Arctic and Antarctic Sea Ice Mean State in the Community Earth System Model Version 2 and the Influence of Atmospheric Chemistry

DuVivier, Alice K.; Holland, Marika M.; Kay, J. E.; Tilmes, Simone; Gettelman, Andrew; Bailey, David A.

doi:10.1029/2019jc015934

Cited by 40 publications

(45 citation statements)

References 72 publications

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“…Locally, however, Lenaerts et al (2020) found that CAM6 simulated excessive rainfall over the coastal GrIS in the modern era relative to observationally validated regional model data, which is likely linked to the CAM6 cloud liquid sedimentation issue we present here. DuVivier et al (2020) found that CESM2-CAM6 modern era simulations substantially underestimate both Arctic sea ice volume and sea ice extent relative to observationally based estimates. Similarly,…”

Section: Journal Of Geophysical Research: Atmospheresmentioning

confidence: 90%

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Arctic Clouds and Precipitation in the Community Earth System Model Version 2

2020

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The Arctic climate is changing rapidly, warming at about twice the rate of the planet. Global climate models (GCMs) are invaluable tools both for understanding the drivers of these changes and predicting future Arctic climate evolution. While GCMs are continually improving, there remain difficulties in representing cloud processes which occur on scales smaller than GCM resolution. Since clouds influence the Arctic energy and water cycles, their accurate representation in models is critical for robust future projections. In this work, we examine the representation of Arctic clouds and precipitation in the Community Earth System Model (CESM) with the Community Atmosphere Model (CAM), comparing the newly released version (CESM2 with CAM6) with its predecessor (CESM1 with CAM5). To isolate changes in the Arctic mean state, we compare preindustrial control runs. Arctic cloud ice has decreased slightly, while cloud water has increased dramatically in CESM2. Annual mean liquid-containing cloud (LCC) frequency has increased from 19% in CESM1 to 51% in CESM2. Since LCCs strongly modulate downwelling radiation at the surface, their increase has led to an increase in mean downwelling longwave (+22 W m −2) and corresponding decrease in downwelling shortwave (−23 W m −2) radiation. The mean Arctic surface temperature increased from 257 K in CESM1 to 260 K in CESM2, with the largest seasonal difference in winter (+6 K). Annual average snowfall has decreased slightly (−1 mm month −1), while rainfall has increased (+5 mm month −1).

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Section: Journal Of Geophysical Research: Atmospheresmentioning

confidence: 90%

“…DuVivier et al. (2020) found that CESM2‐CAM6 modern era simulations substantially underestimate both Arctic sea ice volume and sea ice extent relative to observationally based estimates. Similarly, DeRepentigny et al.…”

Section: Discussionmentioning

confidence: 99%

Arctic Clouds and Precipitation in the Community Earth System Model Version 2

2020

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“…Conversely, the CESM2(CAM6) September ice area is consistently lower than observed (Figure 1a), with too little ice in the Pacific and Eurasian sectors of the Arctic (Figures 2a–2c). DuVivier et al (2020) found that differences in ice area already exist between CESM2(CAM6) and CESM2(WACCM6) in their preindustrial control simulations, with the largest differences in the summer months. These discrepancies in ice area and volume can be attributed to thinner early spring clouds in the CESM2(CAM6), which drive a strong ice‐albedo feedback and result in a lower ice area in September and significantly thinner ice year‐round (DuVivier et al, 2020).…”

Section: Historical Arctic Sea Icementioning

confidence: 99%

Arctic Sea Ice in Two Configurations of the CESM2 During the 20th and 21st Centuries

et al. 2020

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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, a behavior 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.

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“…We note that this difference in phase is hinted at in Figure 4a but is not as obvious perhaps because the apparent amplitude difference is dominant. This phase difference also appears (but is not discussed) in the monthly analysis carried out by DuVivier et al (2020). They show that sea ice retreat in the CESM2 begins in October rather than September.…”

Section: Resultsmentioning

confidence: 77%

“…The sea ice regions used in this analysis (Figure 1) were defined by Raphael and Hobbs (2014) and are based on coherent spatial variability in the SIC field. DuVivier et al (2020) assesses the seasonal distribution of SIC simulated by the CESM2. They show that the model does a credible job of simulating the distribution of SIC.…”

Section: Methodsmentioning

confidence: 99%

An Assessment of the Temporal Variability in the Annual Cycle of Daily Antarctic Sea Ice in the NCAR Community Earth System Model, Version 2: A Comparison of the Historical Runs With Observations

et al. 2020

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Understanding the variability of Antarctic sea ice is an ongoing challenge given the limitations of observed data. Coupled climate model simulations present the opportunity to examine this variability in Antarctic sea ice. Here, the daily sea ice extent simulated by the newly released National Center for Atmospheric Research (NCAR) Community Eart h System Model Version 2 (CESM2) for the historical period (1979-2014) is compared to the satellite-observed daily sea ice extent for the same period. The comparisons are made using a newly developed suite of statistical metrics that estimates the variability of the sea ice extent on timescales ranging from the long-term decadal to the short term, intraday scales. Assessed are the annual cycle, trend, day-today change, and the volatility, a new statistic that estimates the variability at the daily scale. Results show that the trend in observed daily sea ice is dominated by subdecadal variability with a weak positive linear trend superimposed. The CESM2 simulates comparable subdecadal variability but with a strong negative linear trend superimposed. The CESM2's annual cycle is similar in amplitude to the observed, key differences being the timing of ice advance and retreat. The sea ice begins its advance later, reaches its maximum later and begins retreat later in the CESM2. This is confirmed by the day-today change. Apparent in all of the sea ice regions, this behavior suggests the influence of the semiannual oscillation of the circumpolar trough. The volatility, which is associated with smaller scale dynamics such as storms, is smaller in the CESM2 than observed. Plain Language Summary Antarctic sea ice is strongly variable in space and in time. Lack of observed data makes it difficult to determine what causes this variability and limits our ability to understand the variability and to project how it might change in the future. Climate models give the opportunity to study the sea ice and to project change. We compare the sea ice simulations produced by the National Center for Atmospheric Research (NCAR) Community Earth System Model Version 2 (CESM2) with satellite-observed data for the years 1979-2014. We examine the annual cycle, trend, day-today change in sea ice and the volatility, a new statistic that estimates the variability at the daily scale. We show that the CESM2 is able to simulate subdecadal variability comparable to that apparent in the observed sea ice but not the weak, positive, linear trend. The CESM2 also simulates an annual cycle of similar amplitude to that observed but the ice starts growing later and retreating later in the CESM2 than is observed. This difference in timing in the annual cycle occurs in the sea ice all around Antarctica, which suggests that it might be because of a circum-Antarctic atmospheric circulation feature called the circumpolar trough.

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Arctic and Antarctic Sea Ice Mean State in the Community Earth System Model Version 2 and the Influence of Atmospheric Chemistry

Cited by 40 publications

References 72 publications

Arctic Clouds and Precipitation in the Community Earth System Model Version 2

Arctic Clouds and Precipitation in the Community Earth System Model Version 2

Arctic Sea Ice in Two Configurations of the CESM2 During the 20th and 21st Centuries

An Assessment of the Temporal Variability in the Annual Cycle of Daily Antarctic Sea Ice in the NCAR Community Earth System Model, Version 2: A Comparison of the Historical Runs With Observations

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