Sea Ice Distribution Research Articles

The influence of the spatial distribution of leads and ice floes on the atmospheric boundary layer over fragmented sea ice

ABSTRACTThe response of the atmospheric boundary layer (ABL) to subgrid-scale variations of sea ice properties and fracturing is poorly understood and not taken into account in mesoscale Numerical Weather Prediction (NWP) model parametrizations. In this paper we analyze three-dimensional air circulation within the ABL over fragmented sea ice. A series of idealized high-resolution simulations with the Weather Research and Forecasting (WRF) model is performed for several spatial distributions of ice floes and leads for two values of sea ice concentration (0.5 and 0.9) and several ambient wind speed profiles. The results show that the convective circulation within the ABL is sensitive to the subgrid-scale spatial distribution of sea ice. Considerable variability of several domain-averaged quantities – cloud liquid water content, surface turbulent heat flux (THF) – is found for different arrangements of floes. Moreover, the organized structure of air circulation leads to spatial covariance of variables characterizing the ABL. Based on the example of THF, it is demonstrated that this covariance may lead to substantial errors when THF values are estimated from area-averaged quantities, as it is done in mesoscale NWP models. This suggests the need for developing suitable parametrizations of ABL effects related to subgrid-scale sea ice features for these models.

Automatic Mapping Technique of Sea Ice in the Coastal Waters of the Arctic Ocean Using Sentinel-1 Data

Hong, D.-B.; Bae, J.-J., and Yang, C.-S., 2018. Automatic mapping technique of sea ice in the coastal waters of the Arctic Ocean using Sentinel-1 data. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 556–560. Coconut Creek (Florida), ISSN 0749-0208.The sea ice information such as ice extent, area, concentration, and thickness has been widely used for analyses of sea level, weather, and climate changes in the Polar Regions. Passive microwave sensing of sea ice traditionally has been applied to the Arctic Ocean for a shipping route support in spite of its low-spatial resolution. C-band Sentinel-1 (constellation of two satellites, Sentinel-1A and Sentinel-1B) synthetic aperture radar (SAR) is considered as one of the effective satellites because it provides an improvement in revisit time, and offers higher resolution and dual polarization (HH and HV). In this study, the Sentinel-1 sea ice mapping system was developed to acquire data automatically for the region of interest in the Arctic coastal region and to map sea ice areas extracted by using the sea ice discrimination algorithm. The system including a data acquisition process can make a sea ice product in 13 minutes. To intuitively understand the distribution of sea ice for safe navigation in coastal waters, the result can be visualized in a KML file that facilitates interfacing with other systems.

Microalgal photophysiology and macronutrient distribution in summer sea ice in the Amundsen and Ross Seas, Antarctica.

Our study addresses how environmental variables, such as macronutrients concentrations, snow cover, carbonate chemistry and salinity affect the photophysiology and biomass of Antarctic sea-ice algae. We have measured vertical profiles of inorganic macronutrients (phosphate, nitrite + nitrate and silicic acid) in summer sea ice and photophysiology of ice algal assemblages in the poorly studied Amundsen and Ross Seas sectors of the Southern Ocean. Brine-scaled bacterial abundance, chl a and macronutrient concentrations were often high in the ice and positively correlated with each other. Analysis of photosystem II rapid light curves showed that microalgal cells in samples with high phosphate and nitrite + nitrate concentrations had reduced maximum relative electron transport rate and photosynthetic efficiency. We also observed strong couplings of PSII parameters to snow depth, ice thickness and brine salinity, which highlights a wide range of photoacclimation in Antarctic pack-ice algae. It is likely that the pack ice was in a post-bloom situation during the late sea-ice season, with low photosynthetic efficiency and a high degree of nutrient accumulation occurring in the ice. In order to predict how key biogeochemical processes are affected by future changes in sea ice cover, such as in situ photosynthesis and nutrient cycling, we need to understand how physicochemical properties of sea ice affect the microbial community. Our results support existing hypothesis about sea-ice algal photophysiology, and provide additional observations on high nutrient concentrations in sea ice that could influence the planktonic communities as the ice is retreating.

