scholarly journals Polar Cooling Effect Due to Increase of Phytoplankton and Dimethyl-Sulfide Emission

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 384 ◽  
Author(s):  
Ah-Hyun Kim ◽  
Seong Yum ◽  
Hannah Lee ◽  
Dong Chang ◽  
Sungbo Shim
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Models ◽  
Dimethyl Sulfide ◽  
Climate Model ◽  
Cloud Condensation Nuclei ◽  
Marine Phytoplankton ◽  
The Arctic ◽  
Polar Regions ◽  
Cloud Albedo

The effects of increased dimethyl-sulfide (DMS) emissions due to increased marine phytoplankton activity are examined using an atmosphere-ocean coupled climate model. As the DMS emission flux from the ocean increases globally, large-scale cooling occurs due to the DMS-cloud condensation nuclei (CCN)-cloud albedo interactions. This cooling increases as DMS emissions are further increased, with the most pronounced effect occurring over the Arctic, which is likely associated with a change in sea-ice fraction as sea ice mediates the air-sea exchange of the radiation, moisture and heat flux. These results differ from recent studies that only considered the bio-physical feedback that led to amplified Arctic warming under greenhouse warming conditions. Therefore, climate negative feedback from DMS-CCN-cloud albedo interactions that involve marine phytoplankton and its impact on polar climate should be properly reflected in future climate models to better estimate climate change, especially over the polar regions.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

scholarly journals Impact of ocean circulation on regional polar climate simulations using the Arctic Region Climate System Model

1997 ◽  
Vol 25 ◽  
pp. 203-207 ◽  
Author(s):  
David A. Bailey ◽  
Amanda H. Lynch ◽  
Katherine S. Hedström
Keyword(s):  
Sea Ice ◽  
Mixed Layer ◽  
Climate Models ◽  
Regional Climate ◽  
The Arctic ◽  
Water Runoff ◽  
Polar Regions ◽  
Ice Dynamics ◽  
Climate System Model ◽  
Ice Model

Global climate models have pointed to the polar regions as very sensitive areas in response to climate change. However, these models often do not contain representations of processes peculiar to the polar regions such as dynamic sea ice, permafrost, and Arctic stratus clouds. Further, global models do not have the resolution necessary to model accurately many of the important processes and feedbacks. Thus, there is a need for regional climate models of higher resolution. Our such model (ARCSy M) has been developed by A. Lynch and W. Chapman. This model incorporates the NCAR Regional Climate Model (RegCM2) with the addition of Flato–Hibler cavitating fluid sea-ice dynamics and Parkinson–Washington ice thermodynamic formulation. Recently work has been conducted to couple a mixed-layer ocean to the atmosphere–ice model, and a three-dimensional (3-D) dynamical ocean model, in this case the S-Coordinate Primitive Equation Model (SPEM), to the ice model. Simulations including oceanic circulation will allow investigations of the feedbacks involved in fresh-water runoff from sea-ice melt and sea-ice transport. Further, it is shown that the definition of the mixed-layer depth has significant impact on ice thermodynamics.

scholarly journals Inter-hemispheric seasonal comparison of Polar Amplification using radiative forcing of quadrupling CO<sub>2</sub> experiment

2019 ◽  
Author(s):  
Fernanda Casagrande ◽  
Ronald Buss de Souza ◽  
Paulo Nobre ◽  
Andre Lanfer Marquez
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Radiative Forcing ◽  
Climate Models ◽  
Initial Conditions ◽  
The Arctic ◽  
Climate Simulation ◽  
Polar Regions ◽  
High Latitudes ◽  
Polar Amplification

Abstract. The numerical climate simulation from Brazilian Earth System Model (BESM) are used here to investigate the response of Polar Regions to a forced increase of CO2 (Abrupt-4xCO2) and compared with Coupled Model Intercomparison Project 5 (CMIP5) simulations. Polar Regions are described as the most climatically sensitive areas of the globe, with an enhanced warming occurring during the cold seasons. The asymmetry between the two poles is related to the thermal inertia and the coupled ocean atmosphere processes involved. While in the northern high latitudes the amplified warming signal is associated to a positive snow and sea ice albedo feedback, for southern high latitudes the warming is related to a combination of ozone depletion and changes in the winds pattern. The numerical experiments conducted here demonstrated a very clear evidence of seasonality in the polar amplification response. In winter, for the northern high latitudes (southern high latitudes) the range of simulated polar warming varied from 15 K to 30 K (2.6 K to 10 K). In summer, for northern high latitudes (southern high latitudes) the simulated warming varies from 3 K to 15 K (3 K to 7 K). The vertical profiles of air temperature indicated stronger warming at surface, particularly for the Arctic region, suggesting that the albedo-sea ice feedback overlaps with the warming caused by meridional transport of heat in atmosphere. The latitude of the maximum warming was inversely correlated with changes in the sea ice within the model’s control run. Three climate models were identified as having high polar amplification for cold season in both poles: MIROC-ESM, BESM-OA V2.5 and GFDL-ESM2M. We suggest that the large BIAS found between models can be related to the differences in each model to represent the feedback process and also as a consequence of the distinct sea ice initial conditions of each model. The polar amplification phenomenon has been observed previously and is expected to become stronger in coming decades. The consequences for the atmospheric and ocean circulation are still subject to intense debate in the scientific community.

