Summer Arctic Sea Ice Research Articles

Comparing elevation and backscatter retrievals from CryoSat-2 and ICESat-2 over Arctic summer sea ice

Abstract. The CryoSat-2 radar altimeter and ICESat-2 laser altimeter can provide complementary measurements of the freeboard and thickness of Arctic sea ice. However, both sensors face significant challenges for accurately measuring the ice freeboard when the sea ice is melting in summer months. Here, we used crossover points between CryoSat-2 and ICESat-2 to compare elevation retrievals over summer sea ice between 2018–2021. We focused on the electromagnetic (EM) bias documented in CryoSat-2 measurements, associated with surface melt ponds over summer sea ice which cause the radar altimeter to underestimate elevation. The laser altimeter of ICESat-2 is not susceptible to this bias but has other biases associated with melt ponds. So, we compared the elevation difference and reflectance statistics between the two satellites. We found that CryoSat-2 underestimated elevation compared to ICESat-2 by a median difference of 2.4 cm and by a median absolute deviation of 5.3 cm, while the differences between individual ICESat-2 beams and CryoSat-2 ranged between 1–3.5 cm. Spatial and temporal patterns of the bias were compared to surface roughness information derived from the ICESat-2 elevation data, the ICESat-2 photon rate (surface reflectivity), the CryoSat-2 backscatter, and the melt pond fraction derived from Sentinel-3 Ocean and Land Color Instrument (OLCI) data. We found good agreement between theoretical predictions of the CryoSat-2 EM melt pond bias and our new observations; however, at typical roughness <0.1 m the experimentally measured bias was larger (5–10 cm) compared to biases resulting from the theoretical simulations (0–5 cm). This intercomparison will be valuable for interpreting and improving the summer sea ice freeboard retrievals from both altimeters.

Are thunderstorms linked to the rapid Sea ice loss in the Arctic?

Sea ice in the Arctic grows during the winter and retreats in the summer. The highly reflective white surface of sea ice reflects solar energy, cooling the planet. However, when it melts, the darker ocean absorbs more solar radiation, reinforcing the cycle of melting sea ice. Since sea ice plays a critical role in regulating Earth's climate, changes in sea ice may influence global weather patterns and ocean circulations. In addition to the rise in greenhouse gases in the Arctic, upper tropospheric water vapor (UTWV) or the specific humidity (SH) is also increasing, while acting as an additional greenhouse gas trapping in heat released from the Earth's surface. While annual greenhouse gas concentrations in the Arctic are increasing rather smoothly over time, the interannual variability in sea ice is shown here to be linked to the variability of UTWV at 400 hPa in the Arctic. We propose that increasing thunderstorm activity in the Arctic in the last decade is increasing the water vapor in the upper troposphere, partially explaining the interannual variability, and long term decrease, in the Arctic summer sea ice extent. Both the temporal and spatial analysis between UTWV and Sea Ice changes show that the decline of the summer sea ice cover in the Arctic may be linked to the increasing thunderstorm activity in the Arctic in the last decades.

When will Arctic sea ice disappear? Projections of area, extent, thickness, and volume

Rapidly diminishing Arctic summer sea ice is a strong signal of the pace of global climate change. We provide point, interval, and density forecasts for four measures of Arctic sea ice: area, extent, thickness, and volume. Importantly, we enforce the joint constraint that these measures must simultaneously arrive at an ice-free Arctic. We apply this constrained joint forecast procedure to models relating sea ice to atmospheric carbon dioxide concentration and models relating sea ice directly to time. The resulting “carbon-trend” and “time-trend” projections are mutually consistent and predict a nearly ice-free summer Arctic Ocean by the mid-2030s with an 80% probability. Moreover, the carbon-trend projections show that global adoption of a lower carbon path would likely delay the arrival of a seasonally ice-free Arctic by only a few years.

Concentrations and controls of dissolved inorganic carbon in Arctic summer sea ice and adjacent surface seawaters

The carbonate chemistry of sea ice plays a critical role in global ocean carbon cycles, particularly in polar regions which are subject to significant climate change-induced sea ice variation. However, less is known about the interaction of carbonate system between sea ice and its adjacent seawaters due to sparse sampling and disparities in reported results. Here we provide an insight into this issue by collecting and measuring dissolved inorganic carbon (DIC) and associated environmental parameters in Arctic sea ice during a cruise in the summer of 2014. Our observations show that DIC in Arctic summer sea ice has a mean concentration of 463.3 ± 213.0 μmol/kg and appears to be controlled mainly by the fraction of brine water in the ice. The low Chl a and nutrients content in sea ice indicate minor contribution of biological uptake to sea-ice DIC in the western Arctic Ocean. The DIC concentration in surface water (<100 m depth) decreased from a mean of 2108.3 ± 45.4 μmol/kg in 1994 to a mean of 2052.4 ± 98.6 μmol/kg in 2014, due to the enhanced sea ice melting that dilutes the DIC concentrations of surrounding seawaters.

