A year-round satellite sea-ice thickness record from CryoSat-2.

Arctic sea ice is diminishing with climate warming1 at a rate unmatched for at least 1,000 years2. As the receding ice pack raises commercial interest in the Arctic3, it has become more variable and mobile4, which increases safety risks to maritime users5. Satellite observations of sea-ice thickness are currently unavailable during the crucial melt period from May to September, when they would be most valuable for applications such as seasonal forecasting6, owing to major challenges in the processing of altimetry data7. Here we use deep learning and numerical simulations of the CryoSat-2 radar altimeter response to overcome these challenges and generate a pan-Arctic sea-ice thickness dataset for the Arctic melt period. CryoSat-2 observations capture the spatial and the temporal patterns of ice melting rates recorded by independent sensors and match the time series of sea-ice volume modelled by the Pan-Arctic Ice Ocean Modelling and Assimilation System reanalysis8. Between 2011 and 2020, Arctic sea-ice thickness was 1.87 ± 0.10 m at the start of the melting season in May and 0.82 ± 0.11 m by the end of the melting season in August. Our year-round sea-ice thickness record unlocks opportunities for understanding Arctic climate feedbacks on different timescales. For instance, sea-ice volume observations from the early summer may extend the lead time of skilful August-October sea-ice forecasts by several months, at the peak of the Arctic shipping season.

Shine a light: Under-ice light and its ecological implications in a changing Arctic Ocean.

The Arctic marine ecosystem is shaped by the seasonality of the solar cycle, spanning from 24-h light at the sea surface in summer to 24-h darkness in winter. The amount of light available for under-ice ecosystems is the result of different physical and biological processes that affect its path through atmosphere, snow, sea ice and water. In this article, we review the present state of knowledge of the abiotic (clouds, sea ice, snow, suspended matter) and biotic (sea ice algae and phytoplankton) controls on the underwater light field. We focus on how the available light affects the seasonal cycle of primary production (sympagic and pelagic) and discuss the sensitivity of ecosystems to changes in the light field based on model simulations. Lastly, we discuss predicted future changes in under-ice light as a consequence of climate change and their potential ecological implications, with the aim of providing a guide for future research.

New climate models reveal faster and larger increases in Arctic precipitation than previously projected.

As the Arctic continues to warm faster than the rest of the planet, evidence mounts that the region is experiencing unprecedented environmental change. The hydrological cycle is projected to intensify throughout the twenty-first century, with increased evaporation from expanding open water areas and more precipitation. The latest projections from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) point to more rapid Arctic warming and sea-ice loss by the year 2100 than in previous projections, and consequently, larger and faster changes in the hydrological cycle. Arctic precipitation (rainfall) increases more rapidly in CMIP6 than in CMIP5 due to greater global warming and poleward moisture transport, greater Arctic amplification and sea-ice loss and increased sensitivity of precipitation to Arctic warming. The transition from a snow- to rain-dominated Arctic in the summer and autumn is projected to occur decades earlier and at a lower level of global warming, potentially under 1.5 °C, with profound climatic, ecosystem and socio-economic impacts.

The call of the emperor penguin: Legal responses to species threatened by climate change.

Species extinction risk is accelerating due to anthropogenic climate change, making it urgent to protect vulnerable species through legal frameworks in order to facilitate conservation actions that help mitigate risk. Here, we discuss fundamental concepts for assessing climate change risks to species using the example of the emperor penguin (Aptenodytes forsteri), currently being considered for protection under the US Endangered Species Act (ESA). This species forms colonies on Antarctic sea ice, which is projected to significantly decline due to ongoing greenhouse gas (GHG) emissions. We project the dynamics of all known emperor penguin colonies under different GHG emission scenarios using a climate-dependent meta-population model including the effects of extreme climate events based on the observational satellite record of colonies. Assessments for listing species under the ESA require information about how species resiliency, redundancy and representation (3Rs) will be affected by threats within the foreseeable future. Our results show that if sea ice declines at the rate projected by climate models under current energy system trends and policies, the 3Rs would be dramatically reduced and almost all colonies would become quasi-extinct by 2100. We conclude that the species should be listed as threatened under the ESA.

Divergence of Arctic shrub growth associated with sea ice decline.

