scholarly journals The Effect of Atmospheric Transmissivity on Model and Observational Estimates of the Sea Ice Albedo Feedback

2020 ◽  
Vol 33 (13) ◽  
pp. 5743-5765
Author(s):  
Aaron Donohoe ◽  
Ed Blanchard-Wrigglesworth ◽  
Axel Schweiger ◽  
Philip J. Rasch
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Surface Temperature Change ◽  
Feedback Parameter ◽  
Radiative Fluxes ◽  
Albedo Feedback ◽  
Concentration Changes

AbstractThe sea ice-albedo feedback (SIAF) is the product of the ice sensitivity (IS), that is, how much the surface albedo in sea ice regions changes as the planet warms, and the radiative sensitivity (RS), that is, how much the top-of-atmosphere radiation changes as the surface albedo changes. We demonstrate that the RS calculated from radiative kernels in climate models is reproduced from calculations using the “approximate partial radiative perturbation” method that uses the climatological radiative fluxes at the top of the atmosphere and the assumption that the atmosphere is isotropic to shortwave radiation. This method facilitates the comparison of RS from satellite-based estimates of climatological radiative fluxes with RS estimates across a full suite of coupled climate models and, thus, allows model evaluation of a quantity important in characterizing the climate impact of sea ice concentration changes. The satellite-based RS is within the model range of RS that differs by a factor of 2 across climate models in both the Arctic and Southern Ocean. Observed trends in Arctic sea ice are used to estimate IS, which, in conjunction with the satellite-based RS, yields an SIAF of 0.16 ± 0.04 W m−2 K−1. This Arctic SIAF estimate suggests a modest amplification of future global surface temperature change by approximately 14% relative to a climate system with no SIAF. We calculate the global albedo feedback in climate models using model-specific RS and IS and find a model mean feedback parameter of 0.37 W m−2 K−1, which is 40% larger than the IPCC AR5 estimate based on using RS calculated from radiative kernel calculations in a single climate model.

scholarly journals Time-Dependent Variations in the Arctic’s Surface Albedo Feedback and the Link to Seasonality in Sea Ice

2017 ◽  
Vol 30 (1) ◽  
pp. 393-410 ◽  
Author(s):  
Olivier Andry ◽  
Richard Bintanja ◽  
Wilco Hazeleger
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Kernel Method ◽  
Ice Cover ◽  
Temporal Variations ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Dominant Factor ◽  
Strong Impact ◽  
Albedo Feedback

The Arctic is warming 2 to 3 times faster than the global average. Arctic sea ice cover is very sensitive to this warming and has reached historic minima in late summer in recent years (e.g., 2007 and 2012). Considering that the Arctic Ocean is mainly ice covered and that the albedo of sea ice is very high compared to that of open water, any change in sea ice cover will have a strong impact on the climate response through the radiative surface albedo feedback. Since sea ice area is projected to shrink considerably, this feedback will likely vary considerably in time. Feedbacks are usually evaluated as being constant in time, even though feedbacks and climate sensitivity depend on the climate state. Here the authors assess and quantify these temporal changes in the strength of the surface albedo feedback in response to global warming. Analyses unequivocally demonstrate that the strength of the surface albedo feedback exhibits considerable temporal variations. Specifically, the strength of the surface albedo feedback in the Arctic, evaluated for simulations of the future climate (CMIP5 RCP8.5) using a kernel method, shows a distinct peak around the year 2100. This maximum is found to be linked to increased seasonality in sea ice cover when sea ice recedes, in which sea ice retreat during spring turns out to be the dominant factor affecting the strength of the annual surface albedo feedback in the Arctic. Hence, changes in sea ice seasonality and the associated fluctuations in surface albedo feedback strength will exert a time-varying effect on Arctic amplification during the projected warming over the next century.

scholarly journals Arctic Energy Budget in Relation to Sea Ice Variability on Monthly-to-Annual Time Scales

2015 ◽  
Vol 28 (16) ◽  
pp. 6335-6350 ◽  
Author(s):  
F. Krikken ◽  
W. Hazeleger
Keyword(s):  
Sea Ice ◽  
Time Scales ◽  
Energy Budget ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Albedo Feedback ◽  
Arctic Sea ◽  
Cloud Ice

Abstract The large decrease in Arctic sea ice in recent years has triggered a strong interest in Arctic sea ice predictions on seasonal-to-decadal time scales. Hence, it is important to understand physical processes that provide enhanced predictability beyond persistence of sea ice anomalies. This study analyzes the natural variability of Arctic sea ice from an energy budget perspective, using 15 climate models from phase 5 of CMIP (CMIP5), and compares these results to reanalysis data. The authors quantify the persistence of sea ice anomalies and the cross correlation with the surface and top-of-atmosphere energy budget components. The Arctic energy balance components primarily indicate the important role of the seasonal ice–albedo feedback, through which sea ice anomalies in the melt season reemerge in the growth season. This is a robust anomaly reemergence mechanism among all 15 climate models. The role of the ocean lies mainly in storing heat content anomalies in spring and releasing them in autumn. Ocean heat flux variations play only a minor role. Confirming a previous (observational) study, the authors demonstrate that there is no direct atmospheric response of clouds to spring sea ice anomalies, but a delayed response is evident in autumn. Hence, there is no cloud–ice feedback in late spring and summer, but there is a cloud–ice feedback in autumn, which strengthens the ice–albedo feedback. Anomalies in insolation are positively correlated with sea ice variability. This is primarily a result of reduced multiple reflection of insolation due to an albedo decrease. This effect counteracts the ice-albedo effect up to 50%. ERA-Interim and Ocean Reanalysis System 4 (ORAS4) confirm the main findings from the climate models.