Pacific Water impacts the burial of black and total organic carbon on the Chukchi Sea shelf, Arctic Ocean

The Arctic shelf is an important carbon reservoir, especially the Chukchi Sea, which plays a vital role in the biogeochemical processes of polar carbon cycles. In this study, we measured the contents of black carbon (BC) and total organic carbon (TOC) in a sediment core of the Chukchi Sea shelf, to evaluate the controlling factors of distribution and burial of BC and TOC. Our results show that the distribution of TOC and BC was strongly influenced by the Pacific Water (PW) inflow, resulting in nearly synchronous change since the early Holocene. The early Holocene (∼9.9 to 8.0 cal kyr BP) was characterized by the minimum of TOC, total nitrogen (TN), and BC, and the most depleted δ13CTOC and δ13CBC values throughout the Holocene, which indicate low primary productivity and low BC supplies under the weak PW flux. The carbon (TOC and BC) burial on the Chukchi Sea shelf was significantly enhanced during the middle Holocene (8.0–4.0 cal kyr BP) due to the rapid increase in PW flux. Since 4.0 cal kyr BP, PW inflow is stable and active, which enables sea ice extent to modulate the stratigraphic variations of BC. In particular, an increase in summer Arctic sea ice during this period may enhance ice-rafted debris and terrestrial carbon supply by promoting erosion of coastal peat soils and permafrost. Our results suggest that PW inflow is the first-order factor controlling Arctic carbon burial during the Holocene, while insolation-induced sea ice increase started playing a role when the PW inflow is active and stable during the late Holocene.

Reducing the Spring Barrier in Predicting Summer Arctic Sea Ice Concentration

AbstractThe predictive skill of summer sea ice concentration (SIC) in the Arctic presents a steep decline when initialized before June, which is the so‐called spring predictability barrier for Arctic sea ice. This study explores the potential influence of surface heat flux, cloud and water vapor anomalies on monthly to seasonal predictions of Arctic SIC anomalies. The results show an enhancement in skill predicting Arctic September SIC in the models that use surface fluxes, clouds, or water vapor in combination with SIC and surface sea temperature as predictors when initialized in boreal spring. This result shows the potential to reduce the spring barrier for Arctic SIC predictions by including the surface heat budget. The enhanced predictive skill can be very likely linked to the improved representation of the thermodynamics associated with water vapor and cloudiness anomalies in spring.

Temporal evolution of under-ice meltwater layers and false bottoms and their impact on summer Arctic sea ice mass balance

Low-salinity meltwater from Arctic sea ice and its snow cover accumulates and creates under-ice meltwater layers below sea ice. These meltwater layers can result in the formation of new ice layers, or false bottoms, at the interface of this low-salinity meltwater and colder seawater. As part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), we used a combination of sea ice coring, temperature profiles from thermistor strings and underwater multibeam sonar surveys with a remotely operated vehicle (ROV) to study the areal coverage and temporal evolution of under-ice meltwater layers and false bottoms during the summer melt season from mid-June until late July. ROV surveys indicated that the areal coverage of false bottoms for a part of the MOSAiC Central Observatory (350 by 200 m2) was 21%. Presence of false bottoms reduced bottom ice melt by 7–8% due to the local decrease in the ocean heat flux, which can be described by a thermodynamic model. Under-ice meltwater layer thickness was larger below first-year ice and thinner below thicker second-year ice. We also found that thick ice and ridge keels confined the areas in which under-ice meltwater accumulated, preventing its mixing with underlying seawater. While a thermodynamic model could reproduce false bottom growth and melt, it could not describe the observed bottom melt rates of the ice above false bottoms. We also show that the evolution of under-ice meltwater-layer salinity below first-year ice is linked to brine flushing from the above sea ice and accumulating in the meltwater layer above the false bottom. The results of this study aid in estimating the contribution of under-ice meltwater layers and false bottoms to the mass balance and salt budget for Arctic summer sea ice.

