Global Sea Ice Research Articles

Assessing the representation of Arctic sea ice and the marginal ice zone in ocean–sea ice reanalyses

Abstract. The recent development of data-assimilating reanalyses of the global ocean and sea ice enables a better understanding of the polar region dynamics and provides gridded descriptions of sea ice variables without temporal and spatial gaps. Here, we study the spatiotemporal variability of the Arctic sea ice area and thickness using the Global ocean Reanalysis Ensemble Product (GREP) produced and disseminated by the Copernicus Marine Service (CMS). GREP is compared and validated against the state-of-the-art regional reanalyses PIOMAS and TOPAZ, as well as observational datasets of sea ice concentration and thickness for the period 1993–2020. Our analysis presents pan-Arctic metrics but also emphasizes the different responses of ice classes, the marginal ice zone (MIZ), and pack ice to climate changes. This aspect is of primary importance since the MIZ accounts for an increasing percentage of the summer sea ice as a consequence of the Arctic warming and sea ice extent retreat, among other processes. Our results show that GREP provides reliable estimates of present-day and recent-past Arctic sea ice states and that the seasonal to interannual variability and linear trends in the MIZ area are properly reproduced, with the ensemble spread often being as broad as the uncertainty of the observational dataset. The analysis is complemented by an assessment of the average MIZ latitude and its northward migration in recent years, a further indicator of the Arctic sea ice decline. There is substantial agreement between GREP and reference datasets in the summer. Overall, GREP is an adequate tool for gaining an improved understanding of the Arctic sea ice, also in light of the expected warming and the Arctic transition to ice-free summers.

Intersensor Calibration of Spaceborne Passive Microwave Radiometers and Algorithm Tuning for Long-Term Sea Ice Trend Analysis Based on AMSR-E Observations

Sea ice monitoring is key to analyzing the Earth’s climate system. Long-term sea ice extent (SIE) has been continuously monitored using various spaceborne passive microwave radiometers (PMRs) since November 1978. As the lifetime of a satellite is usually approximately 5 years, bias caused by differences in PMRs should be eliminated to obtain objective SIE trends. Most sea ice products have been analyzed for long-term trends with a bias adjustment based on the coarse resolution special sensor microwave imager (SSM/I) in operation for the longest period. However, since 2002, Japanese microwave radiometers of the Advanced Microwave Scanning Radiometer (AMSR) series, which have the highest spatial resolution in PMR, have been available. In this study, we developed standardization techniques for processing SIE including calibration of the brightness temperature (TB), tuning the sea ice concentration (SIC) algorithm, and adjusting the SIC threshold to retrieve a consistent SIE trend based on the AMSR for the Earth Observing System (AMSR-E, one of the AMSR that operated from May 2002 to October 2011). Analysis results showed that the root-mean-square error between AMSR-E SICs and those of moderate resolution imaging spectroradiometer (MODIS) was 15%. In this study, SIE was defined as the sum of the areas where the AMSR-E SIC was >15%. When retrieving SIE, we adjusted the SIC threshold for each PMR to be consistent with the SIE calculated based on the 15% SIC threshold for AMSR-E. We then calculated a time-series of the SIE trends over approximately 45 years using the adjusted SIE data. Therefore, we revealed the dramatic decrease in global sea ice extent since 1978. This technique enables retrieval of more accurate long-term sea ice trends for more than half a century in the future.

Role of atmospheric and oceanic processes on interannual summertime (2016–2017) decrease of sea ice in the Antarctic regions of the Southern Ocean

In this article, the interannual variability of sea ice in the Antarctic sea ice regions between 2013–2018 is studied using a global ocean sea ice coupled model and satellite observation. The numerical model reasonably well simulates satellite observed interannual variability of sea ice concentration (SIC) and sea surface temperature (SST) in the Antarctic regions of Southern Ocean during all four austral seasons; summer (December–February), autumn (March–May), winter (June–August), and spring (September–November).A comparison of satellite and model shows that, during last two decades between 2001–2020, summertime of 2016–2017 had the lowest (highest) SIC (SST) across the Antarctic sea ice regions. Mixed layer heat budget analysis has been performed to comprehend how thermodynamic processes affect changes in SIC and SST in the Antarctic sea ice regions. The strong positive net atmospheric heat flux and the negative ocean vertical entrainment during summertime of 2016–2017 resulted in increased SST compared to other years, which lead to decreased SIC during above years. Also, loss of sea ice during summertime of 2016–2017 in the Antarctic sea ice regions are linked with significant decrease of wind stress magnitude and increase of wind stress curl.

