Explore the vast range of titles available.

The impact of projected Arctic sea ice loss on the atmospheric circulation is investigated using the Whole Atmosphere Community Climate Model (WACCM), a model with a well-resolved stratosphere. Two 160-yr simulations are conducted: one with surface boundary conditions fixed at late twentieth-century values and the other with identical conditions except for Arctic sea ice, which is prescribed at late twenty-first-century values. Their difference isolates the impact of future Arctic sea ice loss upon the atmosphere. The tropospheric circulation response to the imposed ice loss resembles the negative phase of the northern annular mode, with the largest amplitude in winter, while the less well-known stratospheric response transitions from a slight weakening of the polar vortex in winter to a strengthening of the vortex in spring. The lack of a significant winter stratospheric circulation response is shown to be a consequence of largely cancelling effects from sea ice loss in the Atlantic and Pacific sectors, which drive opposite-signed changes in upward wave propagation from the troposphere to the stratosphere. Identical experiments conducted with Community Atmosphere Model, version 4, WACCM’s low-top counterpart, show a weaker tropospheric response and a different stratospheric response compared to WACCM. An additional WACCM experiment in which the imposed ice loss is limited to August–November reveals that autumn ice loss weakens the stratospheric polar vortex in January, followed by a small but significant tropospheric response in late winter and early spring that resembles the negative phase of the North Atlantic Oscillation, with attendant surface climate impacts.

We present a method for analysing changes in the modelled volume budget of the Arctic sea ice as the ice declines during the 21st century. We apply the method to the CMIP5 global coupled model HadGEM2-ES to evaluate how the budget components evolve under a range of different forcing scenarios. As the climate warms and the ice cover declines, the sea ice processes that change the most in HadGEM2-ES are summer melting at the top surface of the ice due to increased net downward radiation and basal melting due to extra heat from the warming ocean. There is also extra basal ice formation due to the thinning ice. However, the impact of these changes on the volume budget is affected by the declining ice cover. For example, as the autumn ice cover declines the volume of ice formed by basal growth declines as there is a reduced area over which this ice growth can occur. As a result, the biggest contribution to Arctic ice decline in HadGEM2-ES is the reduction in the total amount of basal ice growth during the autumn and early winter. Changes in the volume budget during the 21st century have a distinctive seasonal cycle, with processes contributing to ice decline occurring in May–June and September to November. During July and August the total amount of sea ice melt decreases, again due to the reducing ice cover. The choice of forcing scenario affects the rate of ice decline and the timing and magnitude of changes in the volume budget components. For the HadGEM2-ES model and for the range of scenarios considered for CMIP5, the mean changes in the volume budget depend strongly on the evolving ice area and are independent of the speed at which the ice cover declines.

This study reveals a close relation between autumn Arctic sea ice change (SIC) in the Laptev Sea-eastern Siberian Sea-Beaufort Sea and subsequent spring Eurasian surface air temperature (SAT) variation. Specifically, more (less) SIC over the above regions in early autumn generally correspond to SAT warming (cooling) over the mid-high latitudes of Eurasia during subsequent spring. Early autumn Arctic SIC affects spring Eurasian SAT via modulating spring Arctic Oscillation (AO) associated atmospheric changes. The meridional temperature gradient over the mid-high latitudes decreases following the Arctic sea ice loss. This results in deceleration of prevailing westerly winds over the mid-latitudes of the troposphere, which leads to increase in the upward propagation of planetary waves and associated Eliassen-Palm flux convergence in the stratosphere over the mid-high latitudes. Thereby, westerly winds in the stratosphere are reduced and the polar vortex is weakened. Through the wave-mean flow interaction and downward propagation of zonal wind anomalies, a negative spring AO pattern is formed in the troposphere, which favors SAT cooling over Eurasia. The observed autumn Arctic SIC-spring Eurasian SAT connection is reproduced in the historical simulation (1850–2005) of the flexible global ocean-atmosphere-land system model, spectral version 2 (FGOALS-s2). The FGOALS-s2 also simulates the close connection between autumn SIC and subsequent spring AO. Further analysis suggests that the prediction skill of the spring Eurasian SAT was enhanced when taking the autumn Arctic SIC signal into account.