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 Importance of open-water ice growth and ice concentration evolution: a study based on FESOM-ECHAM6

2015 ◽  
Vol 6 (2) ◽  
pp. 2137-2179
Author(s):  
X. Shi ◽  
G. Lohmann
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Global Climate Model ◽  
Open Water ◽  
Arctic Sea Ice ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
Water Ice ◽  
Ice Growth ◽  
Ice Concentration

Abstract. A newly developed global climate model FESOM-ECHAM6 with an unstructured mesh and high resolution is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. A sensitivity experiment is performed which reduces the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting decrease in the Arctic winter sea-ice concentration strongly reduces the surface albedo, enhances the ocean heat release to the atmosphere, and increases the sea-ice production. Furthermore, our simulations show a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the sea ice transport affects the freshwater budget in regions of deep water formation. A warming over Europe, Asia and North America, associated with a negative anomaly of Sea Level Pressure (SLP) over the Arctic (positive phase of the Arctic Oscillation (AO)), is also simulated by the model. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), especially for the Pacific sector. Additionally, a series of sensitivity tests are performed using an idealized 1-D thermodynamic model to further investigate the influence of the open-water ice growth, which reveals similar results in terms of the change of sea ice and ocean temperature. In reality, the distribution of new ice on open water relies on many uncertain parameters, for example, surface albedo, wind speed and ocean currents. Knowledge of the detailed processes is currently too crude for those processes to be implemented realistically into models. Our sensitivity experiments indicate a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system.

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 Climate Policy Implications of Nonlinear Decline of Arctic Land Permafrost and Sea Ice

2017 ◽  
Author(s):  
Dmitry Yumashev ◽  
Chris Hope ◽  
Kevin Schaefer ◽  
Kathrin Riemann-Campe ◽  
Fernando Iglesias-Suarez ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Policy ◽  
Arctic Sea Ice ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Policy Implications ◽  
The Arctic ◽  
Solar Absorption ◽  
Albedo Feedback ◽  
The Impact

Arctic feedbacks will accelerate climate change and could jeopardise mitigation efforts. The permafrost carbon feedback releases carbon to the atmosphere from thawing permafrost and the sea ice albedo feedback increases solar absorption in the Arctic Ocean. A constant positive albedo feedback and zero permafrost feedback have been used in nearly all climate policy studies to date, while observations and models show that the permafrost feedback is significant and that both feedbacks are nonlinear. Using novel dynamic emulators in the integrated assessment model PAGE-ICE, we investigate nonlinear interactions of the two feedbacks with the climate and economy under a range of climate scenarios consistent with the Paris Agreement. The permafrost feedback interacts with the land and ocean carbon uptake processes, and the albedo feedback evolves through a sequence of nonlinear transitions associated with the loss of Arctic sea ice in different months of the year. The US’s withdrawal from the current national pledges could increase the total discounted economic impact of the two Arctic feedbacks until 2300 by $25 trillion, reaching nearly $120 trillion, while meeting the 1.5 °C and 2 °C targets will reduce the impact by an order of magnitude.

Spring Arctic Atmospheric Preconditioning: Do Not Rule Out Shortwave Radiation Just Yet

2018 ◽  
Vol 31 (11) ◽  
pp. 4225-4240 ◽  
Author(s):  
Joseph Sedlar
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Atmospheric Transport ◽  
High Surface ◽  
Longwave Radiation ◽  
Absolute Magnitude ◽  
Arctic Sea Ice ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Ice Melt

Abstract Springtime atmospheric preconditioning of Arctic sea ice for enhanced or buffered sea ice melt during the subsequent melt year has received considerable research focus. Studies have identified enhanced poleward atmospheric transport of moisture and heat during spring, leading to increased emission of longwave radiation to the surface. Simultaneously, these studies ruled out the role of shortwave radiation as an effective preconditioning mechanism because of relatively weak incident solar radiation, high surface albedo from sea ice and snow, and increased clouds during spring. These conclusions are derived primarily from atmospheric reanalysis, which may not always accurately represent the Arctic climate system. Here, top-of-atmosphere shortwave radiation observations from a state-of-the-art satellite sensor are compared with ERA-Interim reanalysis to examine similarities and differences in the springtime absorbed shortwave radiation (ASR) over the Arctic Ocean. Distinct biases in regional location and absolute magnitude of ASR anomalies are found between satellite-based measurements and reanalysis. Observations indicate separability between ASR anomalies in spring corresponding to anomalously low and high ice extents in September; the reanalysis fails to capture the full extent of this separability. The causes for the difference in ASR anomalies between observations and reanalysis are considered in terms of the variability in surface albedo and cloud presence. Additionally, biases in reanalysis cloud water during spring are presented and are considered for their impact on overestimating spring downwelling longwave anomalies. Taken together, shortwave radiation should not be overlooked as a contributing mechanism to springtime Arctic atmospheric preconditioning.

