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>

scholarly journals Impact of refreezing melt ponds on Arctic sea ice basal growth

2016 ◽  
Author(s):  
Daniela Flocco ◽  
Daniel L. Feltham ◽  
David Schroeder ◽  
Michel Tsamados
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Pond Water ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Growth ◽  
Melt Pond ◽  
Melt Ponds ◽  
Ocean Properties ◽  
The Impact

Abstract. Melt ponds forming over the sea ice cover in the Arctic profoundly impact the surface albedo inducing a positive feedback leading to further melting. Here we examine the processes involved in melt pond refreezing and their impact on basal sea ice growth. When ponds freeze, the ice that forms on them insulates the pond trapping it between the sea ice and the ice lid. Trapped melt ponds delay basal sea ice growth in Autumn: ice thickens only after (1) the pond water has been fully frozen and (2) a temperature gradient is established that will conduct heat away from the ocean. Sea ice thickening in the areas where ponds are present is mainly due to the pond's water refreezing. Pan-Arctic simulations with a stand-alone sea ice model and studies with a high-resolution one-dimensional, three-layer refreezing model are used to study the impact on sea ice growth of trapped melt ponds. Basal sea ice growth may be inhibited by up to two months. We estimate an inhibited basal growth of up to 228 km3, which represents 25 % of the basal sea ice growth estimated by PIOMAS during the months of September and October. The brine not released due to the inhibited basal growth during this period could have implications for the ocean properties and circulation. The impact of trapped melt ponds has not been accounted for so far in any climate model.

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 Regional melt-pond fraction and albedo of thin Arctic first-year drift ice in late summer

2015 ◽  
Vol 9 (1) ◽  
pp. 255-268 ◽  
Author(s):  
D. V. Divine ◽  
M. A. Granskog ◽  
S. R. Hudson ◽  
C. A. Pedersen ◽  
T. I. Karlsen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Open Water ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Surface Type ◽  
Melt Pond ◽  
Melt Ponds

Abstract. The paper presents a case study of the regional (≈150 km) morphological and optical properties of a relatively thin, 70–90 cm modal thickness, first-year Arctic sea ice pack in an advanced stage of melt. The study combines in situ broadband albedo measurements representative of the four main surface types (bare ice, dark melt ponds, bright melt ponds and open water) and images acquired by a helicopter-borne camera system during ice-survey flights. The data were collected during the 8-day ICE12 drift experiment carried out by the Norwegian Polar Institute in the Arctic, north of Svalbard at 82.3° N, from 26 July to 3 August 2012. A set of > 10 000 classified images covering about 28 km2 revealed a homogeneous melt across the study area with melt-pond coverage of ≈ 0.29 and open-water fraction of ≈ 0.11. A decrease in pond fractions observed in the 30 km marginal ice zone (MIZ) occurred in parallel with an increase in open-water coverage. The moving block bootstrap technique applied to sequences of classified sea-ice images and albedo of the four surface types yielded a regional albedo estimate of 0.37 (0.35; 0.40) and regional sea-ice albedo of 0.44 (0.42; 0.46). Random sampling from the set of classified images allowed assessment of the aggregate scale of at least 0.7 km2 for the study area. For the current setup configuration it implies a minimum set of 300 images to process in order to gain adequate statistics on the state of the ice cover. Variance analysis also emphasized the importance of longer series of in situ albedo measurements conducted for each surface type when performing regional upscaling. The uncertainty in the mean estimates of surface type albedo from in situ measurements contributed up to 95% of the variance of the estimated regional albedo, with the remaining variance resulting from the spatial inhomogeneity of sea-ice cover.

scholarly journals Applying high-resolution visible imagery to satellite melt pond fraction retrieval: A neural network approach

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Qi Liu 1 ◽  
Yawen Zhang 1
Keyword(s):  
Neural Network ◽  
Sea Ice ◽  
Satellite Data ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Neural Network Approach ◽  
Melt Pond ◽  
Melt Ponds ◽  
Arctic Sea ◽  
Visible Imagery

During summer, melt ponds have a significant influence on Arctic sea-ice albedo. The melt pond fraction (MPF) also has the ability to forecast the Arctic sea-ice in a certain period. It is important to retrieve accurate melt pond fraction (MPF) from satellite data for Arctic research. This paper proposes a satellite MPF retrieval model based on the multi-layer neural network, named MPF-NN. Our model uses multi-spectral satellite data as model input and MPF information from multi-site and multi-period visible imagery as prior knowledge for modeling. It can effectively model melt ponds evolution of different regions and periods over the Arctic. Evaluation results show that the MPF retrieved from MODIS data using the proposed model has an RMSE of 3.91% and a correlation coefficient of 0.73. The seasonal distribution of MPF is also consistent with previous results.

