scholarly journals The detectability of sea-ice leads in satellite data as a function of atmospheric conditions and measurement scale

1993 ◽  
Vol 17 ◽  
pp. 227-232 ◽  
Author(s):  
J. Key ◽  
R. Stone ◽  
J. Maslanik ◽  
E. Ellefsen
Keyword(s):  
Sea Ice ◽  
Brightness Temperature ◽  
Satellite Data ◽  
The Arctic ◽  
Transfer Model ◽  
Atmospheric Effects ◽  
Ice Crystal ◽  
Model Calculations ◽  
Ice Leads ◽  
The Impact

The release of heat from sea-ice leads is an important component of the heat budget in the Arctic, but the impact of leads on regional scale climate is difficult to assess without information on their distribution in both space and time. Remote sensing of leads using satellite data, specifically AVHRR thermal and Landsat visible imagery, is examined with respect to one lead parameter: lead width. Atmospheric effects are illustrated through the concept of thermal contrast transmittance, where the brightness temperature contrast between leads of various ice thicknesses and the surrounding multi-year ice is simulated using a radiative transfer model. Calculations are made as a function of aerosol, ice crystal precipitation, and cirrus cloud optical depths. For example, at ice crystal optical depths of more than about 1.5 under mean January conditions in the central Arctic, the brightness temperature differences between 2 m and 5 cm thick ice are similar to the ice temperature variability so that there would be insufficient contrast to distinguish a lead from the surrounding ice. The geometrical aspects of the sensor are also simulated by degrading Landsat data so that the effect of sensor field-of-view on retrieved lead width statistics can be assessed. Large leads tend to “grow” with increased pixel size while small leads disappear. Changes in lead width and orientation distributions can readily be seen.

scholarly journals The detectability of sea-ice leads in satellite data as a function of atmospheric conditions and measurement scale

1993 ◽  
Vol 17 ◽  
pp. 227-232 ◽  
Author(s):  
J. Key ◽  
R. Stone ◽  
J. Maslanik ◽  
E. Ellefsen
Keyword(s):  
Sea Ice ◽  
Brightness Temperature ◽  
Satellite Data ◽  
The Arctic ◽  
Transfer Model ◽  
Atmospheric Effects ◽  
Ice Crystal ◽  
Model Calculations ◽  
Ice Leads ◽  
The Impact

The release of heat from sea-ice leads is an important component of the heat budget in the Arctic, but the impact of leads on regional scale climate is difficult to assess without information on their distribution in both space and time. Remote sensing of leads using satellite data, specifically AVHRR thermal and Landsat visible imagery, is examined with respect to one lead parameter: lead width. Atmospheric effects are illustrated through the concept of thermal contrast transmittance, where the brightness temperature contrast between leads of various ice thicknesses and the surrounding multi-year ice is simulated using a radiative transfer model. Calculations are made as a function of aerosol, ice crystal precipitation, and cirrus cloud optical depths. For example, at ice crystal optical depths of more than about 1.5 under mean January conditions in the central Arctic, the brightness temperature differences between 2 m and 5 cm thick ice are similar to the ice temperature variability so that there would be insufficient contrast to distinguish a lead from the surrounding ice. The geometrical aspects of the sensor are also simulated by degrading Landsat data so that the effect of sensor field-of-view on retrieved lead width statistics can be assessed. Large leads tend to “grow” with increased pixel size while small leads disappear. Changes in lead width and orientation distributions can readily be seen.

scholarly journals Spatial and Temporal Variability of Minimum Brightness Temperature at the 6.925 GHz Band of AMSR2 for the Arctic and Antarctic Oceans

2021 ◽  
Vol 13 (11) ◽  
pp. 2122
Author(s):  
Young-Joo Kwon ◽  
Sungwook Hong ◽  
Jeong-Won Park ◽  
Seung Hee Kim ◽  
Jong-Min Kim ◽  
...  
Keyword(s):  
Sea Ice ◽  
Brightness Temperature ◽  
Seasonal Variability ◽  
Sea Surface ◽  
The Arctic ◽  
Transfer Model ◽  
Concentration Data ◽  
Sea Ice Concentration ◽  
Significant Difference ◽  
Ice Concentration

