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The seasonal cycle in Arctic sea ice extent is asymmetric. Its amplitude has grown in recent decades as the ice has retreated more rapidly in summer than in winter. These seasonal disparities have typically been attributed to different physical factors operating during different seasons. Here we show instead that the seasonal asymmetries in Arctic sea ice extent are a geometric consequence of the distribution of continents. Coastlines block southward ice extension during winter, thereby muting changes in ice extent, but they have relatively little effect at the time of summer minimum extent. We suggest that the latitude of the Arctic sea ice edge, averaged zonally over locations where it is free to migrate, is the most readily interpretable quantity to describe the Northern Hemisphere sea ice cover. We find that the zonal‐mean sea ice edge latitude during the 1978–present era of satellite measurements has been following an approximately sinusoidal seasonal cycle that has been migrating northward at an approximately annually constant rate of 8 km/year. These results suggest a change in perspective of the most critical quantities for understanding changes in Arctic sea ice.

This report summarises visual shipboard ice observations carried out during leg ARK 17/2 of RV Polarstern in August and September 2001, operating along the Gakkel Ridge and at the North Pole. Data on general ice conditions, navigational information as well as photographs taken from the ships bridge are presented. Although most data are subject to large uncertainties due to the different experience of observers, they provide a general and quite representative overview of recent summer conditions in the Transpolar Drift, as seen from a ship. The data and photographs might be of interest as background information for discussions of recent changes of Arctic sea ice, and for comparisons with observations performed in other years. For those who have not seen a sea ice landscape so far, this report might yield first impressions of what the Arctic sea ice cover looks like. For scientists working on remote sensing, modelling, or other aspects of sea ice, the report provides some ground-truth and boundary conditions for their work in the summer of 2001.Ice conditions were characterised by very easily penetrable ice in the first half of the cruise, west of 30°E. There were many large leads with ice concentrations ranging between only 60 and 90%. Only from late August onwards, and east of 30°E, narrower leads and ice concentrations above 90% were observed. At that time, also new ice started to form on the leads. In the late period, sometimes the ship became beset in convergent ice conditions. Initially, melt ponds were observed to cover 10 to 30% of the ice surface. The ponds were ice covered already when we entered the ice in early August. However, the pond ice cover was thick enough to step on (>0.05 m) only after about August 20. Melt ponds became snow covered for some period, before they were visible again. Only after mid-September air temperatures permanently dropped below 0°C, and no snow or surface melting was observed any more.

The Arctic region has been warming at a rate significantly faster than the global average, leading to an accelerated decline in sea ice. This trend is expected to continue, potentially resulting in a "low-ice regime," which could make sea ice conditions more unpredictable. Anticipating changes in Arctic sea ice and climate states is therefore crucial for guiding various human activities, from natural resource management to risk assessment decisions. While global climate and Earth system models project continuous sea ice decline over decadal time scales, achieving reliable seasonal forecasts remains challenging. To address this, we apply dynamical downscaling with the state-of-the-art Regional Arctic System Model (RASM), which enables us to forecast Arctic sea ice on time scales ranging from weeks to six months. RASM is a fully coupled regional climate model that integrates components for the atmosphere, ocean, sea ice, and land, interconnected through the flux coupler of the Community Earth System Model. In our study, we simulate RASM at a horizontal resolution of 1/12 degree (approximately 9 km) for both the ocean and sea ice, with 45 vertical levels in the ocean and five thickness categories for sea ice. The atmosphere is configured on a 50-km grid with 40 vertical levels, dynamically downscaled from the NOAA/NCEP Climate Forecasting System version 2 (CFSv2) at 72-hour intervals for the upper half of the atmosphere. Monthly ensemble forecasts extending up to six months are generated using initial conditions derived from a fully-coupled RASM hindcast simulation without bias correction and assimilation. This presentation highlights results for September sea ice predictions initialized on April 1, May 1, June 1, July 1, August 1, and September 1, covering pan-Arctic and regional sea ice spatio-temporal conditions from 2012 to 2021. Specifically, we examine how lead time and initial conditions affect the quantitative skill of seasonal predictability for Arctic sea ice and demonstrate skillful predictions of September sea ice up to six months in advance. Overall, our study underscores that enhancing model physics and obtaining more realistic initial conditions are crucial for achieving skillful sub-seasonal to seasonal predictions.

