scholarly journals Relationship of the Extent of Antarctic and Arctic Ice with Temperature Changes, 1979–2020

2021 ◽  
Vol 496 (1) ◽  
pp. 66-71
Author(s):  
I. I. Mokhov ◽  
M. R. Parfenova
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Surface Air Temperature ◽  
Sharp Decrease ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Cross Wavelet Analysis

Abstract Quantitative estimates of the relationship between interannual variations in the extent of Antarctic and Arctic sea ice and changes in the surface air temperature in the Northern and Southern hemispheres are obtained using satellite, ground-based, and reanalysis data for the past four decades (1980–2019). It is shown that the previously noted general increase in the extent of Antarctic sea ice observed until recent years from satellite data (available only since the late 1970s) over the background global warming and a rapid decrease in the extent of Arctic sea ice is associated with a regional decrease in the surface temperature at Antarctic latitudes from the end of the 1970s. This is a result of regional manifestation of natural climate variations with periods of up to several decades against the background of global secular warming with a relatively weak temperature trend over the ocean in the Southern Hemisphere. Since 2016, a sharp decrease in the extent of Antarctic sea ice in the Southern Ocean has been observed. The results of the correlation and cross-wavelet analysis indicate significant coherence and negative correlation with the surface temperature of the extent of sea ice in recent decades, not only in the Arctic, but also in the Antarctic.

Features of changes in the sea ice and snow cover extents associated with temperature changes in the Northern and Southern Hemispheres in recent decades.

2021 ◽  
Author(s):  
Maria Parfenova ◽  
Igor I. Mokhov
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Snow Cover ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Northern And Southern Hemispheres

<p>Quantitative estimates of the relationship between the interannual variability of Antarctic and Arctic sea ice and changes in the surface temperature in the Northern and Southern Hemispheres using satellitedata, observational data and reanalysis data for the last four decades (1980-2019) are obtained. The previously noted general increase in the Antarctic sea ice extent (up to 2016) (according to satellite data available only since the late 1970s), happening simultaneously with global warming and rapid decrease in the Arctic sea ice extent, is associated with the regional manifestation of natural climate fluctuations with periods of up to several decades. The results of correlation and crosswavelet analysis indicate significant coherence and negative correlation of hemispheric surface temperature with not only Arctic,but also Antarctic sea ice extent in recent decades.</p><p>Seasonal and regional peculiarities of snow cover sensitivity to temperature regime changes in the Northern Hemisphere are noted with an assessment of changes in recent decades. Peculiarities of snow cover variability in Eurasia and North America are presented. In particular, the peculiarities of changes in snow cover during the autumn seasons are noted.</p>

Gridded Arctic sea ice concentration reconstruction for the first half of the 20th century based on different proxy data

2021 ◽  
Author(s):  
Vladimir Semenov ◽  
Tatiana Matveeva
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
The North ◽  
Arctic Sea ◽  
Ice Concentration

<p>Global warming in the recent decades has been accompanied by a rapid recline of the Arctic sea ice area most pronounced in summer (10% per decade). To understand the relative contribution of external forcing and natural variability to the modern and future sea ice area changes, it is necessary to evaluate a range of long-term variations of the Arctic sea ice area in the period before a significant increase in anthropogenic emissions of greenhouse gases into the atmosphere. Available observational data on the spatiotemporal dynamics of Arctic sea ice until 1950s are characterized by significant gaps and uncertainties. In the recent years, there have appeared several reconstructions of the early 20<sup>th</sup> century Arctic sea ice area that filled the gaps by analogue methods or utilized combined empirical data and climate model’s output. All of them resulted in a stronger that earlier believed negative sea ice area anomaly in the 1940s concurrent with the early 20<sup>th</sup> century warming (ETCW) peak. In this study, we reconstruct the monthly average gridded sea ice concentration (SIC) in the first half of the 20th century using the relationship between the spatiotemporal features of SIC variability, surface air temperature over the Northern Hemisphere extratropical continents, sea surface temperature in the North Atlantic and North Pacific, and sea level pressure. In agreement with a few previous results, our reconstructed data also show a significant negative anomaly of the Arctic sea ice area in the middle of the 20th century, however with some 15% to 30% stronger amplitude, about 1.5 million km<sup>2</sup> in September and 0.7 million km<sup>2</sup> in March. The reconstruction demonstrates a good agreement with regional Arctic sea ice area data when available and suggests that ETWC in the Arctic has been accompanied by a concurrent sea ice area decline of a magnitude that have been exceeded only in the beginning of the 21<sup>st</sup> century.</p>