The minimum brightness temperature (mBT) of seawater in the polar region is an important parameter in algorithms for determining sea ice concentration or snow depth. To estimate the mBT of seawater at 6.925 GHz for the Arctic and Antarctic Oceans and to find their physical characteristics, we collected brightness temperature and sea ice concentration data from the Advanced Microwave Scanning Radiometer 2 (AMSR2) for eight years from 2012 to 2020. The estimated mBT shows constant annual values, but we found a significant difference in the seasonal variability between the Arctic and Antarctic Oceans. We calculated the mBT with the radiative transfer model parameterized by sea surface temperature (SST), sea surface wind speed (SSW), and integrated water vapor (IWV) and compared them with our observations. The estimated mBT represents the modeled mBT emitted from seawater under conditions of 2–5 m/s SSW and SST below 0 °C, except in the Arctic summer. The exceptional summer mBT in the Arctic Ocean was related to unusually high SST. We found evidence of Arctic amplification in the seasonal variability of Arctic mBT.

scholarly journals The Arctic response to remote and local forcing of black carbon

2012 ◽  
Vol 12 (7) ◽  
pp. 18379-18418 ◽  
Author(s):  
M. Sand ◽  
T. K. Berntsen ◽  
J. E. Kay ◽  
J. F. Lamarque ◽  
Ø. Seland ◽  
...  
Keyword(s):  
Sea Ice ◽  
Black Carbon ◽  
Temperature Response ◽  
Mitigation Strategies ◽  
Arctic Climate ◽  
The Arctic ◽  
Comprehensive Treatment ◽  
Model Calculations ◽  
The Impact ◽  
Ice Fraction

Abstract. Recent studies suggest that the Arctic temperature response to black carbon (BC) forcing depend on the location of the forcing. We investigate how BC in the mid-latitudes remotely influence the Arctic climate, and compare this with the response to BC located in the Arctic it self. In this study, idealized climate simulations are carried out with a fully coupled Earth System Model, which includes a comprehensive treatment of aerosol microphysics. In order to determine how BC transported to the Arctic and BC sources not reaching the Arctic impact the Arctic climate, forcing from BC aerosols is artificially increased by a factor of 10 in different latitude bands in the mid-latitudes (28° N–60° N) and in the Arctic (60° N–90° N), respectively. Estimates of the impact on the Arctic energy budget are represented by analyzing radiation fluxes at the top of the atmosphere, at the surface and at the lateral boundaries. Our calculations show that increased BC forcing in the Arctic atmosphere reduces the surface air temperature in the Arctic with a corresponding increase in the sea-ice fraction, despite the increased planetary absorption of sunlight. The analysis indicates that this effect may be due to a combination of a weakening of the northward heat transport caused by a reduction in the meridional temperature gradient and a reduction in the turbulent mixing of heat downward to the surface. The latter factor is explained by the fact that most of the BC is located in the free troposphere and causes a warming at higher altitudes which increases the static stability in the Arctic. On the other hand we find that BC forcing at the mid-latitudes warms the Arctic surface significantly and decreases the sea-ice fraction. Our model calculations indicate that atmospheric BC forcing outside the Arctic is more important for the Arctic climate change than the forcing in the Arctic itself. Although the albedo effect of BC on snow does show a more regional response to an Arctic forcing, these results suggest that mitigation strategies for the Arctic climate should also address BC sources in locations outside the Arctic even if they do not contribute much to BC in the Arctic.

scholarly journals The Arctic response to remote and local forcing of black carbon

2013 ◽  
Vol 13 (1) ◽  
pp. 211-224 ◽  
Author(s):  
M. Sand ◽  
T. K. Berntsen ◽  
J. E. Kay ◽  
J. F. Lamarque ◽  
Ø. Seland ◽  
...  
Keyword(s):  
Sea Ice ◽  
Black Carbon ◽  
Heat Transport ◽  
Mitigation Strategies ◽  
Arctic Climate ◽  
The Arctic ◽  
Comprehensive Treatment ◽  
Model Calculations ◽  
The Impact ◽  
Ice Fraction

