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1. Current-climate sea ice amount and seasonality as constraints for future Arctic amplification

   https://doi.org/10.1088/2752-5295/acf4b7  

   Linke, Olivia; Feldl, Nicole; Quaas, Johannes (September 2023, Environmental Research: Climate)

   Abstract The recent Arctic sea ice loss is a key driver of the amplified surface warming in the northern high latitudes, and simultaneously a major source of uncertainty in model projections of Arctic climate change. Previous work has shown that the spread in model predictions of future Arctic amplification (AA) can be traced back to the inter-model spread in simulated long-term sea ice loss. We demonstrate that the strength of future AA is further linked to the current climate’s, observable sea ice state across the multi-model ensemble of the 6th Coupled Model Intercomparison Project (CMIP6). The implication is that the sea-ice climatology sets the stage for long-term changes through the 21st century, which mediate the degree by which Arctic warming is amplified with respect to global warming. We determine that a lower base-climate sea ice extent and sea ice concentration (SIC) in CMIP6 models enable stronger ice melt in both future climate and during the seasonal cycle. In particular, models with lower Arctic-mean SIC project stronger future ice loss and a more intense seasonal cycle in ice melt and growth. Both processes systemically link to a larger future AA across climate models. These results are manifested by the role of climate feedbacks that have been widely identified as major drivers of AA. We show in particular that models with low base-climate SIC predict a systematically stronger warming contribution through both sea-ice albedo feedback and temperature feedbacks in the future, as compared to models with high SIC. From our derived linear regressions in conjunction with observations, we estimate a 21st-century AA over sea ice of 2.47–3.34 with respect to global warming. Lastly, from the tight relationship between base-climate SIC and the projected timing of an ice-free September, we predict a seasonally ice-free Arctic by mid-century under a high-emission scenario. 

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2. Evaluation of Arctic warming from the CMIP6 models

   https://doi.org/https://doi.org/10.1175/JCLI-D-20-0791.1  

   Cai, Z. (June 2021, Journal of climate)

   null (Ed.)

   The Arctic has experienced a warming rate higher than the global mean in the past decades, but previous studies show that there are large uncertainties associated with future Arctic temperature projections. In this study, near- surface mean temperatures in the Arctic are analyzed from 22 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Compared with the ERA5 reanalysis, most CMIP6 models underestimate the observed mean temperature in the Arctic during 1979–2014. The largest cold biases are found over the Greenland Sea the Barents Sea, and the Kara Sea. Under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, the multimodel ensemble mean of 22 CMIP6 models exhibits significant Arctic warming in the future and the warming rate is more than twice that of the global/Northern Hemisphere mean. Model spread is the largest contributor to the overall uncertainty in projections, which accounts for 55.4% of the total uncertainty at the start of projections in 2015 and remains at 32.9% at the end of projections in 2095. Internal variability uncertainty accounts for 39.3% of the total uncertainty at the start of projections but decreases to 6.5% at the end of the twenty-first century, while scenario uncertainty rapidly increases from 5.3% to 60.7% over the period from 2015 to 2095. It is found that the largest model uncertainties are consistent cold bias in the oceanic regions in the models, which is connected with excessive sea ice area caused by the weak Atlantic poleward heat transport. These results suggest that large intermodel spread and uncertainties exist in the CMIP6 models’ simulation and projection of the Arctic near- surface temperature and that there are different responses over the ocean and land in the Arctic to greenhouse gas forcing. Future research needs to pay more attention to the different characteristics and mechanisms of Arctic Ocean and land warming to reduce the spread. 

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3. Seasonal Variations and Spatial Patterns of Arctic Cloud Changes in Association with Sea Ice Loss during 1950–2019 in ERA5

   https://doi.org/10.1175/JCLI-D-23-0117.1  

   Jenkins, Matthew T.; Dai, Aiguo; Deser, Clara (January 2024, Journal of Climate)

   Abstract The dynamic and thermodynamic mechanisms that link retreating sea ice to increased Arctic cloud amount and cloud water content are unclear. Using the fifth generation of the ECMWF Reanalysis (ERA5), the long-term changes between years 1950–79 and 1990–2019 in Arctic clouds are estimated along with their relationship to sea ice loss. A comparison of ERA5 to CERES satellite cloud fractions reveals that ERA5 simulates the seasonal cycle, variations, and changes of cloud fraction well over water surfaces during 2001–20. This suggests that ERA5 may reliably represent the cloud response to sea ice loss because melting sea ice exposes more water surfaces in the Arctic. Increases in ERA5 Arctic cloud fraction and water content are largest during October–March from ∼950 to 700 hPa over areas with significant (≥15%) sea ice loss. Further, regions with significant sea ice loss experience higher convective available potential energy (∼2–2.75 J kg⁻¹), planetary boundary layer height (∼120–200 m), and near-surface specific humidity (∼0.25–0.40 g kg⁻¹) and a greater reduction of the lower-tropospheric temperature inversion (∼3°–4°C) than regions with small (<15%) sea ice loss in autumn and winter. Areas with significant sea ice loss also show strengthened upward motion between 1000 and 700 hPa, enhanced horizontal convergence (divergence) of air, and decreased (increased) relative humidity from 1000 to 950 hPa (950–700 hPa) during the cold season. Analyses of moisture divergence, evaporation minus precipitation, and meridional moisture flux fields suggest that increased local surface water fluxes, rather than atmospheric motions, provide a key source of moisture for increased Arctic clouds over newly exposed water surfaces during October–March. Significance StatementSea ice loss has been shown to be a primary contributor to Arctic warming. Despite the evidence linking large sea ice retreat to Arctic warming, some studies have suggested that enhanced downwelling longwave radiation associated with increased clouds and water vapor is the primary reason for Arctic amplification. However, it is unclear how sea ice loss is linked to changes in clouds and water vapor in the Arctic. Here, we investigate the relationship between Arctic sea ice loss and changes in clouds using the ERA5 dataset. Improved knowledge of the relationship between Arctic sea ice loss and changes in clouds will help further our understanding of the role of the cloud feedback in Arctic warming. 