Analysis of the Antarctic Marginal Ice Zone Based on Unsupervised Classification of Standalone Sea Ice Model Data

AbstractThe Antarctic marginal ice zone, the regularly wave‐affected outer band of the sea ice covered Southern Ocean, typically contains an unconsolidated ice cover comprised of smaller, thinner floes than the inner ice pack. Thus, it is a highly dynamic region and susceptible to rapid expansion and contraction, making it a focal area for understanding and predicting the response of Antarctic sea ice to a changing climate. This novel study uses unsupervised statistical clustering of sea ice data simulated by a global sea ice model (standalone CICE6 combined with a wave propagation module and prescribed ocean) to address the outstanding challenge of separating the marginal ice zone from the inner ice pack in sea ice data sets. The method identifies a marginal ice zone with the desired characteristics and floe size is shown to be the key variable in the classification. Simulated marginal ice zone widths are similar to those derived from satellite observations of wave penetration distances, but contrast with those using the standard 15%–80% areal sea ice concentration proxy, particularly during austral winter. The simulated marginal ice zone is found to undergo a seasonal transition due to new ice formation in winter, increased drift in spring, and increased rates of wave‐induced breakup and melting in summer. The understanding gained from the study motivates incorporation of wave and floe‐scale processes in sea ice models, and the methods are available for application to outputs from high‐resolution and coupled sea ice–ocean–wave models for more detailed studies of the marginal ice zone (in both hemispheres).

Assessing the population consequences of disturbance and climate change for the Pacific walrus

Climate change and anthropogenic disturbance are increasingly affecting wildlife at a global scale. Predicting how varying types and degrees of disturbance may interact to influence population dynamics is a key management challenge. Population consequences of disturbance (PCoD) models provide a framework to link effects of anthropogenic disturbance on an individual’s behavior and physiology to population-level changes. In the present study, we develop a Pacific walrus (Odobenus rosmarus divergens) PCoD model to encompass the population-level effects of both anthropogenic disturbance and climate change. As the Arctic becomes increasingly ice-free, walruses spend more time at coastal (vs. ice-based) haulouts, from which they must expend more energy to reach foraging areas and where they have an elevated risk of mortality. Concurrently, sea ice loss is increasing the anthropogenic footprint in the Arctic (e.g. fisheries, shipping, energy exploration), which creates additional disturbance. We applied the PCoD model to 4 scenarios (ranging from optimistic to pessimistic) which incorporate different global sea ice model projections along with varying degrees of anthropogenic disturbance. All scenarios indicated a decline in Pacific walrus vital rates by the end of the 21st century, but our results demonstrated that the intensity of that decline could be mitigated by global efforts to reduce carbon emissions, along with local management and conservation efforts to protect important coastal haulouts and foraging grounds. In summary, we introduce a flexible PCoD modeling framework in a novel context which will prove useful to researchers studying species threatened by rapid environmental change.

Earth's Sea Ice Radiative Effect From 1980 to 2023

AbstractSea ice cools Earth by reducing its absorbed solar energy. We combine radiative transfer modeling with satellite‐derived surface albedo, sea ice, and cloud distributions to quantify the top‐of‐atmosphere sea ice radiative effect (SIRE). Averaged over 1980–2023, Arctic and Antarctic SIREs range from −0.64 to −0.86 W m−2 and −0.85 to −0.98 W m−2, respectively, with different cloud data sets and assumptions of climatological versus annually‐varying clouds. SIRE trends, however, are relatively insensitive to these assumptions. Arctic SIRE has weakened quasi‐linearly at a rate of 0.04–0.05 W m−2 decade−1, implying a 21%–27% reduction in the reflective power of Arctic sea ice since 1980. Antarctic sea ice exhibited a regime change in 2016, resulting in 2016–2023 Antarctic and global SIRE being 0.08–0.12 and 0.22–0.27 W m−2 weaker, respectively, relative to 1980–1988. Global sea ice has therefore lost 13%–15% of its planetary cooling effect since the early/mid 1980s, and the implied global sea ice albedo feedback is 0.24–0.38 W m−2 K−1.

