Regional climate model runs using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesocale Model modified for use in polar regions (Polar MM5), calibrated by independent in situ observations, demonstrate coherent regional patterns of Greenland ice sheet surface mass balance (SMB) change over a 17-yr period characterized by warming (1988–2004). Both accumulation and melt rates increased, partly counteracting each other for an overall negligible SMB trend. However, a 30% increase in meltwater runoff over this period suggests that the overall ice sheet mass balance has been increasingly negative, given observed meltwater-induced flow acceleration. SMB temporal variability of the whole ice sheet is best represented by ablation zone variability, suggesting that increased melting dominates over increased accumulation in a warming scenario. The melt season grew in duration over nearly the entire ablation zone by up to 40 days, 10 days on average. Accumulation area ratio decreased by 3%. Albedo reductions are apparent in five years of the Moderate Resolution Imaging Spectroradiometer (MODIS) derived data (2000–04). The Advanced Very High Resolution Radiometer (AVHRR)-derived albedo changes (1988–99) were less consistent spatially. A conservative assumption as to glacier discharge and basal melting suggests an ice sheet mass loss over this period greater than 100 km3 yr−1, framing the Greenland ice sheet as the largest single glacial contributor to recent global sea level rise. Surface mass balance uncertainty, quantified from residual random error between model and independent observations, suggests two things: 1) changes smaller than approximately 200 km3 yr−1 would not satisfy conservative statistical significance thresholds (i.e., two standard deviations) and 2) although natural variability and model uncertainty were separated in this analysis, the magnitude of each were roughly equivalent. Therefore, improvements in model accuracy and analysis of longer periods (assuming larger changes) are both needed for definitive mass balance change assessments.

Meteorological station records and regional climate model output are combined to develop a continuous 168-yr (1840–2007) spatial reconstruction of monthly, seasonal, and annual mean Greenland ice sheet near-surface air temperatures. Independent observations are used to assess and compensate for systematic errors in the model output. Uncertainty is quantified using residual nonsystematic error. Spatial and temporal temperature variability is investigated on seasonal and annual time scales. It is found that volcanic cooling episodes are concentrated in winter and along the western ice sheet slope. Interdecadal warming trends coincide with an absence of major volcanic eruptions. Year 2003 was the only year of 1840–2007 with a warm anomaly that exceeds three standard deviations from the 1951–80 base period. The annual whole ice sheet 1919–32 warming trend is 33% greater in magnitude than the 1994–2007 warming. The recent warming was, however, stronger along western Greenland in autumn and southern Greenland in winter. Spring trends marked the 1920s warming onset, while autumn leads the 1994–2007 warming. In contrast to the 1920s warming, the 1994–2007 warming has not surpassed the Northern Hemisphere anomaly. An additional 1.0°–1.5°C of annual mean warming would be needed for Greenland to be in phase with the Northern Hemispheric pattern. Thus, it is expected that the ice sheet melt rates and mass deficit will continue to grow in the early twenty-first century as Greenland’s climate catches up with the Northern Hemisphere warming trend and the Arctic climate warms according to global climate model predictions.

[1] A version of the state-of-the-art Weather Research and Forecasting model (WRF) has been developed for polar applications. The model known as ''Polar WRF'' is tested over the Arctic Ocean with a western Arctic grid using 25-km resolution. The model is based upon WRF version 2.2, with improvements to the Noah land surface model and the snowpack treatment. The ocean surface treatment is modified to include fractional sea ice. Simulations consist of a series of 48-h integrations initialized daily at 0000 UTC. The initial 24 h are taken as model spin-up time for the atmospheric hydrology and boundary layer processes. Arctic conditions are simulated for the selected months: January 1998, June 1998, and August 1998 representing midwinter, early summer, and late summer conditions, respectively, from the Surface Heat Budget of the Arctic (SHEBA) study. The albedo of sea ice is specified as a function of time and latitude for June and as a function of time for August. Simulation results are compared with observations of the drifting ice station SHEBA in the Arctic ice pack. Polar WRF simulations show good agreement with observations for all three months. Some differences between the simulations and observation occur owing to apparent errors in the synoptic forecasts and the representation of clouds. Nevertheless, the biases in the simulated fields appear to be small, and Polar WRF appears to be a very good tool for studies of Arctic Ocean meteorology.

A version of the state-of-the-art Weather Research and Forecasting model (WRF) has been developed for use in polar climates. The model known as ''Polar WRF'' is tested for land areas with a western Arctic grid that has 25-km resolution. This work serves as preparation for the high-resolution Arctic System Reanalysis of the years 2000-10. The model is based upon WRF version 3.0.1.1, with improvements to the Noah land surface model and snow/ice treatment. Simulations consist of a series of 48-h integrations initialized daily at 0000 UTC, with the initial 24 h taken as spinup for atmospheric hydrology and boundary layer processes. Soil temperature and moisture that have a much slower spinup than the atmosphere are cycled from 48-h output of earlier runs. Arctic conditions are simulated for a winter-to-summer seasonal cycle from 15 November 2006 to 1 August 2007. Simulation results are compared with a variety of observations from several Alaskan sites, with emphasis on the North Slope. Polar WRF simulation results show good agreement with most near-surface observations. Warm temperature biases are found for winter and summer. A sensitivity experiment with reduced soil heat conductivity, however, improves simulation of near-surface temperature, ground heat flux, and soil temperature during winter. There is a marked deficit in summer cloud cover over land with excessive incident shortwave radiation. The cloud deficit may result from anomalous vertical mixing of moisture by the turbulence parameterization. The new snow albedo parameterization for WRF 3.1.1 is successfully tested for snowmelt over the North Slope of Alaska.

