Peter Toose

Snow Density and Ground Permittivity Retrieved from L-Band Radiometry: A Synthetic Analysis

A synthetic study was performed to determine the potential to retrieve dry-snow density and ground permittivity from multiangular L-band brightness temperatures. The thereto employed emission model 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. The restriction to L-band made it possible to avoid scattering and absorption in the snow volume, leading to a rather simple formulation of our emission model. Parametric model studies revealed L-band signatures related to the mass density of the bottom layer of a dry snowpack. This gave rise to the presented analysis of corresponding retrieval performances based on measurements synthesized with the developed emission model. The question regarding the extent to which random noise translates into retrieval uncertainties was investigated. It was found that several classes of snow densities could be distinguished by retrievals based on L-band brightness temperatures with soil moisture and ocean salinity (SMOS)-typical data quality. Further synthetic retrievals demonstrated that propagation effects must be taken into account in dry snow even at L-band when retrieving permittivity of the underlying ground surface. Accordingly, current SMOS-based retrievals seam to underestimate actual ground permittivity by typically 30% as dry snow is wrongly considered as “invisible.” Although experimental validation has not yet been performed, the proposed retrieval approach is seen as a promising step toward the full exploitation of L-band brightness temperatures available from current and future satellite Earth observation missions, especially over the cold regions of the Northern Hemisphere.

Physical properties of Arctic versus subarctic snow: Implications for high latitude passive microwave snow water equivalent retrievals

Two unique observational data sets are used to evaluate the ability of multi-layer snow emission models to simulate passive microwave brightness temperatures (TB) in high latitude, observation sparse, snow-covered environments. Data were utilized from a coordinated series of 18 sites measured across the subarctic Northwest Territories and Nunavut, Canada in April 2007 during a 1000 km segment of a 4200 km snowmobile traverse from Fairbanks, Alaska to Baker Lake, Nunavut (~64°N). In April 2011, a network of 22 high Arctic sites was sampled across a 60 × 60 km study area on the Fosheim Peninsula, Ellesmere Island (~80°N). In comparison to sites across the subarctic, high Arctic snow was more spatially variable, thinner (site averages between 15 and 25 cm versus 30 to 40 cm), colder (−25°C versus −10°C), composed of fewer layers, had a proportionally higher fraction of wind slabs (storing 57% of the snow water equivalent (SWE) versus 15%), with these slabs comparatively denser (often exceeding 450 g/cm3, compared to 350 g/cm3 in the subarctic). The physical snow measurements were used as inputs to snow emission model simulations. The radiometric difference between simulations of “typical” arctic and subarctic snow reached 30 K at 37 GHz. Sensitivity analysis showed that this TB difference could be partitioned between the effects of physical temperature (~5 K between −25°C and −10°C), wind slab density (~5 K between 0.40and 0.35 g/cm3), and vertical depth hoar fraction (~20 K between 70% and 30% vertical fraction of total snow depth). Model simulations at the satellite scale (625 km2) were produced using the observational spread for snow depth and snow stratigraphy. The range of TB from simulations with varied stratigraphy extended unrealistically far below the magnitude of satellite measured TB, illustrating that the snow depth first guess is very important for SWE retrieval schemes that are based on forward emission model simulations.

Evaluation of Operation IceBridge quick‐look snow depth estimates on sea ice

We evaluate Operation IceBridge (OIB) ‘quick-look’ (QL) snow depth on sea ice retrievals using in situ measurements taken over immobile first-year ice (FYI) and multi-year ice (MYI) during March of 2014. Good agreement was found over undeformed FYI (-4.5 cm mean bias) with reduced agreement over deformed FYI (-6.6 cm mean bias). Over MYI, the mean bias was -5.7 cm but 54% of retrievals were discarded by the OIB retrieval process as compared to only 10% over FYI. Footprint scale analysis revealed a root mean square error (RMSE) of 6.2 cm over undeformed FYI with RMSE of 10.5 cm and 17.5 cm in the more complex deformed FYI and MYI environments. Correlation analysis was used to demonstrate contrasting retrieval uncertainty associated with spatial aggregation and ice surface roughness.

Snow stratigraphic heterogeneity within ground‐based passive microwave radiometer footprints: Implications for emission modeling

Two-dimensional measurements of snowpack properties (stratigraphic layering, density, grain size, and temperature) were used as inputs to the multilayer Helsinki University of Technology (HUT) microwave emission model at a centimeter-scale horizontal resolution, across a 4.5 m transect of ground-based passive microwave radiometer footprints near Churchill, Manitoba, Canada. Snowpack stratigraphy was complex (between six and eight layers) with only three layers extending continuously throughout the length of the transect. Distributions of one-dimensional simulations, accurately representing complex stratigraphic layering, were evaluated using measured brightness temperatures. Large biases (36 to 68 K) between simulated and measured brightness temperatures were minimized (−0.5 to 0.6 K), within measurement accuracy, through application of grain scaling factors (2.6 to 5.3) at different combinations of frequencies, polarizations, and model extinction coefficients. Grain scaling factors compensated for uncertainty relating optical specific surface area to HUT effective grain size inputs and quantified relative differences in scattering and absorption properties of various extinction coefficients. The HUT model required accurate representation of ice lenses, particularly at horizontal polarization, and large grain scaling factors highlighted the need to consider microstructure beyond the size of individual grains. As variability of extinction coefficients was strongly influenced by the proportion of large (hoar) grains in a vertical profile, it is important to consider simulations from distributions of one-dimensional profiles rather than single profiles, especially in sub-Arctic snowpacks where stratigraphic variability can be high. Model sensitivity experiments suggested that the level of error in field measurements and the new methodological framework used to apply them in a snow emission model were satisfactory. Layer amalgamation showed that a three-layer representation of snowpack stratigraphy reduced the bias of a one-layer representation by about 50%.

