Atmospheric feedbacks on Arctic summer sea-ice anomalies in ensemble simulations of a coupled regional climate model

Ensemble simulations with the Arctic coupled regional climate model HIRHAM-NAOSIM have been analyzed to investigate atmospheric feedbacks to September sea-ice anomalies in the Arctic in autumn and the following winter. Different ＂low- minus high ice＂ composites have been calculated using selected model runs and different periods. This approach allows us to investigate the robustness of the simulated regional atmospheric feedbacks to detected sea-ice anomalies. Since the position and strength of the September sea-ice anomaly varies between the different ＂low- minus high ice＂ composites, the related simulated atmospheric patterns in autumn differ depending on the specific surface heat flux forcing through the oceaaa-atmosphere interface. However, irrespective of those autumn differences, the regional atmospheric feedback in the following winter is rather insensitive to the applied compositing. Neither the selection of simulations nor the considered period impacts the results. The simulated consistent large-scale atmospheric circulation pattern show-s a wave-like pattern with positive pressure anomaly over the region of the Barents/Kara Seas and Scandinavia/western Russia （＂Scandinavian-Ural blocking＂） and negative pressure anomaly over the East Siberian/Laptev Seas.

Estimating sea ice albedo feedback in a regional climate modeling sensitivity experiment

Surface albedo feedback （SAF）, or sea ice albedo feedback over the Arctic Ocean, has an important effect on the Arctic climate, even though it is not the leading contributor to polar amplification. Previous model-based studies on SAF have primarily used global climate models to exploit their global coverage and favorable configurations. This study verified the capability of using regional climate models （RCMs） to investigate SAF by designing a sensitivity experinaent in terms of sea ice coverage. This study modeled two control cases of the years 1980 and 2012, as well as two sensitivity cases performed by switching the sea ice coverages in the control cases. The results proved the Weather Research and Forecast model capable of separating and quantifying the respective contributions of the atmosphere and the surface albedo to the surface radiation budget. Supported by the ALL/CLR model, the balanced surface shortwave radiation absorption was used to calculate SAF. The experiments overestimated SAF, largely because of the canceled cloud effect during model initialization. This study highlights a new possibility of designing experiments for studying climatic sensitivity and feedback using RCMs.

Negative Feedback in the Polar Ice System

One of the ingredients of the anthropogenic global warming hypothesis is the existence of large positive feedback in the climate system. An example is polar ice that, once melted, turns into blacker water that will increase radiation absorption and this rein-forces the melting. This causes a run-away scenario with a point of no return. Here it is shown that the polar ice can also have negative feedback aspects, where a melting of polar ice will cause it to reappear.

Causes for different spatial distributions of minimum Arctic sea-ice extent in 2007 and 2012

Satellite records show the minimum Arctic sea ice extents （SIEs） were observed in the Septembers of 2007 and 2012, but the spatial distributions of sea ice concentration reduction in these two years were quite different. Atmospheric circulation pattern and the upper-ocean state in summer were investigated to explain the difference. By employing the ice-temperature and ice-specific humidity （SH） positive feedbacks in the Arctic Ocean, this paper shows that in 2007 and 2012 the higher surface air temperature （SAT） and sea level pressure （SLP） accompanied by more surface SH and higher sea surface temperature （SST）, as a consequence, the strengthened poleward wind was favorable for melting summer Arctic sea ice in different regions in these two years. SAT was the dominant factor influencing the distribution of Arctic sea ice melting. The correlation coefficient is -0.84 between SAT anomalies in summer and the Arctic SIE anomalies in autumn. The increase SAT in different regions in the summers of 2007 and 2012 corresponded to a quicker melting of sea ice in the Arctic. The SLP and related wind were promoting factors connected with SAT. Strengthening poleward winds brought warm moist air to the Arctic and accelerated the melting of sea ice in different regions in the summers of 2007 and 2012. Associated with the rising air temperature, the higher surface SH and SST also played a positive role in reducing summer Arctic sea ice in different regions in these two years, which form two positive feedbacks mechanism.