The Relative Importance of Antarctic Sea Ice Loss within the Response to Greenhouse Warming

Abstract The response to Antarctic sea ice loss within a coupled modeling framework is examined in comparison to the response to Arctic sea ice loss and within the context of general greenhouse warming. Sea ice loss responses are found to be linear (particularly in response to Antarctic or global sea ice loss) with respect to the degree of imposed perturbation and additive when perturbations are applied in hemispheres separately and concurrently. Globally, and in the tropical Pacific in particular, Antarctic sea ice loss plays a relatively larger role than Arctic sea ice loss in both the atmosphere and the ocean, within the parameters of our experiments. The pattern of response to Antarctic sea ice loss is also found to more closely resemble that of greenhouse warming, again particularly in the tropics. An extension to multiparameter pattern scaling is developed to include a scaling factor for Antarctic change in addition to those for tropical warming and Arctic sea ice loss. The decomposition is applied to the modeled response to Antarctic sea ice loss to break it down into component partial responses that scale with Antarctic, tropical, and Arctic changes. This reveals the aspects of the response that are directly related to Antarctic change, such as an equatorward intensification of tropical precipitation in the Northern Hemisphere, and those that are modified via the induced changes in the tropics and Arctic, such as Northern Hemisphere temperature change. With this, we hope to gain a deeper understanding of the role of each of these changes for the development of physical mechanisms of the response.

Dynamical reconstruction of the upper-ocean state in the central Arctic during the winter period of the MOSAiC expedition

Abstract. This paper presents a methodological tool for dynamic reconstruction of the state of the ocean, based, as an example, on observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) experiment. The data used in this study were collected in the Amundsen Basin between October 2019 and January 2020. Analysing observational data to assess tracer field and upper-ocean dynamics is highly challenging when measurement platforms drift with the ice pack due to continuous drift speed and direction changes. We have equipped the new version of the coastal branch of the global Finite-volumE sea ice–Ocean Model (FESOM-C) with a nudging method. Model nudging was carried out assuming a quasi-steady state. Overall, the model can reproduce the lateral and vertical structure of the temperature, salinity, and density fields, which allows for projecting dynamically consistent features of these fields onto a regular grid. We identify two separate depth ranges of enhanced eddy kinetic energy located around two maxima in buoyancy frequency: the depth of the upper halocline and the depth of the warm (modified) Atlantic Water. Simulations reveal a notable decrease in surface layer salinity and density in the Amundsen Basin towards the north but no significant gradient from east to west. However, we find a mixed-layer deepening from east to west, with a 0.084 m km−1 gradient at 0.6 m km−1 standard deviation, compared to a weak deepening from south to north. The model resolves several stationary eddies in the warm Atlantic Water and provides insights into the associated dynamics. The model output can be used to further analyse the thermohaline structure and related dynamics associated with mesoscale and submesoscale processes in the central Arctic, such as estimates of heat fluxes or mass transport. The developed nudging method can be utilized to incorporate observational data from a diverse set of instruments and for further analysis of data from the MOSAiC expedition.