Observing Scattering Mechanisms of Bubbled Freshwater Lake Ice Using Polarimetric RADARSAT-2 (C-Band) and UW-Scat (X- and Ku-Bands)

A winter time series of ground-based (X- and Ku-bands) scatterometer and spaceborne synthetic aperture radar (SAR) (C-band) fully polarimetric observations coincident with in situ snow and ice measurements are used to identify the dominant scattering mechanism in bubbled freshwater lake ice in the Hudson Bay Lowlands near Churchill, Manitoba. Scatterometer observations identify two physical sources of backscatter from the ice cover: the snow–ice and ice–water interfaces. Backscatter time series at all frequencies show increases from the ice–water interface prior to the inclusion of tubular bubbles in the ice column based on in situ observations, indicating scattering mechanisms independent of double-bounce scatter. The co-polarized phase difference of interactions at the ice–water interface from both scatterometer and SAR observations is centered at 0° during the time series, also indicating a scattering regime other than double bounce. A Yamaguchi three-component decomposition of the RADARSAT-2 C-band time series is presented, which suggests the dominant scattering mechanism to be single-bounce off the ice–water interface with appreciable surface roughness or preferentially oriented facets, regardless of the presence, absence, or density of tubular bubble inclusions. This paper builds on newly established evidence of single-bounce scattering mechanism for freshwater lake ice and is the first to present a winter time series of ground-based and spaceborne fully polarimetric active microwave observations with polarimetric decompositions for bubbled freshwater lake ice.

Exploring the influence of snow microstructure on dual-frequency radar measurements

Recent advancements to the understanding of snow-microwave interaction have helped to identify the considerable potential for radar-based retrieval of terrestrial snow mass. If applied to space-borne platforms, such retrievals could provide much needed improvements to the spatial and temporal availability of snow mass estimates. To further understanding of these interactions in tundra environments, this study evaluates an extensive set of coincident in situ snow measurements and airborne dual-frequency (17.2 and 9.6 GHz) radar observations near Inuvik, Northwest Territories, Canada. Given known uncertainties related to the role of microstructure in radar-based retrievals, an enhanced snow pit protocol was introduced to objectively characterize specific surface area (SSA) with a shortwave infrared integrating sphere (IRIS) system. Snow pit and bulk snow measurements including SSA are used to parameterize the Microwave Emission Model of Layered Snowpacks Adapted to Include Backscattering (MEMLS3&a) and evaluate observed spatial diversity in the airborne radar signal.

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

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.

Investigating the influence of variable freshwater ice types on passive and active microwave observations

Dual-polarized airborne passive microwave (PM) brightness temperatures (Tb) at 6.9 GHz H/V, 19 GHz H/V and 37 GHz H/V and spaceborne active microwave (AM) X-band (9.65 GHz VV, VH) backscatter (σ0) are observed coincident to in situ snow and lake-ice measurements collected over two lakes near Inuvik, Canada. Lake-ice thickness is found to be positively correlated with 19 GHz V emission (R = 0.67) and negatively with 19 GHz H emission (R = −0.79), indicating surface ice conditions influence microwave interaction. Lake ice types are delineated from TerraSAR-X synthetic aperture radar (SAR) images using the iterative region growing with semantics (IRGS) segmentation algorithm implemented in the MAGIC (MAp Guided Ice Classification) system. The spatial extent of derived ice type classes correspond well to in situ observations. The overall magnitude of emission at 19 GHz H and X-band VH σ0 increase with the scattering potential of associated ice types (grey/rafted ice). Transects of 6.9 GHz PM and 19 GHz PM exhibit positive relationships with VH σ0 over freshwater lake ice, with the greatest R coefficients at H-pol (R = 0.64, 0.46). Conversely, 6.9 GHz Tb and 19 GHz Tb exhibit negative R coefficients in regions of brackish water due to tubular bubble and brine inclusions in the ice. This study identifies congruency between PM and AM scattering mechanisms over lake ice for the purpose of identifying the influence of ice types on overall microwave interaction within the lake-ice system.

Analysis of L-Band brightness temperatures response to freeze/thaw in two prairie environments from surface-based radiometer measurements

The database helps to better understand and quantify the effect of F/T and snow on the L-Band signal. The information will be useful for the validation and calibration of satellite based products. The database will also be used to validate and calibrate different L-Band snow emission models [3-4-5].

Potential of L-band passive microwave radiometry for snow parameter retrieval

Dry snow is conventionally considered as having minimal effect on microwave radiation at long wavelengths (such as L-band). However, dry snow affects observed microwave signatures even at these wavelengths through changes in impedance matching between soil and the overlying media, as well as through changes in the refraction angle at the soil interface. Exploiting these effects, the multi-angular, dual-polarized L-band observations of e.g. the European Space Agencys SMOS (Soil Moisture and Ocean Salinity) mission have the potential to derive snow properties, such as the density of the lowest layers of the snowpack in contact with the ground. This in turn, would have the potential to inform retrieval schemes of snow cover based on EO-data from other sensors. In addition, the theoretical studies demonstrate that the effect of dry snow on retrieval of other geophysical variables, such as soil moisture, is not negligible. In this study, we demonstrate the simultaneous retrieval of snow density and ground permittivity in dry snow conditions, using a multi-year dataset of tower-based L-band observations. We show that following predictions of the theoretical studies, the retrieved snow density matches that of the density measured for the lowest snow layers; dry snow cover is also shown to affect retrievals of ground permittivity by up to 40 %.