Uncertainty in Forced and Natural Arctic Solar Absorption Variations in CMIP6 Models

2021 ◽  
Vol 34 (3) ◽  
pp. 931-948
Author(s):  
Anne Sledd ◽  
Tristan L’Ecuyer
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Internal Variability ◽  
Global Climate Models ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Solar Absorption ◽  
Clear Sky

AbstractThe Arctic is rapidly changing, with increasingly dramatic sea ice loss and surface warming in recent decades. Shortwave radiation plays a key role in Arctic warming during summer months, and absorbed shortwave radiation has been increasing largely because of greater sea ice loss. Clouds can influence this ice–albedo feedback by modulating the amount of shortwave radiation incident on the Arctic Ocean. In turn, clouds impact the amount of time that must elapse before forced trends in Arctic shortwave absorption emerge from internal variability. This study determines whether the forced climate response of absorbed shortwave radiation in the Arctic has emerged in the modern satellite record and global climate models. From 18 years of satellite observations from CERES-EBAF, we find that recent declines in sea ice are large enough to produce a statistically significant trend (1.7 × 106 PJ or 3.9% per decade) in observed clear-sky absorbed shortwave radiation. However, clouds preclude any forced trends in all-sky absorption from emerging within the existing satellite record. Across 18 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6), the predicted time to emergence of absorbed shortwave radiation trends varies from 8 to 39 and from 8 to 35 years for all-sky and clear-sky conditions, respectively, across two future scenarios. Furthermore, most models fail to reproduce the observed cloud delaying effect because of differences in internal variability. Contrary to observations, one-third of models suggest that clouds may reduce the time to emergence of absorbed shortwave trends relative to clear skies, an artifact that may be the result of inaccurate representations of cloud feedbacks.

scholarly journals Observation-based selection of climate models projects Arctic ice-free summers around 2035

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.

scholarly journals Refinement of future Arctic sea-ice projections

2021 ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk
Keyword(s):  
Model Selection ◽  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Arctic Sea ◽  
Area And Volume

Abstract Arctic sea ice has been retreating at unprecedented pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) in order to reduce these uncertainties. We select the models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to smaller Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of the future Arctic sea-ice loss when including all models.

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.

scholarly journals Can a coupled meteorology–chemistry model reproduce the historical trend in aerosol direct radiative effects over the Northern Hemisphere?

2015 ◽  
Vol 15 (17) ◽  
pp. 9997-10018 ◽  
Author(s):  
J. Xing ◽  
R. Mathur ◽  
J. Pleim ◽  
C. Hogrefe ◽  
C.-M. Gan ◽  
...  
Keyword(s):  
Northern Hemisphere ◽  
Climate Models ◽  
Global Climate ◽  
Eastern China ◽  
Global Climate Models ◽  
Shortwave Radiation ◽  
Historical Trend ◽  
Clear Sky ◽  
Northern Pacific ◽  
Central Atlantic

Abstract. The ability of a coupled meteorology–chemistry model, i.e., Weather Research and Forecast and Community Multiscale Air Quality (WRF-CMAQ), to reproduce the historical trend in aerosol optical depth (AOD) and clear-sky shortwave radiation (SWR) over the Northern Hemisphere has been evaluated through a comparison of 21-year simulated results with observation-derived records from 1990 to 2010. Six satellite-retrieved AOD products including AVHRR, TOMS, SeaWiFS, MISR, MODIS-Terra and MODIS-Aqua as well as long-term historical records from 11 AERONET sites were used for the comparison of AOD trends. Clear-sky SWR products derived by CERES at both the top of atmosphere (TOA) and surface as well as surface SWR data derived from seven SURFRAD sites were used for the comparison of trends in SWR. The model successfully captured increasing AOD trends along with the corresponding increased TOA SWR (upwelling) and decreased surface SWR (downwelling) in both eastern China and the northern Pacific. The model also captured declining AOD trends along with the corresponding decreased TOA SWR (upwelling) and increased surface SWR (downwelling) in the eastern US, Europe and the northern Atlantic for the period of 2000–2010. However, the model underestimated the AOD over regions with substantial natural dust aerosol contributions, such as the Sahara Desert, Arabian Desert, central Atlantic and northern Indian Ocean. Estimates of the aerosol direct radiative effect (DRE) at TOA are comparable with those derived by measurements. Compared to global climate models (GCMs), the model exhibits better estimates of surface-aerosol direct radiative efficiency (Eτ). However, surface-DRE tends to be underestimated due to the underestimated AOD in land and dust regions. Further investigation of TOA-Eτ estimations as well as the dust module used for estimates of windblown-dust emissions is needed.