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

The literature on sea ice predictions uses a variety of general circulation models (GCMs), which suggest diverse predictions of the date of ice-free or almost ice-free oceans, and focus mainly on the Arctic. GCMs are not sensitive enough to tipping points in the Atlantic meridional overturning circulation (AMOC), and they underestimate the sensitivity of Arctic sea ice to carbon emissions. We contribute to the literature in two ways: First, we use a novel time series model, named the score-driven threshold climate (SDTC) model, and we report global, Arctic, and Antarctic sea ice predictions. For the SDTC model, the estimations are computationally less demanding than those of the GCMs. Second, we combine long-run 1,000-year frequency climate data from 798,000 to 1,000 years ago, and short-run annual data from year 850 to year 2014. We present the evolution of long-run and short-run climate data with descriptive statistics. We estimate the SDTC model using annual data from 850 to 2014 for Arctic and Antarctic sea ice volume Icet and Antarctic land surface temperature Tempt. We use the atmospheric CO2,t concentration as a clustering variable to define periods of climate change. Hence, CO2,t concentration drives the regime-switching dynamics of parameters in the SDTC model. We report in-sample interval forecasts of global, Arctic, and Antarctic sea ice from 1980 to 2014. Observed global and Arctic sea ice volumes are below the forecasted interval from 2003. The observed Antarctic sea ice volume is below the forecasted interval from 2011. We report out-of-sample interval forecasts of sea ice from 2015 to 2314. The out-of-sample forecasts, μ[μ±2σ], indicate that if the current trend of climate change continues, then Arctic sea ice will disappear around 2058[2049,2068], and global and Antarctic sea ice will disappear around 2174[2123,2270].

Characterization of hydrocarbon degraders from Northwest Passage beach sediments and assessment of their ability for bioremediation.

Global warming-induced sea ice loss in the Canadian Northwest Passage (NWP) will result in more shipping traffic, increasing the risk of oil spills. Microorganisms inhabiting NWP beach sediments may degrade hydrocarbons, offering a potential bioremediation strategy. In this study, the characterization and genomic analyses of 22 hydrocarbon-biodegradative bacterial isolates revealed that they contained a diverse range of key alkane and aromatic hydrocarbon-degradative genes, as well as cold and salt tolerance genes indicating they are highly adapted to the extreme Arctic environment. Some isolates successfully degraded Ultra Low Sulfur Fuel Oil (ULSFO) at temperatures as low as -5°C and high salinities (3%-10%). Three isolates were grown in liquid medium containing ULSFO as sole carbon source over 3 months and variation of hydrocarbon concentration was measured at three time points to determine their rate of hydrocarbon biodegradation. Our results demonstrate that two isolates (Rhodococcus sp. R1B_2T and Pseudarthrobacter sp. R2D_1T) possess complete degradation pathways and can grow on alkane and aromatic components of ULSFO under Arctic conditions. Overall, these results demonstrate that diverse hydrocarbon-degrading microorganisms exist in the NWP beach sediments, offering a potential bioremediation strategy in the events of a marine fuel spill reaching the shores of the NWP.

Eddy activity in the Arctic Ocean projected to surge in a warming world

Ocean eddies play a critical role in climate and marine life. In the rapidly warming Arctic, little is known about how ocean eddy activity will change because existing climate models cannot resolve Arctic Ocean mesoscale eddies. Here, by employing a next-generation global sea ice–ocean model with kilometre-scale horizontal resolution in the Arctic, we find a surge of eddy kinetic energy in the upper Arctic Ocean, tripling on average in a four-degree-warmer world. The driving mechanism behind this surge is an increase in eddy generation due to enhanced baroclinic instability. Despite the decline of sea ice, eddy killing (a process in which eddies are dampened by sea ice and winds) will not weaken in its annual mean effect in the considered warming scenario. Our study suggests the importance of adequately representing Arctic eddy activity in climate models for understanding the impacts of its increase on climate and ecosystems.

Recent Strengthening of the ENSO Influence on the Early Winter East Atlantic Pattern

Previous studies have demonstrated that the influence of the El Niño–Southern Oscillation (ENSO) on the Euro-Atlantic atmospheric circulation varies considerably during the boreal winter. Compared to the late winter (January–March) relationship, the early winter (November–December) teleconnection is more uncertain and less understood. In this paper, we revisited this early winter regional ENSO teleconnection using the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) and the European Centre for Medium-Range Weather Forecasting (ECMWF) fifth generation reanalysis (ERA5) datasets for the period 1979–2022. It was found that the signal projected well onto the second dominant mode of Euro-Atlantic atmospheric variability, the East Atlantic Pattern (EAP), rather than the previously mentioned North Atlantic Oscillation (NAO). This influence is associated with ENSO-induced dipolar convection anomalies in the Gulf of Mexico and Caribbean Sea (GMCA), which leads to an EAP via exciting Rossby waves propagating northward into the North Atlantic. We further revealed that this ENSO–EAP teleconnection underwent a pronounced interdecadal strengthening around the late 1990s. Prior to the late 1990s, the convective response to ENSO in the GMCA was weak. The atmospheric responses over the Euro-Atlantic were mainly driven by the ENSO-induced convective forcing in the tropical Indian Ocean, which favors an NAO-like pattern. In contrast, since the late 1990s, ENSO has induced stronger precipitation anomalies in the GMCA, which exert a dominant influence on the Euro-Atlantic atmospheric circulation and produce an EAP. These results have useful implications for the further understanding of ENSO-related early winter atmospheric and climate variability in the Euro-Atlantic region.