Appearance of the Pacific diatom Neodenticula seminae in the northern Nordic Seas — An indication of changes in Arctic sea ice and ocean circulation

<p>With the presented work we aim to improve sea ice forecasts and our understanding of Arcitc sea ice formation though freeboard assimilation. Over the last years understanding Arctic sea ice changes and being able to make a reliable sea ice forecast has gained in importance. The central roll of Arctic sea ice extent in climate warming makes it a highly discussed topic in the climate research community. However a reliable Arctic sea ice forecast both on short term to seasonal time scales remains a challenge to be mastered, hinting that there are still many processes at play to be better understood. <br>One promising approach to improve forecasts has been to assimilate satellite sea ice data into numerical sea ice models. Mainly two parameters measured by satellites have been used for assimilation: Sea ice concentration, which is competitively easy to obtain from satellites measuring passive microwave emissions as for example obtained by the SMOS satellite, and sea ice thickness, which is not directly measured, but has to be calculated from surface elevation measurements, as for example obtained by Cryosat 2. Compering the skill, of assimilation products using sea ice thickness and sea ice concentration shows that sea ice thickness has a longer memory and is over all leading to a better performance then sea ice concentration assimilation. Knowing this, sea ice thickness assimilation is far from being straight forward. Surface elevation measurements, obtained from satellite altemitry measurements, have to be separated into snow and ice freeborad, by assuming a snow thickness, to derive sea ice thickness from. Most of the time this is done using a snow thickness climatology obtained from Soviet drift stations measuring snow over multi year ice during the period 1954-1991 with adaption over first year sea ice, where this climatology has proven to be overestimating snow thickness. The technique is widely used jet known to introduce an error. <br>To avoid errors caused by wrongly assumed snow covers the DMI and Aalborg University and DTU are at the moment collaborating on assimilating freebord instead of sea ice thickness into the CICE-NEMO modeling frame work using LARS NGen (LARS the Advanced Retracking System, Next Generation) sate of the art retracing software. In the presented work we will show first results of freeboard assimilation with a focus how this assimilation influences winter sea ice formation as well as the upper Arctic Ocean dynamics.</p>

Abstract. Parameters in sea ice-ocean coupled models greatly affect the simulated evolution of the ocean and sea ice, and are typically tuned to bring the model state close to observations. Using an adjoint method, spatiotemporally varying parameters of an Arctic sea ice-ocean coupled model are optimized simultaneously with the initial conditions and atmospheric forcing by assimilating satellite and in-situ observations. The assimilation results show that the joint state and parameter estimation (SPE) substantially improves the sea ice concentration simulations. Particularly in October, when the ocean surface starts to refreeze, SPE reduces the lead closing parameter Ho (which determines the minimum ice thickness formed in the open water), thereby increasing the sea ice growth and facilitating the seasonal rapid sea ice recovery in the Arctic's Pacific sector. Comparisons with sea ice thickness observations from the moored upward-looking sonars and Ice Mass Balance buoys demonstrate that incorporating optimized model parameters into the coupled model also leads to better sea ice thickness estimation. Given that the optimal set of sea ice parameters may evolve alongside the thinning of Arctic sea ice, the adjoint-based SPE scheme has the potential to more accurately reconstruct the histical Arctic ocean and sea ice changes covering the satellite era, supporting research on Arctic sea ice and ocean variability.

Abstract. The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×106 km2, compared to 6.46×106 km2 for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×106 km2 for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 % yr−1) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.

The decrease in the September sea‐ice extent over the Arctic has been accelerating since 1996. This study examined the contributions of atmospheric circulation anomalies and trends in winter and summer to changes in Arctic sea ice during the periods 1979–1996 and 1996–2010. In recent years, winter westerly winds over the Beaufort Sea and summer anticyclonic circulation over the Arctic toward the Fram Strait have contributed to accelerated decreases in sea ice over areas east of Europe and north of Alaska. In particular, recent strong anticyclonic circulation has caused an accelerating decrease in the Arctic sea ice in summer. Copyright © 2013 Royal Meteorological Society

This chapter reviews the efforts under SIKU-ISIUOP to expand upon previous research that characterized the importance of sea ice processes, use, and change around the Baffin Island communities of Cape Dorset, Igloolik, and Pangnirtung, Nunavut. In these three communities, local ice conditions are intertwined with daily activities and provide a means of traveling and hunting, as well as sustaining marine wildlife and aspects of Inuit culture. In order for people to effectively travel and hunt on the sea ice, they have to become knowledgeable about the complexity and dynamism of the oceanic environment. Through these understandings and long-term experience and observation, local experts (such as Inuit elders and active hunters) are acutely aware of the local and regional manifestations of climate change, as indicated by long-term changes and increased unpredictability of sea ice. Specifically, Inuit have observed changes in floe edge position, weather, the timing of freeze-up and breakup, ice thickness, and the presence of multi-year ice. This chapter reviews specific indicators used to evaluate sea ice changes, offers a regional comparison of sea ice changes in the three communities, and provides an overview of some of the local implications of sea ice changes.

