Edward G. Josberger

The Effects of Layers in Dry Snow on Its Passive Microwave Emissions Using Dense Media Radiative Transfer Theory Based on the Quasicrystalline Approximation (QCA/DMRT)

A model for the microwave emissions of multilayer dry snowpacks, based on dense media radiative transfer (DMRT) theory with the quasicrystalline approximation (QCA), provides more accurate results when compared to emissions determined by a homogeneous snowpack and other scattering models. The DMRT model accounts for adhesive aggregate effects, which leads to dense media Mie scattering by using a sticky particle model. With the multilayer model, we examined both the frequency and polarization dependence of brightness temperatures (Tbs) from representative snowpacks and compared them to results from a single-layer model and found that the multilayer model predicts higher polarization differences, twice as much, and weaker frequency dependence. We also studied the temporal evolution of Tb from multilayer snowpacks. The difference between Tbs at 18.7 and 36.5 GHz can be 5 K lower than the single-layer model prediction in this paper. By using the snowpack observations from the Cold Land Processes Field Experiment as input for both multi- and single-layer models, it shows that the multilayer Tbs are in better agreement with the data than the single-layer model. With one set of physical parameters, the multilayer QCA/DMRT model matched all four channels of Tb observations simultaneously, whereas the single-layer model could only reproduce vertically polarized Tbs. Also, the polarization difference and frequency dependence were accurately matched by the multilayer model using the same set of physical parameters. Hence, algorithms for the retrieval of snowpack depth or water equivalent should be based on multilayer scattering models to achieve greater accuracy.

Analysis of ground-measured and passive-microwave-derived snow depth variations in midwinter across the northern Great Plains

Abstract Accurate estimation of snow mass is important for the characterization of the hydrological cycle at different space and time scales. For effective water resources management, accurate estimation of snow storage is needed. Conventionally, snow depth is measured at a point, and in order to monitor snow depth in a temporally and spatially comprehensive manner, optimum interpolation of the points is undertaken. Yet the spatial representation of point measurements at a basin or on a larger distance scale is uncertain. Spaceborne scanning sensors, which cover a wide swath and can provide rapid repeat global coverage, are ideally suited to augment the global snow information. Satellite-borne passive microwave sensors have been used to derive snow depth (SD) with some success. The uncertainties in point SD and areal SD of natural snowpacks need to be understood if comparisons are to be made between a point SD measurement and satellite SD. In this paper three issues are addressed relating satellite deriva...

Characterization of Errors in a Coupled Snow Hydrology–Microwave Emission Model

Abstract Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (TB) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while TB model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (G...

Estimating terrestrial snow depth with the TOPEX-Poseidon altimeter and radiometer

Active and passive microwave measurements obtained by the dual-frequency TOPEX-Poseidon radar altimeter from the Northern Great Plains of the United States are used to develop a snow pack radar backscatter model. The model results are compared with daily time series of surface snow observations made by the U.S. National Weather Service. The model results show that Ku-band provides more accurate snow depth determinations than does C-band. Comparing the snow depth determinations derived from the TOPEX-Poseidon nadir-looking passive microwave radiometers with the oblique-looking Satellite Sensor Microwave Imager (SSM/I) passive microwave observations and surface observations shows that both instruments accurately portray the temporal characteristics of the snow depth time series. While both retrievals consistently underestimate the actual snow depths, the TOPEX-Poseidon results are more accurate.

Glacier mass-balance fluctuations in the Pacific Northwest and Alaska, USA

Abstract The more than 40 year record of net and seasonal mass-balance records from measurements made by the United States Geological Survey on South Cascade Glacier, Washington, and Wolverine and Gulkana Glaciers, Alaska, shows annual and interannual fluctuations that reflect changes in the controlling climatic conditions at regional and global scales. As the mass-balance record grows in length, it is revealing significant changes in previously described glacier mass-balance behavior, and both inter-glacier and glacier–climate relationships. South Cascade and Wolverine Glaciers are strongly affected by the warm and wet maritime climate of the northeast Pacific Ocean. Their net balances have generally been controlled by winter accumulation, with fluctuations that are strongly related to the Pacific Decadal Oscillation (PDO). Recently, warm dry summers have begun to dominate the net balance of the two maritime glaciers, with a weakening of the correlation between the winter balance fluctuations and the PDO. Non-synchronous periods of positive and negative net balance for each glacier prior to 1989 were followed by a 1989–2004 period of synchronous and almost exclusively negative net balances that averaged –0.8m for the three glaciers.