Surface snow accumulation is the primary mass input to the Antarctic ice sheets. As the dominant term among various components of surface snow accumulation (precipitation, sublimation/deposition, and snow drift), precipitation is of particular importance in helping to assess the mass balance of the Antarctic ice sheets and their contribution to global sea level change. The Polar MM5, a mesoscale atmospheric model based on the fifth-generation Pennsylvania State University-NCAR Mesoscale Model, has been run for the period of July 1996 through June 1999 to evaluate the spatial and temporal variability of Antarctic precipitation. Drift snow effects on the redistribution of surface snow over Antarctica are also assessed with surface wind fields from Polar MM5 in this study. It is found that areas with large drift snow transport convergence and divergence are located around escarpment areas where there is considerable katabatic wind acceleration. It is also found that the drift snow transport generally diverges over most areas of East and West Antarctica with relatively small values. The use of the dynamic retrieval method (DRM) to calculate precipitation has been developed and verified for the Greenland ice sheet. The DRM is also applied to retrieve the precipitation over Antarctica from 1979 to 1999 in this study. Most major features in the spatial distribution of Antarctic accumulation are well captured by the DRM results. In comparison with predicted precipitation amounts from atmospheric analyses and reanalyses, DRM calculations capture more mesoscale features of the precipitation distribution over Antarctica. A significant upward trend of ϩ1.3 to ϩ1.7 mm yr Ϫ2 for 1979-99 is found from DRM and forecast precipitation amounts for Antarctica that is consistent with results reported by other investigators and indicates that an additional 0.05 mm yr Ϫ1 is being extracted from the global ocean and locked up in the Antarctic ice sheets. While there is good agreement in this trend among all of the datasets, the interannual variability about the trend on the continental scale is not well captured. However, on the subcontinental scale, the interannual variability about the trend is well resolved for sectors in West Antarctica and the South Atlantic. It is also noted that the precipitation trend is weakly downward over much of the continent.

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Abstract. The Arctic has experienced large climate changes over recent decades, the largest for any region on Earth. To understand the underlying reasons for this climate sensitivity, reanalysis is an invaluable tool. The Arctic System Reanalysis (ASR) is a regional reanalysis, forced by ERA-Interim at the lateral boundaries and incorporating model physics adapted to Arctic conditions, developed to serve as a stateof-the-art, high-resolution synthesis tool for assessing Arctic climate variability and monitoring Arctic climate change.We use data from Arctic Summer Cloud-Ocean Study (ASCOS) to evaluate the performance of ASR and ERAInterim for the Arctic Ocean. The ASCOS field experiment was deployed on the Swedish icebreaker Oden north of 87 • N in the Atlantic sector of the Arctic during August and early September 2008. Data were collected during the transits from and to Longyearbyen and the 3-week ice drift with Oden moored to a drifting multiyear ice floe. These data are independent and detailed enough to evaluate process descriptions.The reanalyses captures basic meteorological variations coupled to the synoptic-scale systems, but have difficulties in estimating clouds and atmospheric moisture. While ERAInterim has a systematic warm bias in the lowest troposphere, ASR has a cold bias of about the same magnitude on average. The results also indicate that more sophisticated descriptions of cloud microphysics in ASR did not significantly improve the modeling of cloud properties compared to ERA-Interim. This has consequences for the radiation balance, and hence the surface temperature, and illustrate how a modeling problem in one aspect of the atmosphere, here the clouds, feeds back to other parameters, especially near the surface and in the boundary layer.

The Polar Weather Research and Forecasting Model (Polar WRF), a polar-optimized version of the WRF Model, is developed and made available to the community by Ohio State University's Polar Meteorology Group (PMG) as a code supplement to the WRF release from the National Center for Atmospheric Research (NCAR). While annual NCAR official releases contain polar modifications, the PMG provides very recent updates to users. PMG supplement versions up to WRF version 3.4 include modified Noah land surface model sea ice representation, allowing the specification of variable sea ice thickness and snow depth over sea ice rather than the default 3-m thickness and 0.05-m snow depth. Starting with WRF V3.5, these options are implemented by NCAR into the standard WRF release. Gridded distributions of Arctic ice thickness and snow depth over sea ice have recently become available. Their impacts are tested with PMG's WRF V3.5-based Polar WRF in two case studies. First, 20-km-resolution model results for January 1998 are compared with observations during the Surface Heat Budget of the Arctic Ocean project. Polar WRF using analyzed thickness and snow depth fields appears to simulate January 1998 slightly better than WRF without polar settings selected. Sensitivity tests show that the simulated impacts of realistic variability in sea ice thickness and snow depth on near-surface temperature is several degrees. The 40-km resolution simulations of a second case study covering Europe and the Arctic Ocean demonstrate remote impacts of Arctic sea ice thickness on midlatitude synoptic meteorology that develop within 2 weeks during a winter 2012 blocking event.