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Sebastian H. Mernild
,
Glen E. Liston
,
Christopher A. Hiemstra
,
Jens H. Christensen
,
Martin Stendel
, and
Bent Hasholt

Abstract

A regional atmospheric model, the HIRHAM4 regional climate model (RCM) using boundary conditions from the ECHAM5 atmosphere–ocean general circulation model (AOGCM), was downscaled to a 500-m gridcell increment using SnowModel to simulate 131 yr (1950–2080) of hydrologic cycle evolution in west Greenland’s Kangerlussuaq drainage. Projected changes in the Greenland Ice Sheet (GrIS) surface mass balance (SMB) and runoff are relevant for potential hydropower production and prediction of ecosystem changes in sensitive Kangerlussuaq Fjord systems. Mean annual surface air temperatures and precipitation in the Kangerlussuaq area were simulated to increase by 3.4°C and 95 mm water equivalent (w.eq.), respectively, between 1950 and 2080. The local Kangerlussuaq warming was less than the average warming of 4.8°C simulated for the entire GrIS. The Kangerlussuaq SMB loss increased by an average of 0.3 km3 because of a 0.4 km3 rise in precipitation, 0.1 km3 rise in evaporation and sublimation, and 0.6 km3 gain in runoff (1950–2080). By 2080, the spring runoff season begins approximately three weeks earlier. The average modeled SMB and runoff is approximately −0.1 and 1.2 km3 yr−1, respectively, indicating that ∼10% of the Kangerlussuaq runoff is explained by the GrIS SMB net loss. The cumulative net volume loss (1950–2080) from SMB was 15.9 km3, and runoff was 151.2 km3 w.eq. This runoff volume is expected to have important hydrodynamic and ecological impacts on the stratified salinity in the Kangerlussuaq Fjord and on the transport of freshwater to the ocean.

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John E. Walsh
,
William L. Chapman
,
Vladimir Romanovsky
,
Jens H. Christensen
, and
Martin Stendel

Abstract

The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958–2000 climatology of the 40-yr ECMWF Re-Analysis (ERA-40) are summed over the seasonal cycles of three variables: surface air temperature, precipitation, and sea level pressure. The specific models that perform best over the larger domains tend to be the ones that perform best over Alaska and Greenland. The rankings of the models are largely unchanged when the bias of each model’s climatological annual mean is removed prior to the error calculation for the individual models. The annual mean biases typically account for about half of the models’ root-mean-square errors. However, the root-mean-square errors of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic precipitation and decreases of Arctic sea level pressure, when greenhouse gas concentrations are increased. Because several models have substantially smaller systematic errors than the other models, the differences in greenhouse projections imply that the choice of a subset of models may offer a viable approach to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic.

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Frauke Feser
,
Martina Schubert-Frisius
,
Hans von Storch
,
Matthias Zahn
,
Monika Barcikowska
,
Susanne Haeseler
,
Christiana Lefebvre
, and
Martin Stendel
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