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

Local climatology of fast ice in McMurdo Sound, Antarctica

AbstractFast ice plays important physical and ecological roles: as a barrier to wind, waves and radiation, as both barrier and safe resting place for air-breathing animals, and as substrate for microbial communities. While sea ice has been monitored for decades using satellite imagery, high-resolution imagery sufficient to distinguish fast ice from mobile pack ice extends only back toc.2000. Fast ice trends may differ from previously identified changes in regional sea ice distributions. To investigate effects of climate and human activities on fast ice dynamics in McMurdo Sound, Ross Sea, the sea and fast ice seasonal events (1978–2015), ice thicknesses and temperatures (1986–2014), wind velocities (1973–2015) and dates that an icebreaker annually opens a channel to McMurdo Station (1956–2015) are reported. A significant relationship exists between sea ice concentration and fast ice extent in the Sound. While fast/sea ice retreat dates have not changed, fast/sea ice reaches a minimum later and begins to advance earlier, in partial agreement with changes in Ross Sea regional pack ice dynamics. Fast ice minimum extent within McMurdo Sound is significantly correlated with icebreaker arrival date as well as wind velocity. The potential impacts of changes in fast ice climatology on the local marine ecosystem are discussed.

Spatio-temporal Variation of Arctic Sea Ice in Summer from 2003 to 2013

The variation in Arctic sea ice has significant implications for climate change due to its huge influence on the global heat balance. In this study, we quantified the spatio-temporal variation of Arctic sea ice distribution using Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice concentration data from 2003 to 2013. The results found that, over this period, the extent of sea ice reached a maximum in 2004, whereas in 2007 and 2012, the extent of summer sea ice was at a minimum. It declined continuously from 2010 to 2012, falling to its lowest level since 2003. Sea-ice extent fell continuously each summer between July and mid-September before increasing again. It decreased most rapidly in September, and the summer reduction rate was 1.35 × 105 km2/yr, twice as fast as the rate between1979 and 2006, and slightly slower than from 2002 to 2011. Area with >90% sea-ice concentration decreased by 1.32 × 107 km2/yr, while locations with >50% sea-ice concentration, which were mainly covered by perennial ice, were near the North Pole, the Beaufort Sea, and the Queen Elizabeth Islands. Perennial Arctic ice decreased at a rate of 1.54 × 105 km2 annually over the past 11 years.

Influence of Okhotsk Sea Ice Distribution on a Snowstorm Associated with an Explosive Cyclone in Hokkaido, Japan

Influence of Okhotsk Sea Ice Distribution on a Snowstorm Associated with an Explosive Cyclone in Hokkaido, Japan

Delta progradation in Greenland driven by increasing glacial mass loss.

Climate changes are pronounced in Arctic regions and increase the vulnerability of the Arctic coastal zone. For example, increases in melting of the Greenland Ice Sheet and reductions in sea ice and permafrost distribution are likely to alter coastal morphodynamics. The deltas of Greenland are largely unaffected by human activity, but increased freshwater runoff and sediment fluxes may increase the size of the deltas, whereas increased wave activity in ice-free periods could reduce their size, with the net impact being unclear until now. Here we show that southwestern Greenland deltas were largely stable from the 1940s to 1980s, but prograded (that is, sediment deposition extended the delta into the sea) in a warming Arctic from the 1980s to 2010s. Our results are based on the areal changes of 121 deltas since the 1940s, assessed using newly discovered aerial photographs and remotely sensed imagery. We find that delta progradation was driven by high freshwater runoff from the Greenland Ice Sheet coinciding with periods of open water. Progradation was controlled by the local initial environmental conditions (that is, accumulated air temperatures above 0 °C per year, freshwater runoff and sea ice in the 1980s) rather than by local changes in these conditions from the 1980s to 2010s at each delta. This is in contrast to a dominantly eroding trend of Arctic sedimentary coasts along the coastal plains of Alaska, Siberia and western Canada, and to the spatially variable patterns of erosion and accretion along the large deltas of the main rivers in the Arctic. Our results improve the understanding of Arctic coastal evolution in a changing climate, and reveal the impacts on coastal areas of increasing ice mass loss and the associated freshwater runoff and lengthening of open-water periods.