scholarly journals Nudging the Arctic Ocean to Quantify Sea Ice Feedbacks

2019 ◽  
Vol 32 (8) ◽  
pp. 2381-2395
Author(s):  
Evelien Dekker ◽  
Richard Bintanja ◽  
Camiel Severijns
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Climate Sensitivity ◽  
Surface Albedo ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Response ◽  
Arctic Sea ◽  
The Arctic Ocean

AbstractWith Arctic summer sea ice potentially disappearing halfway through this century, the surface albedo and insulating effects of Arctic sea ice will decrease considerably. The ongoing Arctic sea ice retreat also affects the strength of the Planck, lapse rate, cloud, and surface albedo feedbacks together with changes in the heat exchange between the ocean and the atmosphere, but their combined effect on climate sensitivity has not been quantified. This study presents an estimate of all Arctic sea ice related climate feedbacks combined. We use a new method to keep Arctic sea ice at its present-day (PD) distribution under a changing climate in a 50-yr CO2 doubling simulation, using a fully coupled global climate model (EC-Earth, version 2.3). We nudge the Arctic Ocean to the (monthly dependent) year 2000 mean temperature and minimum salinity fields on a mask representing PD sea ice cover. We are able to preserve about 95% of the PD mean March and 77% of the September PD Arctic sea ice extent by applying this method. Using simulations with and without nudging, we estimate the climate response associated with Arctic sea ice changes. The Arctic sea ice feedback globally equals 0.28 ± 0.15 W m−2 K−1. The total sea ice feedback thus amplifies the climate response for a doubling of CO2, in line with earlier findings. Our estimate of the Arctic sea ice feedback agrees reasonably well with earlier CMIP5 global climate feedback estimates and shows that the Arctic sea ice exerts a considerable effect on the Arctic and global climate sensitivity.

Sea-ice algal phenology in a warmer Arctic

2020 ◽  
Author(s):  
Letizia Tedesco ◽  
Marcello Vichi ◽  
Enrico Scoccimarro
Keyword(s):  
Sea Ice ◽  
Algal Blooms ◽  
Climate Models ◽  
Time Windows ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Biogeochemical Model ◽  
Biological Time ◽  
Algal Productivity ◽  
The Impact

<p>The Arctic sea-ice decline is among the most emblematic manifestations of climate change and is occurring before we understand its ecological consequences. We investigated future changes in algal productivity combining a biogeochemical model for sympagic algae with sea-ice drivers from an ensemble of 18 CMIP5 climate models. Model projections indicate quasi-linear physical changes along latitudes but markedly nonlinear response of sympagic algae, with distinct latitudinal patterns. While snow cover thinning explains the advancement of algal blooms below 66°N, narrowing of the biological time windows yields small changes in the 66°N to 74°N band, and shifting of the ice seasons toward more favorable photoperiods drives the increase in algal production above 74°N. These diverse latitudinal responses indicate that the impact of declining sea ice on Arctic sympagic production is both large and complex, with consequent trophic and phenological cascades expected in the rest of the food web.</p>

scholarly journals How Climate Model Complexity Influences Sea Ice Stability

2015 ◽  
Vol 28 (10) ◽  
pp. 3998-4014 ◽  
Author(s):  
Till J. W. Wagner ◽  
Ian Eisenman
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Model Complexity ◽  
The Arctic ◽  
Arctic Sea ◽  
The Stability ◽  
Low Order

Abstract Record lows in Arctic sea ice extent have been making frequent headlines in recent years. The change in albedo when sea ice is replaced by open water introduces a nonlinearity that has sparked an ongoing debate about the stability of the Arctic sea ice cover and the possibility of Arctic “tipping points.” Previous studies identified instabilities for a shrinking ice cover in two types of idealized climate models: (i) annual-mean latitudinally varying diffusive energy balance models (EBMs) and (ii) seasonally varying single-column models (SCMs). The instabilities in these low-order models stand in contrast with results from comprehensive global climate models (GCMs), which typically do not simulate any such instability. To help bridge the gap between low-order models and GCMs, an idealized model is developed that includes both latitudinal and seasonal variations. The model reduces to a standard EBM or SCM as limiting cases in the parameter space, thus reconciling the two previous lines of research. It is found that the stability of the ice cover vastly increases with the inclusion of spatial communication via meridional heat transport or a seasonal cycle in solar forcing, being most stable when both are included. If the associated parameters are set to values that correspond to the current climate, the ice retreat is reversible and there is no instability when the climate is warmed. The two parameters have to be reduced by at least a factor of 3 for instability to occur. This implies that the sea ice cover may be substantially more stable than has been suggested in previous idealized modeling studies.

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