The launch of the Dual-frequency Precipitation Radar (DPR) opens up new opportunities for studying and monitoring the land and inland waters. It is the first time radar with a swath (±65°) covering regions with cold climate where waters are covered with ice and land with snow for prolonged periods of time has been used. It is also the first time that the remote sensing is carried out at small incidence angles (less than 19°) at two frequencies (13.6 and 35.5 GHz). The high spatial resolution (4–5 km) significantly increases the number of objects that can be studied using the new radar. Ilmen Lake is chosen as the first test object for the development of complex programs for processing and analyzing data obtained by the DPR. The problem of diagnostics of ice-cover formation and destruction according to DPR data has been considered. It is shown that the dependence of the radar backscatter cross section on the incidence angle for autumn ice is different from that of spring ice, and can be used for classification. A comparison with scattering on the water surface has shown that, at incidence angles exceeding 10°, it is possible to discern all three types of reflecting surfaces: open water, autumn ice, and spring ice, under the condition of making repeated measurements to avoid possible ambiguity caused by wind.

The potential predictability of winter temperature in China from autumn Arctic sea ice anomalies is studied by examining and statistically modeling the large–scale interannual covariability between them on the basis of singular value decomposition analysis. It is demonstrated that an intimate relationship exists between September and October sea ice anomalies in the Eurasian Arctic and following winter temperature anomalies in China, except in the Tibetan Plateau. When the autumn sea ice anomalies decline in the Eurasian Arctic, above-normal pressure anomalies appear to prevail over the region from the Eurasian Arctic to Eastern Europe and Mongolia, and below-normal anomalies prevail over the mid-latitudes of Asia and Northwestern Pacific in the following winter. Consequently, the winter Siberian High and East Asian trough are both strengthened, favoring the southward invasion of high–latitude cold air masses and thus cold temperature anomalies in China. It is found that the Siberian High plays a crucial role in delivering effects of the autumn Arctic sea ice anomalies on winter temperature variability in China. Based on this evidence, a statistical model is established to examine the potential predictability of winter temperature anomalies in China by taking the autumn Arctic sea ice signals as a predictor. Validation shows considerable skill in predicting winter temperature anomalies over a large part of China, indicating a significant potential for improving winter climate prediction in China.

Associations between autumn Arctic sea ice concentration（SIC） and early winter precipitation in China are studied using singular value decomposition analysis. The results show that a reduced SIC almost everywhere in the Arctic Ocean, except the northern Greenland Sea and Canadian Basin, are accompanied by dry conditions over central China, extending northeast from the Tibetan Plateau toward the Japan Sea, the Bohai Sea and the Yellow Sea, and wet conditions over South China and North China. Atmospheric circulation anomalies associated with SIC variability show two wave-train structures, which are persistent from autumn to winter, leading to the identified relationship between autumn Arctic SIC and early winter precipitation in China. Given that the decline in autumn SIC in the Arctic Ocean is expected to continue as the climate warms, this relationship provides a possible long-term outlook for early winter precipitation in China.

In this study, we applied the 1988–2017 monthly average sea ice concentration data from the Met Office Hadley Centre and the 1988–2017 monthly average reanalysis data from the National Centers for Environmental Prediction/Department of Energy (NCEP/DOE) Reanalysis II to analyze the relationship between the winter precipitation in the Barents and Kara Seas (BKS) and the previous autumn eastern Siberian Sea ice anomalies. Through the correlation analysis, we found that the correlation between eastern Siberian Sea ice and the BKS winter precipitation was strongest in September and weakest in November. The results indicated that, when the eastern Siberian Sea ice extent decreased in September–October, a significant positive geopotential height anomaly would occur in the coming winter (December–February) in the Norwegian–Barents region. This result in turn caused anomalies in the northward meridional wind. Consequently, the anomalous water vapor from the mid-latitude Atlantic to the Arctic passed through the Greenland Sea before finally reaching the BKS. The meridional wind also caused the temperature in said seas to increase and the BKS ice to melt, leading to an increase of winter precipitation. We also found that the increase of the Siberian high (SH) in winter was related to the decrease of autumn East Siberian Sea ice extent and the increase of the winter BKS precipitation anomaly. Further research still needs to be refined for this issue in future studies.