China launched its Arctic research program and organized the first Chinese National Arctic Research Expedition (CHINARE-Arctic) in 1999. By 2016, six further expeditions had been conducted using the R/V Xuelong. The main region of the expeditions has focused on the Pacific sector of the Arctic Ocean for sea ice observations. The expeditions have used icebreaker, helicopter, boat, floe, and buoy platforms to perform these observations. Some new technologies have been developed, in particular, the underway auto-observing system for sea ice thickness using an electromagnetic instrument. The long-term measurement systems, e.g., the sea ice mass balance buoy, allow observations to extend from summer to winter. Some international cooperation projects have been involved in CHINARE-Arctic, especially the “Developing Arctic Modeling and Observing Capabilities for Long-Term Environmental Studies” project funded by the European Union during the International Polar Year. Arctic sea ice observations have been used to verify remote sensing products, identify changes in Arctic sea ice, optimize the parameterizations of sea ice physical processes, and assess the accessibility of ice-covered waters, especially around the Northeast Passage. Recommendations are provided as guidance to future CHINARE-Arctic projects. For example, a standardized operation system of sea ice observations should be contracted, and the observations of sea ice dynamics should be enhanced. The upcoming launch of a new Chinese icebreaker will allow increased ship time in support of future CHINARE Arctic oceanographic investigations. Citation: Lei R B, Zhang Z H, Li Z J, et al. Review of research on Arctic sea ice physics based on the Chinese National Arctic Research Expedition. Adv Polar Sci, 2017, 28 (2): 100-110, doi:10.13679/j.advps.2017.2.00100

Sea ice in the Arctic has been reducing rapidly in the past half century due to global warming. This study analyzes the variations of sea ice extent in the entire Arctic Ocean and its sub regions. The results indicate that sea ice extent reduction during 1979–2013 is most significant in summer, following by that in autumn, winter and spring. In years with rich sea ice, sea ice extent anomaly with seasonal cycle removed changes with a period of 4–6 years. The year of 2003–2006 is the ice-rich period with diverse regional difference in this century. In years with poor sea ice, sea ice margin retreats further north in the Arctic. Sea ice in the Fram Strait changes in an opposite way to that in the entire Arctic. Sea ice coverage index in melting-freezing period is an critical indicator for sea ice changes, which shows an coincident change in the Arctic and sub regions. Since 2002, Region C2 in north of the Pacific sector contributes most to sea ice changes in the central Aarctic, followed by C1 and C3. Sea ice changes in different regions show three relationships. The correlation coefficient between sea ice coverage index of the Chukchi Sea and that of the East Siberian Sea is high, suggesting good consistency of ice variation. In the Atlantic sector, sea ice changes are coincided with each other between the Kara Sea and the Barents Sea as a result of warm inflow into the Kara Sea from the Barents Sea. Sea ice changes in the central Arctic are affected by surrounding seas.

The Arctic is rapidly warming and experiencing tremendous changes in sea ice, ocean and terrestrial regions. Lack of long-term scientific observations makes it difficult to assess whether Arctic changes statistically represent a ‘new Arctic’ climate. Here we use five Coupled Model Intercomparison Project 5 class Earth system model large ensembles to show how the Arctic is transitioning from a dominantly frozen state and to quantify the nature and timing of an emerging new Arctic climate in sea ice, air temperatures and precipitation phase (rain versus snow). Our results suggest that Arctic climate has already emerged in sea ice. Air temperatures will emerge under the representative concentration pathway 8.5 scenario in the early- to mid-twenty-first century, followed by precipitation-phase changes. Despite differences in mean state and forced response, these models show striking similarities in their anthropogenically forced emergence from internal variability in Arctic sea ice, surface temperatures and precipitation-phase changes. The short observational record makes it difficult to gauge how unprecedented recent Arctic warming is. A multi-model large ensemble estimates a new Arctic climate has emerged for sea-ice extent. As the Arctic shifts from a primarily frozen state, temperature and precipitation follow within decades.

