An official website of the United States government
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.
more »
« less
Evaluation of Arctic warming from the CMIP6 models
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.
more »
« less
- Award ID(s):
- 1901352
- PAR ID:
- 10275320
- Date Published:
- Journal Name:
- Journal of climate
- Volume:
- 34
- ISSN:
- 1520-0442
- Page Range / eLocation ID:
- 4871-4892
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
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.more » « less
-
As a step towards understanding the fundamental drivers of polar climate change, we evaluate contributions to polar warming and its seasonal and hemispheric asymmetries in Coupled Model Intercomparison Project phase 6 (CMIP6) as compared with CMIP5. CMIP6 models broadly capture the observed pattern of surface- and winter-dominated Arctic warming that has outpaced both tropical and Antarctic warming in recent decades. For both CMIP5 and CMIP6, CO 2 quadrupling experiments reveal that the lapse-rate and surface albedo feedbacks contribute most to stronger warming in the Arctic than the tropics or Antarctic. The relative strength of the polar surface albedo feedback in comparison to the lapse-rate feedback is sensitive to the choice of radiative kernel, and the albedo feedback contributes most to intermodel spread in polar warming at both poles. By separately calculating moist and dry atmospheric heat transport, we show that increased poleward moisture transport is another important driver of Arctic amplification and the largest contributor to projected Antarctic warming. Seasonal ocean heat storage and winter-amplified temperature feedbacks contribute most to the winter peak in warming in the Arctic and a weaker winter peak in the Antarctic. In comparison with CMIP5, stronger polar warming in CMIP6 results from a larger surface albedo feedback at both poles, combined with less-negative cloud feedbacks in the Arctic and increased poleward moisture transport in the Antarctic. However, normalizing by the global-mean surface warming yields a similar degree of Arctic amplification and only slightly increased Antarctic amplification in CMIP6 compared to CMIP5.more » « less
-
Abstract Cold winters over Eurasia often coincide with warm winters in the Arctic, which has become known as the “warm Arctic–cold Eurasia” pattern. The extent to which this observed correlation is indicative of a causal response to sea ice loss is debated. Here, using large multimodel ensembles of coordinated experiments, we find that the Eurasian temperature response to Arctic sea ice loss is weak compared to internal variability and is not robust across climate models. We show that Eurasian cooling is driven by tropospheric and stratospheric circulation changes in response to sea ice loss but is counteracted by tropospheric thermodynamical warming, as the local warming induced by sea ice loss spreads into the midlatitudes by eddy advection. Although opposing effects of thermodynamical warming and dynamical cooling are found robustly across different models or different sea ice perturbations, their net effect varies in sign and magnitude across the models, resulting in diverse model temperature responses over Eurasia. The contributions from both tropospheric dynamics and thermodynamics show substantial intermodel spread. Although some of this spread in the Eurasian winter temperature response to sea ice loss may stem from model uncertainty, even with several hundred ensemble members, it is challenging to isolate model differences in the forced response from internal variability.more » « less
-
Abstract State‐of‐the‐art climate models simulate a large spread in the projected decline of Arctic sea‐ice area (SIA) over the 21st century. Here we diagnose causes of this intermodel spread using a simple model that approximates future SIA based on present SIA and the sensitivity of SIA to Arctic temperatures. This model accounts for 70%–95% of the intermodel variance, with the majority of the spread arising from present‐day biases. The remaining spread arises from intermodel differences in Arctic warming, with some contribution from differences in the local sea‐ice sensitivity. Using observations to constrain the projections moves the probability of an ice‐free Arctic forward by 10–35 years when compared to unconstrained projections. Under a high‐emissions scenario, an ice‐free Arctic will likely (66% probability) occur between 2036 and 2056 in September and between 2050 and 2068 from July to October. Under a medium‐emissions scenario, the “likely” date occurs between 2040 and 2062 in September and much later in the 21st century from July to October.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/https://doi.org/10.1175/JCLI-D-20-0791.1
