scholarly journals Modeling turbulent heat fluxes over arctic sea ice using a maximum-entropy-production approach

2021 ◽  
Author(s):  
Yi-Ming ZHANG ◽  
Mi-Rong Song ◽  
Chang-Ming Dong ◽  
Ji-Ping Liu
Keyword(s):  
Sea Ice ◽  
Entropy Production ◽  
Maximum Entropy ◽  
Arctic Sea Ice ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Maximum Entropy Production ◽  
Arctic Sea ◽  
Turbulent Heat Fluxes ◽  
Production Approach

scholarly journals Evaluation of Six Atmospheric Reanalyses over Arctic Sea Ice from Winter to Early Summer

2019 ◽  
Vol 32 (14) ◽  
pp. 4121-4143 ◽  
Author(s):  
Robert M. Graham ◽  
Lana Cohen ◽  
Nicole Ritzhaupt ◽  
Benjamin Segger ◽  
Rune G. Graversen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Correlation Coefficients ◽  
Early Summer ◽  
Arctic Sea Ice ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Temperature Bias ◽  
Arctic Sea ◽  
Turbulent Heat Fluxes ◽  
Longwave Flux

AbstractThis study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January–March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3–19 W m−2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April–May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5–79 W m−2) and underestimate the net longwave flux (8–38 W m−2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.

Air-Sea Fluxes following the Unusually Early Ice Retreats in the Arctic

2020 ◽  
Author(s):  
Dongxiao Zhang ◽  
Chidong Zhang ◽  
Jessica Cross ◽  
Calvin Mordy ◽  
Edward Cokelet ◽  
...  
Keyword(s):  
Sea Ice ◽  
Numerical Models ◽  
Green Energy ◽  
Arctic Sea Ice ◽  
Heat Fluxes ◽  
The Arctic ◽  
Energy Fluxes ◽  
The Pacific ◽  
Arctic Sea ◽  
Ice Retreat

<p>The Arctic has been rapidly changing over the last decade, with more frequent unusually early ice retreats in late spring and summer. Vast Arctic areas that were usually covered by sea ice are now exposed to the atmosphere because of earlier ice retreat and later arrival. Assessment of consequential changes in the energy cycle of the Arctic and their potential feedback to the variability of Arctic sea ice and marine ecosystems critically depends on the accuracy of surface flux estimates. In the Pacific sector of the Arctic, earlier ice retreat generally follows the warm Pacific water inflow into the Arctic through the Bering and Chukchi Seas. Due to ice coverage and irregularity of seasonal ice retreats, air-sea flux measurements following the ice retreats has been difficult to plan and execute. A recent technology development is the Unmanned Surface Vehicles (USVs): The long-range USV saildrones are powered by green energy with wind for propulsion and solar energy for instrumentation and vehicle control. NOAA/PMEL and University of Washington scientists have made surface measurements of the ocean and atmosphere in the Pacific Arctic using saildrones for the past several years. In 2019, for the 1<sup>st</sup> time a fleet of six saildrones capable of measuring both turbulent and radiative heat fluxes, wind stress, air-sea CO<sub>2</sub> flux and upper ocean currents was deployed to follow the ice retreat from May to October, with five of the USVs into the Chukchi and Beaufort Seas while one staying in the Bering Sea. These in situ measurements provide rare opportunities of estimating air-sea energy fluxes during a period of rapid reduction in Arctic sea ice in different scenarios: open water after ice melt, free-floating ice bands, and marginal ice zones. In this study, Arctic air-sea heat and momentum fluxes measured by the saildrones are compared to gridded flux products based on satellite data and numerical models to investigate the circumstances under which they agree and differ, and the main sources of their discrepancies. The results will quantify the uncertainty margins in the gridded flux products and provide insights needed to improve their accuracy. We will also discuss the feasibility of using USVs in sustained Arctic observing system to collect benchmark datasets of the changing surface energy fluxes due to rapid sea ice reduction and provide real time data for improved weather and ocean forecasts.  </p>

scholarly journals Variability of Subantarctic Mode Water and Antarctic Intermediate Water in the Drake Passage during the Late-Twentieth and Early-Twenty-First Centuries

2009 ◽  
Vol 22 (13) ◽  
pp. 3661-3688 ◽  
Author(s):  
Alberto C. Naveira Garabato ◽  
Loïc Jullion ◽  
David P. Stevens ◽  
Karen J. Heywood ◽  
Brian A. King
Keyword(s):  
Sea Ice ◽  
Drake Passage ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Intermediate Water ◽  
The West ◽  
Mode Water ◽  
Subantarctic Mode Water ◽  
Turbulent Heat Fluxes ◽  
The Antarctic

