Modeling the Observed Microwave Emission from Shallow Multi-Layer Tundra Snow Using DMRT-ML

Abstract

Abstract:The observed brightness temperatures (Tb) at 37 GHz from typical moderate density dry snow in mid-latitudes decreases with increasing snow water equivalent (SWE) due to volume scattering of the ground emissions by the overlying snow. At a certain point, however, as SWE increases, the emission from the snowpack offsets the scattering of the sub-nivean emission. In tundra snow, the Tb slope reversal occurs at shallower snow thicknesses. While it has been postulated that the inflection point in the seasonal time series of observed Tb V 37 GHz of tundra snow is controlled by the formation of a thick wind slab layer, the simulation of this effect has yet to be confirmed. Therefore, the Dense Media Radiative Transfer Theory for Multi Layered (DMRT-ML) snowpack is used to predict the passive microwave response from airborne observations over shallow, dense, slab-layered tundra snow. Airborne radiometer observations coordinated with ground-based in situ snow measurements were acquired in the Canadian high Arctic near Eureka, NT, in April 2011. The DMRT-ML was parameterized with the in situ snow measurements using a two-layer snowpack and run in two configurations: a depth hoar and a wind slab dominated pack. With these two configurations, the calibrated DMRT-ML successfully predicted the Tb V 37 GHz response (R correlation of 0.83) when compared with the observed airborne Tb footprints containing snow pits measurements. Using this calibrated model, the DMRT-ML was applied to the whole study region. At the satellite observation scale, observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) over the study area reflected seasonal differences between Tb V 37 GHz and Tb V 19 GHz that supports the hypothesis of the development of an early season volume scattering depth hoar layer, followed by the growth of the late season emission-dominated wind slab layer. This research highlights the necessity to consider the two-part emission characteristics of a slab-dominated tundra snowpack at 37 GHz Tb.

Characterizing tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals

“…Also included in Fig. 4 are in situ CV sd estimates with variable high-density sampling (magnaprobe) over different spatial extents at Daring Lake, NWT (Derksen et al, 2009;Rees et al, 2014); Puvirnituq, QC (Derksen et al, 2010); and at Eureka, NU (Saberi et al, 2017). The two points at the limit coverage scale correspond to areas of respectively 625 km 2 (CV sd = 1, Daring Lake site; Chris Derksen, personal communication, 2009) and 198 km 2 (CV sd = 0.89, Eureka site; Saberi et al, 2007).…”

Characterizing Tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals

“…In Figure 3, we investigated the relationship between spatial coverage of sampling and the parameter. Datasets include RPAS-derived data at TVC (TVC18-RPAS) containing 7 areas with various size from 1-4 km 2 , and at CB (map of 0.2 km 2 ), and in-situ (magnaprobe) with variable highdensity sampling over different spatial extents at Daring Lake, NWT (Derksen et al, 2009;Rees et al, 2014), Puvirnituq, QC (Derksen et al, 2010) and at Eureka, NU (Saberi et al, 2017). Results showed that the converges toward 0.9 as spatial coverage increased up to 4 km 2 , suggesting typical values of 0.8-1.0 for microwave pixels of 3.125 km (Fig.…”

The influence of tree transmissivity variations in winter on satellite snow parameter observations

“…Spaceborne passive microwave (PM) snow retrieval methods are an important approach to estimate terrestrial seasonal snow depth (SD) and snow water equivalent (SWE) (see Kelly et al 2003;Derksen 2008;Kelly 2009;Takala et al 2011;Tedesco and Jeyaratnam 2016;Pan et al 2016;Saberi et al 2017). Tb differences between a lower frequency channel and a higher frequency channel (e.g.…”