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 Sea-ice algal phenology in a warmer Arctic

2019 ◽  
Vol 5 (5) ◽  
pp. eaav4830 ◽  
Author(s):  
L. Tedesco ◽  
M. Vichi ◽  
E. Scoccimarro
Keyword(s):  
Sea Ice ◽  
Algal Blooms ◽  
Climate Models ◽  
Time Windows ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Biogeochemical Model ◽  
Biological Time ◽  
Algal Productivity ◽  
The Impact

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.

Modelling melt ponds in Global Circulation Models

2020 ◽  
Author(s):  
Jean Sterlin ◽  
Thierry Fichefet ◽  
François Massonnet ◽  
Olivier Lecomte ◽  
Martin Vancoppenolle
Keyword(s):  
Aspect Ratio ◽  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Global Circulation ◽  
Melt Pond ◽  
Global Circulation Models ◽  
Melt Ponds ◽  
The Impact

<p>Melt ponds appear during the Arctic summer on the sea ice cover when meltwater and liquid precipitation collect in the depressions of the ice surface. The albedo of the melt ponds is lower than that of surrounding ice and snow areas. Consequently, the melt ponds are an important factor for the ice-albedo feedback, a mechanism whereby a decrease in albedo results in greater absorption of solar radiation, further ice melt, and lower albedos </p><p>To account for the effect of melt ponds on the climate, several numerical schemes have been introduced for Global Circulation Models. They can be classified into two groups. The first group makes use of an explicit relation to define the aspect ratio of the melt ponds. The scheme of Holland et al. (2012) uses a constant ratio of the melt pond depth to the fraction of sea ice covered by melt ponds. The second group relies on theoretical considerations to deduce the area and volume of the melt ponds. The scheme of Flocco et al. (2012) uses the ice thickness distribution to share the meltwater between the ice categories and determine the melt ponds characteristics.</p><p>Despite their complexity, current melt pond schemes fail to agree on the trends in melt pond fraction of sea ice area during the last decades. The disagreement casts doubts on the projected melt pond changes. It also raises questions on the definition of the physical processes governing the melt ponds in the schemes and their sensitivity to atmospheric surface conditions.</p><p>In this study, we aim at identifying 1) the conceptual difference of the aspect ratio definition in melt pond schemes; 2) the role of refreezing for melt ponds; 3) the impact of the uncertainties in the atmospheric reanalyses. To address these points, we have run the Louvain-la-Neuve Ice Model (LIM), part of the Nucleus for European Modelling of the Ocean (NEMO) version 3.6 along with two different atmospheric reanalyses as surface forcing sets. We used the reanalyses in association with Holland et al. (2012) and Flocco et al. (2012) melt pond schemes. We selected Holland et al. (2012) pond refreezing formulation for both schemes and tested two different threshold temperatures for refreezing. </p><p>From the experiments, we describe the impact on Arctic sea ice and state the importance of including melt ponds in climate models. We attempt at disentangling the separate effects of the type of melt pond scheme, the refreezing mechanism, and the atmospheric surface forcing method, on the climate. We finally formulate a recommendation on the use of melt ponds in climate models. </p>

Evaluation of a multilayer snow scheme in NEMO-LIM3

2020 ◽  
Author(s):  
Gaëlle Gilson ◽  
Thierry Fichefet ◽  
Olivier Lecomte ◽  
Pierre-Yves Barriat ◽  
Jean Sterlin ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Climate Models ◽  
Thickness Distribution ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Optimum Number ◽  
Ice Growth ◽  
Arctic Sea ◽  
The Impact

