scholarly journals The Accuracy of Sea Ice Drafts Measured from U.S. Navy Submarines

2007 ◽  
Vol 24 (11) ◽  
pp. 1936-1949 ◽  
Author(s):  
D. A. Rothrock ◽  
Mark Wensnahan
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Open Water ◽  
The Arctic ◽  
Precision Error ◽  
Sources Of Error ◽  
Speed Error ◽  
The Arctic Ocean ◽  
Recorded Data ◽  
Data Source

Abstract Navy submarines in the Arctic Ocean routinely obtain observations from an upward-looking sonar of the draft of the sea ice cover overhead. Draft data are now publicly available from some 40 cruises from 1975 to 2000 covering over 120 000 km of track in roughly the central half of the Arctic Ocean. To apply these observations to geophysics, error estimates are needed. This paper assesses how well the correction of the data during normal processing accounts for the major sources of error in the draft data from U.S. Navy submarines and what errors remain in the data. The error treated is the error for the average draft over tens of kilometers. The following sources of error are considered: measurement precision error; errors in identifying open water (as ice of zero draft); sound speed error; errors caused by variable sonar footprint size, by uncontrolled gain and thresholds, and by ship’s trim; and differences between data from analog charts and digitally recorded data. The bias with respect to the actual draft is +29 cm and is important both for knowing the actual ice draft and for comparing drafts from submarines with thicknesses in models and with draft, thickness, or freeboard estimated by other vehicles and technologies. The standard deviation is 25 cm. This number estimates the repeatability and comparability of draft measurements by U.S. Navy submarines and is important for examining the submarine data for regional and temporal variation. These errors are tolerable for an operational data source with a signal many meters in amplitude.

Changes in phytoplankton concentration now drive increased Arctic Ocean primary production

Science ◽  
2020 ◽  
Vol 369 (6500) ◽  
pp. 198-202 ◽  
Author(s):  
K. M. Lewis ◽  
G. L. van Dijken ◽  
K. R. Arrigo
Keyword(s):  
Sea Ice ◽  
Primary Production ◽  
Arctic Ocean ◽  
Open Water ◽  
Water Area ◽  
The Arctic ◽  
Carbon Export ◽  
Phytoplankton Primary Production ◽  
Open Water Area ◽  
The Arctic Ocean

Historically, sea ice loss in the Arctic Ocean has promoted increased phytoplankton primary production because of the greater open water area and a longer growing season. However, debate remains about whether primary production will continue to rise should sea ice decline further. Using an ocean color algorithm parameterized for the Arctic Ocean, we show that primary production increased by 57% between 1998 and 2018. Surprisingly, whereas increases were due to widespread sea ice loss during the first decade, the subsequent rise in primary production was driven primarily by increased phytoplankton biomass, which was likely sustained by an influx of new nutrients. This suggests a future Arctic Ocean that can support higher trophic-level production and additional carbon export.

Increased Arctic Ocean sea ice loss through the Canadian Arctic Archipelago under a warmer climate

2020 ◽  
Author(s):  
Stephen Howell ◽  
Mike Brady
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Canadian Arctic ◽  
Open Water ◽  
The Arctic ◽  
Canadian Arctic Archipelago ◽  
Nares Strait ◽  
The Arctic Ocean ◽  
Important Pathway

<p>The ice arches that ring the northern Canadian Arctic Archipelago have historically blocked the inflow of Arctic Ocean sea ice for the majority of the year. However, annual average air temperature in northern Canada has increased by more than 2°C over the past 65+ years and a warmer climate is expected to contribute to the deterioration of these ice arches, which in turn has implications for the overall loss of Arctic Ocean sea ice. We investigated the effect of warming on the Arctic Ocean ice area flux into the Canadian Arctic Archipelago using a 22-year record (1997-2018) of ice exchange derived from RADARSAT-1 and RADARSAT-2 imagery. Results indicated that there has been a significant increase in the amount of Arctic Ocean sea ice (10<sup>3</sup> km<sup>2</sup>/year) entering the northern Canadian Arctic Archipelago over the period of 1997-2018. The increased Arctic Ocean ice area flux was associated with reduced ice arch duration but also with faster (thinner) moving ice and more southern latitude open water leeway as a result of the Canadian Arctic Archipelago’s long-term transition to a younger and thinner ice regime. Remarkably, in 2016, the Arctic Ocean ice area flux into the Canadian Arctic Archipelago (161x10<sup>3</sup> km<sup>2</sup>) was 7 times greater than the 1997-2018 average (23x10<sup>3</sup> km<sup>2</sup>) and almost double the 2007 ice area flux into Nares Strait (87x10<sup>3</sup> km<sup>2</sup>). Indeed, Nares Strait is known to be an important pathway for Arctic Ocean ice loss however, the results of this study suggest that with continued warming, the Canadian Arctic Archipelago may also become a large contributor to Arctic Ocean ice loss.</p>

A comparison of factors that led to the extreme sea ice minima in the 21st century in the Arctic Ocean

2021 ◽  
pp. 1-56
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Atmospheric Circulation ◽  
21St Century ◽  
Open Water ◽  
The Arctic ◽  
Area Loss ◽  
The Arctic Ocean ◽  
The Difference

