More Like this

1. Increasing confidence in projecting the Arctic ice-free year with emergent constraints

   https://doi.org/10.1088/1748-9326/ac0b17  

   Wang, Bin ; Zhou, Xiao ; Ding, Qinghua ; Liu, Jiping ( August 2021 , Environmental Research Letters)

   Abstract An ice-free Arctic summer is a landmark of global change and has the far-reaching climate, environmental, and economic impacts. However, the Coupled Model Intercomparison Project Phase 6 models’ projected occurrence remains notoriously uncertain. Finding emergent constraints to reduce the projection uncertainties has been a foremost challenge. To establish a physical basis for the constraints, we first demonstrate, with numerical experiments, that the observed trend of Arctic ice loss is primarily driven by the Arctic near-surface air temperature. Thus, two constraints are proposed: the Arctic sea ice sensitivity that measures Arctic sea ice response to the local warming, and the Arctic amplification sensitivity that assesses how well the model responds to anthropogenic forcing and allocates heat to the Arctic region. The two constraints are complementary and nearly scenario-independent. The model-projected first Arctic ice-free year significantly depends on the model’s two climate sensitivities. Thus, the first Arctic ice-free year can be predicted by the linear combination of the two Arctic sensitivity measures. Based on model-simulated sensitivity skills, 20 CMIP models are divided into two equal number groups. The ten realistic-sensitivity models project, with a likelihood of 80%, the ice-free Arctic will occur by additional 0.8 °C global warming from 2019 levelmore »or before 2040 under the SSP2-4.5 (medium emission) scenario. The ten realistic-sensitivity models’ spread is reduced by about 70% compared to the ten underestimate-sensitivity models’ large spread. The strategy for creating physics-based emergent constraints through numerical experiments may be instrumental for broad application to other fields for advancing robust projection and understanding uncertainty sources.« less
2. Partitioning uncertainty in projections of Arctic sea ice

   https://doi.org/10.1088/1748-9326/abe0ec  

   Bonan, David B. ; Lehner, Flavio ; Holland, Marika M. ( March 2021 , Environmental Research Letters)

   Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIA change, internal variability accounts for as much as 40%–60% of the total uncertainty in the next decade, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for 60%–70% of the total uncertainty by mid-century and declines to 30% at the end of the 21st century in the summer months. For projections of wintertime Arctic SIA change, internal variability contributes as much as 50%–60% of the total uncertainty in the next decade and impacts total uncertainty at longer lead times when compared to the summertime. In winter, there exists a considerable scenario dependence of model uncertainty with relatively larger model uncertainty under strong forcing compared to weak forcing. At regional scales, the contribution of internal variability can varymore »widely and strongly depends on the calendar month and region. For wintertime SIA change in the Greenland-Iceland-Norwegian and Barents Seas, internal variability contributes 60%–70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate that internal variability is a significant source of uncertainty in projections of Arctic sea ice.

   « less
3. Sea ice directs changes in bowhead whale phenology through the Bering Strait

   https://doi.org/10.1186/s40462-023-00374-5  

   Szesciorka, Angela R. ; Stafford, Kathleen M. ( February 2023 , Movement Ecology)

   Climate change is warming the Arctic faster than the rest of the planet. Shifts in whale migration timing have been linked to climate change in temperate and sub-Arctic regions, and evidence suggests Bering–Chukchi–Beaufort (BCB) bowhead whales (Balaena mysticetus) might be overwintering in the Canadian Beaufort Sea.

   We used an 11-year timeseries (spanning 2009–2021) of BCB bowhead whale presence in the southern Chukchi Sea (inferred from passive acoustic monitoring) to explore relationships between migration timing and sea ice in the Chukchi and Bering Seas.

   Fall southward migration into the Bering Strait was delayed in years with less mean October Chukchi Sea ice area and earlier in years with greater sea ice area (p = 0.04, r² = 0.40). Greater mean October–December Bering Sea ice area resulted in longer absences between whales migrating south in the fall and north in the spring (p < 0.01, r² = 0.85). A stepwise shift after 2012–2013 shows some whales are remaining in southern Chukchi Sea rather than moving through the Bering Strait and into the northwestern Bering Sea for the winter. Spring northward migration into the southern Chukchi Sea was earlier in years with less mean January–March Chukchi Sea ice area and delayed in years with greater sea ice area (p < 0.01, r² = 0.82).

   more »

   As sea ice continues to decline, northward spring-time migration could shift earlier or more bowhead whales may overwinter at summer feeding grounds. Changes to bowhead whale migration could increase the overlap with ships and impact Indigenous communities that rely on bowhead whales for nutritional and cultural subsistence.

   « less
4. Arctic Sea Ice in Two Configurations of the Community Earth System Model Version 2 (CESM2) During the 20th and 21st Centuries

   https://doi.org/10.1029/2020JC016133  

   DeRepentigny, Patricia ; Jahn, Alexandra ; Holland, Marika M. ; Smith, Abigail ( July 2020 , Journal of Geophysical Research: Oceans)

   We provide an assessment of the current and future states of Arctic sea ice simulated by the Community Earth System Model version 2 (CESM2). The CESM2 is the version of the CESM contributed to the sixth phase of the Coupled Model Intercomparison Project (CMIP6). We analyze changes in Arctic sea ice cover in two CESM2 configurations with differing atmospheric components: the CESM2(CAM6) and the CESM2(WACCM6). Over the historical period, the CESM2(CAM6) winter ice thickness distribution is biased thin, which leads to lower summer ice area compared to CESM2(WACCM6) and observations. In both CESM2 configurations, the timing of first ice‐free conditions is insensitive to the choice of CMIP6 future emissions scenario. In fact, the probability of an ice‐free Arctic summer remains low only if global warming stays below 1.5°C, which none of the CMIP6 scenarios achieve. By the end of the 21st century, the CESM2 simulates less ocean heat loss during the fall months compared to its previous version, delaying sea ice formation and leading to ice‐free conditions for up to 8 months under the high emissions scenario. As a result, both CESM2 configurations exhibit an accelerated decline in winter and spring ice area under the high emissions scenario, a behaviormore »that had not been previously seen in CESM simulations. Differences in climate sensitivity and higher levels of atmospheric CO2 by 2100 in the CMIP6 high emissions scenario compared to its CMIP5 analog could explain why this winter ice loss was not previously simulated by the CESM.« less
5. Arctic sea ice growth in response to synoptic- and large-scale atmospheric forcing from CMIP5 models

   Cai, L. ( July 2020 , Journal of climate)

   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.more »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.« less