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  1. Abstract

    The Arctic’s rapid sea ice decline may influence global weather patterns, making the understanding of Arctic weather variability (WV) vital for accurate weather forecasting and analyzing extreme weather events. Quantifying this WV and its impacts under human-induced climate change remains a challenge. Here we develop a complexity-based approach and discover a strong statistical correlation between intraseasonal WV in the Arctic and the Arctic Oscillation. Our findings highlight an increased variability in daily Arctic sea ice, attributed to its decline accelerated by global warming. This weather instability can influence broader regional patterns via atmospheric teleconnections, elevating risks to human activities and weather forecast predictability. Our analyses reveal these teleconnections and a positive feedback loop between Arctic and global weather instabilities, offering insights into how Arctic changes affect global weather. This framework bridges complexity science, Arctic WV, and its widespread implications.

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    Free, publicly-accessible full text available October 18, 2024
  2. Climate change is generating sufficient risk for nation‐states and citizens throughout the Arctic to warrant potentially radical geoengineering solutions. Currently, geoengineering solutions such as surface albedo modification or aerosol deployment are in the early stages of testing and development. Due to the scale of deployments necessary to enact change, and their preliminary nature, these methods are likely to result in unforeseen consequences. These consequences may range in severity from local ecosystem impacts to large scale changes in available solar energy. The Arctic is an area that is experiencing rapid change, increased development, and exploratory interest, and proposed solutions have the potential to produce new risks to both natural and human systems. This article examines potential security and ethical considerations of geoengineering solutions in the Arctic from the perspectives of securitization, consequentialism, and risk governance ap‐ proaches, and argues that proactive and preemptive frameworks at the international level, and es‐ pecially the application of risk governance approaches, will be needed to prevent or limit negative consequences resulting from geoengineering efforts. Utilizing the unique structures already present in Arctic governance provides novel options for addressing these concerns from both the perspec‐ tive of inclusive governance and through advancing the understanding of uncertainty analysis and precautionary principles. 
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  3. The timing of sea ice retreat and advance in Arctic coastal waters varies substantially from year to year. Various activities, ranging from marine transport to the use of sea ice as a platform for industrial activity or winter travel, are af- fected by variations in the timing of breakup and freeze-up, resulting in a need for indicators to document the regional and temporal variations in coastal areas. The primary objec- tive of this study is to use locally based metrics to construct indicators of breakup and freeze-up in the Arctic and subarc- tic coastal environment. The indicators developed here are based on daily sea ice concentrations derived from satellite passive-microwave measurements. The “day of year” indica- tors are designed to optimize value for users while building on past studies characterizing breakup and freeze-up dates in the open pack ice. Relative to indicators for broader adja- cent seas, the coastal indicators generally show later breakup at sites known to have landfast ice. The coastal indicators also show earlier freeze-up at some sites in comparison with freeze-up for broader offshore regions, likely tied to ear- lier freezing of shallow-water regions and areas affected by freshwater input from nearby streams and rivers. A factor analysis performed to synthesize the local indicator varia- tions shows that the local breakup and freeze-up indicators have greater spatial variability than corresponding metrics based on regional ice coverage. However, the trends towards earlier breakup and later freeze-up are unmistakable over the post-1979 period in the synthesized metrics of coastal breakup and freeze-up and the corresponding regional ice coverage. The findings imply that locally defined indicators can serve as key links between pan-Arctic or global indica- tors such as sea ice extent or volume and local uses of sea ice, with the potential to inform community-scale adaptation and response. 
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    We explore the response of wintertime Arctic sea ice growth to strong cyclones and to large-scale circulation patterns on the daily scale using Earth system model output in phase 5 of the Coupled Model Intercomparison Project (CMIP5). A combined metrics ranking method selects three CMIP5 models that are successful in reproducing the wintertime Arctic dipole (AD) pattern. A cyclone identification method is applied to select strong cyclones in two subregions in the North Atlantic to examine their different impacts on sea ice growth. The total change of sea ice growth rate (SGR) is split into those respectively driven by the dynamic and thermodynamic atmospheric forcing. Three models reproduce the downward longwave radiation anomalies that generally match thermodynamic SGR anomalies in response to both strong cyclones and large-scale circulation patterns. For large-scale circulation patterns, the negative AD outweighs the positive Arctic Oscillation in thermodynamically inhibiting SGR in both impact area and magnitude. Despite the disagreement on the spatial distribution, the three CMIP5 models agree on the weaker response of dynamic SGR than thermodynamic SGR. As the Arctic warms, the thinner sea ice results in more ice production and smaller spatial heterogeneity of thickness, dampening the SGR response to the dynamic forcing. The higher temperature increases the specific heat of sea ice, thus dampening the SGR response to the thermodynamic forcing. In this way, the atmospheric forcing is projected to contribute less to change daily SGR in the future climate. 