Internal variability and unforced trends of all-sky and clear-sky SSR: quantitative estimates using CMIP6

2021 ◽  
Author(s):  
Boriana Chtirkova ◽  
Doris Folini ◽  
Lucas Ferreira Correa ◽  
Martin Wild
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Grid Cell ◽  
Internal Variability ◽  
Global Climate Models ◽  
Geographical Region ◽  
Positive Trend ◽  
Surface Solar Radiation ◽  
Anthropogenic Effect ◽  
Clear Sky

<p>Quantifying trends in surface solar radiation (SSR) of unforced simulations is of substantial importance when one tries to quantify the anthropogenic effect in forced trends, as the net effect may be dampened or amplified by the internal variability of the system. In our analysis, we consider trends on different temporal scales (10, 30, 50 and 100 years) from 58 global climate models, participating in the Coupled Model Intercomparison Project - Phase 6 (CMIP6). We calculate the trends at the grid-box level for all-sky and clear-sky SSR using annual mean data of the multi-century pre-industrial control (piControl) experiments. The trends from both variables are found to depend strongly on the geographical region, as the most pronounced trends of the all-sky variable are observed in the Tropical Pacific, while the largest clear-sky trends are found in the large desert regions. Inspecting for each grid cell the statistical distribution of occurring N-year trends  shows that they are normally distributed in the majority of grid cells for both all-sky and clear-sky SSR. The 75-th percentile taken from these distributions (i.e. a positive trend with a 25 % chance of occurrence) varies with geographical region, taking values in the ranges 0.79 - 12.03 Wm<sup>-2</sup>/decade for 10-year trends, 0.15 - 2.05 Wm<sup>-2</sup>/decade for 30-year trends, 0.07 - 0.92 Wm<sup>-2</sup>/decade for 50-year trends and 0.02 - 0.29 Wm<sup>-2</sup>/decade for 100-year trends for all-sky SSR. The unforced trends become less significant on longer timescales – the trend medians, corresponding to the above ranges, are 3.18 Wm<sup>-2</sup>/decade, 0.62 Wm<sup>-2</sup>/decade, 0.29 Wm<sup>-2</sup>/decade, 0.10 Wm<sup>-2</sup>/decade respectively. The trends for clear-sky SSR are found to differ from the all-sky SSR by a factor of 0.16 on average, independent of the trend length. The model spread becomes greater at longer trend timescales, the differences being more substantial between large model families rather than between individual models. To elucidate the dominant causes of variability in different regions, we examine the correlations of the SSR variables with ambient aerosol optical thickness at 550 nm, atmosphere mass content of water vapour, cloud area fraction and albedo.</p>

scholarly journals Detection and Attribution of Observed Changes in Northern Hemisphere Spring Snow Cover

2013 ◽  
Vol 26 (18) ◽  
pp. 6904-6914 ◽  
Author(s):  
David E. Rupp ◽  
Philip W. Mote ◽  
Nathaniel L. Bindoff ◽  
Peter A. Stott ◽  
David A. Robinson
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
Internal Variability ◽  
Global Climate Models ◽  
Anthropogenic Forcing ◽  
Detection And Attribution ◽  
Snow Cover Extent

Abstract Significant declines in spring Northern Hemisphere (NH) snow cover extent (SCE) have been observed over the last five decades. As one step toward understanding the causes of this decline, an optimal fingerprinting technique is used to look for consistency in the temporal pattern of spring NH SCE between observations and simulations from 15 global climate models (GCMs) that form part of phase 5 of the Coupled Model Intercomparison Project. The authors examined simulations from 15 GCMs that included both natural and anthropogenic forcing and simulations from 7 GCMs that included only natural forcing. The decline in observed NH SCE could be largely explained by the combined natural and anthropogenic forcing but not by natural forcing alone. However, the 15 GCMs, taken as a whole, underpredicted the combined forcing response by a factor of 2. How much of this underprediction was due to underrepresentation of the sensitivity to external forcing of the GCMs or to their underrepresentation of internal variability has yet to be determined.

scholarly journals Atmospheric drag coefficients of Weddell Sea ice computed from roughness profiles

1998 ◽  
Vol 27 ◽  
pp. 455-460 ◽  
Author(s):  
R. Fisher ◽  
Victoria I. Lytle
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Weddell Sea ◽  
The Arctic ◽  
Speed Ratio ◽  
Surface Drag ◽  
Drag Coefficients ◽  
The Antarctic

Sea ice is a highly mobile component of the Antarctic environment. Its velocity and deformation are critical processes, important in global climate models. These variables are determined by the balance of atmospheric and oceanic forces on each ice Hoe and variations in these forcings, and can produce regions ofdivcrgence or convergence. Surface drag coefficients relate the forces due to wind or water to the stress applied to the ice floe. This study adds to the limited drag coefficients reported previously for Antarctic data. Surface elevation profiles were collected during two ship-based voyages to the Weddell Sea in 1992 and 1994, and were also recorded on Ice Station Weddell in 1992. These data are used to derive surface drag coefficients using an empirical formulation following Banke and others (1980). The eastern and western regions of the Weddell Sea contain primarily first- and second-year ice, respectively. Despite these different ice types, the drag coefficients calculated are similar. The difieren! ice-drifl/wind-speed ratio in the two regions suggests a difference in ocean currents, internal ice stress or water drag. The drag coefficients calculated ranged between 1.2 X 10 −3 and 2.2 X 10 −3 The results compare well with other published Antarctic coefficients, and are generally smaller than those reported for the Arctic.