scholarly journals Impact of ocean circulation on regional polar climate simulations using the Arctic Region Climate System Model

1997 ◽  
Vol 25 ◽  
pp. 203-207 ◽  
Author(s):  
David A. Bailey ◽  
Amanda H. Lynch ◽  
Katherine S. Hedström
Keyword(s):  
Sea Ice ◽  
Mixed Layer ◽  
Climate Models ◽  
Regional Climate ◽  
The Arctic ◽  
Water Runoff ◽  
Polar Regions ◽  
Ice Dynamics ◽  
Climate System Model ◽  
Ice Model

Global climate models have pointed to the polar regions as very sensitive areas in response to climate change. However, these models often do not contain representations of processes peculiar to the polar regions such as dynamic sea ice, permafrost, and Arctic stratus clouds. Further, global models do not have the resolution necessary to model accurately many of the important processes and feedbacks. Thus, there is a need for regional climate models of higher resolution. Our such model (ARCSy M) has been developed by A. Lynch and W. Chapman. This model incorporates the NCAR Regional Climate Model (RegCM2) with the addition of Flato–Hibler cavitating fluid sea-ice dynamics and Parkinson–Washington ice thermodynamic formulation. Recently work has been conducted to couple a mixed-layer ocean to the atmosphere–ice model, and a three-dimensional (3-D) dynamical ocean model, in this case the S-Coordinate Primitive Equation Model (SPEM), to the ice model. Simulations including oceanic circulation will allow investigations of the feedbacks involved in fresh-water runoff from sea-ice melt and sea-ice transport. Further, it is shown that the definition of the mixed-layer depth has significant impact on ice thermodynamics.

Arctic Sea Ice Reemergence: The Role of Large-Scale Oceanic and Atmospheric Variability*

2015 ◽  
Vol 28 (14) ◽  
pp. 5477-5509 ◽  
Author(s):  
Mitchell Bushuk ◽  
Dimitrios Giannakis ◽  
Andrew J. Majda
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Spring Sea Ice ◽  
Phase Relationships

Abstract Arctic sea ice reemergence is a phenomenon in which spring sea ice anomalies are positively correlated with fall anomalies, despite a loss of correlation over the intervening summer months. This work employs a novel data analysis algorithm for high-dimensional multivariate datasets, coupled nonlinear Laplacian spectral analysis (NLSA), to investigate the regional and temporal aspects of this reemergence phenomenon. Coupled NLSA modes of variability of sea ice concentration (SIC), sea surface temperature (SST), and sea level pressure (SLP) are studied in the Arctic sector of a comprehensive climate model and in observations. It is found that low-dimensional families of NLSA modes are able to efficiently reproduce the prominent lagged correlation features of the raw sea ice data. In both the model and observations, these families provide an SST–sea ice reemergence mechanism, in which melt season (spring) sea ice anomalies are imprinted as SST anomalies and stored over the summer months, allowing for sea ice anomalies of the same sign to reappear in the growth season (fall). The ice anomalies of each family exhibit clear phase relationships between the Barents–Kara Seas, the Labrador Sea, and the Bering Sea, three regions that compose the majority of Arctic sea ice variability. These regional phase relationships in sea ice have a natural explanation via the SLP patterns of each family, which closely resemble the Arctic Oscillation and the Arctic dipole anomaly. These SLP patterns, along with their associated geostrophic winds and surface air temperature advection, provide a large-scale teleconnection between different regions of sea ice variability. Moreover, the SLP patterns suggest another plausible ice reemergence mechanism, via their winter-to-winter regime persistence.

scholarly journals The GFDL CM3 Coupled Climate Model: Characteristics of the Ocean and Sea Ice Simulations

2011 ◽  
Vol 24 (13) ◽  
pp. 3520-3544 ◽  
Author(s):  
Stephen M. Griffies ◽  
Michael Winton ◽  
Leo J. Donner ◽  
Larry W. Horowitz ◽  
Stephanie M. Downes ◽  
...  
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Atmospheric Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Simulation ◽  
Climate Indices ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Coupled Climate Model

