Sea Ice Extent Research Articles

Tracking Local Sea Ice Extent in the Beaufort Sea Using Distributed Acoustic Sensing and Machine Learning

Abstract Monitoring sea ice extent is critical to understand long-term trends in climate change. Here, we show that ambient noise recorded by fiber-optic sensing technology deployed in an Arctic shallow marine seafloor environment can track sea ice extent. We use a 37.4 km long section of fiber-optic cable deployed offshore of Oliktok Point, Alaska. Data are analyzed for two weeks: one in July 2021 and another in November 2021, when there is incomplete and evolving sea ice coverage. We apply different Machine Learning algorithms to identify types of ambient seismic noise in frequency–time scalogram images. We find evidence for two dominant noise types related to excitation of oceanic gravity waves in open water and the presence of sea ice with sufficient strength to suppress wave action. Comparison of the Distributed Acoustic Sensing (DAS) noise clustering results with satellite-based observations indicates that seafloor DAS can complement sea ice constraints from satellite imagery by locally increasing spatial and temporal resolution and tracking for which ice coverage is sufficient to diminish ocean waves.

Alaska Terrestrial and Marine Climate Trends, 1957–2021

Abstract Some of the largest climatic changes in the Arctic have been observed in Alaska and the surrounding marginal seas. Near-surface air temperature (T2m), precipitation (P), snowfall, and sea ice changes have been previously documented, often in disparate studies. Here, we provide an updated, long-term trend analysis (1957–2021; n = 65 years) of such parameters in ERA5, NOAA U.S. Climate Gridded Dataset (NClimGrid), NOAA National Centers for Environmental Information (NCEI) Alaska climate division, and composite sea ice products preceding the upcoming Fifth National Climate Assessment (NCA5) and other near-future climate reports. In the past half century, annual T2m has broadly increased across Alaska, and during winter, spring, and autumn on the North Slope and North Panhandle (T2m > 0.50°C decade−1). Precipitation has also increased across climate divisions and appears strongly interrelated with temperature–sea ice feedbacks on the North Slope, specifically with increased (decreased) open water (sea ice extent). Snowfall equivalent (SFE) has decreased in autumn and spring, perhaps aligned with a regime transition of snow to rain, while winter SFE has broadly increased across the state. Sea ice decline and melt-season lengthening also have a pronounced signal around Alaska, with the largest trends in these parameters found in the Beaufort Sea. Alaska’s climatic changes are also placed in context against regional and contiguous U.S. air temperature trends and show ∼50% greater warming in Alaska relative to the lower-48 states. Alaska T2m increases also exceed those of any contiguous U.S. subregion, positioning Alaska at the forefront of U.S. climate warming. Significance Statement This study produces an updated, long-term trend analysis (1957–2021) of key Alaska climate parameters, including air temperature, precipitation (including snowfall equivalent), and sea ice, to inform upcoming climate assessment reports, including the Fifth National Climate Assessment (NCA5) scheduled for publication in 2023. Key findings include widespread annual and seasonal warming with increased precipitation across much of the state. Winter snowfall has broadly increased, but spring and autumn snowfalls have decreased as rainfall increased. Autumn warming and precipitation increases over the North Slope, in particular, appear related to decreased sea ice coverage in the Beaufort Sea and Chukchi Seas. These trends may result from interrelated processes that accelerate Alaska climate changes relative to those of the contiguous United States.

Tidewater glaciers as “climate refugia” for zooplankton-dependent food web in Kongsfjorden, Svalbard