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

Increasing concern about the impacts of climate change on ecosystems is prompting ecologists and ecosystem managers to seek reliable projections of physical drivers of change. The use of global climate models in ecology is growing, although drawing ecologically meaningful conclusions can be problematic. The expertise required to access and interpret output from climate and earth system models is hampering progress in utilizing them most effectively to determine the wider implications of climate change. To address this issue, we present a joint approach between climate scientists and ecologists that explores key challenges and opportunities for progress. As an exemplar, our focus is the Southern Ocean, notable for significant change with global implications, and on sea ice, given its crucial role in this dynamic ecosystem. We combined perspectives to evaluate the representation of sea ice in global climate models. With an emphasis on ecologically-relevant criteria (sea ice extent and seasonality) we selected a subset of eight models that reliably reproduce extant sea ice distributions. While the model subset shows a similar mean change to the full ensemble in sea ice extent (approximately 50% decline in winter and 30% decline in summer), there is a marked reduction in the range. This improved the precision of projected future sea ice distributions by approximately one third, and means they are more amenable to ecological interpretation. We conclude that careful multidisciplinary evaluation of climate models, in conjunction with ongoing modeling advances, should form an integral part of utilizing model output.

GEOS-5 seasonal forecast system

Ensembles of numerical forecasts based on perturbed initial conditions have long been used to improve estimates of both weather and climate forecasts. The Goddard Earth Observing System (GEOS) Atmosphere–Ocean General Circulation Model, Version 5 (GEOS-5 AOGCM) Seasonal-to-Interannual Forecast System has been used routinely by the GMAO since 2008, the current version since 2012. A coupled reanalysis starting in 1980 provides the initial conditions for the 9-month experimental forecasts. Once a month, sea surface temperature from a suite of 11 ensemble forecasts is contributed to the North American Multi-Model Ensemble (NMME) consensus project, which compares and distributes seasonal forecasts of ENSO events. Since June 2013, GEOS-5 forecasts of the Arctic sea-ice distribution were provided to the Sea-Ice Outlook project. The seasonal forecast output data includes surface fields, atmospheric and ocean fields, as well as sea ice thickness and area, and soil moisture variables. The current paper aims to document the characteristics of the GEOS-5 seasonal forecast system and to highlight forecast biases and skills of selected variables (sea surface temperature, air temperature at 2 m, precipitation and sea ice extent) to be used as a benchmark for the future GMAO seasonal forecast systems and to facilitate comparison with other global seasonal forecast systems.

Holocene dynamics in the Bering Strait inflow to the Arctic and the Beaufort Gyre circulation based on sedimentary records from the Chukchi Sea

Abstract. The Beaufort Gyre (BG) and the Bering Strait inflow (BSI) are important elements of the Arctic Ocean circulation system and major controls on the distribution of Arctic sea ice. We report records of the quartz ∕ feldspar and chlorite ∕ illite ratios in three sediment cores from the northern Chukchi Sea, providing insights into the long-term dynamics of the BG circulation and the BSI during the Holocene. The quartz ∕ feldspar ratio, interpreted as a proxy of the BG strength, gradually decreased during the Holocene, suggesting a long-term decline in the BG strength, consistent with an orbitally controlled decrease in summer insolation. We propose that the BG rotation weakened as a result of the increasing stability of sea-ice cover at the margins of the Canada Basin, driven by decreasing insolation. Millennial to multi-centennial variability in the quartz ∕ feldspar ratio (the BG circulation) is consistent with fluctuations in solar irradiance, suggesting that solar activity affected the BG strength on these timescales. The BSI approximation by the chlorite ∕ illite record, despite a considerable geographic variability, consistently shows intensified flow from the Bering Sea to the Arctic during the middle Holocene, which is attributed primarily to the effect of higher atmospheric pressure over the Aleutian Basin. The intensified BSI was associated with decrease in sea-ice concentrations and increase in marine production, as indicated by biomarker concentrations, suggesting a major influence of the BSI on sea-ice and biological conditions in the Chukchi Sea. Multi-century to millennial fluctuations, presumably controlled by solar activity, were also identified in a proxy-based BSI record characterized by the highest age resolution.