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 Arctic and Antarctic Sea-Ice Area Index Records versus Measured and Modeled Temperature Data

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Nicola Scafetta ◽  
Adriano Mazzarella
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Indices ◽  
Area Index ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
The Antarctic

Here we study the Arctic and Antarctic sea-ice area records provided by the National Snow and Ice Data Center (NSIDC). These records reveal an opposite climatic behavior: since 1978 the Arctic sea-ice area index decreased, that is, the region has warmed, while the Antarctic sea-ice area index increased, that is, the region has cooled. During the last 7 years the Arctic sea-ice area has stabilized while the Antarctic sea-ice area has increased at a rate significantly higher than during the previous decades; that is, the sea-ice area of both regions has experienced a positive acceleration. This result is quite robust because it is confirmed by alternative temperature climate indices of the same regions. We also found that a significant 4-5-year natural oscillation characterizes the climate of these sea-ice polar areas. On the contrary, we found that the CMIP5 general circulation models have predicted significant warming in both polar sea regions and failed to reproduce the strong 4-5-year oscillation. Because the CMIP5 GCM simulations are inconsistent with the observations, we suggest that important natural mechanisms of climate change are missing in the models.

scholarly journals The Community Climate System Model Version 4

2011 ◽  
Vol 24 (19) ◽  
pp. 4973-4991 ◽  
Author(s):  
Peter R. Gent ◽  
Gokhan Danabasoglu ◽  
Leo J. Donner ◽  
Marika M. Holland ◽  
Elizabeth C. Hunke ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Frequency Distribution ◽  
Arctic Sea Ice ◽  
Climate System ◽  
System Model ◽  
The Arctic ◽  
Community Climate System Model ◽  
Climate System Model ◽  
Arctic Sea

The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all CCSM components, and documents fully coupled preindustrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1° results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4°-resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in CCSM4 producing El Niño–Southern Oscillation variability with a much more realistic frequency distribution than in CCSM3, although the amplitude is too large compared to observations. These changes also improve the Madden–Julian oscillation and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the Gulf Stream path and the North Atlantic Ocean meridional overturning circulation. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than CCSM3, and for several reasons the Arctic sea ice concentration is improved in CCSM4. An ensemble of twentieth-century simulations produces a good match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4°C. This is consistent with the fact that CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of shortwave and longwave cloud forcings.

scholarly journals Impacts of sea ice on the marine iron cycle and phytoplankton productivity

2014 ◽  
Vol 11 (2) ◽  
pp. 2383-2418 ◽  
Author(s):  
S. Wang ◽  
D. Bailey ◽  
K. Lindsay ◽  
K. Moore ◽  
M. Holland
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Phytoplankton Production ◽  
Iron Cycle ◽  
Surface Ocean ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Iron Concentrations

Abstract. Iron is a key nutrient for phytoplankton growth in the surface ocean. At high latitudes, the iron cycle is closely related to sea ice. In recent decades, Arctic sea ice cover has been declining rapidly and Antarctic sea ice has exhibited large regional trends. A significant reduction of sea ice in both hemispheres is projected in future climate scenarios. To study impacts of sea ice on the iron cycle, iron sequestration in ice is incorporated to the Biogeochemical Elemental Cycling (BEC) model. Sea ice acts as a reservoir of iron during winter and releases iron to the surface ocean in spring and summer. Simulated iron concentrations in sea ice generally agree with observations, in regions where iron concentrations are lower. The maximum iron concentrations simulated in the Arctic sea ice and the Antarctic sea ice are 192 nM and 134 nM, respectively. These values are much lower than observed, which is likely due to missing biological processes in sea ice. The largest iron source to sea ice is suspended sediments, contributing fluxes of iron of 2.2 × 108 mol Fe month−1 to the Arctic and 4.1 × 106 mol Fe month−1 to the Southern Ocean during summer. As a result of the iron flux from ice, iron concentrations increase significantly in the Arctic. Iron released from melting ice increases phytoplankton production in spring and summer and shifts phytoplankton community composition in the Southern Ocean. Simulation results for the period of 1998 to 2007 indicate that a reduction of sea ice in the Southern Ocean will have a negative influence on phytoplankton production. Iron transport by sea ice appears to be an important process bringing iron to the central Arctic. Impacts of iron fluxes from ice to ocean on marine ecosystems are negligible in the current Arctic Ocean, as iron is not typically the growth-limiting nutrient. However, it may become a more important factor in the future, particularly in the central Arctic, as iron concentrations will decrease with declining sea ice cover and transport.