Abstract This paper documents time mean simulation characteristics from the ocean and sea ice components in a new coupled climate model developed at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). The GFDL Climate Model version 3 (CM3) is formulated with effectively the same ocean and sea ice components as the earlier CM2.1 yet with extensive developments made to the atmosphere and land model components. Both CM2.1 and CM3 show stable mean climate indices, such as large-scale circulation and sea surface temperatures (SSTs). There are notable improvements in the CM3 climate simulation relative to CM2.1, including a modified SST bias pattern and reduced biases in the Arctic sea ice cover. The authors anticipate SST differences between CM2.1 and CM3 in lower latitudes through analysis of the atmospheric fluxes at the ocean surface in corresponding Atmospheric Model Intercomparison Project (AMIP) simulations. In contrast, SST changes in the high latitudes are dominated by ocean and sea ice effects absent in AMIP simulations. The ocean interior simulation in CM3 is generally warmer than in CM2.1, which adversely impacts the interior biases.

Recent atmospheric circulation trends: two major flaws in reanalyses and in climate models

2020 ◽  
Author(s):  
Rei Chemke ◽  
Lorenzo Polvani
Keyword(s):  
Sea Ice ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Heat Fluxes ◽  
Hadley Cell ◽  
Polar Regions ◽  
Large Scale Circulation ◽  
Model Simulations ◽  
Eddy Heat Flux

&lt;p&gt;The weakening of the Hadley cell and of the midlatitude eddy heat fluxes are two of the most robust responses of the atmospheric circulation to increasing concentrations of greenhouse gases.&amp;#160; These changes have important global climatic impacts, as the large-scale circulation acts to transfer heat and moisture from the tropics to polar regions.&amp;#160; Here, we examine Hadley cell and eddy heat flux trends in recent decades: contrasting model simulations with reanalyses, we uncover two important flaws -- one in the reanalyses and other in the model simulations -- that have, to date, gone largely unnoticed.&lt;br&gt;&lt;br&gt;First, we find that while climate models simulate a weakening of the Hadley cell over the past four decades, most atmospheric reanalyses indicate a considerable strengthening.&amp;#160; Interestingly, that discrepancy does not stem from biases in climate models, but appears to be related to artifacts in the representation of latent heating in the reanalyses.&amp;#160; This suggests that when dealing with the divergent part of the large-scale circulation, reanalyses may be fundamentally unreliable for the calculation of trends, even for trends spanning several decades.&lt;br&gt;&lt;br&gt;Second, we examine recent trends in eddy heat fluxes at midlatitudes, which are directly linked the equator-to-pole temperature gradient.&amp;#160; In the Northern Hemisphere models and reanalyses are in good agreement. In the Southern Hemisphere, however, models show a weakening while reanalyses indicate a robust strengthening.&amp;#160; In this case, the flaw is found to be with the climate models, which are unable to simulate the observed multidecadal cooling of the Southern Ocean at high-latitudes, and the accompanying increase in sea-ice.&amp;#160; While the biases in modeled Antarctic sea ice trends have been widely reported, our results demonstrates that such biases have important implications well beyond the high Southern latitudes, as they impact the equator-to-pole temperature and, as a consequence, the midlatitude atmospheric circulation.&lt;/p&gt;

scholarly journals A Decade of Spaceborne Observations of the Arctic Atmosphere: Novel Insights from NASA’s AIRS Instrument

2016 ◽  
Vol 97 (11) ◽  
pp. 2163-2176 ◽  
Author(s):  
Abhay Devasthale ◽  
Joseph Sedlar ◽  
Brian H. Kahn ◽  
Michael Tjernström ◽  
Eric J. Fetzer ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Numerical Models ◽  
Lower Troposphere ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Projections ◽  
Polar Regions ◽  
Arctic Atmosphere ◽  
Warming World