<p>Arctic sea ice is a major component of the Earth’s climate system and has been experiencing a drastic decline over the past decades, with important consequences regionally and globally. With the sustained warming of the Arctic, sea ice loss is expected to continue in the future. However, the estimation of its magnitude is model-dependent. As a result, the representation of sea ice in climate models requires further consideration. A major issue relates to the long-standing misrepresentation of snow properties on sea ice. However, the presence of snow strongly impacts sea ice growth and surface energy balance. Through its high albedo, snow reflects more solar radiation than bare sea ice does. When a snow cover is present, sea ice growth is reduced because snow is an effective insulator, with a thermal conductivity an order of magnitude lower than that of sea ice. Ocean circulation models usually use multiple layers to resolve sea ice thermodynamics but only one single layer for snow. Lecomte et al. (2013) developed a multilayer snow scheme for ocean circulation models and improved the snow depth distribution by considering the macroscopic effects of wind packing and redeposition. Since then, this snow scheme has been revisited and implemented in a more recent and much more robust NEMO-LIM version, using a simpler technical approach. In addition, new instrumental observations of snow thickness, distribution and density are available since these exploratory works. They are used in the current study to: 1) evaluate the performance of the multilayer snow scheme for sea ice in the NEMO-LIM3 model, and 2) investigate the climatic importance of this snow scheme. Here, we present results of simulations with a varying number of snow layers. By comparing these to the latest observational datasets, we recommend an optimum number of snow  layers to be used in ocean circulation models in both hemispheres. Finally, we explore the impact of a few specific parameterizations of snow thermophysical properties on the representation of sea ice in climate models.</p>

The role of air-sea ice-ocean interaction processes for Arctic-midlatitude linkages

2020 ◽  
Author(s):  
Sara Khosravi ◽  
Annette Rinke ◽  
Wolfgang Dorn ◽  
Christof Lüpkes ◽  
Vladimir Gryanik ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Sea Ice ◽  
Large Scale ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
Surface Fluxes ◽  
The Arctic ◽  
Russian Science ◽  
Large Scale Circulation ◽  
The Impact

<p>Climate models have deficits in reproducing Arctic circulation and sea ice development. The air-sea ice-ocean interaction parametrizations could be a potential reason of this shortcoming. In most climate models air-sea ice-ocean interaction are parametrized based on mid-latitude conditions which is not appropriate for polar region. The POLEX project, funded by Helmholtz Association and Russian Science Foundation, is studying the impact of improved representation of Arctic air-sea ice-ocean interaction on changes in Arctic atmospheric circulation and Arctic-midlatitude linkages. We have used a new suite of parametrizations, which are easily applicable for climate simulations and have been developed based on SHEBA expedition data by Gryanik and Lüpkes (2018). We implemented the new parametrizations in the global atmospheric model (ECHAM6) in the framework of POLEX to estimate its effect on regional Arctic and large-scale circulation changes. Several steps have been defined for implementing the new parameterization to be able to distinguish and understand better the impact of its parameters. Roughness length and stability functions for stable stratification have been modified. Here the initial results of ECHAM6 sensitivity runs for different steps of the parameterization will be presented. We will present first results from process-oriented evaluation over the Arctic sea ice, e.g. how is the impact on the simulation of the two states of the Arctic boundary layer in winter. Furthermore, we will show that the large-scale circulation reacts to the new parametrization in different months and years differently.<br>Reference:<br>Gryanik, V.M. and C. Lüpkes (2018) An efficient non-iterative bulk parametrization of surface fluxes for stable atmospheric conditions over polar sea-ice, Boundary-Layer Meteorol., 166, 301-325</p>

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.

Importance of Human-Induced Nitrogen Flux Increases for Simulated Arctic Warming

2021 ◽  
Vol 34 (10) ◽  
pp. 3799-3819
Author(s):  
Hyung-Gyu Lim ◽  
Jong-Yeon Park ◽  
John P. Dunne ◽  
Charles A. Stock ◽  
Sung-Ho Kang ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
The Arctic ◽  
Biogeochemical Model ◽  
Biological Feedback ◽  
Arctic Warming ◽  
The Arctic Ocean ◽  
N Fluxes ◽  
The Impact ◽  
Chlorophyll Concentrations

