The response of the Arctic atmosphere to low and high sea ice concentration phases based on European Center for Medium-Range Weather Forecast (ECMWF) Re-Analysis Interim (ERA-Interim) atmospheric ...data and Hadley Centre's sea ice dataset (HadISST1) from 1989 until 2010 has been studied. Time slices of winter atmospheric circulation with high (1990-2000) and low (2001-2010) sea ice concentration in the preceding August/September have been analysed with respect to tropospheric interactions between planetary and baroclinic waves. It is shown that a changed sea ice concentration over the Arctic Ocean impacts differently the development of synoptic and planetary atmospheric circulation systems. During the low ice phase, stronger heat release to the atmosphere over the Arctic Ocean reduces the atmospheric vertical static stability. This leads to an earlier onset of baroclinic instability that further modulates the non-linear interactions between baroclinic wave energy fluxes on time scales of 2.5-6 d and planetary scales of 10-90 d. Our analysis suggests that Arctic sea ice concentration changes exert a remote impact on the large-scale atmospheric circulation during winter, exhibiting a barotropic structure with similar patterns of pressure anomalies at the surface and in the mid-troposphere. These are connected to pronounced planetary wave train changes notably over the North Pacific.
A new climate model has been developed that employs a multi-resolution dynamical core for the sea ice-ocean component. In principle, the multi-resolution approach allows one to use enhanced ...horizontal resolution in dynamically active regions while keeping a coarse-resolution setup otherwise. The coupled model consists of the atmospheric model ECHAM6 and the finite element sea ice-ocean model (FESOM). In this study only moderate refinement of the unstructured ocean grid is applied and the resolution varies from about 25 km in the northern North Atlantic and in the tropics to about 150 km in parts of the open ocean; the results serve as a benchmark upon which future versions that exploit the potential of variable resolution can be built. Details of the formulation of the model are given and its performance in simulating observed aspects of the mean climate is described. Overall, it is found that ECHAM6–FESOM realistically simulates many aspects of the observed climate. More specifically it is found that ECHAM6–FESOM performs at least as well as some of the most sophisticated climate models participating in the fifth phase of the Coupled Model Intercomparison Project. ECHAM6–FESOM shares substantial shortcomings with other climate models when it comes to simulating the North Atlantic circulation.
The coupled regional climate model HIRHAM‐NAOSIM is used to investigate feedbacks between September sea ice anomalies in the Arctic and atmospheric conditions in autumn and the subsequent winter. A ...six‐member ensemble of simulations spanning the period 1949–2008 is analyzed. The results show that negative Arctic sea ice anomalies are associated with increased heat and moisture fluxes, decreased static stability, increased lower tropospheric moisture, and modified baroclinicity, synoptic activity, and atmospheric large‐scale circulation. The circulation changes in the following winter display meridionalized flow but are not fully characteristic of a negative Arctic Oscillation pattern, though they do support cold winter temperatures in northern Eurasia. Internally generated climate variability causes significant uncertainty in the simulated circulation changes due to sea ice‐atmosphere interactions. The simulated atmospheric feedback patterns depend strongly on the position and strength of the regional sea ice anomalies and on the analyzed time period. The strongest atmospheric feedbacks are related to sea ice anomalies in the Beaufort Sea. This work suggests that there are complex feedback mechanisms that support a statistical link between reduced September sea ice and Arctic winter circulation. However, the feedbacks depend on regional and decadal variations in the coupled atmosphere‐ocean‐sea ice system.
Key Points
Coupled regional model simulates Arctic feedbacks
Summer sea ice anomalies affect atmospheric winter circulation
Atmospheric feedback patterns depend on the regional sea ice anomaly
While wave heights globally have been growing over recent decades, observations of their regional trends vary. Simulations of future wave climate can be achieved by coupling wave and climate models. ...At present, wave heights and their future trends in the Arctic Ocean remain unknown. We use the third‐generation wave forecast model WAVEWATCH‐III forced by winds and sea ice concentration produced within the regional model HIRHAM, under the anthropogenic scenario SRES‐A1B. We find that significant wave height and its extremes will increase over different inner Arctic areas due to reduction of sea ice cover and regional wind intensification in the 21st century. The opposite tendency, with a slight reduction in wave height appears for the Atlantic sector and the Barents Sea. Our results demonstrate the complex wave response in the Arctic Ocean to a combined effect of wind and sea ice forcings in a climate‐change scenario during the 21st century.
Key Points
Significant wave height will increase over the Arctic Ocean in the 21st centuryReduction in wave height is expected for the Atlantic sector and the Barents Sea
Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. ...Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron‐Findeisen process and (2) a more generalized subgrid‐scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low‐level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low‐level (<700 m) cloud observations, as these clouds exert a strong impact on the near‐surface climate.
