ALBERT

Description: The 1998 annual cycle and 1991–98 summer simulations of Greenland ice sheet surface climate are made with the 0.5°-horizontal resolution HIRHAM regional climate model of the Arctic. The model output is compared with meteorological and energy balance observations from 15 Greenland Climate Network automatic weather stations. The model reproduces the monthly average surface climate parameters, to a large extent within model and observational uncertainty. However, certain systematic model biases were identified, caused in particular by inaccurate GTOPO30 elevation data over Greenland, 180 m lower on average, with errors as large as −840 m over 50-km grid cells. The resulting warm biases enhance a negative albedo bias, which in turn leads to positive net shortwave radiation biases. Surface sensible and latent heat fluxes are overestimated, apparently due to model warm bias and 100% greater than observed wind speeds. Interannual variability in temperature and albedo are smaller in the model than in the observations, while the opposite is evident for incoming shortwave radiation and wind speed. Annual maps and total mass fluxes of precipitation and evaporation are compared with results from other studies. Based on the results of a multiparameter comparison, solid recommendations for improved regional models of ice sheet climate are made.

Description: Various temporal and spatial changes have manifested in Arctic storm activities, including the occurrence of the anomalously intense storms in the summers of 2012 and 2016, along with the amplified warming and rapidly decreased sea ice. To detect the variability of and changes in storm activity and understand its role in sea ice changes, we examined summer storm count and intensity year-by-year from ensemble hindcast simulations with an Arctic regional coupled climate model for the period of 1948–2008. The results indicated that the model realistically simulated the climatological spatial structure of the storm activity, characterized by the storm count and intensity. The simulated storm count captures the variability derived from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP–NCAR) reanalysis, though the simulated one is higher than that in the reanalysis. This could be attributed to the higher resolution of the model that may better represent smaller and shallower cyclones. The composite analysis shows that intense storms tend to form a low-pressure pattern with centers over the Kara Sea and Chukchi Sea, respectively, generating cyclonic circulation over the North Atlantic and North Pacific Arctic Ocean. The former drives intensification of the transpolar drift and Fram Strait sea ice export, and the latter suppresses thick ice transport from the Canada Basin to the Beaufort–Chukchi Seas, in spite of an increase in sea ice transport to the East Siberian Sea. Associated with these changes in sea ice transport, sea ice concentration and thickness show large decreases in the Barents–Kara Seas and the Chukchi–East-Siberian Seas, respectively. Energy budgets analysis suggests that more numerous intense storms substantially decrease the downward net sea ice heat fluxes, including net radiative fluxes, turbulent fluxes, and oceanic heat fluxes, compared with that when a lower number of intense storms occur. The decrease in the heat fluxes could be attributable to an increased cloudiness and the resultant reduction of downward shortwave radiation, as well as a destabilized boundary layer induced increase in upward turbulent fluxes.

Description: The sea-ice climatology and sea-ice trends and variability are evaluated in simulations with the new version of the coupled Arctic atmosphere-ocean-sea ice model HIRHAM–NAOSIM 2.0. This version utilizes upgraded model components for the coupled subsystems, which include physical and numerical improvements and higher horizontal and vertical resolution, and a revised coupling procedure with the aid of the coupling software YAC (Yet Another Coupler). The model performance is evaluated against observationally based data sets and compared with the previous version. Ensemble simulations for the period 1979–2016 reveal that Arctic sea ice is thicker in all seasons and closer to observations than in the previous version. Wintertime biases in sea-ice extent, upper ocean temperatures, and near-surface air temperatures are reduced, while summertime biases are of similar magnitude as in the previous version. Problematic issues of the current model configuration and potential corrective measures and further developments are discussed.

Description: Using NCEP–NCAR reanalysis and Japanese 25-yr Reanalysis (JRA-25) winter daily (1 December–28 February) data for the period 1979–2012, this paper reveals the leading pattern of winter daily 850-hPa wind variability over northern Eurasia from a dynamic perspective. The results show that the leading pattern accounts for 18% of the total anomalous kinetic energy and consists of two subpatterns: the dipole and the tripole wind patterns. The dipole wind pattern does not exhibit any apparent trend. The tripole wind pattern, however, has displayed significant trends since the late 1980s. The negative phase of the tripole wind pattern corresponds to an anomalous anticyclone over northern Eurasia during winter, as well as two anomalous cyclones occurring over southern Europe and in the mid- to high latitudes of East Asia. These anomalous cyclones in turn lead to enhanced winter precipitation in these two regions, as well as negative surface temperature anomalies over the mid- to high latitudes of Asia. The intensity of the tripole wind pattern and the frequency of its extreme negative phase are significantly correlated with autumn Arctic sea ice anomalies. Simulation experiments further demonstrate that the winter atmospheric response to Arctic sea ice decrease is dynamically consistent with the observed trend in the tripole wind pattern over the past 24 winters, which is one of the causes of the observed declining winter surface air temperature trend over Central and East Asia. The results of this study also imply that East Asia may experience more frequent and/or intense winter extreme weather events in association with the loss of Arctic sea ice.

Description: The regional climate model HIRHAM has been applied over the Asian continent to simulate the Indian monsoon circulation under present-day conditions. The model is driven at the lateral and lower boundaries by European reanalysis (ERA40) data for the period from 1958 to 2001. Simulations with a horizontal resolution of 50 km are carried out to analyze the regional monsoon patterns. The focus in this paper is on the validation of the long-term summer monsoon climatology and its variability concerning circulation, temperature, and precipitation. Additionally, the monsoonal behavior in simulations for wet and dry years has been investigated and compared against several observational data sets. The results successfully reproduce the observations due to a realistic reproduction of topographic features. The simulated precipitation shows a better agreement with a high-resolution gridded precipitation data set over the central land areas of India and in the higher elevated Tibetan and Himalayan regions than ERA40.

Description: The regional climate model HIRHAM has been applied to Antarctica driven at the lateral and lower boundaries by European Reanalysis data ERA-40 for the period 1958–1998. Simulations over 4 decades, carried out with a horizontal resolution of 50 km, deliver a realistic simulation of the Antarctic atmospheric circulation, synoptic-scale pressure systems, and the spatial distribution of precipitation minus sublimation (P-E) structures. The simulated P-E pattern is in qualitative agreement with glaciological estimates. The estimated (P-E) trends demonstrate surfacemass accumulation increase at the West Antarctic coasts and reductions in parts of East Antarctica. The influence of the Antarctic Oscillation (AAO) on the near-surface climate and the surface mass accumulation over Antarctica have been investigated on the basis of ERA-40 data and HIRHAM simulations. It is shown that the regional accumulation changes are largely driven by changes in the transient activity around the Antarctic coasts due to the varying AAO phases. During positive AAO, more transient pressure systems travelling towards the continent, and Western Antarctica and parts of South-Eastern Antarctica gain more precipitation and mass. Over central Antarctica the prevailing anticyclone causes a strengthening of polar desertification connected with a reduced surface mass balance in the northern part of East Antarctica.

Description: This study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January–March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3–19 W m−2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April–May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5–79 W m−2) and underestimate the net longwave flux (8–38 W m−2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.