Abstract. Recent studies suggest that the Arctic temperature response to black carbon (BC) forcing depend strongly on the location of the forcing. We investigate how atmospheric BC in the mid-latitudes remotely influence the Arctic climate, and compare this with the response to atmospheric BC located in the Arctic itself. In this study, idealized climate simulations are carried out with a fully coupled Earth System Model, which includes a comprehensive treatment of aerosol microphysics. In order to determine how BC transported to the Arctic and BC sources not reaching the Arctic impact the Arctic climate, atmospheric BC concentrations are scaled up in the mid-latitudes (28–60° N) and in the Arctic (60–90° N), respectively. Estimates of the impact on the Arctic energy budget are represented by analyzing radiation fluxes at the top of the atmosphere and at the surface, surface turbulent fluxes, and meridional heat transport in the atmosphere. Our calculations show that increased BC forcing in the Arctic atmosphere reduces the surface air temperature in the Arctic with a corresponding increase in the sea-ice fraction, despite the increased planetary absorption of sunlight. The analysis indicates that this effect is due to a combination of a weakening of the northward heat transport caused by a reduction in the meridional temperature gradient and a dimming at the surface. On the other hand we find that BC forcing at the mid-latitudes warms the Arctic surface significantly and decreases the sea-ice fraction. Our model calculations indicate that atmospheric BC forcing outside the Arctic may be more important for the Arctic climate change than the forcing in the Arctic itself. These results suggest that mitigation strategies for the Arctic climate should also address BC sources in locations outside the Arctic even if they do not contribute much to BC in the Arctic.

scholarly journals Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data

2021 ◽  
Vol 13 (11) ◽  
pp. 2174
Author(s):  
Lijian Shi ◽  
Sen Liu ◽  
Yingni Shi ◽  
Xue Ao ◽  
Bin Zou ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ocean Circulation ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Atmospheric Effects ◽  
Observation Data ◽  
Long Time Series ◽  
Ice Concentration ◽  
Long Time

Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites.

scholarly journals Retrieval of Summer Sea Ice Concentration in the Pacific Arctic Ocean from AMSR2 Observations and Numerical Weather Data Using Random Forest Regression

2021 ◽  
Vol 13 (12) ◽  
pp. 2283
Author(s):  
Hyangsun Han ◽  
Sungjae Lee ◽  
Hyun-Cheol Kim ◽  
Miae Kim
Keyword(s):  
Random Forest ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Open Water ◽  
The Arctic ◽  
Atmospheric Effects ◽  
Sea Ice Concentration ◽  
Air Temperatures ◽  
The Pacific ◽  
Ice Concentration

The Arctic sea ice concentration (SIC) in summer is a key indicator of global climate change and important information for the development of a more economically valuable Northern Sea Route. Passive microwave (PM) sensors have provided information on the SIC since the 1970s by observing the brightness temperature (TB) of sea ice and open water. However, the SIC in the Arctic estimated by operational algorithms for PM observations is very inaccurate in summer because the TB values of sea ice and open water become similar due to atmospheric effects. In this study, we developed a summer SIC retrieval model for the Pacific Arctic Ocean using Advanced Microwave Scanning Radiometer 2 (AMSR2) observations and European Reanalysis Agency-5 (ERA-5) reanalysis fields based on Random Forest (RF) regression. SIC values computed from the ice/water maps generated from the Korean Multi-purpose Satellite-5 synthetic aperture radar images from July to September in 2015–2017 were used as a reference dataset. A total of 24 features including the TB values of AMSR2 channels, the ratios of TB values (the polarization ratio and the spectral gradient ratio (GR)), total columnar water vapor (TCWV), wind speed, air temperature at 2 m and 925 hPa, and the 30-day average of the air temperatures from the ERA-5 were used as the input variables for the RF model. The RF model showed greatly superior performance in retrieving summer SIC values in the Pacific Arctic Ocean to the Bootstrap (BT) and Arctic Radiation and Turbulence Interaction STudy (ARTIST) Sea Ice (ASI) algorithms under various atmospheric conditions. The root mean square error (RMSE) of the RF SIC values was 7.89% compared to the reference SIC values. The BT and ASI SIC values had three times greater values of RMSE (20.19% and 21.39%, respectively) than the RF SIC values. The air temperatures at 2 m and 925 hPa and their 30-day averages, which indicate the ice surface melting conditions, as well as the GR using the vertically polarized channels at 23 GHz and 18 GHz (GR(23V18V)), TCWV, and GR(36V18V), which accounts for atmospheric water content, were identified as the variables that contributed greatly to the RF model. These important variables allowed the RF model to retrieve unbiased and accurate SIC values by taking into account the changes in TB values of sea ice and open water caused by atmospheric effects.