With climate warming, many tidewater glaciers are retreating. Fresh, sediment-rich sub-glacial meltwater is discharged at the glacier grounding line, where it mixes with deep marine water resulting in an upwelling of a plume visible in front of the glacial wall. Zooplankton may suffer increased mortality within the plume due to osmotic shock when brought in contact with the rising meltwater. The constant replenishment of zooplankton and juvenile fish to the surface areas attracts surface-foraging seabirds. Because access to other feeding areas, such as the marginal ice zone, has become energetically costly due to reduced sea-ice extent, glacial plumes may become increasingly important as “climate refugia” providing enhanced prey availability. Here, we investigated zooplankton concentrations within the plume and adjacent waters of four tidewater glaciers in Kongsfjorden, Svalbard, in early August 2016 and late July 2017. Our aim was to compare the zooplankton composition, abundance, and isotopic signatures within the plumes to those in adjacent fjord and shelf waters. Our hypothesis was that the plumes resulted in increased zooplankton mortality through osmotic shock and increased prey availability to predators. The mortality due to osmotic shock in the glacial plume was low (<5% dead organisms in samples), although slightly higher than in surrounding waters. This indicates that plumes are inefficient “death traps” for zooplankton. However, the high abundance and biomass of zooplankton within plume areas suggest that the “elevator effect” of rising glacial water supplies zooplankton to the sea surface, thereby enhancing prey availability for surface-feeding seabirds. Thus, our study provides evidence that glacial plumes are important as “climate refugia” for foraging seabirds. Stable isotope signatures showed that the glacial bay zooplankton and fish community represent a distinct isotopic niche. Additionally, zooplankton mortality associated with the plume estimated over 100-days of melt season supports a flux of 12.8 tonnes of organic carbon to benthic communities in the glacial bays. Benthic scavengers, such as Onisimus caricus and Anonyx nugax, were abundant in the glacial bay, where they feed on sinking organic matter.

Morphology of Arctic cod (Boreogadus saida) assessed according to habitat preference and age in the Beaufort Sea

The Arctic cod ( Boreogadus saida (Lepechin, 1774)) represents the most widespread and abundant fish in the Arctic and is a critical trophic link in its ecosystems. Like many species endemic to the region, it has lost essential habitat as the extent and thickness of sea ice have declined substantially in recent decades. Extreme warming induced by climate change continues to deteriorate polar marine environments. Thus, understanding how Arctic cod use and partition their habitat/environment is central to their conservation. We assessed Arctic cod functional morphology using traditional (including gill rakers) and geometric morphometrics and explored whether these differed among primarily depth-based habitats and age classes using multivariate techniques. While distinct ecotypes have been proposed, these were not detected in our analyses. Rather, results show similar patterns in external morphology of Arctic cod across habitats and age classes in the Beaufort Sea. However, analysis of gill rakers revealed concurrent habitat- and age-specific changes likely associated with dietary preferences. Findings indicate that although Arctic cod do not specialise in external morphological features in any habitat, important aspects of their internal feeding morphology shift as they grow, likely underpinning important distributional shifts and its critical role in transferring energy in Arctic marine ecosystems.

Effects of Last Glacial Maximum (LGM) sea surface temperature and sea ice extent on the isotope–temperature slope at polar ice core sites

Abstract. Stable water isotopes in polar ice cores are widely used to reconstruct past temperature variations over several orbital climatic cycles. One way to calibrate the isotope–temperature relationship is to apply the present-day spatial relationship as a surrogate for the temporal one. However, this method leads to large uncertainties because several factors like the sea surface conditions or the origin and transport of water vapor influence the isotope–temperature temporal slope. In this study, we investigate how the sea surface temperature (SST), the sea ice extent, and the strength of the Atlantic Meridional Overturning Circulation (AMOC) affect these temporal slopes in Greenland and Antarctica for Last Glacial Maximum (LGM, ∼ 21 000 years ago) to preindustrial climate change. For that, we use the isotope-enabled atmosphere climate model ECHAM6-wiso, forced with a set of sea surface boundary condition datasets based on reconstructions (e.g., GLOMAP) or MIROC 4m simulation outputs. We found that the isotope–temperature temporal slopes in East Antarctic coastal areas are mainly controlled by the sea ice extent, while the sea surface temperature cooling affects the temporal slope values inland more. On the other hand, ECHAM6-wiso simulates the impact of sea ice extent on the EPICA Dome C (EDC) and Vostok sites through the contribution of water vapor from lower latitudes. Effects of sea surface boundary condition changes on modeled isotope–temperature temporal slopes are variable in West Antarctica. This is partly due to the transport of water vapor from the Southern Ocean to this area that can dampen the influence of local temperature on the changes in the isotopic composition of precipitation and snow. In the Greenland area, the isotope–temperature temporal slopes are influenced by the sea surface temperatures near the coasts of the continent. The greater the LGM cooling off the coast of southeastern Greenland, the greater the transport of water vapor from the North Atlantic, and the larger the temporal slopes. The presence or absence of sea ice very near the coast has a large influence in Baffin Bay and the Greenland Sea and influences the slopes at some inland ice core stations. The extent of the sea ice far south slightly influences the temporal slopes in Greenland through the transport of more depleted water vapor from lower latitudes to this area. The seasonal variations of sea ice distribution, especially its retreat in summer, influence the isotopic composition of the water vapor in this region and the modeled isotope–temperature temporal slopes in the eastern part of Greenland. A stronger LGM AMOC decreases LGM-to-preindustrial isotopic anomalies in precipitation in Greenland, degrading the isotopic model–data agreement. The AMOC strength modifies the temporal slopes over inner Greenland slightly and by a little on the coasts along the Greenland Sea where the changes in surface temperature and sea ice distribution due to the AMOC strength mainly occur.

