Reply on RC2

Abstract. The Last Interglacial period (129–116 ka) is characterised by a strong orbital forcing which leads to a different seasonal and latitudinal distribution of insolation compared to the pre-industrial period. In particular, these changes amplify the seasonality of the insolation in the high latitudes of the Northern Hemisphere. Here, we investigate the Arctic climate response to this forcing by comparing the CMIP6 lig127k and piControl simulations performed with the IPSL-CM6A-LR (the global climate model developed at Institut Pierre-Simon Laplace) model. Using an energy budget framework, we analyse the interactions between the atmosphere, ocean, sea ice and continents. In summer, the insolation anomaly reaches its maximum and causes a rise in near-surface air temperature of 3.1 ∘C over the Arctic region. This warming is primarily due to a strong positive anomaly of surface downwelling shortwave radiation over continental surfaces, followed by large heat transfer from the continents to the atmosphere. The surface layers of the Arctic Ocean also receive more energy but in smaller quantity than the continents due to a cloud negative feedback. Furthermore, while heat exchange from the continental surfaces towards the atmosphere is strengthened, the ocean absorbs and stores the heat excess due to a decline in sea ice cover. However, the maximum near-surface air temperature anomaly does not peak in summer like insolation but occurs in autumn with a temperature increase of 4.2 ∘C relative to the pre-industrial period. This strong warming is driven by a positive anomaly of longwave radiation over the Arctic Ocean enhanced by a positive cloud feedback. It is also favoured by the summer and autumn Arctic sea ice retreat (-1.9×106 and -3.4×106 km2, respectively), which exposes the warm oceanic surface and thus allows oceanic heat storage and release of water vapour in summer. This study highlights the crucial role of sea ice cover variations, Arctic Ocean, as well as changes in polar cloud optical properties on the Last Interglacial Arctic warming.

Recent changes in the Arctic hydrological cycle are explored using in situ observations and an improved atmospheric reanalysis data set, ERA-Interim. We document a pronounced decline in summer snowfall over the Arctic Ocean and Canadian Archipelago. The snowfall decline is diagnosed as being almost entirely caused by changes in precipitation form (snow turning to rain) with very little influence of decreases in total precipitation. The proportion of precipitation falling as snow has decreased as a result of lower-atmospheric warming. Statistically, over 99% of the summer snowfall decline is linked to Arctic warming over the past two decades. Based on the reanalysis snowfall data over the ice-covered Arctic Ocean, we derive an estimate for the amount of snow-covered ice. It is estimated that the area of snow-covered ice, and the proportion of sea ice covered by snow, have decreased significantly. We perform a series of sensitivity experiments in which inter-annual changes in snow-covered ice are either unaccounted for, or are parameterized. In the parameterized case, the loss of snow-on-ice results in a substantial decrease in the surface albedo over the Arctic Ocean, that is of comparable magnitude to the decrease in albedo due to the decline in sea ice cover. Accordingly, the solar input to the Arctic Ocean is increased, causing additional surface ice melt. We conclude that the decline in summer snowfall has likely contributed to the thinning of sea ice over recent decades. The results presented provide support for the existence of a positive feedback in association with warming-induced reductions in summer snowfall.

Decline of the Arctic summer minimum sea ice extent is characterized by large expanses of open water in the Siberian, Laptev, Chukchi, and Beaufort Seas, and introduces large fetch distances in the Arctic Ocean. Long waves can propagate deep into the pack ice, thereby causing flexural swell and failure of the sea ice. This process shifts the floe size diameter distribution smaller, increases floe surface area, and thereby affects sea ice dynamic and thermodynamic processes. The results of Radarsat-2 imagery analysis show that a flexural fracture event which occurred in the Beaufort Sea region on 6 September 2009 affected ∼40,000 km2. Open water fractional area in the area affected initially decreased from 3.7% to 2.7%, but later increased to ∼20% following wind-forced divergence of the ice pack. Energy available for lateral melting was assessed by estimating the change in energy entrainment from longwave and shortwave radiation in the mixed-layer of the ocean following flexural fracture. 11.54 MJ m−2 of additional energy for lateral melting of ice floes was identified in affected areas. The impact of this process in future Arctic sea ice melt seasons was assessed using estimations of earlier occurrences of fracture during the melt season, and is discussed in context with ocean heat fluxes, atmospheric mixing of the ocean mixed layer, and declining sea ice cover. We conclude that this process is an important positive feedback to Arctic sea ice loss, and timing of initiation is critical in how it affects sea ice thermodynamic and dynamic processes.

