Sea-ice volume fluxes through Fram Strait, Arctic Ocean, are estimated for the two Icesat measurement periods in February/March and October/November 2003 by combining Sea-ice area fluxes, determined from Space-borne microwave observations, with estimates of the Sea-ice thickness distribution, inferred from measurements of Icesat’s Geoscience Laser Altimeter System (GLAs) instrument. The thickness is derived from Icesat data by converting its Surface elevation measurements into an ice freeboard estimate. Combined with prior information about ice density and Snow depth and density, the freeboard is converted into ice thickness. Uncertainties in freeboard estimates due to geoid model errors are reduced through the use of the recent geoid from the Arctic Gravity Project. Missing information about the ocean circulation and ocean tides is approximated locally by interpolating the Sea Surface height linearly between open leads. Meridional ice volume fluxes estimated for 79˚N using ice drift observed by AMSR-E (QuiksCAT) amount to 168 km³(236km³) and 62 km³(77 km³) for 30 day periods in February/March and October/November 2003, respectively. These values lie in the range of previous results from Similar Studies, but are considerably Smaller than the average ice flux during the 1990s, most likely because of a Smaller ice-drift Speed during 2003.

Significant changes in Arctic systems are underway, which are attributed to global warming. An important example is reduction in snow and ice coverage due to intensified melting in many regions. Active microwave instruments are used to detect surface melt and freeze-up based on the high sensitivity of radar backscatter to liquid water in the snow. We monitor two snowmelt parameters, the annual total of melt days and the date of summer melt onset across the archipelago of Svalbard using microwave backscatter measurements from the Ku-band scatterometer SeaWinds onboard the QuikSCAT satellite. Our analysis covers a nine-year time span from 2000 to 2008. Meteorological data from synoptic and automatic weather stations at several locations in Svalbard are used to investigate climatologic controls on pattern and timing of snowmelt. Svalbard temperature and precipitation regimes are highly variable throughout the year due to the location of the archipelago within a zone that is characterized by the convergence o...

Enhanced-resolution QuikSCAT/SeaWinds (QS_er) data recently entered the daily ice chart operation of the national ice services. Algorithms have been developed to extract four important sea ice parameters from this data over the whole Arctic: sea ice edge, type, concentration, and drift. This paper will summarize the different algorithms with a more detailed presentation of the sea ice concentration (IC) algorithm that has not been previously published. The sea ice edge can be detected to IC as low as 10%. Sea ice types can be roughly separated by a single threshold of 12 dB in the horizontal polarization. The IC algorithm gives reasonable qualitative results, separating into three classes: high, medium, and low ICs. It resolves even some characteristic ice features in the marginal ice zone and dynamic areas like the Fram Strait. However, it is very empirical and quantitatively not reliable. Sea ice drift can be determined with an accuracy of about 2.6 cm/s for a 48-h drift. Operating since 1999, QS is an important global data set for climate research, and two crucial applications how these sea ice products can be used for climate research are presented: the seasonal evolution of the sea ice cover and the export of sea ice volume through Fram Strait.

The transformation of ocean water masses at high latitudes is closely related to the freezing and melting processes during the year. Downward salt fluxes from brine rejection during freezing increase the salinity and density of the water column underneath. Fresh-water input from river run-off and melting of sea ice reduces the density, mainly of the surface layer. Hydrographic profiles collected in Storfjorden, Svalbard, in spring and summer, show the strong seasonal and interannual variability of the water masses. Using, in addition, data from moorings, a ship-borne acoustic Doppler current profiler and drifting buoys, and results from models of ice drift, polynya evolution, ice formation and convection processes during freezing, we document the seasonal water-mass transformation and try to explain its interannual variability. The advection of ice and water through the two northern sounds and over the sill in the south of the fjord is examined. The release of brine-enriched bottom water over the sill must be balanced by advection from the Barents Sea in the upper layers. The interannual variability of the brine-enriched bottom layer is very high, and higher salinities are observed in a milder winter. The density anomaly resulting from freezing might depend more on the ice cover and geographical position of the polynya than on the total atmospheric forcing during winter.