Arctic sea ice extent (SIE) is declining at an accelerating rate with a wide range of ecological consequences. However, determining sea ice effects on tundra vegetation remains a challenge. In this study, we examined the universality or lack thereof in tundra shrub growth responses to changes in SIE and summer climate across the Pan-Arctic, taking advantage of 23 tundra shrub-ring chronologies from 19 widely distributed sites (56°N to 83°N). We show a clear divergence in shrub growth responses to SIE that began in the mid-1990s, with 39% of the chronologies showing declines and 57% showing increases in radial growth (decreasers and increasers, respectively). Structural equation models revealed that declining SIE was associated with rising air temperature and precipitation for increasers and with increasingly dry conditions for decreasers. Decreasers tended to be from areas of the Arctic with lower summer precipitation and their growth decline was related to decreases in the standardized precipitation evapotranspiration index. Our findings suggest that moisture limitation, associated with declining SIE, might inhibit the positive effects of warming on shrub growth over a considerable part of the terrestrial Arctic, thereby complicating predictions of vegetation change and future tundra productivity.

A Lagrangian Snow-Evolution System for Sea-Ice Applications (SnowModel-LG): Part I-Model Description.

A Lagrangian snow-evolution model (SnowModel-LG) was used to produce daily, pan-Arctic, snow-on-sea-ice, snow property distributions on a 25 × 25-km grid, from 1 August 1980 through 31 July 2018 (38 years). The model was forced with NASA's Modern Era Retrospective-Analysis for Research and Applications-Version 2 (MERRA-2) and European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis-5th Generation (ERA5) atmospheric reanalyses, and National Snow and Ice Data Center (NSIDC) sea ice parcel concentration and trajectory data sets (approximately 61,000, 14 × 14-km parcels). The simulations performed full surface and internal energy and mass balances within a multilayer snowpack evolution system. Processes and features accounted for included rainfall, snowfall, sublimation from static-surfaces and blowing-snow, snow melt, snow density evolution, snow temperature profiles, energy and mass transfers within the snowpack, superimposed ice, and ice dynamics. The simulations produced horizontal snow spatial structures that likely exist in the natural system but have not been revealed in previous studies spanning these spatial and temporal domains. Blowing-snow sublimation made a significant contribution to the snowpack mass budget. The superimposed ice layer was minimal and decreased over the last four decades. Snow carryover to the next accumulation season was minimal and sensitive to the melt-season atmospheric forcing (e.g., the average summer melt period was 3 weeks or 50% longer with ERA5 forcing than MERRA-2 forcing). Observed ice dynamics controlled the ice parcel age (in days), and ice age exerted a first-order control on snow property evolution.

The polar regions in a 2°C warmer world.

Over the past decade, the Arctic has warmed by 0.75°C, far outpacing the global average, while Antarctic temperatures have remained comparatively stable. As Earth approaches 2°C warming, the Arctic and Antarctic may reach 4°C and 2°C mean annual warming, and 7°C and 3°C winter warming, respectively. Expected consequences of increased Arctic warming include ongoing loss of land and sea ice, threats to wildlife and traditional human livelihoods, increased methane emissions, and extreme weather at lower latitudes. With low biodiversity, Antarctic ecosystems may be vulnerable to state shifts and species invasions. Land ice loss in both regions will contribute substantially to global sea level rise, with up to 3 m rise possible if certain thresholds are crossed. Mitigation efforts can slow or reduce warming, but without them northern high latitude warming may accelerate in the next two to four decades. International cooperation will be crucial to foreseeing and adapting to expected changes.

The Trajectory Towards a Seasonally Ice-Free Arctic Ocean.

PURPOSE OF REVIEW: The observed substantial loss of Arctic sea ice has raised prospects of a seasonally ice-free Arctic Ocean within the foreseeable future. In this review, we summarize our current understanding of the most likely trajectory of the Arctic sea-ice cover towards this state. RECENT FINDINGS: The future trajectory of the Arctic sea-ice cover can be described through a deterministic component arising primarily from future greenhouse gas emissions, and a chaotic component arising from internal variability. The deterministic component is expected to cause a largely ice-free Arctic Ocean during summer for less than 2 ∘C global warming relative to pre-industrial levels. To keep chances below 5 % that the Arctic Ocean will largely be ice free in a given year, total future CO2 emissions must remain below 500 Gt. SUMMARY: The Arctic Ocean will become ice free during summer before mid-century unless greenhouse gas emissions are rapidly reduced.

Sea ice, rain-on-snow and tundra reindeer nomadism in Arctic Russia.

