ALBERT

Description: Airborne, Ship-borne and Surface low-frequency electromagnetic (EM) methods have become widely applied to measure Sea-ice thickness. EM responses measured over Sea ice depend mainly on the Sea-water conductivity and on the height of the Sensor above the Sea-ice–sea-water interface, but may be Sensitive to the Sea-ice conductivity at high excitation frequencies. We have conducted in Situ measurements of direct-current conductivity of Sea ice using Standard geophysical geoelectrical methods. Sea-ice thickness estimated from the geoelectrical Sounding data was found to be consistently underestimated due to the pronounced vertical-to-horizontal conductivity anisotropy present in level Sea ice. At five Sites, it was possible to determine the approximate horizontal and vertical conductivities from the Sounding data. The average horizontal conductivity was found to be 0.017 Sm–1, and that in the vertical direction to be 9–12 times higher. EM measurements over level Sea ice are Sensitive only to the horizontal conductivity. Numerical modelling has Shown that the assumption of zero Sea-ice conductivity in interpretation of airborne EM data results in a negligible error in interpreted thickness for typical level Antarctic Sea ice.

Description: Climate warming makes an increasing thin-ice fraction likely to occur in the Arctic, underpinning the need for its regular observation. Synchronous helicopter-borne measurements of the sea-ice thickness and like-polarized L-Band radar backscatter carried out along identical flight tracks north of Svalbard, Arctic, during winter are combined to develop an algorithm to estimate the thin-ice thickness solely from the L-Band backscatter co-polarization ratio (LCPR). Airborne ice thickness and LCPR data are smoothed along track (to reduce noise), co-located and compared. A linear and a logarithmic fit are applied using thickness values between 0.0 and 0.6 m and 0.0 and 1.0 m, respectively. The thin-ice thickness is derived from the LCPR data using above fits, first for dependent data (used to obtain the fits) and subsequently for independent data. The results are compared to airborne ice-thickness measurements for ice-thickness values between 0.0 and 0.6 m using linear regression. The logarithmic fit gives the most reliable results with a correlation of 0.72, and a RMS-difference of 8 cm. It permits to derive the thickness from airborne LCPR data with an uncertainty of about 10 cm, provided that observed thin-ice areas extend 100 to 200 m along the flight track.

Description: Airborne, ship-borne and surface low-frequency electromagnetic (EM) methods have become widely applied to measure sea-ice thickness. EM responses measured over sea ice depend mainly on the sea-water conductivity and on the height of the sensor above the sea-icesea-water interface, but may be sensitive to the sea-ice conductivity at high excitation frequencies. We have conducted in situ measurements of direct-current conductivity of sea ice using standard geophysical geoelectrical methods. Sea-ice thickness estimated from the geoelectrical sounding data was found to be consistently underestimated due to the pronounced vertical-to-horizontal conductivity anisotropy present in level sea ice. At five sites, it was possible to determine the approximate horizontal and vertical conductivities from the sounding data. The average horizontal conductivity was found to be 0.017 Sm1, and that in the vertical direction to be 912 times higher. EM measurements over level sea ice are sensitive only to the horizontal conductivity. Numerical modelling has shown that the assumption of zero sea-ice conductivity in interpretation of airborne EM data results in a negligible error in interpreted thickness for typical level Antarctic sea ice.

Description: Preliminary results are presented from the first validation of geophysical dataproducts (ice concentration, snow thickness on sea ice ( ) and ice temperature ( ) fromthe NASA EOS Aqua AMSR-E sensor, in East Antarctica (in September-October 2003). Thechallenge of collecting sufficient measurements with which to adequately validate thecoarse-resolution AMSR-E data products was addressed by means of a hierarchicalapproach, using detailed in situ measurements, digital aerial photography and other satellitedata. Initial results indicate that, at least under cold conditions with a dry snowcover, thereis a reasonably close agreement between satellite- and aerial photo-derived iceconcentrations i.e., 97.2 ±3.6% for NT2 and 96.5 ±2.5% for BBA algorithms versus 94.3±10% for the aerial photos. In general, the AMSR-E concentration represents a slightoverestimate of the actual concentration, with the largest discrepancies occurring in regionscontaining a relatively high proportion of thin ice. Although the AMSR-E concentrations fromthe NT2 and BBA algorithms are similar on average, differences of 〉5% occur on a point-by-point basis, again related to thin ice distribution. The AMSR-E ice temperature ( ) productagrees with coincident surface measurements to within approximately 0.5o C. Regardingsnow thickness, the AMSR retrieval is a significant underestimate compared to in situmeasurements weighted by the percentage of thin ice (and open water) present. For thecase study analysed, the underestimate was 46% for the overall average, but 23%compared to smooth ice measurements. An encouraging factor is that the spatialdistribution of the AMSR-E product follows an expected and consistent spatial pattern,suggesting that the observed difference may be an offset (at least under freezingconditions). Areas of discrepancy are identified, and the need for future work highlighted.

Description: Sea ice plays a key role in the earth climate system as it controls the fluxes between ocean and atmosphere and drives the global circulation due to its seasonal cycle of melting and freezing. Ice covered oceans also govern the earth's albedo and, therefore, the atmosphere's energy flux.Although satellites provide information on sea ice extent and seasonal variability, very little is known about the thickness of the sea ice and its long term thinning or thickening.Electromagnetic methods are perfectly suitable for sea ice thickness measurements as the ice represents a resistive layer covering a highly conductive ocean. For more than ten years, the Alfred Wegener Institute uses active frequency domain EM devices to assess the spatial and temporal evolution of Arctic and Antarctic sea ice. For that purpose Geonics' EM31 has been towed with sledges on ice surfaces and suspended from the ship's bow crane for continuos measurements while steaming through sea ice. Since 2001 a purpose built helicopter EM system is operating from ships and land stations delivering a unique sea ice thickness dataset in space and time.A ramac GPR system was used on sea ice in March and October 2003 in the Arctic and Antarctic respectively. These campaigns where one of the first successful adoptions of the GPR technique on sea ice.

Description: Semi-empirical methods are routinely used for Helicopter Electromagnetic (HEM) sea ice thickness mapping. Although these methods yield sufficiently accurate thickness data, it is of interest to determine whether formal one-dimensional (1D) geophysical inversion could yield improved results. If both the thickness and the ice conductivity could be mapped, the results could be used to estimate glaciological parameters such as the age of the sea ice. Sea ice conductivity data could also be potentially used to estimate the strength of the ice sheet, which would be valuable information for planning of icebreaking operations. By investigating synthetic and field data we show that, in the case of level sea ice of thickness up to 2 m, the accuracy of our HEM system is not high enough to sense the small conductivity variations arising from the age of the ice. Sea ice conductivity has a stronger influence on the measured HEM responses in areas of thick, deformed sea ice (pressure ridges), where bulk conductivity is higher as a result of the large seawater-filled porosity. Synthetic three-dimensional HEM data generated for pressure ridge models has shown that the 1D interpretation methods conventionally used for interpretation of sea ice thickness overestimate the true bulk conductivity at 3D features.