Arctic sea ice cover has decreased dramatically over the last three decades. Global climate models under‐predicted this decline, most likely a result of the misrepresentation of one or more processes that influence sea ice. The cloud feedback is the primary source of uncertainty in model simulations, especially in the polar regions. A better understanding of the interaction between sea ice and clouds, and specifically the impact of decreased sea ice on cloud cover, will provide valuable insight into the Arctic climate system and may ultimately help in improving climate model parameterizations. In this study, an equilibrium feedback assessment is employed to quantify the relationship between changes in sea ice and clouds, using satellite‐derived sea ice concentration and cloud cover over the period 2000–2010. Results show that a 1% decrease in sea ice concentration leads to a 0.36–0.47% increase in cloud cover, suggesting that a further decline in sea ice cover will result in an even cloudier Arctic.

The sea ice extent in the Arctic Ocean has reduced dramatically with the last 16 years (2007-2022) showing the 16 lowest September extents observed in the satellite era. Besides a declining sea ice cover and increase in ocean heat content in summer, the winter sea ice concentration and thickness have also become more vulnerable to changes. We present results from the Fram Strait Arctic Outflow Observatory showing that the upper ocean temperature in the East Greenland Current in the Fram Strait has increased significantly between 2003 and 2019. While the cold Polar Water now contains more heat in summer due to lower sea ice concentration and longer periods of open water upstream, the warmer returning Atlantic Water has shown a greater presence in winter the central Fram Strait, impacting the winter sea ice thickness and sea ice extent. These processes combined result in a reduced sea ice cover downstream along the whole east coast of Greenland both in summer and winter, which has consequences for winter-time ocean convection in the Greenland Sea.

Mechanisms associated with the rapid decline in sea ice cover around a stranded ship in the Lazarev Sea, Antarctica

Climate warming has enabled the Arctic region to achieve seasonal navigation, and sea ice concentration is an important factor affecting the navigation of the Arctic waterways. This article uses the Arctic sea ice concentration data of the three highest temperatures in 2016, 2019, and 2020, combined with the Arctic summer sea level pressure, wind field, temperature, temperature anomaly, ice age, and sea ice movement data to analyze the spatial and temporal variation of sea ice and connectivity in the Northeast Passage (NEP) of the Arctic in Summer in three hot years, and summarizes the causes of sea ice anomalies. The results show that: (1) the summer Arctic sea ice extent in 2016, 2019 and 2020 were all lower than the multi-year average sea ice extent, and the summer sea ice extent in 2020 had the largest change trend; (2) in October of these three years, the sea ice was all negative anomalies, extending the opening time of the NEP; (3) when the sea ice concentration was 30% as the threshold, the navigation period of the NEP in 2016 was from mid-August to late October, 2019 was from the beginning of August to mid-October, 2020 was from the end of July to the end of October, and 2020 was the longest year since the opening of the NEP; (4) when the sea ice concentration was 10% as the threshold, the navigation period of the NEP in 2016 was from the end of August to the end of October, 2019 was from early August to mid-October, and 2020 was from the beginning of August to the end of October; (5) the key navigable areas of the NEP in the past three years were the central waters of the East Siberian Sea, the New Siberian Islands and the Vilkitsky Strait; (6) the navigation period of the NEP in 2016, 2019 and 2020 was longer. The main reasons were that the temperature of the NEP in the past 3 years was relatively high, the wind was weak, the sea ice movement had little effect, and the sea ice age in the key navigable areas was first year ice, which was easy to melt, which greatly promoted the opening of the NEP.