Stratospheric Ozone-induced Cloud Radiative Effects on Antarctic Sea Ice

Recent studies demonstrate that the Antarctic Ozone Hole has important influences on Antarctic sea ice.While most of these works have focused on effects associated with atmospheric and oceanic dynamic processes caused by stratospheric ozone changes,here we show that stratospheric ozone-induced cloud radiative effects also play important roles in causing changes in Antarctic sea ice.Our simulations demonstrate that the recovery of the Antarctic Ozone Hole causes decreases in clouds over Southern Hemisphere(SH)high latitudes and increases in clouds over the SH extratropics.The decrease in clouds leads to a reduction in downward infrared radiation,especially in austral autumn.This results in cooling of the Southern Ocean surface and increasing Antarctic sea ice.Surface cooling also involves ice-albedo feedback.Increasing sea ice reflects solar radiation and causes further cooling and more increases in Antarctic sea ice.

Factors contributing to rapid decline of Arctic sea ice in autumn

Autumn Arctic sea ice has been declining since the beginning of the era of satellite sea ice observations.In this study,we examined the factors contributing to the decline of autumn sea ice concentration.From the Beaufort Sea to the Barents Sea,autumn sea ice concentration has decreased considerably between 1982 and 2020,and the rates of decline were the highest around the Beaufort Sea.We calculated the correlation coefficients between sea ice extent(SIE)anomalies and anomalies of sea surface temperature(SST),surface air temperature(SAT)and specific humidity(SH).Among these coefficients,the largest absolute value was found in the coefficient between SIE and SAT anomalies for August to October,which has a value of−0.9446.The second largest absolute value was found in the coefficient between SIE and SH anomalies for September to November,which has a value of−0.9436.Among the correlation coefficients between SIE and SST anomalies,the largest absolute value was found in the coefficient for August to October,which has a value of−0.9410.We conducted empirical orthogonal function(EOF)analyses of sea ice,SST,SAT,SH,sea level pressure(SLP)and the wind field for the months where the absolute values of the correlation coefficient were the largest.The first EOFs of SST,SAT and SH account for 39.07%,63.54%and 47.60%of the total variances,respectively,and are mainly concentrated in the area between the Beaufort Sea and the East Siberian Sea.The corresponding principal component time series also indicate positive trends.The first EOF of SLP explains 41.57%of the total variance.It is mostly negative in the central Arctic.Over the Beaufort,Chukchi and East Siberian seas,the zonal wind weakened while the meridional wind strengthened.Results from the correlation and EOF analyses further verified the effects of the ice-temperature,ice-SH and ice-SLP feedback mechanisms in the Arctic.These mechanisms accelerate melting and decrease the rate of formation of sea ice.In addition,stronger meridional winds favor the flow of warm air from lower latitudes towards the polar region,further promoting Arctic sea ice decline.

Advancing the understanding of variations of Arctic sea ice optical and thermal behaviors through an international research and mobility project

In recent decades, significant changes of Arctic sea ice have taken place. These changes are expected to influence the surface energy balance of the ice-covered Arctic Ocean. To quantify this energy balance and to increase our understanding of mechanisms leading to observed changes in the Arctic sea ice, the project ＂Advancing Modelling and Observing solar Radiation of Arctic sea ice--understanding changes and processes （AMORA）＂ was initiated and conducted from 2009 to 2013. AMORA was funded and organized under a frame of Norway-China bilateral collaboration program with partners from Finland, Germany, and the USA. The primary goal of the project was achieved by developing an autonomous spectral radiation buoy, deploying it on drifting sea ice close to the North Pole, and receiving a high-resolution time series of spectral radiation over and under sea ice from spring （before melt onset） to autumn （after freeze-up） 2012. Beyond this, in-situ sea ice data were collected during several field campaigns and simulations of snow and sea ice thermodynamics were performed. More autonomous measurements are available through deployments of sea ice mass balance buoys. These new observational data along with numerical model studies are helping us to better understand the key thermodynamic processes of Arctic sea ice and changes in polar climate. A strong scientific, but also cultural exchange between Norway, China, and the partners from the USA and Europe initiated new collaborations in Arctic reseach.