Detecting linear trend changes in data sequences

We propose TrendSegment, a methodology for detecting multiple change-points corresponding to linear trend changes in one dimensional data. A core ingredient of TrendSegment is a new Tail-Greedy Unbalanced Wavelet transform: a conditionally orthonormal, bottom-up transformation of the data through an adaptively constructed unbalanced wavelet basis, which results in a sparse representation of the data. Due to its bottom-up nature, this multiscale decomposition focuses on local features in its early stages and on global features next which enables the detection of both long and short linear trend segments at once. To reduce the computational complexity, the proposed method merges multiple regions in a single pass over the data. We show the consistency of the estimated number and locations of change-points. The practicality of our approach is demonstrated through simulations and two real data examples, involving Iceland temperature data and sea ice extent of the Arctic and the Antarctic. Our methodology is implemented in the R package trendsegmentR, available from CRAN.

Underrepresentation of the Linkage between the Barents–Kara Sea Ice and East Asian Rainfall in Early Summer by CMIP6 Models

Our previous study revealed the link between Barents–Kara sea ice and rainfall in eastern China. This study continues evaluating the performance of multiple models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating this linkage. Most CMIP6 models can simulate Arctic sea ice coverage in the present climate system, although the sea ice extent in the edge areas show some biases. Only a few models can roughly reproduce the observed rainfall dipole pattern associated with Arctic sea ice variability. The linkage between Arctic sea ice variability in winter and eastern China rainfall in early summer is performed through a long memory of the sea ice, the stratospheric variability as the mediator, and downward propagation of stratospheric signals. Very few CMIP6 models can exhibit a realistic interannual relationship between the Arctic sea ice and China rainfall. The selected high-skill models with a more realistic linkage between sea ice and China rainfall present a clear downward impact of the stratospheric circulation anomalies associated with sea ice variability. The reversal of the Northern Hemisphere Annular Mode (NAM) from the negative phase in early winter to the positive phase in spring in the high-skill models and observations denotes the important role of the stratosphere as a mediator to bridge the Arctic sea ice and China rainfall. The long memory of the Arctic sea ice with the stratosphere as the mediator has a deep implication on the seasonal forecasts of East Asian countries.

Sea Ice Extent Prediction with Machine Learning Methods and Subregional Analysis in the Arctic

The decline of sea ice in the Arctic region is a critical indicator of rapid global warming and can also influence the feedback processes in the Arctic, so the prediction of sea ice extent and thickness plays an important role in climate modeling and prediction. This paper uses machine learning methods to predict the sea ice extent, and by adjusting the methods and factors, which include the climate variables, the past sea ice extent, and the simple linear-regression-simulated sea ice extent, then we found the best combination to give the result with the highest R2 score. We noticed that with longer periods of past sea ice extent data and shorter periods of climate data, the results appeared to be better. This might be related to the difference in climate and ocean memory. The sub-region sea ice extent prediction shows that the regions with whole-year ice cover are easier to predict and that those regions with sudden weather changes and significant seasonal variability appear to have lower R2 scores in the sea ice extent prediction.

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.