Sea ice loss is accelerating in the Barents and Kara Seas (BKS). Assessing potential linkages between sea ice retreat/thinning and the region's ancient and unique social-ecological systems is a pressing task. Tundra nomadism remains a vitally important livelihood for indigenous Nenets and their large reindeer herds. Warming summer air temperatures have been linked to more frequent and sustained summer high-pressure systems over West Siberia, Russia, but not to sea ice retreat. At the same time, autumn/winter rain-on-snow (ROS) events have become more frequent and intense. Here, we review evidence for autumn atmospheric warming and precipitation increases over Arctic coastal lands in proximity to BKS ice loss. Two major ROS events during November 2006 and 2013 led to massive winter reindeer mortality episodes on the Yamal Peninsula. Fieldwork with migratory herders has revealed that the ecological and socio-economic impacts from the catastrophic 2013 event will unfold for years to come. The suggested link between sea ice loss, more frequent and intense ROS events and high reindeer mortality has serious implications for the future of tundra Nenets nomadism.

Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission.

Arctic sea ice is retreating rapidly, raising prospects of a future ice-free Arctic Ocean during summer. Because climate-model simulations of the sea-ice loss differ substantially, we used a robust linear relationship between monthly-mean September sea-ice area and cumulative carbon dioxide (CO2) emissions to infer the future evolution of Arctic summer sea ice directly from the observational record. The observed linear relationship implies a sustained loss of 3 ± 0.3 square meters of September sea-ice area per metric ton of CO2 emission. On the basis of this sensitivity, Arctic sea ice will be lost throughout September for an additional 1000 gigatons of CO2 emissions. Most models show a lower sensitivity, which is possibly linked to an underestimation of the modeled increase in incoming longwave radiation and of the modeled transient climate response.

Arctic sea ice trends, variability and implications for seasonal ice forecasting.

September Arctic sea ice extent over the period of satellite observations has a strong downward trend, accompanied by pronounced interannual variability with a detrended 1 year lag autocorrelation of essentially zero. We argue that through a combination of thinning and associated processes related to a warming climate (a stronger albedo feedback, a longer melt season, the lack of especially cold winters) the downward trend itself is steepening. The lack of autocorrelation manifests both the inherent large variability in summer atmospheric circulation patterns and that oceanic heat loss in winter acts as a negative (stabilizing) feedback, albeit insufficient to counter the steepening trend. These findings have implications for seasonal ice forecasting. In particular, while advances in observing sea ice thickness and assimilating thickness into coupled forecast systems have improved forecast skill, there remains an inherent limit to predictability owing to the largely chaotic nature of atmospheric variability.

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models.

Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa , because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SICa , which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems.

Demographic models and IPCC climate projections predict the decline of an emperor penguin population.

Studies have reported important effects of recent climate change on Antarctic species, but there has been to our knowledge no attempt to explicitly link those results to forecasted population responses to climate change. Antarctic sea ice extent (SIE) is projected to shrink as concentrations of atmospheric greenhouse gases (GHGs) increase, and emperor penguins (Aptenodytes forsteri) are extremely sensitive to these changes because they use sea ice as a breeding, foraging and molting habitat. We project emperor penguin population responses to future sea ice changes, using a stochastic population model that combines a unique long-term demographic dataset (1962-2005) from a colony in Terre Adélie, Antarctica and projections of SIE from General Circulation Models (GCM) of Earth's climate included in the most recent Intergovernmental Panel on Climate Change (IPCC) assessment report. We show that the increased frequency of warm events associated with projected decreases in SIE will reduce the population viability. The probability of quasi-extinction (a decline of 95% or more) is at least 36% by 2100. The median population size is projected to decline from approximately 6,000 to approximately 400 breeding pairs over this period. To avoid extinction, emperor penguins will have to adapt, migrate or change the timing of their growth stages. However, given the future projected increases in GHGs and its effect on Antarctic climate, evolution or migration seem unlikely for such long lived species at the remote southern end of the Earth.

Perspectives on the Arctic's shrinking sea-ice cover.

Linear trends in arctic sea-ice extent over the period 1979 to 2006 are negative in every month. This ice loss is best viewed as a combination of strong natural variability in the coupled ice-ocean-atmosphere system and a growing radiative forcing associated with rising concentrations of atmospheric greenhouse gases, the latter supported by evidence of qualitative consistency between observed trends and those simulated by climate models over the same period. Although the large scatter between individual model simulations leads to much uncertainty as to when a seasonally ice-free Arctic Ocean might be realized, this transition to a new arctic state may be rapid once the ice thins to a more vulnerable state. Loss of the ice cover is expected to affect the Arctic's freshwater system and surface energy budget and could be manifested in middle latitudes as altered patterns of atmospheric circulation and precipitation.