Sea Ice Melt Pond Fraction Derived From Sentinel‐2 Data: Along the MOSAiC Drift and Arctic‐Wide

AbstractMelt ponds forming on Arctic sea ice in summer significantly reduce the surface albedo and impact the heat and mass balance of the sea ice. Therefore, their areal coverage, which can undergo rapid change, is crucial to monitor. We present a revised method to extract melt pond fraction (MPF) from Sentinel‐2 satellite imagery, which is evaluated by MPF products from higher‐resolution satellite and helicopter‐borne imagery. The analysis of melt pond evolution during the MOSAiC campaign in summer 2020, shows a split of the Central Observatory (CO) into a level ice and a highly deformed ice part, the latter of which exhibits exceptional early melt pond formation compared to the vicinity. Average CO MPFs are 17% before and 23% after the major drainage. Arctic‐wide analysis of MPF for years 2017–2021 shows a consistent seasonal cycle in all regions and years.

Separation of Atmospheric Circulation Patterns Governing Regional Variability of Arctic Sea Ice in Summer

Separation of Atmospheric Circulation Patterns Governing Regional Variability of Arctic Sea Ice in Summer

The results of flexural and uniaxial compressive tests of summer Arctic sea ice

The results of flexural and uniaxial compressive tests of summer Arctic sea ice

Semantic segmentation of Arctic Sea ice in summer from remote sensing satellite images based on BAU-NET

To effectively solve the accurate identification of gray ice, melt ponds water, floe, brash ice, and thin ice in the melting state of the Arctic Sea ice during summer, we propose adding a batch normalization layer and adaptive moment estimation optimizer of a U-NET (BAU-NET) method for Arctic Sea ice semantic segmentation in summer from remote sensing satellite optical images. The U-NET network structure is optimized to 18 convolution layers, and a batch normalization layer and a nonlinear activation function rectified linear unit are added behind each convolution layer. Then the hyper-parameters of the network structure are adjusted. The cross-entropy loss function based on SOFTMAX and L2 regularization are used in training the model, and the adaptive moment estimation optimizer is used for iterative training until the error convergence. The experimental results show that the accuracy, precision, recall, and F1 score of sea ice extraction results reaches more than 97.26%. Compared with the DeepLabv3 and U-Net methods, the sea ice prediction time efficiency is improved by 90.99s and 1.57s, respectively, and the accuracy is improved by 6.59% and 8.05%, respectively, which indicate that the sea ice prediction time efficiency and accuracy of the BAU-NET method are significantly improved.

Strengthened relationship between sea ice in East Siberian Sea and midsummer rainfall in Northeast China

Arctic sea ice displays the high rates of decay during summer-autumn. Previous studies have revealed the impact of autumn Arctic sea ice on local and remote atmospheric circulation. Few attentions have been paid on the relationship between summer Arctic sea ice and climate variation at Eurasia. This study identifies a strengthened relationship between midsummer rainfall at Northeast China (NEC) and simultaneous sea ice area (SIA) in East Siberian Sea after the 1990s. The NEC’s rainfall shows a significant positive correlation with the SIA during 1994–2016, whereas the relationship is insignificant during 1961–1983. The strengthening of the relationship is attributed to the western elongation of background circulation at the North Pacific and the increased interannual variability of the SIA after the 1990s. The former facilitates the western extension of the SIAI-associated circulation over the Central North Pacific. The enlarged amplitudes of sea ice induce surface heat fluxes in situ, and then it leads to stronger meridional temperature gradient anomalies and intensified interaction between synoptic-scale eddies and mean flow over the North Pacific. These conditions jointly contribute to stronger and western elongation of circulation over the Central North Pacific during 1994–2016. Accordingly, the SIA has an intimate connection with NEC’s rainfall though the modulation of moisture transport and vertical movement.

Nudging Observed Winds in the Arctic to Quantify Associated Sea Ice Loss from 1979 to 2020

Abstract Over the past decades, Arctic climate has exhibited significant changes characterized by strong pan-Arctic warming and a large-scale wind shift trending toward an anticyclonic anomaly centered over Greenland and the Arctic Ocean. Recent work has suggested that this wind change is able to warm the Arctic atmosphere and melt sea ice through dynamically driven warming, moistening, and ice drift effects. However, previous examination of this linkage lacks a capability to fully consider the complex nature of the sea ice response to the wind change. In this study, we perform a more rigorous test of this idea by using a coupled high-resolution modeling framework with observed winds nudged over the Arctic that allows for a comparison of these wind-induced effects with observations and simulated effects forced by anthropogenic forcing. Our nudging simulation can well capture observed variability of atmospheric temperature, sea ice, and the radiation balance during the Arctic summer and appears to simulate around 30% of Arctic warming and sea ice melting over the whole period (1979–2020) and more than 50% over the period 2000–12, which is the fastest Arctic warming decade in the satellite era. In particular, in the summer of 2020, a similar wind pattern reemerged to induce the second-lowest sea ice extent since 1979, suggesting that large-scale wind changes in the Arctic are essential in shaping Arctic climate on interannual and interdecadal time scales and may be critical to determine Arctic climate variability in the coming decades. Significance Statement This work conducts a set of new CESM1 nudging simulations to quantify the impact of the observed evolution of large-scale high-latitude atmospheric winds on Arctic climate variability over the past four decades. Variations in climate parameters, including sea ice, radiation, and atmospheric temperatures are well replicated in the model when observed winds are imposed in the Arctic. By investigating simulated sea ice melting processes in the simulation, we illustrate and estimate how large-scale winds in the Arctic help melt sea ice in summer. The nudging method has the potential to make Arctic climate attribution more tangible and to unravel the important physical processes underlying recent abrupt climate change in the Arctic.

