Solar radiation over and under sea ice and photographic quantification of Ice algal aggregates during the POLARSTERN cruise ARK-XXVII/3 (IceArc) in summer 2012

The ice cover of the Arctic Ocean has been changing dramatically in the last decades and the consequences for the sea-ice associated ecosystem remain difficult to assess. Algal aggregates underneath sea ice have been described sporadically but the frequency and distribution of their occurrence is not well quantified. We used upward looking images obtained by a remotely operated vehicle (ROV) to derive estimates of ice algal aggregate biomass and to investigate their spatial distribution. During the IceArc expedition (ARK-XXVII/3) of RV Polarstern in late summer 2012, different types of algal aggregates were observed floating underneath various ice types in the Central Arctic basins. Our results show that the floe scale distribution of algal aggregates in late summer is very patchy and determined by the topography of the ice underside, with aggregates collecting in dome shaped structures and at the edges of pressure ridges. The buoyancy of the aggregates was also evident from analysis of the aggregate size distribution. Different approaches used to estimate aggregate biomass yield a wide range of results. This highlights that special care must be taken when upscaling observations and comparing results from surveys conducted using different methods or on different spatial scales.

(Table 1) Attenuation coefficient of lateral propagating light in sea ice, southern Beaufort Sea

The attenuation property of a lateral propagating light (LPL) in sea ice was measured using an artificial lamp in the Canadian Arctic during the 2007/2008 winter. A measurement method is proposed and applied whereby a recording instrument is buried in the sea ice and an artificial lamp is moved across the instrument. The apparent attenuation coefficient µ(lamda) for the lateral propagating light is obtained from the measured logarithmic relative variation rate. With the exception of blue and red lights, the attenuation coefficient changed little with wavelength, but changed considerably with depth. The vertical decrease of the attenuation coefficient was found to be correlated with salinity: the greater the salinity, the greater the attenuation coefficient. A clear linear relation of salinity and the lateral attenuation coefficient with R2 = 0.939 exists to address the close correlation of the attenuation of LPL with the scattering from the brine. The observed attenuation coefficient of LPL is much larger than that of the vertical propagation light, which we speculate to be caused by scattering. Part of this scattered component is transmitted out of the sea ice from the upper and lower surfaces.

(Table 1) White ice and melt pond characteristics in Darnley and Franklin Bay, Canada

Melt pond covered sea ice is a ubiquitous feature of the summertime Arctic Ocean when meltwater collects in lower-lying areas of ice surfaces. Horizontal transects were conducted during June 2008 above and below landfast sea ice with melt ponds to characterize surface and bottom topography together with variations in transmitted spectral irradiance. We captured a rapid progression from a highly flooded sea ice surface with lateral drainage toward flaws and seal breathing holes to the formation of distinct melt ponds with steep edges. As the mass of the ice cover decreased due to meltwater drainage and rose upward with respect to the seawater level, the high-scattering properties of ice above the water level (i.e., white ice) were continuously regenerated, while pond waters remained transparent compared to underlying ice. The relatively stable albedos observed throughout the study, even as ice thickness decreased, were directly related to these surface processes. Transmission through the ice cover of incident irradiance in the 400-700 nm wave band ranged from 38% to 67% and from 5% to 16% beneath ponded and white ice, respectively. Our results show that this transmission varied not only as a function of surface type (melt ponds or white ice) areal coverage but also in relation to ice thickness and proximity to other surface types through the influence of horizontal spreading of light. Thus, in contrast to albedo, this implies that regional transmittance estimates need to consider melt pond size and shape distributions and variations in optical properties and thickness of the ice cover.

(Table 3) Air temperatures, and snow and ice characteristics of fresh and brackish water lakes in the Northwest Territories, Canada

The algorithms designed to estimate snow water equivalent (SWE) using passive microwave measurements falter in lake-rich high-latitude environments due to the emission properties of ice covered lakes on low frequency measurements. Microwave emission models have been used to simulate brightness temperatures (Tbs) for snowpack characteristics in terrestrial environments but cannot be applied to snow on lakes because of the differing subsurface emissivities and scattering matrices present in ice. This paper examines the performance of a modified version of the Helsinki University of Technology (HUT) snow emission model that incorporates microwave emission from lake ice and sub-ice water. Inputs to the HUT model include measurements collected over brackish and freshwater lakes north of Inuvik, Northwest Territories, Canada in April 2008, consisting of snowpack (depth, density, and snow water equivalent) and lake ice (thickness and ice type). Coincident airborne radiometer measurements at a resolution of 80x100 m were used as ground-truth to evaluate the simulations. The results indicate that subsurface media are simulated best when utilizing a modeled effective grain size and a 1 mm RMS surface roughness at the ice/water interface compared to using measured grain size and a flat Fresnel reflective surface as input. Simulations at 37 GHz (vertical polarization) produce the best results compared to airborne Tbs, with a Root Mean Square Error (RMSE) of 6.2 K and 7.9 K, as well as Mean Bias Errors (MBEs) of -8.4 K and -8.8 K for brackish and freshwater sites respectively. Freshwater simulations at 6.9 and 19 GHz H exhibited low RMSE (10.53 and 6.15 K respectively) and MBE (-5.37 and 8.36 K respectively) but did not accurately simulate Tb variability (R= -0.15 and 0.01 respectively). Over brackish water, 6.9 GHz simulations had poor agreement with airborne Tbs, while 19 GHz V exhibited a low RMSE (6.15 K), MBE (-4.52 K) and improved relative agreement to airborne measurements (R = 0.47). Salinity considerations reduced 6.9 GHz errors substantially, with a drop in RMSE from 51.48 K and 57.18 K for H and V polarizations respectively, to 26.2 K and 31.6 K, although Tb variability was not well simulated. With best results at 37 GHz, HUT simulations exhibit the potential to track Tb evolution, and therefore SWE through the winter season.