scholarly journals Inorganic carbon dynamics of melt pond-covered first year sea ice in the Canadian Arctic

2014 ◽  
Vol 11 (5) ◽  
pp. 7485-7519 ◽  
Author(s):  
N.-X. Geilfus ◽  
R. J. Galley ◽  
O. Crabeck ◽  
T. Papakyriakou ◽  
J. Landy ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Ice Melt ◽  
Melt Pond ◽  
Melt Ponds ◽  
Arctic Sea ◽  
Melt Water

Abstract. Melt pond formation is a common feature of the spring and summer Arctic sea ice. However, the role of the melt ponds formation and the impact of the sea ice melt on both the direction and size of CO2 flux between air and sea is still unknown. Here we describe the CO2-carbonate chemistry of melting sea ice, melt ponds and the underlying seawater associated with measurement of CO2 fluxes across first year landfast sea ice in the Resolute Passage, Nunavut, in June 2012. Early in the melt season, the increase of the ice temperature and the subsequent decrease of the bulk ice salinity promote a strong decrease of the total alkalinity (TA), total dissolved inorganic carbon (TCO2) and partial pressure of CO2 (pCO2) within the bulk sea ice and the brine. Later on, melt pond formation affects both the bulk sea ice and the brine system. As melt ponds are formed from melted snow the in situ melt pond pCO2 is low (36 μatm). The percolation of this low pCO2 melt water into the sea ice matrix dilutes the brine resulting in a strong decrease of the in situ brine pCO2 (to 20 μatm). As melt ponds reach equilibrium with the atmosphere, their in situ pCO2 increase (up to 380 μatm) and the percolation of this high concentration pCO2 melt water increase the in situ brine pCO2 within the sea ice matrix. The low in situ pCO2 observed in brine and melt ponds results in CO2 fluxes of −0.04 to −5.4 mmol m–2 d–1. As melt ponds reach equilibrium with the atmosphere, the uptake becomes less significant. However, since melt ponds are continuously supplied by melt water their in situ pCO2 still remains low, promoting a continuous but moderate uptake of CO2 (~ −1mmol m–2 d–1). The potential uptake of atmospheric CO2 by melting sea ice during the Arctic summer has been estimated from 7 to 16 Tg of C ignoring the role of melt ponds. This additional uptake of CO2 associated to Arctic sea ice needs to be further explored and considered in the estimation of the Arctic Ocean's overall CO2 budget.

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>

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.

scholarly journals Inorganic carbon dynamics of melt-pond-covered first-year sea ice in the Canadian Arctic

2015 ◽  
Vol 12 (6) ◽  
pp. 2047-2061 ◽  
Author(s):  
N.-X. Geilfus ◽  
R. J. Galley ◽  
O. Crabeck ◽  
T. Papakyriakou ◽  
J. Landy ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Co2 Fluxes ◽  
Ice Melt ◽  
Melt Pond ◽  
Melt Ponds ◽  
Arctic Sea

Abstract. Melt pond formation is a common feature of spring and summer Arctic sea ice, but the role and impact of sea ice melt and pond formation on both the direction and size of CO2 fluxes between air and sea is still unknown. Here we report on the CO2–carbonate chemistry of melting sea ice, melt ponds and the underlying seawater as well as CO2 fluxes at the surface of first-year landfast sea ice in the Resolute Passage, Nunavut, in June 2012. Early in the melt season, the increase in ice temperature and the subsequent decrease in bulk ice salinity promote a strong decrease of the total alkalinity (TA), total dissolved inorganic carbon (TCO2) and partial pressure of CO2 (pCO2) within the bulk sea ice and the brine. As sea ice melt progresses, melt ponds form, mainly from melted snow, leading to a low in situ melt pond pCO2 (36 μatm). The percolation of this low salinity and low pCO2 meltwater into the sea ice matrix decreased the brine salinity, TA and TCO2, and lowered the in situ brine pCO2 (to 20 μatm). This initial low in situ pCO2 observed in brine and melt ponds results in air–ice CO2 fluxes ranging between −0.04 and −5.4 mmol m−2 day−1 (negative sign for fluxes from the atmosphere into the ocean). As melt ponds strive to reach pCO2 equilibrium with the atmosphere, their in situ pCO2 increases (up to 380 μatm) with time and the percolation of this relatively high concentration pCO2 meltwater increases the in situ brine pCO2 within the sea ice matrix as the melt season progresses. As the melt pond pCO2 increases, the uptake of atmospheric CO2 becomes less significant. However, since melt ponds are continuously supplied by meltwater, their in situ pCO2 remains undersaturated with respect to the atmosphere, promoting a continuous but moderate uptake of CO2 (~ −1 mmol m−2 day−1) into the ocean. Considering the Arctic seasonal sea ice extent during the melt period (90 days), we estimate an uptake of atmospheric CO2 of −10.4 Tg of C yr−1. This represents an additional uptake of CO2 associated with Arctic sea ice that needs to be further explored and considered in the estimation of the Arctic Ocean's overall CO2 budget.