Rapid changes are occurring in the Arctic, including a reduction in sea ice thickness and coverage and a shift towards younger and thinner sea ice. Snow and sea ice models are often used to study these ongoing changes in the Arctic, and are typically forced by atmospheric reanalyses in absence of observations. ERA5 is a new global reanalysis that will replace the widely used ERA-Interim (ERA-I). In this study, we compare the 2 m air temperature (T2M), snowfall (SF) and total precipitation (TP) from ERA-I and ERA5, and evaluate these products using buoy observations from Arctic sea ice for the years 2010 to 2016. We further assess how biases in reanalyses can influence the snow and sea ice evolution in the Arctic, when used to force a thermodynamic sea ice model. We find that ERA5 is generally warmer than ERA-I in winter and spring (0–1.2 ∘C), but colder than ERA-I in summer and autumn (0–0.6 ∘C) over Arctic sea ice. Both reanalyses have a warm bias over Arctic sea ice relative to buoy observations. The warm bias is smaller in the warm season, and larger in the cold season, especially when the T2M is below −25 ∘C in the Atlantic and Pacific sectors. Interestingly, the warm bias for ERA-I and new ERA5 is on average 3.4 and 5.4 ∘C (daily mean), respectively, when T2M is lower than −25 ∘C. The TP and SF along the buoy trajectories and over Arctic sea ice are consistently higher in ERA5 than in ERA-I. Over Arctic sea ice, the TP in ERA5 is typically less than 10 mm snow water equivalent (SWE) greater than in ERA-I in any of the seasons, while the SF in ERA5 can be 50 mm SWE higher than in ERA-I in a season. The largest increase in annual TP (40–100 mm) and SF (100–200 mm) in ERA5 occurs in the Atlantic sector. The SF to TP ratio is larger in ERA5 than in ERA-I, on average 0.6 for ERA-I and 0.8 for ERA5 along the buoy trajectories. Thus, the substantial anomalous Arctic rainfall in ERA-I is reduced in ERA5, especially in summer and autumn. Simulations with a 1-D thermodynamic sea ice model demonstrate that the warm bias in ERA5 acts to reduce thermodynamic ice growth. The higher precipitation and snowfall in ERA5 results in a thicker snowpack that allows less heat loss to the atmosphere. Thus, the larger winter warm bias and higher precipitation in ERA5, compared with ERA-I, result in thinner ice thickness at the end of the growth season when using ERA5; however the effect is small during the freezing period.

The role of synoptic-scale cyclones in the trends and variability of Arctic sea ice conditions has remained uncertain. In recognition, we conduct a systematic investigation of how sea-ice concentration (SIC) changes with cyclone passage, including all individual storms that pass over any part of the region's ice pack. For all seasons, especially summer and autumn, we find a pattern of higher ice concentration after a region is influenced by a cyclone compared to when it is not, primarily due to thermodynamic effects. During warm months, cyclones appear to slow the general day-to-day decline in concentration; in cold months, cyclones augment the day-to-day increase. These relationships are changing over time, with cyclone-associated concentration changes becoming less distinct from overall changes. Cyclone effects on ice divergence are spatially variable; computed fields are noisy. In summer, these dynamic effects of cyclone passage generally decrease SIC, but are outweighed by the thermodynamic effects (e.g., reductions in air temperature, shortwave radiation). In autumn, cyclone-associated concentration changes are not as easily explained by observed cyclone conditions. Key questions remain regarding the extent to which our findings are influenced by artifacts of surface melt and weather effects on the passive microwave retrievals.

The Ross Sea is known for showing the greatest sea-ice increase, as observed globally, particularly from 1979 to 2015. However, corresponding changes in sea-ice thickness and production in the Ross Sea are not known, nor how these changes have impacted water masses, carbon fluxes, biogeochemical processes and availability of micronutrients. The PIPERS project sought to address these questions during an autumn ship campaign in 2017 and two spring airborne campaigns in 2016 and 2017. PIPERS used a multidisciplinary approach of manned and autonomous platforms to study the coupled air/ice/ocean/biogeochemical interactions during autumn and related those to spring conditions. Unexpectedly, the Ross Sea experienced record low sea ice in spring 2016 and autumn 2017. The delayed ice advance in 2017 contributed to (1) increased ice production and export in coastal polynyas, (2) thinner snow and ice cover in the central pack, (3) lower sea-ice Chl-a burdens and differences in sympagic communities, (4) sustained ocean heat flux delaying ice thickening and (5) a melting, anomalously southward ice edge persisting into winter. Despite these impacts, airborne observations in spring 2017 suggest that winter ice production over the continental shelf was likely not anomalous.