C12A-01
Streamflow response to seasonal snow cover changes over large Siberian watersheds
We used remotely sensed weekly snow water equivalent (SWE) data (1988–2000) to investigate streamflow response to seasonal snow change in the large Siberian watersheds (the Ob, Yenisei, and Lena basins). We quantified the seasonal cycles and variations of snow cover and river streamflow and identified a clear correspondence of river discharge to seasonal snow cover change. We also examined and compared the weekly mean streamflow with the weekly basin SWE for the study period. The results revealed a strong relation between the streamflow and snow cover change during the spring melt season over the large Siberian watersheds. This relationship provides a practical procedure of using remotely sensed snow cover information for snowmelt runoff estimation over the large northern watersheds. Analyses of extreme (high/low) SWE cases (years) and the associated streamflow conditions indicate an association of high (low) flood peak with high (low) maximum SWE in the Ob and Yenisei basins. Comparative analyses of weekly basin SWE data versus snow cover extent(SCE), peak snowmelt floods, and climatic variables (temperature and winter precipitation) indicate consistency among basin SWE, SCE, and temperature but incompatibility between basin SWE and winter precipitation, particularly for the Lena watershed. The inconsistency suggests uncertainties in determination of basin winter snowfall amounts and limitations in applications of the SWE retrieval algorithm over large watersheds/regions with very different physical characteristics. Overall, the results of this study clearly demonstrate that the weekly SWE data/products derived from microwave remote sensing technology are useful in understanding seasonal streamflow changes in the arctic regions. http://www.uaf.edu/water/faculty/yang/bcp/index.htm
C12A-02 INVITED
Implementation strategies for multi-sensor snow data assimilation
Data assimilation provides a framework for optimally merging model predictions and remote sensing observations of snow properties (snow cover extent, water equivalent, grain size, melt state), ideally overcoming limitations of both. Remotely sensed snow-related observations to be assimilated can include visible (snow cover extent), passive microwave (brightness temperature), as well as IR (snow grain size). Although these observations can potentially provide more information about snow properties, they can also complicate the estimation problem due to differences in spatial/temporal scales between the model and the different types of observations, as well as different error structures associated with each data source. Different strategies of assimilating the three different types of observations (sequentially versus simultaneously) are explored, and simple models of the observation errors for each observation type are evaluated using measurements from the Cold Land Processes Experiment (CLPX). We examine how snow cover extent observations can be combined with passive microwave radiances to effectively downscale the latter observations (coarser scale). Additionally, the effects of forest and partial snow cover on the assimilation of microwave observations are shown, and simple error models that utilize ancillary datasets (e.g. land cover) are derived. Moreover, snow grain sizes estimated from IR sensors are evaluated in the context of simulating microwave brightness temperatures, and the implications of their simultaneous assimilation are discussed. These results are then applied to examples of SWE estimation using two data assimilation techniques: the Ensemble Kalman filter (EnKF) and the Multi-scale Ensemble Kalman filter (MSEnKF). The latter is especially attractive for multi-sensor assimilation applications as a result of its structure that accommodates multi-scale observations in a single tree structure.
C12A-03
Field-based Measurements of 37-GHz Microwave Extinction Length at Summit, Greenland
Microwave emission from ice sheets is related to both firn temperature and other firn properties, including density and grain size. To better understand the relationship between microwave emission, temperature and firn properties, we use a convolution model that relates surface temperatures to microwave brightness temperatures. The convolution model is constructed by using the thermal diffusivity equation to solve for a temperature profile in the radiative transfer equation. The model is fit using a timescale, the extinction-diffusion time, which is physically related to the extinction length, or e-folding depth, of the microwave emission and the thermal diffusivity of the firn. The success of the extinction-diffusion time model at predicting the microwave signal motivated this investigation of the spatial variation of microwave extinction lengths with firn properties on ice sheets. Here we present a method for collecting field-based measurements of microwave extinction lengths and present results from Summit, Greenland. We measure microwave extinction lengths by placing a radiometer at the bottom of undisturbed snow pits looking upwards through different snow depths. This provides a direct measurement of the microwave optical depth as a function of snow thickness. We measured microwave extinction lengths at 5 snow pits within a 25-km radius of Summit and recorded values ranging from 1.4 to 1.8 m at 37 GHz. These measured values are slightly larger than those predicted by an existing model, 1.0 to 1.4 m, using similar firn properties as recorded at Summit.