Ecosystem variability in the offshore northeastern Chukchi Sea

Understanding influences of cumulative effects from multiple stressors in marine ecosystems requires an understanding of the sources for and scales of variability. A multidisciplinary ecosystem study in the offshore northeastern Chukchi Sea during 2008–2013 investigated the variability of the study area’s two adjacent sub-ecosystems: a pelagic system influenced by interannual and/or seasonal temporal variation at large, oceanographic (regional) scales, and a benthic-associated system more influenced by small-scale spatial variations. Variability in zooplankton communities reflected interannual oceanographic differences in waters advected northward from the Bering Sea, whereas variation in benthic communities was associated with seafloor and bottom-water characteristics. Variations in the planktivorous seabird community were correlated with prey distributions, whereas interaction effects in ANOVA for walruses were related to declines of sea-ice. Long-term shifts in seabird distributions were also related to changes in sea-ice distributions that led to more open water. Although characteristics of the lower trophic-level animals within sub-ecosystems result from oceanographic variations and interactions with seafloor topography, distributions of apex predators were related to sea-ice as a feeding platform (walruses) or to its absence (i.e., open water) for feeding (seabirds). The stability of prey resources appears to be a key factor in mediating predator interactions with other ocean characteristics. Seabirds reliant on highly-variable zooplankton prey show long-term changes as open water increases, whereas walruses taking benthic prey in biomass hotspots respond to sea-ice changes in the short-term. A better understanding of how variability scales up from prey to predators and how prey resource stability (including how critical prey respond to environmental changes over space and time) might be altered by climate and anthropogenic stressors is essential to predicting the future state of both the Chukchi and other arctic systems.

Sea‐ice loss boosts visual search: fish foraging and changing pelagic interactions in polar oceans

Light is a central driver of biological processes and systems. Receding sea ice changes the lightscape of high-latitude oceans and more light will penetrate into the sea. This affects bottom-up control through primary productivity and top-down control through vision-based foraging. We model effects of sea-ice shading on visual search to develop a mechanistic understanding of how climate-driven sea-ice retreat affects predator-prey interactions. We adapt a prey encounter model for ice-covered waters, where prey-detection performance of planktivorous fish depends on the light cycle. We use hindcast sea-ice concentrations (past 35years) and compare with a future no-ice scenario to project visual range along two south-north transects with different sea-ice distributions and seasonality, one through the Bering Sea and one through the Barents Sea. The transect approach captures the transition from sub-Arctic to Arctic ecosystems and allows for comparison of latitudinal differences between longitudes. We find that past sea-ice retreat has increased visual search at a rate of 2.7% to 4.2% per decade from the long-term mean; and for high latitudes, we predict a 16-fold increase in clearance rate. Top-down control is therefore predicted to intensify. Ecological and evolutionary consequences for polar marine communities and energy flows would follow, possibly also as tipping points and regime shifts. We expect species distributions to track the receding ice-edge, and in particular expect species with large migratory capacity to make foraging forays into high-latitude oceans. However, the extreme seasonality in photoperiod of high-latitude oceans may counteract such shifts and rather act as a zoogeographical filter limiting poleward range expansion. The provided mechanistic insights are relevant for pelagic ecosystems globally, including lakes where shifted distributions are seldom possible but where predator-prey consequences would be much related. As part of the discussion on photoperiodic implications for high-latitude range shifts, we provide a short review of studies linking physical drivers to latitudinal extent.