Abstract The extreme Arctic sea ice minima in the 21st century have been attributed to multiple factors, such as anomalous atmospheric circulation, excess solar radiation absorbed by open ocean, and thinning sea ice in a warming world. Most likely it is the combination of these factors that drive the extreme sea ice minima, but it has not been quantified, how the factors rank in setting the conditions for these events. To address this question, the sea ice budget of an Arctic regional sea ice-ocean model forced by atmospheric reanalysis data is analyzed to assess the development of the observed sea ice minima. Results show that the ice area difference in the years 2012, 2019, and 2007 is driven to over 60% by the difference in summertime sea ice area loss due to air-ocean heat flux over open water. Other contributions are small. For the years 2012 and 2020 the situation is different and more complex. The air-ice heat flux causes more sea ice area loss in summer 2020 than in 2012 due to warmer air temperatures, but this difference in sea ice area loss is compensated by reduced advective sea ice loss out of the Arctic Ocean mainly caused by the relaxation of the Arctic Dipole. The difference in open water area in early August leads to different air-ocean heat fluxes, which distinguishes the sea ice minima in 2012 and 2020. Further, sensitivity experiments indicate that both the atmospheric circulation associated with the Arctic Dipole and extreme storms are essential conditions for a new low record of sea ice extent.

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.

scholarly journals The Influence of Cloud and Surface Properties on the Arctic Ocean Shortwave Radiation Budget in Coupled Models*

2008 ◽  
Vol 21 (5) ◽  
pp. 866-882 ◽  
Author(s):  
Irina V. Gorodetskaya ◽  
L-Bruno Tremblay ◽  
Beate Liepert ◽  
Mark A. Cane ◽  
Richard I. Cullather
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Liquid Water ◽  
Surface Albedo ◽  
Liquid Water Content ◽  
Radiation Budget ◽  
The Arctic ◽  
Coupled Models ◽  
Arctic Clouds ◽  
The Arctic Ocean

Abstract The impact of Arctic sea ice concentrations, surface albedo, cloud fraction, and cloud ice and liquid water paths on the surface shortwave (SW) radiation budget is analyzed in the twentieth-century simulations of three coupled models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The models are the Goddard Institute for Space Studies Model E-R (GISS-ER), the Met Office Third Hadley Centre Coupled Ocean–Atmosphere GCM (UKMO HadCM3), and the National Center for Atmosphere Research Community Climate System Model, version 3 (NCAR CCSM3). In agreement with observations, the models all have high Arctic mean cloud fractions in summer; however, large differences are found in the cloud ice and liquid water contents. The simulated Arctic clouds of CCSM3 have the highest liquid water content, greatly exceeding the values observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. Both GISS-ER and HadCM3 lack liquid water and have excessive ice amounts in Arctic clouds compared to SHEBA observations. In CCSM3, the high surface albedo and strong cloud SW radiative forcing both significantly decrease the amount of SW radiation absorbed by the Arctic Ocean surface during the summer. In the GISS-ER and HadCM3 models, the surface and cloud effects compensate one another: GISS-ER has both a higher summer surface albedo and a larger surface incoming SW flux when compared to HadCM3. Because of the differences in the models’ cloud and surface properties, the Arctic Ocean surface gains about 20% and 40% more solar energy during the melt period in the GISS-ER and HadCM3 models, respectively, compared to CCSM3. In twenty-first-century climate runs, discrepancies in the surface net SW flux partly explain the range in the models’ sea ice area changes. Substantial decrease in sea ice area simulated during the twenty-first century in CCSM3 is associated with a large drop in surface albedo that is only partly compensated by increased cloud SW forcing. In this model, an initially high cloud liquid water content reduces the effect of the increase in cloud fraction and cloud liquid water on the cloud optical thickness, limiting the ability of clouds to compensate for the large surface albedo decrease. In HadCM3 and GISS-ER, the compensation of the surface albedo and cloud SW forcing results in negligible changes in the net SW flux and is one of the factors explaining moderate future sea ice area trends. Thus, model representations of cloud properties for today’s climate determine the ability of clouds to compensate for the effect of surface albedo decrease on the future shortwave radiative budget of the Arctic Ocean and, as a consequence, the sea ice mass balance.

scholarly journals Attribution of the Recent Winter Sea Ice Decline over the Atlantic Sector of the Arctic Ocean*

2015 ◽  
Vol 28 (10) ◽  
pp. 4027-4033 ◽  
Author(s):  
Doo-Sun R. Park ◽  
Sukyoung Lee ◽  
Steven B. Feldstein
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Environmental Changes ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Positive Trend ◽  
Ir Radiation ◽  
Atlantic Sector ◽  
Sea Ice Decline ◽  
The Arctic Ocean

Abstract Wintertime Arctic sea ice extent has been declining since the late twentieth century, particularly over the Atlantic sector that encompasses the Barents–Kara Seas and Baffin Bay. This sea ice decline is attributable to various Arctic environmental changes, such as enhanced downward infrared (IR) radiation, preseason sea ice reduction, enhanced inflow of warm Atlantic water into the Arctic Ocean, and sea ice export. However, their relative contributions are uncertain. Utilizing ERA-Interim and satellite-based data, it is shown here that a positive trend of downward IR radiation accounts for nearly half of the sea ice concentration (SIC) decline during the 1979–2011 winter over the Atlantic sector. Furthermore, the study shows that the Arctic downward IR radiation increase is driven by horizontal atmospheric water flux and warm air advection into the Arctic, not by evaporation from the Arctic Ocean. These findings suggest that most of the winter SIC trends can be attributed to changes in the large-scale atmospheric circulations.

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