Mapping Antarctic sea ice albedo properties from MISR fused with MODIS

2020 ◽  
Author(s):  
Jan-Peter Muller ◽  
Said Kharbouche
Keyword(s):  
Sea Ice ◽  
Processing System ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
National Academy Of Sciences ◽  
Antarctic Sea Ice ◽  
Ice Coverage ◽  
Time Period ◽  
Arctic Sea ◽  
Academy Of Sciences

<p>In [1] a new method is described for fusing spectral BRF and derived albedo at 1.1km within the 7 minutes that MISR acquires images of a surface point with coincident MODIS nadir spectral data processed into a 1km sea ice mask. NetCDF products were produced in polar stereographic projection and produced on daily, weekly, fortnightly and monthly from November to February each year from 2000-2016. Arctic sea ice albedo has been previously presented and in this presentation, Antarctic time series, will be presented covering the same time period. This area has less complete coverage than the Arctic due to data outages due to telecommunications issues. [2] has recently pointed out that sea ice coverage  has  reduced dramatically since 2014, mainly one quadrant centred on the Wendell sea and the spectral albedo for this area will be highlighted.</p><p>Acknowledgements: Support was provided by EU-FP7 QA4ECV (Quality Assurance for Essential Climate Variables) under Project Number 607405 for the development of the processing system.</p><p>References:<br>[1] Kharbouche, S.; Muller, J.-P. Sea Ice Albedo from MISR and MODIS: Production, Validation, and Trend Analysis. Remote Sens. 2019, 11, 9. doi: https://doi.org/10.3390/rs11010009</p><p>[2] Parkinson, C. A 40-y record reveals gradual Antarctic sea ice increases followed by decreases at rates far exceeding the rates seen in the Arctic. Proceedings of the National Academy of Sciences. 2019, 116 (29) 14414-14423; DOI: 10.1073/pnas.1906556116</p>

scholarly journals The calculation of surface temperature and albedo of Arctic sea ice from AVHRR

1993 ◽  
Vol 17 ◽  
pp. 391-397 ◽  
Author(s):  
R. Lindsay ◽  
D. Rothrock
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Model Calculations ◽  
Arctic Sea ◽  
Arctic Atmosphere ◽  
Using Data ◽  
Cover Thickness ◽  
The Relationship

The temperature and albedo distributions of Arctic sea ice are calculated from images obtained from the AVHRR satellite sensor. The temperature estimate uses a split window correction incorporating regression coefficients appropriate for the arctic atmosphere. The albedo estimate is found assuming a clear and dry atmosphere. Both estimates are made with published correction techniques. Inherent errors due to the uncertainty of the atmospheric interference produced by humidity, aerosols, and diamond dust are judged to be 2–5°C in surface temperature and 0.10–0.20 in surface albedo. Cloudy regions are masked out manually using data from all five channels. The relationship between temperature and albedo is shown for a sample scene. A simple model of a surface composed of only cold, bright ice and warm, dark water is inadequate. Model calculations based on the surface energy balance allow us to relate albedo and temperature to ice thickness and snow-cover thickness and to further assess the accuracy of the surface estimates.

scholarly journals Simulation of observed climate changes in 1850–2014 with climate model INM-CM5

2018 ◽  
Vol 9 (4) ◽  
pp. 1235-1242 ◽  
Author(s):  
Evgeny Volodin ◽  
Andrey Gritsun
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Climate Changes ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ocean Heat Uptake ◽  
Arctic Sea ◽  
Arctic Sea Ice Loss ◽  
Global Mean

Abstract. Climate changes observed in 1850–2014 are modeled and studied on the basis of seven historical runs with the climate model INM-CM5 under the scenario proposed for the Coupled Model Intercomparison Project Phase 6 (CMIP6). In all runs global mean surface temperature rises by 0.8 K at the end of the experiment (2014) in agreement with the observations. Periods of fast warming in 1920–1940 and 1980–2000 as well as its slowdown in 1950–1975 and 2000–2014 are correctly reproduced by the ensemble mean. The notable change here with respect to the CMIP5 results is the correct reproduction of the slowdown in global warming in 2000–2014 that we attribute to a change in ocean heat uptake and a more accurate description of the total solar irradiance in the CMIP6 protocol. The model is able to reproduce the correct behavior of global mean temperature in 1980–2014 despite incorrect phases of the Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation indices in the majority of experiments. The Arctic sea ice loss in recent decades is reasonably close to the observations in just one model run; the model underestimates Arctic sea ice loss by a factor of 2.5. The spatial pattern of the model mean surface temperature trend during the last 30 years looks close to the one for the ERA-Interim reanalysis. The model correctly estimates the magnitude of stratospheric cooling.

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