6th International Workshop on Retrieval of Bio- & Geo-physical Parameters from SAR Data for Land Applications

Ku- and X-band Radar Backscatter and SWE – Observations in Different Snow Cover Regions

18 Nov 2015, 11:20

20m

Harwell, UK

Ice and Snow III - Ice & Snow

Speaker

Mr Helmut Rott (ENVEO IT)

Description

Several field campaigns were conducted in recent years in order to advance the understanding of radar interaction with seasonal snow and to support Phase-A science activities for the ESA Earth Explorer candidate mission CoReH2O. Ku- and X-band backscatter data were acquired by ground-based scatterometer systems and the airborne SnowSAR sensor. The test sites cover tundra sites in Manitoba and the North West Territories, Canada, taiga snow near Sodankylä, northern Finland, and alpine and maritime snow in two different elevation zones of the Austrian Alps. These snow cover classes are characterized by distinct differences in snow depth, stratification and microstructure. Though the boundary conditions triggering the buildup and evolution of the snowpack are quite different in the various climate zones, similar problems arise for inverting the backscatter measurements in terms of snow water equivalent (SWE). A key issue is the separation of effects of evolving snow structure versus the signal arising from the accumulation of snow volume or mass. The snow packs in the various test sites are characterized by bottom layers with coarse grains, superimposed by layers with smaller grain size. Whereas in the tundra sites the temperature gradient metamorphism is the main mechanism for grain growth, it is melt metamorphism for the maritime snow type in the alpine valley Leutasch. In the high alpine site Rotmoos and the taiga site in Sodankylä transient melt events are common in the early snow season, causing the formation of a coarse grained bottom layer. The microstructure of this layer is later on modified through the formation of depth hoar. Snow accumulating on these layers has smaller grains, so that the scattering contribution of the bottom layer is important throughout the winter season. In the high alpine site the contributions of the rough ground/snow interface and of the coarse grained bottom layer dominate the backscatter signal throughout the winter season. Therefore the accumulating fine grained snow does not induce a significant change in backscatter, impeding distinct relations between sigma-0 and SWE both at X-band and Ku-band frequencies. Also in Sodankylä the X-band backscatter signal changes little during winter, whereas the Ku-band backscatter intensity increases. The firmness of the relation between Ku-band sigma-0 and SWE is quite different in the various winter seasons, where the history of snowfall and snow metamorphism seems to be a main factor. At the tundra site near Churchill, Manitoba, the Ku-band backscatter increases significantly during winter, though the maximum snow depth is rather modest. The rising backscatter intensity coincides with the growth of depth hoar, suggesting that depth hoar is a main factor for explaining the observed relationship between backscatter intensity and SWE. On the other hand, for the maritime snow in the alpine valley melt metamorphism is a dominating factor for evolution of the backscatter signal. During the AlpSAR field experiment 2012/13, we observed in January high backscatter coefficients both in X- and Ku-band after a major melt/freeze event. The accumulation of fine-grained snow later on did not cause any substantial change in the backscatter intensity. The observations in the different snow cover regions emphasize the importance of snow structure and metamorphic state for evaluating relations between backscatter intensity and SWE, as well as for explaining cases lacking such relations. Consequently, reliable methods for retrieval of SWE need to account for microstructure and layering of snow, taking into account the temporal evolution of snow state. Radar backscatter measurements by themselves are not sufficient for definite separation of the signal contributions induced by either snow mass or snow structure. Complementary information, supplied by snow process models driven by meteorological data, and possibly also complementary observations of snow properties by means of other remote sensing systems, are needed for supporting reliable SWE retrievals.