scholarly journals Improved Sea Ice Shortwave Radiation Physics in CCSM4: The Impact of Melt Ponds and Aerosols on Arctic Sea Ice

2012 ◽  
Vol 25 (5) ◽  
pp. 1413-1430 ◽  
Author(s):  
Marika M. Holland ◽  
David A. Bailey ◽  
Bruce P. Briegleb ◽  
Bonnie Light ◽  
Elizabeth Hunke
Keyword(s):  
Twentieth Century ◽  
Radiative Transfer ◽  
Sea Ice ◽  
Aerosol Deposition ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate System Model ◽  
Melt Ponds ◽  
Arctic Sea ◽  
The Impact

The Community Climate System Model, version 4 has revisions across all components. For sea ice, the most notable improvements are the incorporation of a new shortwave radiative transfer scheme and the capabilities that this enables. This scheme uses inherent optical properties to define scattering and absorption characteristics of snow, ice, and included shortwave absorbers and explicitly allows for melt ponds and aerosols. The deposition and cycling of aerosols in sea ice is now included, and a new parameterization derives ponded water from the surface meltwater flux. Taken together, this provides a more sophisticated, accurate, and complete treatment of sea ice radiative transfer. In preindustrial CO2 simulations, the radiative impact of ponds and aerosols on Arctic sea ice is 1.1 W m−2 annually, with aerosols accounting for up to 8 W m−2 of enhanced June shortwave absorption in the Barents and Kara Seas and with ponds accounting for over 10 W m−2 in shelf regions in July. In double CO2 (2XCO2) simulations with the same aerosol deposition, ponds have a larger effect, whereas aerosol effects are reduced, thereby modifying the surface albedo feedback. Although the direct forcing is modest, because aerosols and ponds influence the albedo, the response is amplified. In simulations with no ponds or aerosols in sea ice, the Arctic ice is over 1 m thicker and retains more summer ice cover. Diagnosis of a twentieth-century simulation indicates an increased radiative forcing from aerosols and melt ponds, which could play a role in twentieth-century Arctic sea ice reductions. In contrast, ponds and aerosol deposition have little effect on Antarctic sea ice for all climates considered.

scholarly journals Transition in the fractal geometry of Arctic melt ponds

2012 ◽  
Vol 6 (5) ◽  
pp. 1157-1162 ◽  
Author(s):  
C. Hohenegger ◽  
B. Alali ◽  
K. R. Steffen ◽  
D. K. Perovich ◽  
K. M. Golden
Keyword(s):  
Sea Ice ◽  
Statistical Physics ◽  
Climate Modeling ◽  
Critical Length ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Projections ◽  
Transmitted Radiation ◽  
Melt Pond ◽  
Melt Ponds

Abstract. During the Arctic melt season, the sea ice surface undergoes a remarkable transformation from vast expanses of snow covered ice to complex mosaics of ice and melt ponds. Sea ice albedo, a key parameter in climate modeling, is determined by the complex evolution of melt pond configurations. In fact, ice–albedo feedback has played a major role in the recent declines of the summer Arctic sea ice pack. However, understanding melt pond evolution remains a significant challenge to improving climate projections. By analyzing area–perimeter data from hundreds of thousands of melt ponds, we find here an unexpected separation of scales, where pond fractal dimension D transitions from 1 to 2 around a critical length scale of 100 m2 in area. Pond complexity increases rapidly through the transition as smaller ponds coalesce to form large connected regions, and reaches a maximum for ponds larger than 1000 m2, whose boundaries resemble space-filling curves, with D ≈ 2. These universal features of Arctic melt pond evolution are similar to phase transitions in statistical physics. The results impact sea ice albedo, the transmitted radiation fields under melting sea ice, the heat balance of sea ice and the upper ocean, and biological productivity such as under ice phytoplankton blooms.

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