Recent Decline in Antarctic Sea Ice Cover From 2016 to 2022: Insights From Satellite Observations, Argo Floats, and Model Reanalysis

Ever since the abrupt drop in Antarctic sea ice extent (SIE) began in spring of 2016, as opposed to its consistent growth (1.95% decade–1 from 1979 to 2015), the SIE in the satellite era has reached record lows in 2017 and 2022. From spring 2016, the satellite-based SIE remained consistently lower than the long-term mean, with the trend dropping to 0.11% decade–1 from 1979 to 2022. The top record lowest SIE years were observed from 2016 to 2022, corresponding to the warmest years dating back to 1979. With this background, the rare features of Antarctic polynyas reoccurred frequently and the west Antarctic Peninsula remained ice-free throughout 2022. Recently, the SIE dropped to a record low in June 2022, July 2022, August 2022, January 2023, and February 2023, which were 13.67%, 9.91%, 6.79%, 39.29%, 39.56% below the long-term mean value, respectively for months described above. We find that the observed decline in SIE during 2016–2022 occurred due to the combined influences from the intensification of atmospheric zonal waves with enhanced poleward transport of warm-moist air and anomalous warming in the Southern Ocean mixed layer (>1°C). Although the sudden sea ice decline in spring of 2016 occurred corresponding to the transitional climate shift from IPO– (Interdecadal Pacific Oscillation, 2000–2014) to IPO+ (2014–2016), the recent decline after 2016 occurred in a dominant IPO– and Southern Annular Mode (SAM+). CMIP6 models showed a consistent decrease in ensemble-mean SIE from 1979 to 2022. The model trend exhibits similarities to the recent declining trend in SIE from satellite observations since 2016, suggesting a possible shift towards a warmer climatic regime.

Arctic warming trends and their uncertainties based on surface temperature reconstruction under different sea ice extent scenarios

IPCC AR6 states that the neglect of recent rapid warming in the Arctic generally leads to an underestimate of global warming trends. In this study, by reconstructing the surface temperature (ST) datasets in the Arctic under different sea ice extent scenarios (Imax and Imin), we respectively evaluated the annual and seasonal warming trends and their uncertainties from 1900 to 2020. The results show that the reconstructed datasets have a good representation of the ST change trends in the Arctic. In 1900–2020, the annual warming trends in the Arctic (0.17 ± 0.031 and 0.14 ± 0.025 °C per decade under the Imax and Imin reconstruction, respectively) are roughly 1.6–1.8 times the global mean warming trends (0.10 ± 0.008 and 0.09 ± 0.008 °C per decade). While in 1979–2020, the Arctic warming trends (0.66 ± 0.100 and 0.55 ± 0.080 °C per decade) increase to 3.1–3.5 times of the global warming trend (0.19 ± 0.023 and 0.18 ± 0.023 °C per decade) for Imax and Imin, respectively, indicating that the Arctic amplification effect has been significantly enhancing in recent decades. Although the seasonal warming trends are closely related to cloud feedback mechanisms, atmospheric circulation, and ocean circulation, they are not sensitive to the different reconstruction scenarios.

Deglacial and Holocene sea-ice and climate dynamics in the Bransfield Strait, northern Antarctic Peninsula

Abstract. The reconstruction of past sea-ice distribution in the Southern Ocean is crucial for an improved understanding of ice–ocean–atmosphere feedbacks and the evaluation of Earth system and Antarctic ice sheet models. The Antarctic Peninsula (AP) has been experiencing a warming since the start of regular monitoring of the atmospheric temperature in the 1950s. The associated decrease in sea-ice cover contrasts the trend of growing sea-ice extent in East Antarctica. To reveal the long-term sea-ice history at the northern Antarctic Peninsula (NAP) under changing climate conditions, we examined a marine sediment core from the eastern basin of the Bransfield Strait covering the last Deglacial and the Holocene. For sea-ice reconstructions, we focused on the specific sea-ice biomarker lipid IPSO25, a highly branched isoprenoid (HBI), and sea-ice diatoms, whereas a phytoplankton-derived HBI triene (C25:3) and warmer open-ocean diatom assemblages reflect predominantly ice-free conditions. We further reconstruct ocean temperatures using glycerol dialkyl glycerol tetraethers (GDGTs) and diatom assemblages and compare our sea-ice and temperature records with published marine sediment and ice core data. A maximum ice cover is observed during the Antarctic Cold Reversal 13 800–13 000 years before present (13.8–13 ka), while seasonally ice-free conditions permitting (summer) phytoplankton productivity are reconstructed for the late Deglacial and the Early Holocene from 13 to 8.3 ka. An overall decreasing sea-ice trend throughout the Middle Holocene coincides with summer ocean warming and increasing phytoplankton productivity. The Late Holocene is characterized by highly variable winter sea-ice concentrations and a sustained decline in the duration and/or concentration of spring sea ice. Overall diverging trends in GDGT-based TEX86L and RI-OH' subsurface ocean temperatures (SOTs) are found to be linked to opposing spring and summer insolation trends, respectively.