Winter near-surface temperature biases over Arctic sea ice in climate models contribute to uncertainties in future sea ice and Arctic climate projections. Mitigating these biases requires proper evaluation and understanding of their origin. We focus on the 1980-2014 near-surface air temperature simulated in the atmosphere-only and coupled configurations of the IPSL-CM6A-LR climate model. Model outputs are evaluated against multiple observational datasets, including the ERA5, in situ measurements, and satellite-based remote sensing products. To account for the known warm bias in ERA5 near-surface air temperatures during Arctic winters, we applied a simple linear correction fitted on in situ observations over the entire Arctic perennial ice zone, which served as the reference data. Within all observational datasets, a winter warm bias over sea ice is evident in both model configurations: a slight +0.4 °C in the atmosphere-only IPSL-CM6A-LR and +3.1 °C in the fully coupled configuration. A pan-Arctic energy budget analysis attributes this warm bias primarily to excess poleward atmospheric heat transport. In the coupled model, the bias is further amplified by an underestimated summertime sea ice cover, despite a deficit in net oceanic heat transport. The methods developed here could be used in multi-model evaluations to progress understanding and reduce Arctic biases in climate models.

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 sediment composition of deep-sea cores from the central Arctic Ocean, the Fram Strait, and the Yermak Plateau was analyzed for several parameters to reconstruct the history of marine paleoenvironment and terrestrial glaciation in the last 200,000 years. Layers with high amounts of coarse, terrigenous ice-rafted debris (IRD) and often high contents of smectite were deposited during extensive glaciations in northern Eurasia, when ice sheets reached the northern continental margins of the Barents and Kara seas and discharged icebergs into the Arctic Ocean. Intercalated layers with relatively low IRD and smectite contents, but abundant planktic foraminifers in the coarse fraction were deposited during periods of Atlantic Water inflow to the Arctic Ocean and seasonally open waters (leads) in a sea ice cover with only few icebergs in the Arctic Ocean. High IRD contents in the sediments reflect the presence of ice sheets on the Kara and Barents seas shelves and the hinterland during the entire oxygen isotope stage 6 (ca 190-130 ka), in substage 5b (ca 90-80 ka), at the stage boundary 5/4 (around 75 ka), and in late stage 4/early stage 3 (ca 65-50 ka). These results are in excellent correlation with those from recent field work in northern Scandinavia, European Russia, Siberia, and on the shelves. Relatively low amounts of IRD in central Arctic Ocean sediments from the Late Weichselian glacial maximum (ca 24-18 ka) correlate well with the recent reconstruction of a very limited eastern ice sheet extension during this time.Oxygen and carbon isotope records of planktic foraminifers from the analyzed sediment cores show a number of prominent excursions which can be interpreted as evidence for freshwater events in the Arctic Ocean. The synchroneity of freshwater events and IRD input suggests a common source. Strongest events were associated with deglaciations of the Barents and Kara seas after the ice sheets had blocked the outflow of large rivers for several millennia. The outflow of freshwater from large ice-dammed lakes occurred at ca 130, 80-75, and 52 ka. Freshwater events in the central Arctic Ocean during the last deglaciation (ca 18 ka) were relatively small compared to the previous events. This indicates that during most of the Late Weichselian glacial maximum a river outflow from northern Siberia to the Arctic Ocean was possible.Atlantic Water inflow to the Arctic Ocean and seasonally open waters in the ice (leads) occurred during the interglacials of oxygen isotope stage 1 and substage 5e, during several interstadials (stage 3, substages 5a and 5c), and to a lesser degree within stadials and glacials (stages 2, 4, and 6). With the exception of the interglacials, these periods were times of strong ice growth on the continents as revealed by terrestrial data. The coincidence suggests that open waters in the Arctic Ocean and the Nordic Seas were an important moisture source (in addition to more southerly sources) which fostered the growth of ice sheets on northern Eurasia.

Sea ice is an important habitat for a wide variety of microalgal species. Depending on the species composition, sea ice can be a seeding source for pelagic phytoplankton blooms after ice melt in spring. Sea-ice algal communities were studied over 2 full winter seasons in 2014 and 2016 at Rothera Research Station, situated at the Western Antarctic Peninsula (WAP). Algal pigment patterns and microscopic observations were combined with photophysiological studies based on fluorescence analyses to monitor and explain the phenology of ice-algal species. Clear patterns in species succession were identified. Young sea ice contained a mixture of algal species including dinoflagellates, cryptophytes and diatoms like Chaetoceros spp. and Fragillariopsis spp. In winter, severe environmental conditions resulted in a decline in species diversity and selection towards heterotrophy. Pennate diatoms like Amphiprora kufferathii and Berkeleya adeliensis were the first to dominate the nutrient-enriched bottom-ice layers in early spring. The bottom communities exhibited a remarkably stable value for the photoadaptation parameter, Ek, of circa 25 µmol photons m–2 s–1. Whereas pennate diatoms were most abundant in spring ice, the initial seeding event linked to ice melt was associated with flagellate species. Haptophyte species like Phaeocystis antarctica and prymnesiophytes like Pyramimonas spp. best sustained the transition from sea ice to seawater. Comparison with previous studies shows that the seeding patterns observed in Ryder Bay were characteristic over the wider sea-ice domain, Arctic and Antarctic. Over the course of this century, the WAP is predicted to experience continuing thinning and decline in sea-ice cover. For the near future, we expect that especially microalgal communities of haptophytes and chlorophytes will benefit from the changes, with yet unknown implications for carbon fluxes and higher trophic levels.