Key Points
Stratiform cloud parameterization is improved based on satellite data
Cloud reduction is accompanied by smaller low‐level temperature bias over ice
Derived parameterization may reduce uncertainties in Arctic climate projections
The Arctic climate is modulated, in part, by atmospheric aerosols that affect the distribution of radiant energy passing through the atmosphere. Aerosols affect the surface‐atmosphere radiation ...balance directly through interactions with solar and terrestrial radiation and indirectly through interactions with cloud particles. Better quantification of the radiative forcing by different types of aerosol is needed to improve predictions of future climate. During April 2009, the airborne campaign Pan‐Arctic Measurements and Arctic Regional Climate Model Inter‐comparison Project (PAM‐ARCMIP) was conducted. The mission was organized by Alfred Wegener Institute for Polar and Marine Research of Germany and utilized their research aircraft, Polar‐5. The goal was to obtain a snapshot of surface and atmospheric conditions over the central Arctic prior to the onset of the melt season. Characterizing aerosols was one objective of the campaign. Standard Sun photometric procedures were adopted to quantify aerosol optical depth AOD, providing a three‐dimensional view of the aerosol, which was primarily haze from anthropogenic sources. Independent, in situ measurements of particle size distribution and light extinction, derived from airborne lidar, are used to corroborate inferences made using the AOD results. During April 2009, from the European to the Alaskan Arctic, from sub‐Arctic latitudes to near the pole, the atmosphere was variably hazy with total column AOD at 500 nm ranging from ∼0.12 to >0.35, values that are anomalously high compared with previous years. The haze, transported primarily from Eurasian industrial regions, was concentrated within and just above the surface‐based temperature inversion layer. Extinction, as measured using an onboard lidar system, was also greatest at low levels, where particles tended to be slightly larger than at upper levels. Black carbon (BC) (soot) was observed at all levels sampled, but at moderate to low concentrations compared with historical records. BC was highest near the North Pole, suggesting there had been an accumulation of soot within the Arctic vortex. Few, optically thick elevated aerosol layers were observed along the flight track, although independent lidar observations reveal evidence of the passage of volcanic plumes, which may have contributed to abnormally high values of AOD above 4 km. Enhanced opacity at higher altitudes during the campaign is attributed to an accumulation of industrial pollutants in the upper troposphere in combination with volcanic aerosol resulting from the March–April 2009 eruptions of Mount Redoubt in Alaska. The presence of Arctic haze during April 2009 is estimated to have reduced the net shortwave irradiance by ∼2–5 W m−2, resulting in a slight cooling of the surface.
The effects of internal model variability on the simulation of Arctic sea-ice extent and volume have been examined with the aid of a seven-member ensemble with a coupled regional climate model for ...the period 1948-2008. Beyond general weaknesses related to insufficient representation of feedback processes, it is found that the model's ability to reproduce observed summer sea-ice retreat depends mainly on two factors: the correct simulation of the atmospheric circulation during the summer months and the sea-ice volume at the beginning of the melting period. Since internal model variability shows its maximum during the summer months, the ability to reproduce the observed atmospheric summer circulation is limited. In addition, the atmospheric circulation during summer also significantly affects the sea-ice volume over the years leading to a limited ability to start with reasonable sea-ice volume into the melting period. Furthermore, the sea-ice volume pathway shows notable decadal variability that varies in amplitude among the ensemble members. The scatter is particularly large in periods when the ice volume increases, indicating limited skill in reproducing high-ice years.
This study investigates the possible changes in future winter temperature and precipitation extremes in the Arctic using the regional climate model HIRHAM4. Under the B2 emission scenario conditions, ...frequency and intensity of future (2037–2051) extremes have changed significantly compared to the present‐day (1981–1995) extremes. Extreme precipitations have intensified and the number of extreme events has changed significantly over East Siberia and Barents Sea. Extreme warm and extreme cold temperatures have become warmer with maxima over Barents Sea and Central Eurasia. Changes in the mean climate and its variability are modulating the future winter extreme events.
Observations from 1979 to 2014 show a positive trend in the summer sea ice melt rate with an acceleration particularly in June and August. This is associated with atmospheric circulation changes such ...as a tendency toward a dipole pattern in the mean sea level pressure (SLP) trend with an increase over the Arctic Ocean and a decrease over Siberia. Consistent with previous studies, we here show the statistical relationship between the summer sea ice melt rate and SLP and that more than one SLP pattern is associated with anomalously high melt rates. Most high melt rates occur during high pressure over the Arctic Ocean accompanied by low pressure over Siberia, but a strong Beaufort High and advection of warm air associated with a cyclone located over the Taymyr Peninsula can also trigger anomalous high ice melt. We evaluate 10‐member ensemble simulations with the coupled atmosphere‐ice‐ocean Arctic regional climate model HIRHAM‐NAOSIM. The simulations have systematically low acceleration of sea ice melt rate in August, related to shortcomings in representing the strengthening pressure gradient from the Barents/Kara Sea toward Northern Greenland in recent decades. In general, the model shows the same classification of SLP patterns related to anomalous melt rates as the observations. However, the evolution of sea ice melt‐related cloud‐radiation feedback over the summer reveals contrary effects from low‐level clouds in the reanalysis and in the simulations.
Key Points
Trends in Arctic sea ice melt rate and mean sea level pressure in summer months May–August 1979–2014 are quantified
Coupled regional climate simulations reproduce observed statistical relation between melt rate and atmospheric circulation, but show deficits in August
Contrary sea ice melt‐related cloud‐radiation feedback evolving over the summer are found
Regional climate effects of Arctic Haze Rinke, A.; Dethloff, K.; Fortmann, M.
Geophysical research letters,
August 2004, Letnik:
31, Številka:
16
Journal Article
Recenzirano
Odprti dostop
The direct climate effect of aerosols has been studied within a regional atmospheric model of the Arctic. The mean springtime effect on the near surface temperature has been estimated and showed to ...be within ±1 K. However, the aerosol effect varies strongly regionally depending on the surface albedo, atmospheric humidity, and cloud condition of the region. The interannual variability of the aerosol effect is very pronounced (for the near surface temperature in the order of 2 K) and is connected with the strong varying year‐specific atmospheric conditions. Due to the high horizontal resolution of the model, it was possible to assess the influence both on the large‐scale as well as on the meso‐scale atmospheric circulation. Through the aerosol‐radiation‐circulation feedback, the scattering and absorption of radiation by aerosol cause pressure pattern changes which have the potential to modify Arctic teleconnection patterns like the Barents Sea Oscillation.
PDF