Delayed Antarctic melt season reduces albedo feedback.

Antarctica's response to climate change varies greatly both spatially and temporally. Surface melting impacts mass balance and also lowers surface albedo. We use a 43-year record (from 1978 to 2020) of Antarctic snow melt seasons from space-borne microwave radiometers with a machine-learning algorithm to show that both the onset and the end of the melt season are being delayed. Granger-causality analysis shows that melt end is delayed due to increased heat flux from the ocean to the atmosphere at minimum sea-ice extent from warming oceans. Melt onset is Granger-caused primarily by the turbulent heat flux from ocean to atmosphere that is in turn driven by sea-ice variability. Delayed snowmelt season leads to a net decrease in the absorption of solar irradiance, as a delayed summer means that higher albedo occurs after the period of maximum solar radiation, which changes Antarctica's radiation balance more than sea-ice cover.

Deglacial climate changes as forced by different ice sheet reconstructions

Abstract. During the last deglaciation, the climate evolves from a cold state at the Last Glacial Maximum (LGM) at 21 ka (thousand years ago) with large ice sheets to the warm Holocene at ∼9 ka with reduced ice sheets. The deglacial ice sheet melt can impact the climate through multiple ways: changes of topography and albedo, bathymetry and coastlines, and freshwater fluxes (FWFs). In the PMIP4 (Paleoclimate Modelling Intercomparison Project – Phase 4) protocol for deglacial simulations, these changes can be accounted for or not depending on the modelling group choices. In addition, two ice sheet reconstructions are available (ICE-6G_C and GLAC-1D). In this study, we evaluate all these effects related to ice sheet changes on the climate using the iLOVECLIM model of intermediate complexity. We show that the two reconstructions yield the same warming to a first order but with a different amplitude (global mean temperature of 3.9 ∘C with ICE-6G_C and 3.8 ∘C with GLAC-1D) and evolution. We obtain a stalling of temperature rise during the Antarctic Cold Reversal (ACR, from ∼14 to ∼12 ka) similar to proxy data only with the GLAC-1D ice sheet reconstruction. Accounting for changes in bathymetry in the simulations results in a cooling due to a larger sea ice extent and higher surface albedo. Finally, freshwater fluxes result in Atlantic meridional overturning circulation (AMOC) drawdown, but the timing in the simulations disagrees with proxy data of ocean circulation changes. This questions the causal link between reconstructed freshwater fluxes from ice sheet melt and recorded AMOC weakening.

A seasonal analysis of aerosol NO3− sources and NOx oxidation pathways in the Southern Ocean marine boundary layer

Abstract. Nitrogen oxides, collectively referred to as NOx (NO + NO2), are an important component of atmospheric chemistry involved in the production and destruction of various oxidants that contribute to the oxidative capacity of the troposphere. The primary sink for NOx is atmospheric nitrate, which has an influence on climate and the biogeochemical cycling of reactive nitrogen. NOx sources and NOx-to-NO3- formation pathways remain poorly constrained in the remote marine boundary layer of the Southern Ocean, particularly outside of the more frequently sampled summer months. This study presents seasonally resolved measurements of the isotopic composition (δ15N, δ18O, and Δ17O) of atmospheric nitrate in coarse-mode (> 1 µm) aerosols, collected between South Africa and the sea ice edge in summer, winter, and spring. Similar latitudinal trends in δ15N–NO3- were observed in summer and spring, suggesting similar NOx sources. Based on δ15N–NO3-, the main NOx sources were likely a combination of lightning, biomass burning, and/or soil emissions at the low latitudes, as well as oceanic alkyl nitrates and snowpack emissions from continental Antarctica or the sea ice at the mid-latitudes and high latitudes, respectively. Snowpack emissions associated with photolysis were derived from both the Antarctic snowpack and snow on sea ice. A combination of natural NOx sources, likely transported from the lower-latitude Atlantic, contribute to the background-level NO3- observed in winter, with the potential for a stratospheric NO3- source evidenced by one sample of Antarctic origin. Greater values of δ18O–NO3- in spring and winter compared to summer suggest an increased influence of oxidation pathways that incorporate oxygen atoms from O3 into the end product NO3- (i.e. N2O5, DMS, and halogen oxides (XO)). Significant linear relationships between δ18O and Δ17O suggest isotopic mixing between H2O(v) and O3 in winter and isotopic mixing between H2O(v) and O3/XO in spring. The onset of sunlight in spring, coupled with large sea ice extent, can activate chlorine chemistry with the potential to increase peroxy radical concentrations, contributing to oxidant chemistry in the marine boundary layer. As a result, isotopic mixing with an additional third end-member (atmospheric O2) occurs in spring.