An Optimal Atmospheric Circulation Mode in the Arctic Favoring Strong Summertime Sea Ice Melting and Ice–Albedo Feedback

Abstract The rapid decline of summer Arctic sea ice over the past few decades has been driven by a combination of increasing greenhouse gases and internal variability of the climate system. However, uncertainties remain regarding spatial and temporal characteristics of the optimal internal atmospheric mode that most favors summer sea ice melting on low-frequency time scales. To pinpoint this mode, we conduct a suite of simulations in which atmospheric circulation is constrained by nudging tropospheric Arctic (60°–90°N) winds within the Community Earth System Model, version 1 (CESM1), to those from reanalysis. Each reanalysis year is repeated for over 10 model years using fixed greenhouse gas concentrations and the same initial conditions. Composites show the strongest September sea ice losses are closely preceded by a common June–August (JJA) barotropic anticyclonic circulation in the Arctic favoring shortwave absorption at the surface. Successive years of strong wind-driven melting also enhance declines in Arctic sea ice through enhancement of the ice–albedo feedback, reaching a quasi-equilibrium response after repeated wind forcing for over 5–6 years, as the effectiveness of the wind-driven ice–albedo feedback becomes saturated. Strong melting favored by a similar wind pattern as observations is detected in a long preindustrial simulation and 400-yr paleoclimate reanalysis, suggesting that a summer barotropic anticyclonic wind pattern represents the optimal internal atmospheric mode maximizing sea ice melting in both the model and natural world over a range of time scales. Considering strong contributions of this mode to changes in Arctic climate, a better understanding of its origin and maintenance is vital to improving future projections of Arctic sea ice.

Simulating the Impact of the Sustained Melting Arctic on the Global Container Sea–Rail Intermodal Shipping

Global warming trends and the rapid reduction of summer Arctic sea ice extent have increased the feasibility of transarctic transport. How the process of glacier melting affects the existing containerized sea–rail shipping network and container flow assignment has become a challenging economic and policy issue. This paper first examines the meteorological influences on glacier melting and the assignment of container flow over the existing sea–rail network. Then, a three-layer simulation framework is constructed, with the upper layer simulating glacier melting based on the raster grid, the middle layer combining a grid and topology analysis to simulate the evolution of the global sea–rail network and the lower layer establishing a concave cost network flow model to simulate the container flow assignment. Finally, we use MicroCity to achieve the dynamic optimization and simulation of global container flow assignment, solving the large-scale sea–rail shipping network traffic assignment problem. The simulation results show that the proposed model and solution algorithm are feasible and effective, revealing the variation of container flow assignment in the global sea–rail shipping network under different Arctic ice melting scenarios. For instance, in the summer of 2050, the Arctic routes will share the global container flows, resulting in a significant reduction of container flows in the Malacca Strait, Suez Canal and Panama Canal.

Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing

Abstract. Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 × 106 km2 of Earth's surface (31 % of the land area) each year, and is thus an important expression and driver of the Earth's climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (∼ −13 % per decade) as Arctic summer sea ice. More than one-sixth of the world's population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth's cold regions' ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of water stored as snow on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations are not able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high-socio-economic-value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-band synthetic aperture radar (SAR) for global monitoring of SWE. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimeter-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modeling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, density, and layering. We describe radar interactions with snow-covered landscapes, the small but rapidly growing number of field datasets used to evaluate retrieval algorithms, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and application communities on progress made in recent decades and sets the stage for a new era in SWE remote sensing from SAR measurements.

