Sea ice in the Arctic is one of the most rapidly changing components of the global climate system. Over the past few decades, summer areal extent has declined over 30%, and all months show ...statistically significant declining trends. New satellite missions and techniques have greatly expanded information on sea ice thickness, but many uncertainties remain in the satellite data and long‐term records are sparse. However, thickness observations and other satellite‐derived data indicate a 40% decline in thickness, due in large part to the loss of thicker, older ice cover. The changes in sea ice are happening faster than models have projected. With continued increasing temperatures, summer ice‐free conditions are likely sometime in the coming decades, though there are substantial uncertainties in the exact timing and high interannual variability will remain as sea ice decreases. The changes in Arctic sea ice are already having an impact on flora and fauna in the Arctic. Some species will face increasing challenges in the future, while new habitat will open up for other species. The changes are also affecting people living and working in the Arctic. Native communities are facing challenges to their traditional ways of life, while new opportunities open for shipping, fishing, and natural resource extraction. Significant progress has been made in recent years in understanding of Arctic sea ice and its role in climate, the ecosystem, and human activities. However, significant challenges remain in furthering the knowledge of the processes, impacts, and future evolution of the system.
Key Points
Arctic sea ice is rapidly changing; thinning and summer extents are decreasingChanges are faster than model forecasts; feedbacks play a key roleChanging sea ice is impacting biology and human activity in the Arctic
The polar regions have been attracting more and more attention in recent years, fueled by the perceptible impacts of anthropogenic climate change. Polar climate change provides new opportunities, ...such as shorter shipping routes between Europe and East Asia, but also new risks such as the potential for industrial accidents or emergencies in ice-covered seas. Here, it is argued that environmental prediction systems for the polar regions are less developed than elsewhere. There are many reasons for this situation, including the polar regions being (historically) lower priority, with fewer in situ observations, and with numerous local physical processes that are less well represented by models. By contrasting the relative importance of different physical processes in polar and lower latitudes, the need for a dedicated polar prediction effort is illustrated. Research priorities are identified that will help to advance environmental polar prediction capabilities. Examples include an improvement of the polar observing system; the use of coupled atmosphere–sea ice–ocean models, even for short-term prediction; and insight into polar–lower-latitude linkages and their role for forecasting. Given the enormity of some of the challenges ahead, in a harsh and remote environment such as the polar regions, it is argued that rapid progress will only be possible with a coordinated international effort. More specifically, it is proposed to hold a Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 in which the international research and operational forecasting communites will work together with stakeholders in a period of intensive observing, modeling, prediction, verification, user engagement, and educational activities.
Abstract
A simple analytical model of the atmospheric boundary layer (ABL) coupled to sea ice is presented. It describes clear-sky cooling over sea ice during polar night in the presence of leads. ...The model solutions show that the sea ice concentration and wind speed have a strong impact on the thermal regime over sea ice. Leads cause both a warming of the ABL and an increase of stability over sea ice. The model describes a sharp ABL transition from a weakly stable coupled state to a strongly stable decoupled state when wind speed is decreasing. The threshold value of the transition wind speed is a function of sea ice concentration. The decoupled state is characterized by a large air–surface temperature difference over sea ice, which is further increased by leads. In the coupled regime, air and surface temperatures increase almost linearly with wind speed due to warming by leads and also slower cooling of the ABL. The cooling time scale shows a nonmonotonic dependency on wind speed, being lowest for the threshold value of wind speed and increasing for weak and strong winds. Theoretical solutions agree well with results of a more realistic single-column model and with observations performed at the three Russian “North Pole” drifting stations (NP-35, -37, and -39) and at the Surface Heat Budget of the Arctic Ocean ice camp. Both modeling results and observations show a strong implicit dependency of the net longwave radiative flux at the surface on wind speed.