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4. A Review of Arctic–Subarctic Ocean Linkages: Past Changes, Mechanisms, and Future Projections

   https://doi.org/10.34133/olar.0013  

   Wang, Qiang; Shu, Qi; Wang, Shizhu; Beszczynska-Moeller, Agnieszka; Danilov, Sergey; Steur, Laura; Haine, Thomas W.; Karcher, Michael; Lee, Craig M.; Myers, Paul G.; et al (January 2023, Ocean-Land-Atmosphere Research)

   Arctic Ocean gateway fluxes play a crucial role in linking the Arctic with the global ocean and affecting climate and marine ecosystems. We reviewed past studies on Arctic–Subarctic ocean linkages and examined their changes and driving mechanisms. Our review highlights that radical changes occurred in the inflows and outflows of the Arctic Ocean during the 2010s. Specifically, the Pacific inflow temperature in the Bering Strait and Atlantic inflow temperature in the Fram Strait hit record highs, while the Pacific inflow salinity in the Bering Strait and Arctic outflow salinity in the Davis and Fram straits hit record lows. Both the ocean heat convergence from lower latitudes to the Arctic and the hydrological cycle connecting the Arctic with Subarctic seas were stronger in 2000–2020 than in 1980–2000. CMIP6 models project a continuing increase in poleward ocean heat convergence in the 21st century, mainly due to warming of inflow waters. They also predict an increase in freshwater input to the Arctic Ocean, with the largest increase in freshwater export expected to occur in the Fram Strait due to both increased ocean volume export and decreased salinity. Fram Strait sea ice volume export hit a record low in the 2010s and is projected to continue to decrease along with Arctic sea ice decline. We quantitatively attribute the variability of the volume, heat, and freshwater transports in the Arctic gateways to forcing within and outside the Arctic based on dedicated numerical simulations and emphasize the importance of both origins in driving the variability. 

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5. CMIP6 Models Underestimate Arctic Sea Ice Loss during the Early Twentieth-Century Warming, despite Simulating Large Low-Frequency Sea Ice Variability

   https://doi.org/10.1175/JCLI-D-23-0647.1  

   Bianco, Elena; Blanchard-Wrigglesworth, Edward; Materia, Stefano; Ruggieri, Paolo; Iovino, Doroteaciro; Masina, Simona (December 2024, Journal of Climate)

   Abstract The variability of Arctic sea ice extent (SIE) on interannual and multidecadal time scales is examined in 29 models with historical forcing participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) and in twentieth-century sea ice reconstructions. Results show that during the historical period with low external forcing (1850–1919), CMIP6 models display relatively good agreement in their representation of interannual sea ice variability (IVSIE) but exhibit pronounced intermodel spread in multidecadal sea ice variability (MVSIE), which is overestimated with respect to sea ice reconstructions and is dominated by model uncertainty in sea ice simulation in the subpolar North Atlantic. We find that this is associated with differences in models’ sensitivity to Northern Hemispheric sea surface temperatures (SSTs). Additionally, we show that while CMIP6 models are generally capable of simulating multidecadal changes in Arctic sea ice from the mid-twentieth century to present day, they tend to underestimate the observed sea ice decline during the early twentieth-century warming (ETCW; 1915–45). These results suggest the need for an improved characterization of the sea ice response to multidecadal climate variability in order to address the sources of model bias and reduce the uncertainty in future projections arising from intermodel spread. Significance StatementThe credibility of Arctic sea ice predictions depends on whether climate models are capable of reproducing changes in the past climate, including patterns of sea ice variability which can mask or amplify the response to global warming. This study aims to better understand how latest-generation global climate models simulate interannual and multidecadal variability of Arctic sea ice relative to available observations. We find that models differ in their representation of multidecadal sea ice variability, which is overall larger than in observations. Additionally, models underestimate the sea ice decline during the period of observed warming between 1915 and 1945. Our results suggest that, to achieve better predictions of Arctic sea ice, the realism of low-frequency sea ice variability in models should be improved. 

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