AbstractHuman activities such as fossil fuel combustion, land-use change, nitrogen (N) fertilizer use, emission of livestock, and waste excretion accelerate the transformation of reactive N and its impact on the marine environment. This study elucidates that anthropogenic N fluxes (ANFs) from atmospheric and river deposition exacerbate Arctic warming and sea ice loss via physical–biological feedback. The impact of physical–biological feedback is quantified through a suite of experiments using a coupled climate–ocean–biogeochemical model (GFDL-CM2.1-TOPAZ) by prescribing the preindustrial and contemporary amounts of riverine and atmospheric N fluxes into the Arctic Ocean. The experiment forced by ANFs represents the increase in ocean N inventory and chlorophyll concentrations in present and projected future Arctic Ocean relative to the experiment forced by preindustrial N flux inputs. The enhanced chlorophyll concentrations by ANFs reinforce shortwave attenuation in the upper ocean, generating additional warming in the Arctic Ocean. The strongest responses are simulated in the Eurasian shelf seas (Kara, Barents, and Laptev Seas; 65°–90°N, 20°–160°E) due to increased N fluxes, where the annual mean surface temperature increase by 12% and the annual mean sea ice concentration decrease by 17% relative to the future projection, forced by preindustrial N inputs.

scholarly journals Cryospheric Impacts of Soviet River Diversion Schemes

1984 ◽  
Vol 5 ◽  
pp. 61-68 ◽  
Author(s):  
T. Holt ◽  
P. M. Kelly ◽  
B. S. G. Cherry
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
River Discharge ◽  
Large Scale ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
The Arctic Ocean ◽  
The Impact

Soviet plans to divert water from rivers flowing into the Arctic Ocean have led to research into the impact of a reduction in discharge on Arctic sea ice. We consider the mechanisms by which discharge reductions might affect sea-ice cover and then test various hypotheses related to these mechanisms. We find several large areas over which sea-ice concentration correlates significantly with variations in river discharge, supporting two particular hypotheses. The first hypothesis concerns the area where the initial impacts are likely to which is the Kara Sea. Reduced riverflow is associated occur, with decreased sea-ice concentration in October, at the time of ice formation. This is believed to be the result of decreased freshening of the surface layer. The second hypothesis concerns possible effects on the large-scale current system of the Arctic Ocean and, in particular, on the inflow of Atlantic and Pacific water. These effects occur as a result of changes in the strength of northward-flowing gradient currents associated with variations in river discharge. Although it is still not certain that substantial transfers of riverflow will take place, it is concluded that the possibility of significant cryospheric effects and, hence, large-scale climate impact should not be neglected.

scholarly journals Clouds damp the radiative impacts of polar sea ice loss

2020 ◽  
Vol 14 (8) ◽  
pp. 2673-2686 ◽  
Author(s):  
Ramdane Alkama ◽  
Patrick C. Taylor ◽  
Lorea Garcia-San Martin ◽  
Herve Douville ◽  
Gregory Duveiller ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Surface Radiation ◽  
Radiation Budget ◽  
The Arctic ◽  
Cloud Properties ◽  
Surface Radiation Budget ◽  
Cloud Radiative Effect ◽  
Radiative Impact ◽  
The Impact

Abstract. Clouds play an important role in the climate system: (1) cooling Earth by reflecting incoming sunlight to space and (2) warming Earth by reducing thermal energy loss to space. Cloud radiative effects are especially important in polar regions and have the potential to significantly alter the impact of sea ice decline on the surface radiation budget. Using CERES (Clouds and the Earth's Radiant Energy System) data and 32 CMIP5 (Coupled Model Intercomparison Project) climate models, we quantify the influence of polar clouds on the radiative impact of polar sea ice variability. Our results show that the cloud short-wave cooling effect strongly influences the impact of sea ice variability on the surface radiation budget and does so in a counter-intuitive manner over the polar seas: years with less sea ice and a larger net surface radiative flux show a more negative cloud radiative effect. Our results indicate that 66±2% of this change in the net cloud radiative effect is due to the reduction in surface albedo and that the remaining 34±1 % is due to an increase in cloud cover and optical thickness. The overall cloud radiative damping effect is 56±2 % over the Antarctic and 47±3 % over the Arctic. Thus, present-day cloud properties significantly reduce the net radiative impact of sea ice loss on the Arctic and Antarctic surface radiation budgets. As a result, climate models must accurately represent present-day polar cloud properties in order to capture the surface radiation budget impact of polar sea ice loss and thus the surface albedo feedback.

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.

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