the possibility of using airborne or spaceborne L-band radiometry to estimate ( ρ S , ε G ) and additionally snow liquid water as a new passive L-band data product