Scientific background and intentions:
Mass and energy balance of sea ice and its snow cover are key issues within current climate research (e.g. Perovich et al. 2002, 2003; Winton 2006). The Arctic sea ice responds relatively fast to changes in climate variables such as ocean and air temperatures, winds, ocean currents, amount of precipitation, and solar radiation. Those changes have the potential to amplify the processes, as for example snow metamorphosis increases the amount of absorbed heat and snow melt (surface albedo feedback process, see e.g. Curry et al., 1995; Gerland et al., 2004), while reduced ice concentration increases the amount of heat stored in the ocean during summer, and thereby delays the autumn refreeze of ice (e.g. Lindsay & Zhang 2005). In this task we seek to investigate several issues of particular importance both for process understanding and for validation and improvement of coupled general circulation models, namely: thickness of sea ice and its snow cover; the surface albedo feedback process; the local heat-balance of the ice; and parameterization of melt ponds and their development during the summer. Melt ponds are of great scientific interest because they cover a large surface area and have important influence on the summer ice surface albedo (Makshtas & Podgorny 1996; Fetterer & Untersteiner 1998; Perovich et al. 2002; Taylor & Feltham 2004). However, despite the large interest and their importance, both melt pond and snow surface parameterizations are weak points in many general circulation models, so their effects should be better included in these models. Correct modelling of melt ponds and the snow surface are important components when modelling the ice-albedo feedback loop. This feedback is believed to be one of the key mechanisms behind the observed strong reduction in sea ice (Lindsay & Zhang, 2005). In the Arctic, one effect of altered ice albedo modelling is to change the distribution (thickness, concentration and extent) of sea ice. Considerable differences in ice distribution between coupled climate models might explain a large fraction of the inter-model spread experienced in the simulated Arctic surface climate with the IPCC models (Walsh et al. 2002). The global influence of changes in the ice-albedo in a coupled climate model has been shown by Dethloff et al. (2006).

We will apply detailed measurements of spectral surface albedo and surface reflectance, using an existing ASD Fieldspec Pro spectroradiometer (350-2500 nm) and existing TriOS Ramses radiometers (320-950 nm). Parallel to that, we plan logging of all relevant snow and ice parameters (snow thickness, snow classes and grain sizes, snow and ice temperature, snow moisture, etc.) on the surfaces that are measured. Surfaces will include multiyear sea ice with different grades of roughness, snow cover, and melt ponds. We will pay attention to the cross section dimensions of melt ponds and the ice below them. When having access to first-year ice, refrozen leads, and gray ice, these other surface types will be added to the study. Special experiments will be performed with high temporal resolution in order to quantify snow metamorphosis due to solar radiation and its effect on albedo. To complement the observations, a 1-dimensional version of the thermodynamics from the ice model used in WP2 (Røed & Debernard 2004) will be utilized to study the heat balance and changes in snow and sea ice. Compared with the observations the model results will give valuable insight into the performance of the model thermodynamics and the uncertainties in the formulations that are used. The combination of model and observations will also be a powerful tool in the development of new parameterizations for melt ponds and surface albedo. In addition to the measurements mentioned here, the work with the parameterizations will utilize data from other available IPY-sources. By including these new parameterizations into a full sea ice model in Task 2.3, operational ice-ocean forecasting, weather forecasting, climate modelling, and the integrated observing system as a whole will greatly benefit from these improvements.

Workplan:
1.    Collect optical (spectral albedo and reflectance) and physical data of snow and ice surfaces (including melt ponds) during field campaigns in the framework of IAOOS – Norway for implementation in a database.
2.    Set up the 1-D model, compare the standard flux-parameterization used in the model with the observed fluxes. Quantify the important uncertainties in the results.
3.    Use observations as a guide to design a melt-pond parameterization.
4.    Improve parameterizations of sea ice albedo by including the effects of melt-ponds and possible new knowledge based on the field measurements. This work will build on the parameterizations of Køltzow et al. (2003).

Work for 3.7 is planned during all field activities in IAOOS-Norway that include work on ice stations (Fram Strait drifting stations, Tara, NP-35, and also on cruises NPI will arrange in September 2007 and 2008 for maintenance of moorings in the Fram Strait).