Climate Projections Very Likely Underestimate Future Volcanic Forcing and Its Climatic Effects

AbstractStandard climate projections represent future volcanic eruptions by a constant forcing inferred from 1850 to 2014 volcanic forcing. Using the latest ice‐core and satellite records to design stochastic eruption scenarios, we show that there is a 95% probability that explosive eruptions could emit more sulfur dioxide (SO2) into the stratosphere over 2015–2100 than current standard climate projections (i.e., ScenarioMIP). Our simulations using the UK Earth System Model with interactive stratospheric aerosols show that for a median future eruption scenario, the 2015–2100 average global‐mean stratospheric aerosol optical depth (SAOD) is double that used in ScenarioMIP, with small‐magnitude eruptions (<3 Tg of SO2) contributing 50% to SAOD perturbations. We show that volcanic effects on large‐scale climate indicators, including global surface temperature, sea level and sea ice extent, are underestimated in ScenarioMIP because current climate projections do not fully account for the recurrent frequency of volcanic eruptions of different magnitudes.

Generation of the Internal Pycnocline in the Subpolar Southern Ocean by Wintertime Sea Ice Melting

AbstractThe ocean's internal pycnocline is a layer of elevated stratification that separates the well‐ventilated upper ocean from the more slowly renewed deep ocean. Despite its pivotal role in organizing ocean circulation, the processes governing the formation of the internal pycnocline remain little understood. Classical theories on pycnocline formation have been couched in terms of temperature and it is not clear how the theory applies in the high‐latitude Southern Ocean, where stratification is dominated by salinity. Here we assess the mechanisms generating the internal pycnocline at southern high latitudes through the analysis of a high‐resolution, realistic, global sea ice–ocean model. We show evidence suggesting that the internal pycnocline's formation is associated with sea ice‐ocean interactions in two distinct ice‐covered regions, fringing the Antarctic continental slope and the winter sea‐ice edge. In both areas, winter‐persistent sea‐ice melt creates strong, salinity‐based stratification at the base of the winter mixed layer. The resulting sheets of high stratification subsequently descend into the ocean interior at fronts of the Antarctic Circumpolar Current, and connect seamlessly to the internal pycnocline in areas further north in which pycnocline stratification is determined by temperature. Our findings thus suggest an important role of localized sea ice‐ocean interactions in configuring the vertical structure of the Southern Ocean.

Biomarker evidence of the water mass structure and primary productivity changes in the Chukchi Sea over the past 70 years

The Chukchi Sea has experienced significant changes under global warming in the Common Era, including the shift of primary productivity. However, modern observations are too short to fully investigate the effects of environmental changes in this area. Here, we analyzed lipid biomarkers (e.g. long-chain n-alkanes, n-alkanols, n-alkanoic acids, diols, and sterols) from a sediment core (R07) collected from the Chukchi Sea shelf to determine phytoplankton primary productivity variations and factors influencing these changes over the past 70 years. Similar trends of the abundance of terrestrial ecosystem-derived compounds (e.g. long-chain n-alkanes, n-alkanols, n-alkanoic acids, and C32 1,15-diol) indicate that terrigenous input increased from ca. 1946 towards ca. 1983 and then decreased thereafter. In comparison, biomarkers with marine origin indicate that the ratio of diatoms to dinoflagellates increased after ca. 1983 towards the core-top (ca. 2011). Concurrent changes in terrigenous input and phytoplankton community indicated a shift in water mass structure at ca. 1983 (i.e. the Alaska Coastal Water decreased and the Bering Sea Water increased), which may be attributed to the phase shift of the Arctic Oscillation and/or unsynchronized flow changes in different water masses. Owing to the different water mass properties, the change of water mass structure caused intense water mixing and the resulting high turbidity in the study area, which led to light limitation for phytoplankton growth. These conditions probably account for the reduced phytoplankton primary productivity from ca. 1983 to ca. 2000 in the general trend of increasing. The results indicate that, in addition to global warming and sea ice retreat, other factors, such as change in regional water mass structure (i.e. different water masses), may also have a significant influence on the primary productivity and the phytoplankton community in the Chukchi Sea shelf.