Spatial and Temporal Variations of Arctic Sea Ice during 1992-2021

The variation of polar sea ice is an indicator of polar environmental change, which plays an important role in the study of regional and global climate change. The arctic is a region in transition to a warmer climate and one of the most visible signs of that change is in the declining sea ice cover. Sea ice in the arctic is one of the most rapidly changing components of the global climate system. The extent of area covered by arctic sea ice is an important indicator of changes in global climate because warmer air and water temperatures are reducing the amount of sea ice present. Sea ice extent plays an important role in reflecting sunlight back into space, regulating ocean and air temperatures, circulating ocean water, maintaining animal habitats. Similarly, sea ice concentration helps to determine the number of other important climate variables. In this paper, the sea ice data from different institutes were used to analyze the spatial and temporal variation of arctic sea ice concentration (SIC) and sea ice extent (SIE) over the 30-year period 1992-2021. During this period, the results shows that these two variables were increased in the arctic during 2021 due to the decrease of temperatures particularly near Chukchi, Kara, Beaufort, East Siberian and Greenland Seas.

The Role of the Pacific‐Antarctic Ridge in Establishing the Northward Extent of Antarctic Sea‐Ice

AbstractMonitoring the Antarctic sea‐ice is essential for improving our knowledge of the Southern Ocean. We used satellite sea‐ice concentration data for the 2002–2020 period to retrieve the sea‐ice extent (SIE) and analyze its variability in the Pacific sector of the Southern Ocean. Results provide observational evidence of the recurring formation of a sea‐ice protrusion that extends to 60°S at 150°W during the winter season. Furthermore, we discuss how the Pacific‐Antarctic Ridge (PAR) influences this phenomenon. Our findings show that the northward deflection of the southern Antarctic Circumpolar Current front is driven by the PAR and is associated with the enhanced sea‐ice advance. The PAR also constrains eddy trajectories, limiting their interaction with the sea‐ice edge. These factors, within the 160°W–135°W sector, cause an average SIE increase of 61,000 km2 and 46,293 km2 per year more than the upstream and downstream areas, respectively.

SIPN South: six years of coordinated seasonal Antarctic sea ice predictions

Antarctic sea ice prediction has garnered increasing attention in recent years, particularly in the context of the recent record lows of February 2022 and 2023. As Antarctica becomes a climate change hotspot, as polar tourism booms, and as scientific expeditions continue to explore this remote continent, the capacity to anticipate sea ice conditions weeks to months in advance is in increasing demand. Spurred by recent studies that uncovered physical mechanisms of Antarctic sea ice predictability and by the intriguing large variations of the observed sea ice extent in recent years, the Sea Ice Prediction Network South (SIPN South) project was initiated in 2017, building upon the Arctic Sea Ice Prediction Network. The SIPN South project annually coordinates spring-to-summer predictions of Antarctic sea ice conditions, to allow robust evaluation and intercomparison, and to guide future development in polar prediction systems. In this paper, we present and discuss the initial SIPN South results collected over six summer seasons (December-February 2017-2018 to 2022-2023). We use data from 22 unique contributors spanning five continents that have together delivered more than 3000 individual forecasts of sea ice area and concentration. The SIPN South median forecast of the circumpolar sea ice area captures the sign of the recent negative anomalies, and the verifying observations are systematically included in the 10-90% range of the forecast distribution. These statements also hold at the regional level except in the Ross Sea where the systematic biases and the ensemble spread are the largest. A notable finding is that the group forecast, constructed by aggregating the data provided by each contributor, outperforms most of the individual forecasts, both at the circumpolar and regional levels. This indicates the value of combining predictions to average out model-specific errors. Finally, we find that dynamical model predictions (i.e., based on process-based general circulation models) generally perform worse than statistical model predictions (i.e., data-driven empirical models including machine learning) in representing the regional variability of sea ice concentration in summer. SIPN South is a collaborative community project that is hosted on a shared public repository. The forecast and verification data used in SIPN South are publicly available in near-real time for further use by the polar research community, and eventually, policymakers.