Greenland Sea Odden sea ice feature: Intra‐annual and interannual variability

The “Odden” is a large sea ice feature that forms in the east Greenland Sea that may protrude eastward to 5°E from the main sea ice pack (at about 8°W) between 73° and 77°N. It generally forms at the beginning of the winter season and can cover 300,000 km2. Throughout the winter the outer edge of the Odden may advance and retreat by several hundred kilometers on timescales of a few days to weeks. Satellite passive microwave observations from 1978 through 1995 provide a continuous record of the spatial and temporal variations of this extremely dynamic phenomenon. Aircraft synthetic aperture radar, satellite passive microwave, and ship observations in the Odden show that the Odden consists of new ice types, rather than older ice types advected eastward from the main pack. The 17-year record shows both strong interannual and intra-annual variations in Odden extent and temporal behavior. For example, in 1983 the Odden was weak, in 1984 the Odden did not occur, and in 1985 the Odden returned late in the season. An analysis of the ice area and extent time series derived from the satellite passive microwave observations along with meteorological data from the International Arctic Buoy Program (IABP) determined the meteorological forcing associated with Odden growth, maintenance, and decay. The key meteorological parameters that are related to the rapid ice formation and decay associated with the Odden are, in order of importance, air temperature, wind speed, and wind direction. Oceanographic parameters must play an important role in controlling Odden formation, but it is not yet possible to quantify this role because of a lack of long-term oceanographic observations.

The effects of snowpack grain size on satellite passive microwave observations from the Upper Colorado River Basin

Understanding the passive microwave emissions of a snowpack, as observed by satellite sensors, requires knowledge of the snowpack properties : water equivalent, grain size, density, and stratigraphy. For the snowpack in the Upper Colorado River Basin, measurements of snow depth and water equivalent are routinely available from the U.S. Department of Agriculture, but extremely limited information is available for the other properties. To provide this information, a field program from 1984 to 1995 obtained profiles of snowpack grain size, density, and temperature near the time of maximum snow accumulation, at sites distributed across the basin. A synoptic basin-wide sampling program in 1985 showed that the snowpack exhibits consistent properties across large regions. Typically, the snowpack in the Wyoming region contains large amounts of depth hoar, with grain sizes up to 5 mm, while the snowpack in Colorado and Utah is dominated by rounded snow grains less than 2 mm in diameter. In the Wyoming region, large depth hoar crystals in shallow snowpacks yield the lowest emissivities or coldest brightness temperatures observed across the entire basin. Yearly differences in the average grain sizes result primarily from variations in the relative amount of depth hoar within the snowpack. The average grain size for the Colorado and Utah regions shows much less variation than do the grain sizes from the Wyoming region. Furthermore, the greatest amounts of depth hoar occur in the Wyoming region during 1987 and 1992, years with strong El Nino Southern Oscillation, but the Colorado and Utah regions do not show this behavior.

Northern Great Plains 1996/97 seasonal evolution of snowpack parameters from satellite passive-microwave measurements

Abstract For the American northern Great Plains region, the 1996/97 snow season had snow accumulations much greater than normal, which combined with rapid warming to produce extensive flooding in the Red River of the North river basin. Passive-microwave observations from the Special Sensor Microwave/Imager (SSM/I) are used to follow the evolution of the snowpack during the snow season and to map the extent of standing water or very saturated soils during spring 1997. SSM/I-derived snow-depth algorithms that assume a fixed snow grain-size constantly underestimated the snow depth by a factor of 2 in the region where extensive flooding occurred. An estimate of the thermal gradient through the snowpack is used to model the growth of the snow grain-size and to compute more accurately the evolution of the snow depth over the region. As is commonly observed, when the melt season begins, liquid water in the snowpack causes the SSM/I spectral gradient to drop to zero. In this case, the spectral gradient fell to unusually negative values, which were indicative of large areas of open water, and not wet snow or soil.

Remote sensing of the Fram Strait marginal ice zone

Sequential remote sensing images of the Fram Strait marginal ice zone played a key role in elucidating the complex interactions of the atmosphere, ocean, and sea ice. Analysis of a subset of these images covering a 1-week period provided quantitative data on the mesoscale ice morphology, including ice edge positions, ice concentrations, floe size distribution, and ice kinematics. The analysis showed that, under light to moderate wind conditions, the morphology of the marginal ice zone reflects the underlying ocean circulation. High-resolution radar observations showed the location and size of ocean eddies near the ice edge. Ice kinematics from sequential radar images revealed an ocean eddy beneath the interior pack ice that was verified by in situ oceanographic measurements.

Modeling multi-layer effects in passive microwave remote sensing of dry snow using Dense Media Radiative Transfer Theory (DMRT) based on quasicrystalline approximation

The Dense Media Radiative Transfer theory (DMRT) of Quasicrystalline Approximation of Mie scattering by sticky particles is used to study the multiple scattering effects in layered snow in microwave remote sensing. Results are illustrated for various snow profile characteristics. Polarization differences and frequency dependences of multilayer snow model are significantly different from that of the single-layer snow model. Comparisons are also made with CLPX data using snow parameters as given by the VIC model.