Antarctic sea ice region as a source of biogenic organic nitrogen in aerosols

Climate warming affects the development and distribution of sea ice, but at present the evidence of polar ecosystem feedbacks on climate through changes in the atmosphere is sparse. By means of synergistic atmospheric and oceanic measurements in the Southern Ocean near Antarctica, we present evidence that the microbiota of sea ice and sea ice-influenced ocean are a previously unknown significant source of atmospheric organic nitrogen, including low molecular weight alkyl-amines. Given the keystone role of nitrogen compounds in aerosol formation, growth and neutralization, our findings call for greater chemical and source diversity in the modelling efforts linking the marine ecosystem to aerosol-mediated climate effects in the Southern Ocean.

Arctic decadal variability in a warming world

AbstractNatural decadal variability of surface air temperature might obscure Arctic temperature trends induced by anthropogenic forcing. It is therefore imperative to know how Arctic decadal variability (ADV) will change as the climate warms. In this study, we evaluate ADV characteristics in three equilibrium climates with present‐day, double, and quadrupled atmospheric CO2 forcing. The dominant region of variability, which is located over the Barents and Greenland Sea at present, shifts to the central Arctic and Siberian regions as the climate warms. The maximum variability in sea ice cover and surface air temperature occurs in the CO2 doubling climate when sea ice becomes more vulnerable to melt over vast stretches of the Arctic. Furthermore, the links between dominant atmospheric circulation modes and Arctic surface climate characteristics vary strongly with climate change. For instance, a positive Arctic Oscillation index is associated with a colder Arctic in warmer climates, instead of a warmer Arctic at present. Such changing relationships are partly related to the retreat of sea ice because altered wind patterns influence the sea ice distribution and hence the associated local surface fluxes. The atmospheric pressure distributions governing ADV and the associated large‐scale dynamics also change with climate warming. The changing character of the ADV shows that it is vital to consider (changes in) ADV when addressing Arctic warming in climate model projections.

Long-Distance Movement of a Female Polar Bear from Canada to Russia

Polar bears (Ursus maritimus) display fidelity to large geographic regions, and their movements are influenced by sea ice distribution. Polar bear subpopulations are moderately distinct from one another, and long-distance movements between subpopulations are rare. We describe and analyze the movements of a female polar bear tracked by satellite telemetry from spring 2009 for 798 days. This female traveled an exceptionally long distance (totaling 11 686 km) from the sea ice off the Yukon Territory, Canada (Southern Beaufort Sea subpopulation) to Wrangel Island, Russia (Chukchi Sea subpopulation). In comparison to other polar bears in this study, this bear traveled farther, moved faster, and had a much larger home range in the first year. Furthermore, the calculation of the home range size by two different methods demonstrated that the commonly used minimum convex polygon method overestimated the home range compared to the less biased Brownian bridge movement model. This female’s long-distance movement was unusual and provides additional evidence for gene flow between subpopulations. Monitoring polar bear movements is useful to track such events, which is especially important at present because sea ice loss due to climate change can affect subpopulation boundaries and influence management.

How does sea ice influence <i>δ</i><sup>18</sup>O of Arctic precipitation?

Abstract. This study investigates how variations in Arctic sea ice and sea surface conditions influence δ18O of present-day Arctic precipitation. This is done using the model isoCAM3, an isotope-equipped version of the National Center for Atmospheric Research Community Atmosphere Model version 3. Four sensitivity experiments and one control simulation are performed with prescribed sea surface temperature (SST) and sea ice. Each of the four experiments simulates the atmospheric and isotopic response to Arctic oceanic conditions for selected years after the beginning of the satellite era in 1979. Changes in sea ice extent and SSTs have different impacts in Greenland and the rest of the Arctic. The simulated changes in central Arctic sea ice do not influence δ18O of Greenland precipitation, only anomalies of Baffin Bay sea ice. However, this does not exclude the fact that simulations based on other sea ice and sea surface temperature distributions might yield changes in the δ18O of precipitation in Greenland. For the Arctic, δ18O of precipitation and water vapour is sensitive to local changes in sea ice and sea surface temperature and the changes in water vapour are surface based. Reduced sea ice extent yields more enriched isotope values, whereas increased sea ice extent yields more depleted isotope values. The distribution of the sea ice and sea surface conditions is found to be essential for the spatial distribution of the simulated changes in δ18O.