[1] The perennial (September) Arctic sea ice cover exhibits large interannual variability, with changes of over a million square kilometers from one year to the next. Here we explore the role of changes in Arctic cyclone activity, and related factors, in driving these pronounced year-to-year changes in perennial sea ice cover. Strong relationships are revealed between the September sea ice changes and the number of cyclones in the preceding late spring and early summer. In particular, fewer cyclones over the central Arctic Ocean during the months of May, June, and July appear to favor a low sea ice area at the end of the melt season. Years with large losses of sea ice are characterized by abnormal cyclone distributions and tracks: they lack the normal maximum in cyclone activity over the central Arctic Ocean, and cyclones that track from Eurasia into the central Arctic are largely absent. Fewer storms are associated with above-average mean sea level pressure, strengthened anticyclonic winds, an intensification of the transpolar drift stream, and reduced cloud cover, all of which favor ice melt. It is also shown that a strengthening of the central Arctic cyclone maximum helps preserve the ice cover, although the association is weaker than that between low cyclone activity and reduced sea ice. The results suggest that changes in cyclone occurrence during late spring and early summer have preconditioning effects on the sea ice cover and exert a strong influence on the amount of sea ice that survives the melt season.

Arctic sea ice has declined rapidly. A record low of sea ice extent occurred in summer 2012 as observed over three decades of satellite data. The regime of the Arctic ice cover has shifted to a new state dominated by seasonal sea ice, as perennial sea ice has diminished drastically. Changes in the distribution of sea ice classes can precondition summer melt, alter the surface albedo, upset the Bowen ratio, and impact atmospheric photochemical processes. To investigate Arctic sea ice, environmental, and chemical changes, we conducted the Bromine, Ozone, and Mercury Experiment (BROMEX) around Barrow, Alaska, in March-April 2012, together with continuous measurements through the present. We used satellite active microwave scatterometer (AMS) and passive microwave radiometer (PMR) to observe the change in sea ice extent (SIE). A problem for sea ice observations in summer is that surface melt can impact PMR signatures of sea ice, causing large uncertainties in the measurement of SIE. We developed an AMS algorithm to determine SIE, primarily based on a quadruplet combination of relative AMS values rather than the absolute magnitudes of the signature and thus improving SIE accuracy. Then we took the SIE product from AMS in 2000–2009 to calibrate PMR results and reconstruct a SIE time series over three decades (1979–2013). To monitor sea surface temperature change caused by river discharge, we obtain results from two different algorithms using data acquired from the Moderate-resolution Imaging Spectroradiometer (MODIS) instruments that are currently in orbit on both the Terra and Aqua satellites, launched in 1999 and 2002, respectively. We present results from spring-summer 2012 over the Beaufort Sea where warm waters from the Mackenzie River surged onto the sea surface layer thereby accelerating sea ice melt. Additionally, we estimated the total annual heating power carried by 72 rivers into the Arctic Ocean. We found that Arctic rivers could provide an enormous amount of energy to melt sea ice. With their immense watersheds (several million square kilometers), the Arctic rivers are effective conduits that transport heat from the warm continents in summer to the Arctic Ocean, thus contributing to sea ice melt, and enhancing the sensitivity of Arctic sea ice to climate change. In stark contrast, Antarctica is a frozen continent without any warm rivers to affect sea ice in the Southern Ocean. Using satellite observations, we directly address the question: Why has Arctic sea ice decreased precipitously while Antarctic sea ice has been relatively stable? This topic draws tremendous attention from the cryospheric science community, and has been a challenging riddle in climate change research. The influence of river discharge into the Arctic Ocean helps to answer that puzzle.

Arctic sea ice is a critical component of the climate system, yet its long-term variability and drivers remain poorly understood due to the scarcity of direct paleoclimate records. In this study, we utilize bromine records preserved in four Greenland ice cores—NEEM, DYE-3, EGRIP, and RECAP—to reconstruct changes in Arctic sea ice cover over the past 15,000 years. Bromine in polar snow and ice is primarily derived from "bromine explosions" occurring over seasonal sea ice surfaces. These are autocatalytic photochemical reactions in which sea salt from brine and frost flowers on newly formed sea ice is activated, releasing reactive bromine into the atmosphere. Because these processes are strongly linked to the presence of first-year (seasonal) sea ice, bromine enrichment in ice cores reflects the extent and variability of seasonal sea ice cover. The combined records provide a high-resolution, multi-site perspective on sea ice variability during the late glacial–Holocene transition and throughout the Holocene. By integrating these records, we explore the spatial variability of sea ice changes and highlight the heterogeneous response of the Arctic Ocean to climatic perturbation. These results offer new insights into the mechanisms controlling past sea ice variability, providing important context for evaluating future Arctic change.