Abstract Arctic sea ice is declining rapidly and its annual ice extent minima reached record lows twice during the last decade. Large environmental and socioeconomic implications related to sea ice reduction in a warming world necessitate realistic simulations of the Arctic climate system, not least to formulate relevant environmental policies on an international scale. However, despite considerable progress in the last few decades, future climate projections from numerical models still exhibit the largest uncertainties over the polar regions. The lack of sufficient observations of essential climate variables is partly to blame for the poor representation of key atmospheric processes, and their coupling to the surface, in climate models. Observations from the hyperspectral Atmospheric Infrared Sounder (AIRS) instrument on board the National Aeronautics and Space Administration (NASA)’s Aqua satellite are contributing toward improved understanding of the vertical structure of the atmosphere over the poles since 2002, including the lower troposphere. This part of the atmosphere is especially important in the Arctic, as it directly impacts sea ice and its short-term variability. Although in situ measurements provide invaluable ground truth, they are spatially and temporally inhomogeneous and sporadic over the Arctic. A growing number of studies are exploiting AIRS data to investigate the thermodynamic structure of the Arctic atmosphere, with applications ranging from understanding processes to deriving climatologies—all of which are also useful to test and improve parameterizations in climate models. As the AIRS data record now extends more than a decade, a select few of many such noteworthy applications of AIRS data over this challenging and rapidly changing landscape are highlighted here.

scholarly journals September Arctic Sea Ice minimum prediction – a new skillful statistical approach

2018 ◽  
Author(s):  
Monica Ionita ◽  
Klaus Grosfeld ◽  
Patrick Scholz ◽  
Renate Treffeisen ◽  
Gerrit Lohmann
Keyword(s):  
Sea Ice ◽  
Statistical Model ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Polar Regions ◽  
Sea Ice Extent ◽  
Important Indicator ◽  
Predictive Skill

Abstract. Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea ice coverage, variability and long term change. However, its predictability is complex and it depends on various atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we developed a robust statistical model based on oceanic and different atmospheric variables to calculate an estimate of the September sea ice extent (SSIE) on monthly time scale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' atmospheric and oceanic conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.

scholarly journals An inter-hemispheric seasonal comparison of polar amplification using radiative forcing of a quadrupling CO<sub>2</sub> experiment

2020 ◽  
Vol 38 (5) ◽  
pp. 1123-1138
Author(s):  
Fernanda Casagrande ◽  
Ronald Buss de Souza ◽  
Paulo Nobre ◽  
Andre Lanfer Marquez
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Radiative Forcing ◽  
Climate Models ◽  
Cold Season ◽  
Coupled Processes ◽  
The Arctic ◽  
Polar Regions ◽  
High Latitudes ◽  
Polar Amplification

Abstract. The numerical climate simulations from the Brazilian Earth System Model (BESM) are used here to investigate the response of the polar regions to a forced increase in CO2 (Abrupt-4×CO2) and compared with Coupled Model Intercomparison Project phase 5 (CMIP5) and 6 (CMIP6) simulations. The main objective here is to investigate the seasonality of the surface and vertical warming as well as the coupled processes underlying the polar amplification, such as changes in sea ice cover. Polar regions are described as the most climatically sensitive areas of the globe, with an enhanced warming occurring during the cold seasons. The asymmetry between the two poles is related to the thermal inertia and the coupled ocean–atmosphere processes involved. While at the northern high latitudes the amplified warming signal is associated with a positive snow– and sea ice–albedo feedback, for southern high latitudes the warming is related to a combination of ozone depletion and changes in the wind pattern. The numerical experiments conducted here demonstrated very clear evidence of seasonality in the polar amplification response as well as linkage with sea ice changes. In winter, for the northern high latitudes (southern high latitudes), the range of simulated polar warming varied from 10 to 39 K (−0.5 to 13 K). In summer, for northern high latitudes (southern high latitudes), the simulated warming varies from 0 to 23 K (0.5 to 14 K). The vertical profiles of air temperature indicated stronger warming at the surface, particularly for the Arctic region, suggesting that the albedo–sea ice feedback overlaps with the warming caused by meridional transport of heat in the atmosphere. The latitude of the maximum warming was inversely correlated with changes in the sea ice within the model's control run. Three climate models were identified as having high polar amplification for the Arctic cold season (DJF): IPSL-CM6A-LR (CMIP6), HadGEM2-ES (CMIP5) and CanESM5 (CMIP6). For the Antarctic, in the cold season (JJA), the climate models identified as having high polar amplification were IPSL-CM6A-LR (CMIP6), CanESM5(CMIP6) and FGOALS-s2 (CMIP5). The large decrease in sea ice concentration is more evident in models with great polar amplification and for the same range of latitude (75–90∘ N). Also, we found, for models with enhanced warming, expressive changes in the sea ice annual amplitude with outstanding ice-free conditions from May to December (EC-Earth3-Veg) and June to December (HadGEM2-ES). We suggest that the large bias found among models can be related to the differences in each model to represent the feedback process and also as a consequence of each distinct sea ice initial condition. The polar amplification phenomenon has been observed previously and is expected to become stronger in the coming decades. The consequences for the atmospheric and ocean circulation are still subject to intense debate in the scientific community.

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