Holocene hydroclimatic variability recorded in sediments from Maddox Lake (northern California Coast Range)

AbstractPerspectives on past climate using lake sediments are critical for assessing modern and future climate change. These perspectives are especially important for water-stressed regions such as the western United States. One such region is northwestern California (CA), where Holocene-length hydroclimatic records are scarce. Here, we present a 9000-year, relative lake level record from Maddox Lake (CA) using a multi-indicator approach. The Early Holocene is characterized by variably low lake levels with a brief excursion to wetter climates/relative highstand ca. 8.4–8.06 cal ka BP, possibly related to the 8.2 ka cold event and changing Atlantic Meridional Overturning Circulation (AMOC). From 5.2–0.55 cal ka BP, Maddox Lake experienced a long-term regression, tracking changes in summer-winter insolation, tropical and northeast Pacific SSTs, and the southward migration of the ITCZ. This gradual regression culminated in a pronounced relative lowstand during the Medieval Climatic Anomaly (MCA). A marked relative highstand followed the MCA, correlative to the Little Ice Age. The latter reflects a far-field response to North Atlantic volcanism, solar variability, and possibly changes in AMOC and Arctic sea ice extent. Our results further confirm the hydroclimatic sensitivity of northwest California to various forcings including those emanating from the North Atlantic.

Summer surface air temperature proxies point to near-sea-ice-free conditions in the Arctic at 127 ka

Abstract. The Last Interglacial (LIG) period, which had higher summer solar insolation than today, has been suggested as the last time that Arctic summers were ice free. However, the latest suite of Coupled Modelling Intercomparison Project 6 Paleoclimate (CMIP6-PMIP4) simulations of the LIG produce a wide range of Arctic summer minimum sea ice area (SIA) results, with a 30 % to 96 % reduction from the pre-industrial (PI) period. Sea ice proxies are also currently neither abundant nor consistent enough to determine the most realistic state. Here we estimate LIG minimum SIA indirectly through the use of 21 proxy records for LIG summer surface air temperature (SSAT) and 11 CMIP6-PMIP4 models for the LIG. We use two approaches. First, we use two tests to determine how skilful models are at simulating reconstructed ΔSSAT from proxy records (where Δ refers to LIG-PI). This identifies a positive correlation between model skill and the magnitude of ΔSIA: the most reliable models simulate a larger sea ice reduction. Averaging the two most skilful models yields an average SIA of 1.3×106 km2 for the LIG. This equates to a 4.5×106 km2 or 79 % SIA reduction from the PI to the LIG. Second, across the 11 models, the averaged ΔSSAT at the 21 proxy locations and the pan-Arctic average ΔSSAT are inversely correlated with ΔSIA (r=-0.86 and −0.79, respectively). In other words, the models show that a larger Arctic warming is associated with a greater sea ice reduction. Using the proxy-record-averaged ΔSSAT of 4.5±1.7 K and the relationship between ΔSSAT and ΔSIA suggests an estimated sea ice reduction of 4.2±1.4×106 km2 or about 74 % less sea ice than the PI period. The mean proxy-location ΔSSAT is well correlated with the Arctic-wide ΔSSAT north of 60∘ N (r=0.97), and this relationship is used to show that the mean proxy record ΔSSAT is equivalent to an Arctic-wide warming of 3.7±1.5 K at the LIG compared to the PI period. Applying this Arctic-wide ΔSSAT and its modelled relationship to ΔSIA, results in a similar estimate of LIG sea ice reduction of 4.1±1.2×106 km2. These LIG climatological minimum SIA of 1.3 to 1.5×106 km2 are close to the definition of a summer ice-free Arctic, which is a maximum sea ice extent of less than 1×106 km2. The results of this study thus suggest that the Arctic likely experienced a mixture of ice-free and near-ice-free summers during the LIG.