C12A-04
Snowmelt over the Greenland and Antarctica ice sheets from spaceborne radiometric data: extreme events and updated trends
Being able of observing melt extent and duration over ice sheets is fundamental for understanding how they are contributing to current sea level rise and affecting Earth's energy budget. With a surface size about 1.5 times the size of the U.S., Antarctica contains 90 percent of Earth's fresh water, making it the largest potential source of sea level rise. At the other pole, Greenland is the Earth's largest island with a total surface of about 2.2 square million km2 (slightly more than three time the size of Texas), representing another large potential source of sea level rise. Generally, some of the liquid water from snowmelt flows into the ocean, directly contributing to sea level rise while other might percolate at the bottom of the ice sheet, enhancing glacier sliding by lubricating the ice/bedrock interface. Also, after melting, snow changes its properties of absorbing and reflecting the energy irradiated by the sun, with melted/refrozen snow absorbing up to four times more energy than fresh/unthawed snow, strongly affecting Earth's energy budget. In Antarctica, snowmelt on ice shelves surface can lead to melt ponds, with meltwater filling small cracks and eventually causing larger fractures in the ice shelves, which act as brakes for glaciers and keep warmer marine air away from glaciers. Melting and surface temperature are strongly related and, therefore, knowledge of melting distribution and duration is extremely important to understand the spatial distribution of surface temperature over those places where ground measurements are sparse and difficult in view of the harsh conditions and remote locations. The Special Sensor Microwave Imager radiometer (SSM/I) aboard the Defense Meteorological Satellite Program's satellites (DMPS) provides daily measurements of brightness temperatures at several microwave frequencies. Microwave data have the great advantage of not being affected by sun or clouds presence and, differently from visible data, can detect melting occurring below the surface. In this study, results regarding melting over both the Greenland and Antarctica ice sheets derived from 19.35 GHz SSM/I brightness temperatures updated to 2007 are reported. Extreme melting events during the observation period and updated trends and anomalies for both melt extent and index (e.g., melting days x melting area) are reported. Results are obtained from different approaches and preliminarily compared with ground observations for validation purposes.
C12A-05
Unmanned Aircraft System (UAS) Assessment of Melt Lakes in Greenland
The objective of this August 2007 week-long test campaign was to assess the viability of supraglacial lake depths with high-resolution hyperspectral measurements. The knowledge of melt lake depth is essential in determining the volume of water which forms on top of glacial surfaces during the annual melt season. The assessment of melt water volume is a crucial input parameter for modeling the Greenland ice sheet dynamics. UAS operations were flown out of western Greenland. Preliminary results from five hyperspectral data cubes are presented, indicating that supraglacial water depths can be determined from low altitude, high-resolution hyperspectral imaging. The pixel resolution of the hyperspectral sensor is 0.2 meters at an altitude of 300 meters above the ice surface; this provides accuracy that is two orders of magnitude better than imagery obtained by the MODIS sensor or other similar satellite-based methods. Further, a UAS-based hyperspectral approach enables the measurement of supraglacial lake depths under most cloud cover conditions. The capabilities of three UAS types (Manta, Silver Fox, and electric Silver Fox) flight tested in Greenland are discussed. Also, we present future field planning (2008 and 2009) to measure supraglacial lake depths with hyperspectral imagery in conjunction with a green laser altimeter.