Bottom-associated phytoplankton bloom and its expansion in the Arctic Ocean.

Phytoplankton production in the Arctic Ocean is increasing due to global warming-induced sea ice loss, which is generally assessed through satellite observations of surface chlorophyll. Here we show that a diatom bloom can occur near the seafloor rather than at the surface in the open Arctic Ocean. Light can reach the seafloor underlying nutrient-rich bottom water after the spring bloom because the surface water becomes oligotrophic and increases transparency in the region of shallow Arctic shelf. Our microcosm experiment demonstrated that diatoms formed a bloom when sediments on the shelf region, which contained abundant viable diatom cells, were exposed to even weak light reaching the seafloor (~1% of the surface irradiance). Repeated shipboard observations in the shelf region suggested that such bottom-associated blooms occurred occasionally and the primary production was significantly underestimated by satellite observations. The average bottom irradiance (2003-2017) in the Arctic Ocean is particularly promoted in summer in the eastern East Siberian Sea and the Foxe Basin, which were ice-covered throughout the year until the 1990s. Our results imply that hidden bottom-associated blooms are now widespread across the shallow Arctic shelf region.

Predictability of Intra-Seasonal Descriptors of Rainy Season over Senegal Using Global SST Patterns

Seasonal forecasting of the rainfall characteristics in Sahel is of crucial interest in determining crop variability in these countries. This study aims to provide further characterization of nine rainfall metrics over Senegal (Onset, cessation, LRS, CDD, CDD7, CDD15, NR90p, NR95p, NR99p) and their response to global SST patterns from 1981 to 2018. The Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) dataset and the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) were used. The results showed strong spatio-temporal variability with a pronounced south–north gradient for all metrics. The earliest onset was observed in the south of the country from 4 July and the latest onset in the north from 9 August. Since 2012, a new regime is observed with an increase in both long dry spells and extreme wet events. Furthermore, SST forcing has shown that the North tropical Atlantic and the East Equatorial Pacific are better able to explain the interannual variability of the intraseasonal descriptors. However, the prediction of metrics is earlier for the most remote basin (Pacific) compared to the most local basin (Atlantic). These results have implications for the seasonal forecasting of Sahel’s intraseasonal variability based on SST predictors, as significant predictability is found far from the beginning of the season.

Bayesian Sea Ice Detection Algorithm for CFOSAT

This paper describes the adaptation of the Bayesian sea ice detection algorithm for the rotating fan-beam scatterometer CSCAT onboard the China–France Oceanography Satellite (CFOSAT). The algorithm was originally developed and applied for fixed fan-beam and rotating pencil-beam scatterometers. It is based on the probability of the wind and ice backscatter distances from the measurements to their corresponding geophysical model functions (GMFs). The new rotating Ku-band fan-beam design introduces very diverse geometry distributions across the swath, which leads to three main adaptations of the algorithm: (1) a new probability distribution function fit for the backscatter distances over open sea; (2) a linear ice GMF as a function of incidence angle; (3) the separation of outer swath wind vector cells ((WVCs) number 1, 2, 41, 42) from the other WVCs to form two sets of probability distribution function fits for these two WVC groups. The results are validated against sea ice extents from the active microwave ASCAT and the passive microwave SSMI. The validation shows good agreement with both instruments, despite the discrepancies with SSMI during the melting season, and this discrepancy is caused by the lower sensitivity of the passive microwave to detect the ice at a low concentration with a mixed water/ice state, while the scatterometer is more tolerant regarding this situation. We observed that the sea-ice GMF regression between HH and VV sea-ice backscatter at low and high incidence angles decorrelates at around −12 dB (28) and −20 dB (50) and an experiment with truncated backscatter values at these incidence angles is executed, which significantly improves the year-long average sea ice extents. In conclusion, the adapted algorithm for CSCAT works effectively and yields consistent sea ice extents compared with active and passive microwave instruments. As such, it can, in principle, contribute to the long-term global scatterometer sea ice record, and as the algorithm was adapted for a rotating fan-beam scatterometer, it also can serve as a guideline for the recently launched, dual-frequency, rotating fan-beam scatterometer WindRAD.