Remineralization of organic matter at the seafloor is an important ecosystem function, as it drives carbon and nutrient cycling, supplying nutrients for photosynthetic production, but also controls carbon burial within the sediment. In the Arctic Ocean, changes in primary production due to rapid sea-ice decline and thinning affect the export of organic matter to the seafloor and thus, benthic ecosystem functioning. Due to the remoteness and difficult accessibility of the Arctic Ocean, we still lack baseline knowledge about patterns of benthic remineralization rates and their drivers in both shelf and deep-sea sediments. Particularly comparative studies across regions are scarce. Here, we address this knowledge gap by contrasting benthic diffusive and total oxygen uptake rates (DOU and TOU), both established proxies of the benthic remineralization function, between shelf and deep-sea habitats of the Barents Sea and the central Arctic Ocean, sampled during a RV Polarstern expedition in 2015. DOU and TOU were measured using ex situ porewater oxygen microprofiles and sediment core incubations, respectively. In addition, contextual parameters including organic matter availability and microbial cell numbers were determined as environmental predictors. Pan-Arctic regional comparisons were obtained by extending our analyses to previously published data from the Laptev and Beaufort Seas. Our results show that (1) benthic oxygen uptake rates and most environmental predictors varied significantly between shelf and deep-sea habitats; (2) the availability of detrital organic matter is the main driver for patterns in total as well as diffusive respiration, while bacterial abundances were highly variable and only a weak predictor of differences in TOU and DOU; (3) regional differences in oxygen uptake across shelf and deep-sea sediments were mainly related to organic matter availability and may reflect varying primary production regimes and distances to the nearest shelf. Our findings suggest that the expected decline in sea-ice cover and the subsequent increase in export of organic matter to the seafloor may particularly enhance remineralization in the deep seas of the Arctic Ocean, altering benthic ecosystem functioning in future climate scenarios.

Global, Arctic, and Antarctic sea ice volume predictions using score-driven threshold climate models

Abstract. The Arctic marine climate system is changing rapidly, which is seen in the warming of the ocean and atmosphere, decline of sea ice cover, increase in river discharge, acidification of the ocean, and changes in marine ecosystems. Socio-economic activities in the coastal and marine Arctic are simultaneously changing. This calls for the establishment of a marine Arctic component of the Pan-Eurasian Experiment (MA-PEEX). There is a need for more in situ observations on the marine atmosphere, sea ice, and ocean, but increasing the amount of such observations is a pronounced technological and logistical challenge. The SMEAR (Station for Measuring Ecosystem–Atmosphere Relations) concept can be applied in coastal and archipelago stations, but in the Arctic Ocean it will probably be more cost-effective to further develop a strongly distributed marine observation network based on autonomous buoys, moorings, autonomous underwater vehicles (AUVs), and unmanned aerial vehicles (UAVs). These have to be supported by research vessel and aircraft campaigns, as well as various coastal observations, including community-based ones. Major manned drifting stations may occasionally be comparable to terrestrial SMEAR flagship stations. To best utilize the observations, atmosphere–ocean reanalyses need to be further developed. To well integrate MA-PEEX with the existing terrestrial–atmospheric PEEX, focus is needed on the river discharge and associated fluxes, coastal processes, and atmospheric transports in and out of the marine Arctic. More observations and research are also needed on the specific socio-economic challenges and opportunities in the marine and coastal Arctic, and on their interaction with changes in the climate and environmental system. MA-PEEX will promote international collaboration; sustainable marine meteorological, sea ice, and oceanographic observations; advanced data management; and multidisciplinary research on the marine Arctic and its interaction with the Eurasian continent.

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.