C12A-06
Tides Underneath the Ross Ice Shelf from ICESat Laser Altimetry
Satellite laser altimetry holds promise for mapping poorly known tides underneath Antarctic ice shelves. The amount of ICESat data now collected over the southernmost section of the Ross Ice Shelf is sufficient to warrant direct tidal analysis. Tides are estimated here from ten operational ICESat periods. A response analysis is used to help overcome unfavorable tidal sampling, especially an S2 correlation with the annual cycle. Comparisons of tidal estimates against independent station data show RMS constituent differences around 3 cm---still somewhat large, but an encouraging result for such a challenging region.
C12A-07
Estimates of Glacier Mass Change in the St.~Elias Mountains of Alaska, USA and Yukon Territory, Canada: a Strategy for Combining GRACE and Aircraft Laser Altimetry Data
We describe a strategy for estimating the contribution of mountain glaciers to rising sea level by combining two independent geodetic techniques: (1) repeat-pass aircraft laser altimetry measurements of glacier surface elevations; and (2) Gravity Recovery and Climate Experiment (GRACE) estimates of variations in Earth mass. Repeated laser altimetry measurements provide elevation changes along the central flowline of individual glaciers, but extrapolating these to entire glacier regions is a challenge, especially for glaciers with complex dynamics. Conversion of elevation to mass changes can also be problematic, especially over short measurement intervals. GRACE yields a direct measure of mass change over broad regions, but corrections must be made for non-glacier sources of mass change in order to isolate the glacier mass balance signal. In some cases, uncertainties in models or observations of non-glacier sources of mass change, such as glacial isostatic adjustments, can be large. By combining GRACE with aircraft altimetry, we are developing more robust regional estimates of mass change and can make a better assessment of errors in each approach. We apply these methods to glaciers of the St.~Elias Mountains, home to approximately one-half of glaciers (by surface area) in Alaska and northwestern Canada. Most glaciers in this region receive abundant precipitation and terminate in lakes or at tidewater, and many have a large proportion of their surface area at low elevations, making them particularly sensitive to changes in climate. Our GRACE solutions show that this region had the highest rate of mass loss during 2003-2007, relative to all other regions in Alaska/northwestern Canada. During August 2007 we collected laser altimetry surface elevation data along flight paths last measured during August 2003 and, in some cases, September 2005. By calculating the difference between these elevations, and extrapolating to all glaciers in the region, we obtain the net contribution of this region to rising sea level. These new altimetry data are the first regional glacier mass change dataset to be collected concurrently with data from GRACE, and will provide an independent dataset for validation of GRACE estimates. Our updated assessment of glacier mass changes in the St.~Elias Mountains will provide new insights into the response of glaciers to regional climate changes.
C12A-08
First results from a satellite and photo-based glacier inventory for British Columbia, Canada
British Columbia (BC) contains over 28,000 km 2 of glacierized terrain, but any comprehensive glacier inventory is lacking. One primary objective of the Western Canadian Cryospheric Network is to develop former and present extents of glacier cover for this region. In this study we utilize aerial photographs and satellite imagery to calculate changes in glacier cover for four regions in BC over three time periods: the southern Coast Mountains (1984, 2000, 2004); the northern Coast Mountains (1982, 2000, 2003); the Selkirk-Columbia Mountains (1986, 2000, 2006) and the northern Rocky Mountains (1986, 2001, 2006). We select these regions to represent glaciers in northern and southern locations and those that are influenced by maritime and continental climates. Glacier extent declined by 725 km 2 for the 5600 km 2 of mapped glaciers over the last two decades, and this retreat corresponds to an average annual loss of ca. 0.6 % a-1. Glaciers retreated most in the two southern regions: the southern Coast Mountains and the Selkirk-Columbia Mountains where glaciers lost 10.33% and 18.09% of their areas respectively since the 1980s. We observe no detectable change in glacier extent after 2000 except in the northern Rocky Mountains where the annual rate nearly doubled (0.32 to 0.58 % a -1). We hypothesize that this increase is real and may be related to the influence of arctic air masses in the northeast portion of our study area.