Synchronous Variation Patterns of Monthly Sea Ice Anomalies at the Arctic and Antarctic

Abstract Sea ice variability in the opposite polar regions is examined holistically by applying the self-organizing map (SOM) method to global monthly sea ice concentration data over two periods. The results show that the variability modes of sea ice decrease in the Arctic correspond to an overall sea ice increase in the Antarctic, and vice versa. In particular, the monthly sea ice anomaly patterns are dominated by in-phase variability across the Arctic that is stronger in the marginal seas particularly the Barents Sea than the central Arctic Ocean. The corresponding Antarctic sea ice variability is characterized by a zonal wavenumber-3 structure or a dipole pattern of out-of-phase variability between the Bellingshausen/Amundsen Seas and the rest of the Southern Ocean. The frequency of occurrence of these dominant patterns exhibits pronounced seasonal as well as decadal variability and the latter is closely related to the Pacific decadal oscillation and Atlantic multidecadal oscillation. Other less frequent patterns seem to be associated with the central Pacific El Niño and spatially heterogeneous interannual variability of sea surface temperature (SST) in the Indian and the Atlantic Oceans. The dominant modes explain 57% of the four-decade domain-averaged trends in the annual polar sea ice concentration, with more explained in the eastern than western Arctic Ocean and in the Weddell Sea and the Amundsen Sea in the Antarctic. The spatial patterns of the leading modes can be largely explained by the dynamic (sea ice drift) and thermodynamic (sea ice melt) effects of the anomalous atmospheric circulations associated with SST and sea level pressure anomalies. Significance Statement The purpose of this study is to extract the main modes of monthly global sea ice concentration variability in the past four decades, explain the mechanisms behind the occurrences of these modes, and examine the contributions of these modes to the trend in annual global sea ice concentration. Sea ice extent in the past four decades has shown a significant declining trend in the Arctic and a slight, but significant increasing trend in the Antarctic. By jointly analyzing the sea ice variability and trends in the two polar regions, the results here provide a reference for what might have contributed to the opposite sea ice trends in Arctic and Antarctic and highlight the important influence of large-scale sea surface temperature anomalies on the trends in the two polar regions.

Assessing the influence of sea surface temperature and arctic sea ice cover on the uncertainty in the boreal winter future climate projections

We investigate the uncertainty (i.e., inter-model spread) in future projections of the boreal winter climate, based on the forced response of ten models from the CMIP5 following the RCP8.5 scenario. The uncertainty in the forced response of sea level pressure (SLP) is large in the North Pacific, the North Atlantic, and the Arctic. A major part of these uncertainties (31%) is marked by a pattern with a center in the northeastern Pacific and a dipole over the northeastern Atlantic that we label as the Pacific–Atlantic SLP uncertainty pattern (PA∆SLP). The PA∆SLP is associated with distinct global sea surface temperature (SST) and Arctic sea ice cover (SIC) perturbation patterns. To better understand the nature of the PA∆SLP, these SST and SIC perturbation patterns are prescribed in experiments with two atmospheric models (AGCMs): CAM4 and IFS. The AGCM responses suggest that the SST uncertainty contributes to the North Pacific SLP uncertainty in CMIP5 models, through tropical–midlatitude interactions and a forced Rossby wavetrain. The North Atlantic SLP uncertainty in CMIP5 models is better explained by the combined effect of SST and SIC uncertainties, partly related to a Rossby wavetrain from the Pacific and air-sea interaction over the North Atlantic. Major discrepancies between the CMIP5 and AGCM forced responses over northern high-latitudes and continental regions are indicative of uncertainties arising from the AGCMs. We analyze the possible dynamic mechanisms of these responses, and discuss the limitations of this work.