Concentrations and Size Distributions of Bacteria-Containing Particles over Oceans from China to the Arctic Ocean

During the third China Arctic Research Expedition (July–September 2008), size-resolved measurements of bacteria-containing particles (BCPs) in the marine boundary layer (MBL) air were conducted during a cruise through the East China Sea, the Yellow Sea, the Japan Sea, the Okhotsk Sea, the Bering Sea, the Chukchi Sea, and the Arctic Ocean. The concentrations of total airborne BCPs (TBCPs), non-salt tolerant airborne BCPs (NSBCPs), and salt tolerant airborne BCPs (SBCPs) varied from 29 to 955 CFU m−3 (CFU = Colony Forming Unit), 16 to 919 CFU m−3, and 4 to 276 CFU m−3, with an average value of 275, 182, and 92 CFU m−3, respectively. Although the SBCP concentrations were less than the NSBCP concentrations when averaged over all measurements, there are several cases where the reverse is true (e.g., in the high Arctic Ocean). During the cruise, the TBCP sizes were dominated by the diameter >4.7 μm fraction (accounted for 46.3% on average), while the fine fraction (diameter <2.1 μm) accounted for 27.8%. For NSBCPs and SBCPs, the coarse fraction also was the dominant fraction over most regions. The influence of local meteorological conditions on the abundance, size distributions, and species of airborne bacteria is discussed. Notably, in the atmosphere over the Arctic Ocean the abundance of airborne bacteria was apparently related to the distribution of sea ice. As cultivation based methodologies may underestimate the environmental bacterial communities, it is expected that the abundance of bacteria in the ambient air would be higher than that observed in this study. In order to distinguish different species of bacteria, molecular biological techniques (e.g., 16S rDNA analysis) are required for identification in future investigations.

Dominant Covarying Climate Signals in the Southern Ocean and Antarctic Sea Ice Influence during the Last Three Decades

A composite dataset (comprising geopotential height, sea surface temperature, zonal and meridional surface winds, precipitation, cloud cover, surface air temperature, latent plus sensible heat fluxes, and sea ice concentration) has been investigated with the aim of revealing the dominant time scales of variability from 1982 to 2013. Three covarying climate signals associated with variations in the sea ice distribution around Antarctica have been detected through the application of the multiple-taper method with singular value decomposition (MTM-SVD). Features of the established patterns of variation over the Southern Hemisphere extratropics have been identified in each of these three climate signals in the form of coupled or individual oscillations. The climate patterns considered here are the southern annular mode (SAM), the Pacific–South American (PSA) teleconnection, the semiannual oscillation (SAO), and the zonal wavenumber-3 (ZW3) mode. It is shown that most of the sea ice temporal variance is concentrated at the quasi-triennial scale resulting from the constructive superposition of the PSA and ZW3 patterns. In addition, the combination of the SAM and SAO patterns is found to promote the interannual sea ice variations underlying a general change in the Southern Ocean atmospheric and oceanic circulations. These two modes of variability are also found to be consistent with the occurrence of the positive SAM/negative PSA (SAM+/PSA−) or negative SAM/positive PSA (SAM−/PSA+) combinations, which could have favored the cooling of the sub-Antarctic region and important changes in the Antarctic sea ice distribution since 2000.

Automated parameter tuning applied to sea ice in a global climate model

This study investigates the hypothesis that a significant portion of spread in climate model projections of sea ice is due to poorly-constrained model parameters. New automated methods for optimization are applied to historical sea ice in a global coupled climate model (HadCM3) in order to calculate the combination of parameters required to reduce the difference between simulation and observations to within the range of model noise. The optimized parameters result in a simulated sea-ice time series which is more consistent with Arctic observations throughout the satellite record (1980-present), particularly in the September minimum, than the standard configuration of HadCM3. Divergence from observed Antarctic trends and mean regional sea ice distribution reflects broader structural uncertainty in the climate model. We also find that the optimized parameters do not cause adverse effects on the model climatology. This simple approach provides evidence for the contribution of parameter uncertainty to spread in sea ice extent trends and could be customized to investigate uncertainties in other climate variables.