scholarly journals Future Arctic marine access: analysis and evaluation of observations, models, and projections of sea ice

2012 ◽  
Vol 6 (5) ◽  
pp. 3963-3998 ◽  
Author(s):  
T. S. Rogers ◽  
J. E. Walsh ◽  
T. S. Rupp ◽  
L. W. Brigham ◽  
M. Sfraga
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Model Performance ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
State And Local

Abstract. There is an emerging need for regional applications of sea ice projections to provide more accuracy and greater detail to scientists, national, state and local planners, and other stakeholders. The present study offers a prototype for a comprehensive, interdisciplinary study to bridge observational data, climate model simulations, and user needs. The study's first component is an observationally-based evaluation of Arctic sea ice trends during 1980–2008, with an emphasis on seasonal and regional differences relative to the overall pan-Arctic trend. Regional sea ice los has varied, with a significantly larger decline of winter maximum (January–March) extent in the Atlantic region than in other sectors. A lead-lag regression analysis of Atlantic sea ice extent and ocean temperatures indicates that reduced sea ice extent is associated with increased Atlantic Ocean temperatures. Correlations between the two variables are greater when ocean temperatures lag rather than lead sea ice. The performance of 13 global climate models is evaluated using three metrics to compare sea ice simulations with the observed record. We rank models over the pan-Arctic domain and regional quadrants, and synthesize model performance across several different studies. The best performing models project reduced ice cover across key access routes in the Arctic through 2100, with a lengthening of seasons for marine operations by 1–3 months. This assessment suggests that the Northwest and Northeast Passages hold potential for enhanced marine access to the Arctic in the future, including shipping and resource development opportunities.

scholarly journals Marginal ice zone fraction benchmarks sea ice and climate model skill

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Christopher Horvat
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Internal Variability ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Global Mean Temperature ◽  
Marginal Ice Zone ◽  
The Impact

AbstractGlobal climate models (GCMs) consistently underestimate the response of September Arctic sea-ice area (SIA) to warming. Modeled SIA losses are highly correlated to global mean temperature increases, making it challenging to gauge if improvements in modeled sea ice derive from improved sea-ice models or from improvements in forcing driven by other GCM components. I use a set of five large GCM ensembles, and CMIP6 simulations, to quantify GCM internal variability and variability between GCMs from 1979–2014, showing modern GCMs do not plausibly estimate the response of SIA to warming in all months. I identify the marginal ice zone fraction (MIZF) as a metric that is less correlated to warming, has a response plausibly simulated from January–September (but not October–December), and has highly variable future projections across GCMs. These qualities make MIZF useful for evaluating the impact of sea-ice model changes on past, present, and projected sea-ice state.

scholarly journals Assessment and Ranking of Climate Models in Arctic Sea Ice Cover Simulation: From CMIP5 to CMIP6

2021 ◽  
Vol 34 (9) ◽  
pp. 3609-3627
Author(s):  
Zili Shen ◽  
Anmin Duan ◽  
Dongliang Li ◽  
Jinxiao Li
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Substantial Reduction ◽  
Coupled Model ◽  
Internal Variability ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea

AbstractThe capability of 36 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) and their 24 CMIP5 counterparts in simulating the mean state and variability of Arctic sea ice cover for the period 1979–2014 is evaluated. In addition, a sea ice cover performance score for each CMIP5 and CMIP6 model is provided that can be used to reduce the spread in sea ice projections through applying weighted averages based on the ability of models to reproduce the historical sea ice state. Results show that the seasonal cycle of the Arctic sea ice extent (SIE) in the multimodel ensemble (MME) mean of the CMIP6 simulations agrees well with observations, with a MME mean error of less than 15% in any given month relative to the observations. CMIP6 has a smaller intermodel spread in climatological SIE values during summer months than its CMIP5 counterpart. In terms of the monthly SIE trends, the CMIP6 MME mean shows a substantial reduction in the positive bias relative to the observations compared with that of CMIP5. The spread of September SIE trends is very large, not only across different models but also across different ensemble members of the same model, indicating a strong influence of internal variability on SIE evolution. Based on the assumptions that the simulations of CMIP6 models are from the same distribution and that models have no bias in response to external forcing, we can infer that internal variability contributes to approximately 22% ± 5% of the September SIE trend over the period 1979–2014.

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