ALBERT

Beschreibung: We examine the simulated Arctic sea ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM–NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea ice conditions. Considering the seasonal cycle of the Arctic basin averaged drift speed, the model reproduces the summer–autumn drift speed well but significantly overestimates the winter–spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with the near-surface wind. The model calculates a realistic negative correlation between drift speed and ice thickness and between drift speed and ice concentration during summer–autumn when the ice concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive correlation between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for rather calm conditions. The correlation under low-wind conditions is overestimated in the simulations compared to observation/reanalysis data. A sensitivity experiment demonstrates the significant effects of sea ice form drag from floe edges included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modeled drift speed / wind speed ratio with observations based on reanalysis data for wind and remote sensing data for sea ice drift. An improvement might be achieved by tuning parameters that are not well established by observations.

Beschreibung: Every polar spring, phenomena called bromine explosions occur over sea ice. These bromine explosions comprise photochemical heterogeneous chain reactions that release bromine molecules, Br2, to the troposphere and lead to tropospheric plumes of bromine monoxide, BrO. This autocatalytic mechanism depletes ozone, O3, in the boundary layer and troposphere and thereby changes the oxidizing capacity of the atmosphere. The phenomenon also leads to accelerated deposition of metals (e.g., Hg). In this study, we present a 22-year (1996 to 2017) consolidated and consistent tropospheric BrO dataset north of 70∘ N, derived from four different ultraviolet–visible (UV–VIS) satellite instruments (GOME, SCIAMACHY, GOME-2A and GOME-2B). The retrieval data products from the different sensors are compared during periods of overlap and show good agreement (correlations of 0.82–0.98 between the sensors). From our merged time series of tropospheric BrO vertical column densities (VCDs), we infer changes in the bromine explosions and thus an increase in the extent and magnitude of tropospheric BrO plumes during the period of Arctic warming. We determined an increasing trend of about 1.5 % of the tropospheric BrO VCDs per year during polar springs, while the size of the areas where enhanced tropospheric BrO VCDs can be found has increased about 896 km2 yr−1. We infer from comparisons and correlations with sea ice age data that the reported changes in the extent and magnitude of tropospheric BrO VCDs are moderately related to the increase in first-year ice extent in the Arctic north of 70∘ N, both temporally and spatially, with a correlation coefficient of 0.32. However, the BrO plumes and thus bromine explosions show significant variability, which also depends, apart from sea ice, on meteorological conditions.

Beschreibung: The two concerted field campaigns, Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL), took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL) and a tethered balloon, as well as ground-based stations. Here, we present the synoptic development during the 35-day period of the campaigns, using near-surface and upper-air meteorological observations, as well as operational satellite, analysis, and reanalysis data. Over the campaign period, short-term synoptic variability was substantial, dominating over the seasonal cycle. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent 2 weeks were characterized by warm and moist maritime air from the south and east, which included two events of warm air advection. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final 2 weeks, adiabatically warmed air from the west dominated, with cloud properties strongly varying within the range of the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.

Beschreibung: 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.

Beschreibung: A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyse simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models, and compare them with observations from 268 Russian stations. There are large cross-model differences in the simulated differences between near-surface soil and air temperatures (ΔT; 3 to 14 °C), in the sensitivity of soil-to-air temperature (0.13 to 0.96 °C °C−1), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, hence guide improvements to the model's conceptual structure and process parameterisations. Models with better performance apply multilayer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (13.19 to 15.77 million km2). However, there is not a simple relationship between the sophistication of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, because several other factors, such as soil depth used in the models, the treatment of soil organic matter content, hydrology and vegetation cover, also affect the simulated permafrost distribution.

Beschreibung: 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.

Beschreibung: We examine the simulated Arctic sea-ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM-NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea-ice conditions. Considering the seasonal cycle of Arctic basin averaged drift speed, the model reproduces the summer-autumn drift speed well, but significantly overestimates the winter-spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with near-surface wind. The model calculates a realistic negative relationship between drift speed and ice thickness and between drift speed and ice concentration during summer-autumn when concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive relationship between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for calm conditions. The correlation under low-wind conditions is overestimated in the simulations, compared to observation/reanalysis. A sensitivity experiment demonstrates the significant effects of sea-ice form drag included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modelled drift speed/wind speed ratio with observations based on reanalysis for wind and remote sensing for sea ice drift. An improvement might be possible, among others, by tuning the open parameters of the parameterization in future.

Beschreibung: The two concerted field campaigns Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL) took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL), as well as surface-based stations, a tethered balloon, and satellites. Here, we present the synoptic development during the 35 day period of the campaigns, using classical near-surface and upper-air meteorological observations, as well as operational satellite and model data. Over the campaign period, short-term synoptic variability was substantial, dominating over the long-term background effect of Arctic amplification. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent two weeks were characterized by warm and moist maritime air from the south and east, which included two warm air advections. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final two weeks, adiabatically warmed westerly air dominated, with a strongly varying cloud distribution in between the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.

Beschreibung: A realistic simulation of physical and dynamical processes in the Arctic atmosphere and its feedbacks with the surface conditions is still a challenge for state-of-the-art Arctic climate models. This is of critical importance because studies of, for example, transport of pollutants from middle latitudes into the Arctic rely on the skill of the model in correctly representing atmospheric circulation including the key mechanisms and pathways of pollutant transport. In this work the performance of the Weather Research and Forecast model (WRF) with two land surface model schemes (Noah and NoahMP) and two reanalysis data sets for creation of lateral boundary conditions (ERA-interim and ASR) is evaluated focusing on meteorological surface properties and atmospheric dynamics. This includes the position and displacement of the polar dome and other features characterizing atmospheric circulation associated to sea ice maxima/minima extent within the Eurasian Arctic. The model simulations analyzed are carried out at 15-km horizontal resolution over a period of five years (2008 to 2012). The WRF model simulations are evaluated against surface meteorological data from automated weather stations and vertical profiles from radiosondes. Results show that the model is able to reproduce the main features of the atmospheric dynamics and vertical structure of the Arctic atmosphere reasonably well. The influence of the choice of the reanalyses used as initial and lateral boundary condition and of the LSM on the model results is complex and no combination is found to be clearly superior in all variables analyzed. The model results show that a more sophisticated formulation of land surface processes does not necessarily lead to significant improvements in the model results. This suggests that other factors such as the decline of the Arctic sea ice, stratosphere-troposphere interactions, atmosphere-ocean interaction, and boundary layer processes are also highly important and can have a significant influence on the model results. The “best” configuration for simulating Arctic meteorology and processes most relevant for pollutant transport (ASR + NoahMP) is then used in a simulation with WRF including aerosols and chemistry (WRF-Chem) to simulate black carbon (BC) concentrations in and around the Arctic and to assess the role of the modeled atmospheric circulation in the simulated BC concentrations inside the Arctic domain. Results from simulations with chemistry are evaluated against aerosol optical depth from several Aeronet stations and BC concentrations and particle number concentrations from several stations from the EBAS database. The results with WRF-Chem show a strong dependency of the simulated BC concentration on the modeled meteorology and the transport of the pollutants around our domain. The results also show that biases in the modeled BC concentrations can also be related to the emission data. Significant improvements of the models and of our understanding of the impact of anthropogenic BC emissions on the Arctic strongly depends on the availability of suitable, long-term observational data of concentrations of BC and particulate matter, vertical profiles of temperature and humidity and wind.

Beschreibung: A new version of the coupled Arctic atmosphere-ocean-sea ice model HIRHAM-NAOSIM is described. 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. 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 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.