In 2014/2015 a one-year field campaign at the Tiksi observatory in the Laptev Sea area was carried out using Sound Detection and Ranging/Radio Acoustic Sounding System (SODAR/RASS) measurements to ...investigate the atmospheric boundary layer (ABL) with a focus on low-level jets (LLJ) during the winter season. In addition to SODAR/RASS-derived vertical profiles of temperature, wind speed and direction, a suite of complementary measurements at the Tiksi observatory was available. Data of a regional atmospheric model were used to put the local data into the synoptic context. Two case studies of LLJ events are presented. The statistics of LLJs for six months show that in about 23% of all profiles LLJs were present with a mean jet speed and height of about 7 m/s and 240 m, respectively. In 3.4% of all profiles LLJs exceeding 10 m/s occurred. The main driving mechanism for LLJs seems to be the baroclinicity, since no inertial oscillations were found. LLJs with heights below 200 m are likely influenced by local topography.
Measurements of the atmospheric boundary layer (ABL) structure were performed for three years (October 2017–August 2020) at the Russian observatory “Ice Base Cape Baranova” (79.280° N, 101.620° E) ...using SODAR (Sound Detection And Ranging). These measurements were part of the YOPP (Year of Polar Prediction) project “Boundary layer measurements in the high Arctic” (CATS_BL) within the scope of a joint German–Russian project. In addition to SODAR-derived vertical profiles of wind speed and direction, a suite of complementary measurements at the observatory was available. ABL measurements were used for verification of the regional climate model COSMO-CLM (CCLM) with a 5 km resolution for 2017–2020. The CCLM was run with nesting in ERA5 data in a forecast mode for the measurement period. SODAR measurements were mostly limited to wind speeds <12 m/s since the signal was often lost for higher winds. The SODAR data showed a topographical channeling effect for the wind field in the lowest 100 m and some low-level jets (LLJs). The verification of the CCLM with near-surface data of the observatory showed good agreement for the wind and a negative bias for the 2 m temperature. The comparison with SODAR data showed a positive bias for the wind speed of about 1 m/s below 100 m, which increased to 1.5 m/s for higher levels. In contrast to the SODAR data, the CCLM data showed the frequent presence of LLJs associated with the topographic channeling in Shokalsky Strait. Although SODAR wind profiles are limited in range and have a lot of gaps, they represent a valuable data set for model verification. However, a full picture of the ABL structure and the climatology of channeling events could be obtained only with the model data. The climatological evaluation showed that the wind field at Cape Baranova was not only influenced by direct topographic channeling under conditions of southerly winds through the Shokalsky Strait but also by channeling through a mountain gap for westerly winds. LLJs were detected in 37% of all profiles and most LLJs were associated with channeling, particularly LLJs with a jet speed ≥ 15 m/s (which were 29% of all LLJs). The analysis of the simulated 10 m wind field showed that the 99%-tile of the wind speed reached 18 m/s and clearly showed a dipole structure of channeled wind at both exits of Shokalsky Strait. The climatology of channeling events showed that this dipole structure was caused by the frequent occurrence of channeling at both exits. Channeling events lasting at least 12 h occurred on about 62 days per year at both exits of Shokalsky Strait.
Several types of filter-based instruments are used to estimate aerosol light absorption coefficients. Two significant results are presented based on Aethalometer measurements at six Arctic stations ...from 2012 to 2014. First, an alternative method of post-processing the Aethalometer data is presented, which reduces measurement noise and lowers the detection limit of the instrument more effectively than boxcar averaging. The biggest benefit of this approach can be achieved if instrument drift is minimised. Moreover, by using an attenuation threshold criterion for data post-processing, the relative uncertainty from the electronic noise of the instrument is kept constant. This approach results in a time series with a variable collection time (Δt) but with a constant relative uncertainty with regard to electronic noise in the instrument. An additional advantage of this method is that the detection limit of the instrument will be lowered at small aerosol concentrations at the expense of temporal resolution, whereas there is little to no loss in temporal resolution at high aerosol concentrations ( > 2.1–6.7 Mm−1 as measured by the Aethalometers). At high aerosol concentrations, minimising the detection limit of the instrument is less critical. Additionally, utilising co-located filter-based absorption photometers, a correction factor is presented for the Arctic that can be used in Aethalometer corrections available in literature. The correction factor of 3.45 was calculated for low-elevation Arctic stations. This correction factor harmonises Aethalometer attenuation coefficients with light absorption coefficients as measured by the co-located light absorption photometers. Using one correction factor for Arctic Aethalometers has the advantage that measurements between stations become more inter-comparable.