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  7. Abstract. Basic statistical metrics such as autocorrelations and across-region lagcorrelations of sea ice variations provide benchmarks for the assessments offorecast skill achieved by other methods such as more sophisticatedstatistical formulations, numerical models, and heuristic approaches. In thisstudy we use observational data to evaluate the contribution of the trend tothe skill of persistence-based statistical forecasts of monthly and seasonalice extent on the pan-Arctic and regional scales. We focus on the BeaufortSea for which the Barnett Severity Index provides a metric of historicalvariations in ice conditions over the summer shipping season. The varianceabout the trend line differs little among various methods of detrending(piecewise linear, quadratic, cubic, exponential). Application of thepiecewise linear trend calculation indicates an acceleration of the winterand summer trends during the 1990s. Persistence-based statistical forecastsof the Barnett Severity Index as well as September pan-Arctic ice extent showsignificant statistical skill out to several seasons when the data includethe trend. However, this apparent skill largely vanishes when the data aredetrended. In only a few regions does September ice extent correlatesignificantly with antecedent ice anomalies in the same region more than 2months earlier. The springtime “predictability barrier” in regionalforecasts based on persistence of ice extent anomalies is not reduced by theinclusion of several decades of pre-satellite data. No region showssignificant correlation with the detrended September pan-Arctic ice extent atlead times greater than a month or two; the concurrent correlations arestrongest with the East Siberian Sea. The Beaufort Sea's ice extent as farback as July explains about 20 % of the variance of the Barnett SeverityIndex, which is primarily a September metric. The Chukchi Sea is the onlyother region showing a significant association with the Barnett SeverityIndex, although only at a lead time of a month or two. 
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  8. Assimilation of remote-sensing products of sea ice thickness (SIT) into sea ice–ocean models has been shown to improve the quality of sea ice forecasts. Key open questions are whether assimilation of lower-level data products such as radar freeboard (RFB) can further improve model performance and what performance gains can be achieved through joint assimilation of these data products in combination with a snow depth product. The Arctic Mission Benefit Analysis system was developed to address this type of question. Using the quantitative network design (QND) approach, the system can evaluate, in a mathematically rigorous fashion, the observational constraints imposed by individual and groups of data products. We demonstrate the approach by presenting assessments of the observation impact (added value) of different Earth observation (EO) products in terms of the uncertainty reduction in a 4-week forecast of sea ice volume (SIV) and snow volume (SNV) for three regions along the Northern Sea Route in May 2015 using a coupled model of the sea ice–ocean system, specifically the Max Planck Institute Ocean Model. We assess seven satellite products: three real products and four hypothetical products. The real products are monthly SIT, sea ice freeboard (SIFB), and RFB, all derived from CryoSat-2 by the AlfredWegener Institute. These are complemented by two hypothetical monthly laser freeboard (LFB) products with low and high accuracy, as well as two hypothetical monthly snow depth products with low and high accuracy. On the basis of the per-pixel uncertainty ranges provided with the CryoSat-2 SIT, SIFB, and RFB products, the SIT and RFB achieve a much better performance for SIV than the SIFB product. For SNV, the performance of SIT is only low, the performance of SIFB is higher and the performance of RFB is yet higher. A hypothetical LFB product with low accuracy (20 cm uncertainty) falls between SIFB and RFB in performance for both SIV and SNV. A reduction in the uncertainty of the LFB product to 2 cm yields a significant increase in performance. Combining either of the SIT or freeboard products with a hypothetical snow depth product achieves a significant performance increase. The uncertainty in the snow product matters: a higher-accuracy product achieves an extra performance gain. Providing spatial and temporal uncertainty correlations with the EO products would be beneficial not only for QND assessments, but also for assimilation of the products. 
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  9. Impacts of a warming climate are amplified in the Arctic. One notorious impact is recent and record-breaking summertime sea-ice loss. Expanding areas of open water and a prolonged ice-free season create opportunity for some industries but challenge indigenous peoples relying on sea ice for transportation and access to food. The observed and projected increase of Arctic maritime activity requires accurate sea-ice forecasts to protect life, environment, and property. Motivated by emerging prediction needs on the operational timescale (≤10 days), this study explores where local indigenous knowledge (LIK) fits into the forecaster toolbox and how it can be woven into useful sea-ice information products. The 2011 spring ice retreat season in the Bering Sea is presented as a forecasting case study. LIK, housed in a database of community-based ice and weather logs, and an ice-ocean forecast model developed by the US Navy are analyzed for their ability to provide information relevant to stakeholder needs. Additionally, metrics for verifying numerical sea-ice forecasts on multiple scales are derived. The model exhibits skill relative to persistence and climatology on the regional scale. At the community scale, we discuss how LIK and new model guidance can enhance public sea-ice information resources. 
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