The implications of selected processing methods on satellite altimetry derived sea ice thickness state and trends in the seasonal ice zone

2021 ◽  
Author(s):  
Isolde Glissenaar ◽  
Jack Landy ◽  
Alek Petty ◽  
Nathan Kurtz ◽  
Julienne Stroeve
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Satellite Altimetry ◽  
Region Of Interest ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Baffin Bay ◽  
The Impact

<p>The ice cover of the Arctic Ocean is increasingly becoming dominated by seasonal sea ice. It is important to focus on the processing of altimetry ice thickness data in thinner seasonal ice regions to understand seasonal sea ice behaviour better. This study focusses on Baffin Bay as a region of interest to study seasonal ice behaviour.</p><p>We aim to reconcile the spring sea ice thickness derived from multiple satellite altimetry sensors and sea ice charts in Baffin Bay and produce a robust long-term record (2003-2020) for analysing trends in sea ice thickness. We investigate the impact of choosing different snow depth products (the Warren climatology, a passive microwave snow depth product and modelled snow depth from reanalysis data) and snow redistribution methods (a sigmoidal function and an empirical piecewise function) to retrieve sea ice thickness from satellite altimetry sea ice freeboard data.</p><p>The choice of snow depth product and redistribution method results in an uncertainty envelope around the March mean sea ice thickness in Baffin Bay of 10%. Moreover, the sea ice thickness trend ranges from -15 cm/dec to 20 cm/dec depending on the applied snow depth product and redistribution method. Previous studies have shown a possible long-term asymmetrical trend in sea ice thinning in Baffin Bay. The present study shows that whether a significant long-term asymmetrical trend was found depends on the choice of snow depth product and redistribution method. The satellite altimetry sea ice thickness results with different snow depth products and snow redistribution methods show that different processing techniques can lead to different results and can influence conclusions on total and spatial sea ice thickness trends. Further processing work on the historic radar altimetry record is needed to create reliable sea ice thickness products in the marginal ice zone.</p>

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 Recent Sea Ice Decline Did Not Significantly Increase the Total Liquid Freshwater Content of the Arctic Ocean

2018 ◽  
Vol 32 (1) ◽  
pp. 15-32 ◽  
Author(s):  
Qiang Wang ◽  
Claudia Wekerle ◽  
Sergey Danilov ◽  
Dmitry Sidorenko ◽  
Nikolay Koldunov ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Circulation ◽  
General Circulation ◽  
The Arctic ◽  
Sea Ice Decline ◽  
The Arctic Ocean ◽  
Eurasian Basin ◽  
The Impact

Abstract The freshwater stored in the Arctic Ocean is an important component of the global climate system. Currently the Arctic liquid freshwater content (FWC) has reached a record high since the beginning of the last century. In this study we use numerical simulations to investigate the impact of sea ice decline on the Arctic liquid FWC and its spatial distribution. The global unstructured-mesh ocean general circulation model Finite Element Sea Ice–Ocean Model (FESOM) with 4.5-km horizontal resolution in the Arctic region is applied. The simulations show that sea ice decline increases the FWC by freshening the ocean through sea ice meltwater and modifies upper ocean circulation at the same time. The two effects together significantly increase the freshwater stored in the Amerasian basin and reduce its amount in the Eurasian basin. The salinification of the upper Eurasian basin is mainly caused by the reduction in the proportion of Pacific Water and the increase in that of Atlantic Water (AW). Consequently, the sea ice decline did not significantly contribute to the observed rapid increase in the Arctic total liquid FWC. However, the changes in the Arctic freshwater spatial distribution indicate that the influence of sea ice decline on the ocean environment is remarkable. Sea ice decline increases the amount of Barents Sea branch AW in the upper Arctic Ocean, thus reducing its supply to the deeper Arctic layers. This study suggests that all the dynamical processes sensitive to sea ice decline should be taken into account when understanding and predicting Arctic changes.

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.

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