Recent research has demonstrated that additional winter radiosonde observations in Arctic regions enhance the predictability of mid-latitude weather extremes by reducing uncertainty in the flow of ...localised tropopause polar vortices. The impacts of additional Arctic observations during summer are usually confined to high latitudes and they are difficult to realize at mid-latitudes because of the limited scale of localised tropopause polar vortices. However, in certain climatic states, the jet stream can intrude remarkably into the mid-latitudes, even in summer; thus, additional Arctic observations might improve analysis validity and forecast skill for summer atmospheric circulations over the Northern Hemisphere. This study examined such cases that occurred in 2016 by focusing on the prediction of the intensity and track of tropical cyclones (TCs) over the North Atlantic and North Pacific, because TCs are representative of extreme weather in summer. The predictabilities of three TCs were found influenced by additional Arctic observations. Comparisons with ensemble reanalysis data revealed that large errors propagate from the data-sparse Arctic into the mid-latitudes, together with high-potential-vorticity air. Ensemble forecast experiments with different reanalysis data confirmed that additional Arctic observations sometimes improve the initial conditions of upper-level troposphere circulations.
This observational study compares seasonal variations of surface fluxes (turbulent, radiative, and soil heat) and other ancillary atmospheric/surface/permafrost data based on in-situ measurements ...made at terrestrial research observatories located near the coast of the Arctic Ocean. Hourly-averaged multiyear data sets collected at Eureka (Nunavut, Canada) and Tiksi (East Siberia, Russia) are analyzed in more detail to elucidate similarities and differences in the seasonal cycles at these two Arctic stations, which are situated at significantly different latitudes (80.0°N and 71.6°N, respectively). While significant gross similarities exist in the annual cycles of various meteorological parameters and fluxes, the differences in latitude, local topography, cloud cover, snowfall, and soil characteristics produce noticeable differences in fluxes and in the structures of the atmospheric boundary layer and upper soil temperature profiles. An important factor is that even though higher latitude sites (in this case Eureka) generally receive less annual incoming solar radiation but more total daily incoming solar radiation throughout the summer months than lower latitude sites (in this case Tiksi). This leads to a counter-intuitive state where the average active layer (or thaw line) is deeper and the topsoil temperature in midsummer are higher in Eureka which is located almost 10° north of Tiksi. The study further highlights the differences in the seasonal and latitudinal variations of the incoming shortwave and net radiation as well as the moderating cloudiness effects that lead to temporal and spatial differences in the structure of the atmospheric boundary layer and the uppermost ground layer. Specifically the warm season (Arctic summer) is shorter and mid-summer amplitude of the surface fluxes near solar noon is generally less in Eureka than in Tiksi. During the dark Polar night and cold seasons (Arctic winter) when the ground is covered with snow and air temperatures are sufficiently below freezing, the near-surface environment is generally stably stratified and the hourly averaged turbulent fluxes are quite small and irregular with on average small downward sensible heat fluxes and upward latent heat and carbon dioxide fluxes. The magnitude of the turbulent fluxes increases rapidly when surface snow disappears and the air temperatures rise above freezing during spring melt and eventually reaches a summer maximum. Throughout the summer months strong upward sensible and latent heat fluxes and downward carbon dioxide (uptake by the surface) are typically observed indicating persistent unstable (convective) stratification. Due to the combined effects of day length and solar zenith angle, the convective boundary layer forms in the High Arctic (e.g., in Eureka) and can reach long-lived quasi-stationary states in summer. During late summer and early autumn all turbulent fluxes rapidly decrease in magnitude when the air temperature decreases and falls below freezing. Unlike Eureka, a pronounced zero-curtain effect consisting of a sustained surface temperature hiatus at the freezing point is observed in Tiksi during fall due to wetter and/or water saturated soils.
The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of ...thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.
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