Arctic summer sea ice phenology including ponding from 1982 to 2017

Arctic summer sea ice phenology including ponding from 1982 to 2017

Comparison between Large-Scale Circulation Anomalies Associated with Interannual Variability and Decadal Change of Summer Arctic Sea Ice

Abstract Arctic sea ice in summer shows both interannual and long-term variations, and atmospheric circulation anomalies are known to play an important role. This study compares the summertime large-scale circulation anomalies associated with Arctic sea ice on interannual and decadal time scales. The results indicate that the circulation anomalies associated with decreased sea ice on an interannual time scale are characterized by a barotropic anticyclonic anomaly in the central Arctic, and the thermodynamic process is important for the circulation–sea ice coupling. On one hand, the descending adiabatic warming in low levels associated with the central Arctic anticyclonic anomaly leads to decreased sea ice by enhancing the downwelling longwave radiation. On the other hand, the anticyclonic anomaly also induces more moisture in low levels. The enhanced moisture and temperature (coupled with each other) further favor the reduction of sea ice by emitting more downwelling longwave radiation. By contrast, associated with the decadal sea ice decline, there is an anticyclonic anomaly over Greenland and a cyclonic anomaly over northern Siberia, and the wind-driven sea ice drift dominates the sea ice decline. The transpolar circulation anomalies between the anticyclonic and cyclonic anomalies promote transport of the ice away from the coasts of Siberia toward the North Pole, and drive the ice out of the Arctic Ocean to the North Atlantic. These circulation anomalies also induce sea ice decline through thermodynamic process, but it is not as significant as that on an interannual time scale.

Quantifying false bottoms and under-ice meltwater layers beneath Arctic summer sea ice with fine-scale observations

During the Arctic melt season, relatively fresh meltwater layers can accumulate under sea ice as a result of snow and ice melt, far from terrestrial freshwater inputs. Such under-ice meltwater layers, sometimes referred to as under-ice melt ponds, have been suggested to play a role in the summer sea ice mass balance both by isolating the sea ice from saltier water below, and by driving formation of ‘false bottoms’ below the sea ice. Such layers form at the interface of the fresher under-ice layer and the colder, saltier seawater below. During the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition in the Central Arctic, we observed the presence of under-ice meltwater layers and false bottoms throughout July 2020 at primarily first-year ice locations. Here, we examine the distribution, prevalence, and drivers of under-ice ponds and the resulting false bottoms during this period. The average thickness of observed false bottoms and freshwater equivalent of under-ice meltwater layers was 0.08 m, with false bottom ice comprised of 74–87% FYI melt and 13–26% snow melt. Additionally, we explore these results using a 1D model to understand the role of dynamic influences on decoupling the ice from the seawater below. The model comparison suggests that the ice-ocean friction velocity was likely exceptionally low, with implications for air-ice-ocean momentum transfer. Overall, the prevalence of false bottoms was similar to or higher than noted during other observational campaigns, indicating that these features may in fact be common in the Arctic during the melt season. These results have implications for the broader ice-ocean system, as under-ice meltwater layers and false bottoms provide a source of ice growth during the melt season, potentially reduce fluxes between the ice and the ocean, isolate sea ice primary producers from pelagic nutrient sources, and may alter light transmission to the ocean below.

New insight into the influence of the Greenland high on summer Arctic sea ice

The Greenland high (GL-high) coincides with a local center of action of the summer North Atlantic Oscillation and is known to have significant influence on Greenland ice sheet melting and summer Arctic sea ice. However, the mechanism behind the influence on regional Arctic sea ice is not yet clear. In this study, using reanalysis datasets and satellite observations, the influence of the GL-high in early summer on Arctic sea ice variability, and the mechanism behind it, are investigated. In response to an intensified GL-high, sea ice over the Beaufort Sea shows significant decline in both concentration and thickness from June through September. This decline in sea ice is primarily due to thermodynamic and mechanical redistribution processes. Firstly, the intensified GL-high increases subsidence over the Canadian Basin, leading to an increase in surface air temperature by adiabatic heating, and a substantial decrease in cloud cover and thus increased downward shortwave radiation. Secondly, the intensified GL-high increases easterly wind frequency and wind speed over the Beaufort Sea, pushing sea ice over the Canadian Basin away from the coastlines. Both processes contribute to an increase in open water areas, amplifying ice–albedo feedback and leading to sea ice decline. The mechanism identified here differs from previous studies that focused on northward moisture and heat transport and the associated increase in downward longwave radiation over the Arctic. The impact of the GL-high on the regional sea ice (also Arctic sea ice extent) can persist from June into fall, providing an important source for seasonal prediction of Arctic sea ice. The GL-high has an upward trend and reached a record high in 2012 that coincided with a record minimum summer Arctic sea ice extent, and has strong implications for summer Arctic sea ice changes.