Abstract A time series of the physical and biogeochemical properties of Subantarctic Mode Water (SAMW) and Antarctic Intermediate Water (AAIW) in the Drake Passage between 1969 and 2005 is constructed using 24 transects of measurements across the passage. Both water masses have experienced substantial variability on interannual to interdecadal time scales. SAMW is formed by winter overturning on the equatorward flank of the Antarctic Circumpolar Current (ACC) in and to the west of the Drake Passage. Its interannual variability is primarily driven by variations in wintertime air–sea turbulent heat fluxes and net evaporation modulated by the El Niño–Southern Oscillation (ENSO). Despite their spatial proximity, the AAIW in the Drake Passage has a very different source than that of the SAMW because it is ventilated by the northward subduction of Winter Water originating in the Bellingshausen Sea. Changes in AAIW are mainly forced by variability in Winter Water properties resulting from fluctuations in wintertime air–sea turbulent heat fluxes and spring sea ice melting, both of which are linked to predominantly ENSO-driven variations in the intensity of meridional winds to the west of the Antarctic Peninsula. A prominent exception to the prevalent modes of SAMW and AAIW formation occurred in 1998, when strong wind forcing associated with constructive interference between ENSO and the southern annular mode (SAM) triggered a transitory shift to an Ekman-dominated mode of SAMW ventilation and a 1–2-yr shutdown of AAIW production. The interdecadal evolutions of SAMW and AAIW in the Drake Passage are distinct and driven by different processes. SAMW warmed (by ∼0.3°C) and salinified (by ∼0.04) during the 1970s and experienced the reverse trends between 1990 and 2005, when the coldest and freshest SAMW on record was observed. In contrast, AAIW underwent a net freshening (by ∼0.05) between the 1970s and the twenty-first century. Although the reversing changes in SAMW were chiefly forced by a ∼30-yr oscillation in regional air–sea turbulent heat fluxes and precipitation associated with the interdecadal Pacific oscillation, with a SAM-driven intensification of the Ekman supply of Antarctic surface waters from the south contributing significantly too, the freshening of AAIW was linked to the extreme climate change that occurred to the west of the Antarctic Peninsula in recent decades. There, a freshening of the Winter Water ventilating AAIW was brought about by increased precipitation and a retreat of the winter sea ice edge, which were seemingly forced by an interdecadal trend in the SAM and regional positive feedbacks in the air–sea ice coupled climate system. All in all, these findings highlight the role of the major modes of Southern Hemisphere climate variability in driving the evolution of SAMW and AAIW in the Drake Passage region and the wider South Atlantic and suggest that these modes may have contributed significantly to the hemispheric-scale changes undergone by those waters in recent decades.

scholarly journals FEATURES OF SPATIAL-TIME VARIABILITY OF TOTAL TURBULENT HEAT FLUXES AT THE OCEAN-ATMOSPHERE INTERFACE IN THE ATLANTIC

2021 ◽  
pp. 49-55
Author(s):  
Е.А. Averyanova ◽  
Keyword(s):  
Atlantic Ocean ◽  
North Atlantic ◽  
Arctic Sea Ice ◽  
Heat Fluxes ◽  
Total Heat ◽  
Turbulent Heat ◽  
Edge Zone ◽  
The North ◽  
Turbulent Heat Fluxes ◽  
Ice Edge

The features of the spatial distribution of climate values and the coefficients of linear trends of total tur-bulent heat fluxes are revealed, based on NCEP/NCAR reanalysis data for 1950–2020 for the Atlantic Ocean. Variability of total turbulent heat fluxes is investigated on scales of more than 10 and more than 30 years. It is shown that the trends of average annual total heat fluxes significant at 95% level in most part of the Atlantic Ocean area are negative (except for the western parts of anticyclonic gyres and area of arctic sea ice edge). It is confirmed that the maxima of the low-frequency variability of the total heat fluxes correspond to important energy-active zones of the Atlantic, they are North Atlantic deep-water mass formation region, ice edge zone in the north of the North Atlantic and the Atlantic sector of the Arc-tic Ocean.

scholarly journals Arctic sea ice anomalies during the MOSAiC winter 2019/20

2021 ◽  
Author(s):  
Klaus Dethloff ◽  
Wieslaw Maslowski ◽  
Stefan Hendricks ◽  
Younjoo Lee ◽  
Helge F. Goessling ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Barents Sea ◽  
Arctic Sea Ice ◽  
Heat Fluxes ◽  
The Arctic ◽  
Turbulent Heat ◽  
Central Arctic Ocean ◽  
Sea Ice Thickness ◽  
The Arctic Oscillation

Abstract. As the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project went into effect during the winter of 2019/2020, the Arctic Oscillation (AO) has experienced some of the largest shifts from a highly negative index in November 2019 to an extremely positive index during January-February-March (JFM) 2020. Here we analyse the sea ice thickness (SIT) distribution based on CryoSat-2/SMOS satellite data augmented with results from the hindcast simulation by the fully coupled Regional Arctic System Model (RASM) for the time period from November 2019 through March 2020. A notable result of the positive AO phase during JFM 2020 were large SIT anomalies, up to 1.3 m, which emerged in the Barents-Sea (BS), along the northeastern Canadian coast and in parts of the central Arctic Ocean. These anomalies appear to be driven by nonlinear interactions between thermodynamic and dynamic processes. In particular, in the Barents- and Kara Seas (BKS) they are a result of an enhanced ice growth connected with the colder temperature anomalies and the consequence of intensified atmospheric-driven sea ice transport and deformations (i.e. divergence and shear) in this area. Low-pressure anomalies, which developed over the Eastern Arctic during JFM 2020, increased northerly winds from the cold Arctic Ocean to the BS and accelerated the southward drift of the MOSAiC ice floe. The satellite-derived and model-simulated sea ice velocity anomalies, which compared well during JFM 2020, indicate a strong acceleration of the Transpolar Drift relative to the mean for the past decade, with intensified speeds up to 6 km/day. As a consequence, sea ice transport and deformations driven by atmospheric wind forcing accounted for bulk of SIT anomalies, especially in January and February 2020. The unusual AO shift and the related sea ice anomalies during the MOSAiC winter 2019/20 are within the range of simulated states in the forecast ensemble. RASM intra-annual ensemble forecast simulations, forced with different atmospheric boundary conditions from November 1, 2019 through April 30, 2020, show a pronounced internally generated variability in the sea ice volume. A comparison of the respective SIT distribution and turbulent heat fluxes during the positive AO phase in JFM 2020 and the negative AO phase in JFM 2010 further corroborates the conclusion, that winter sea ice conditions of the Arctic Ocean can be significantly altered by AO variability.

scholarly journals The importance of the sea ice marginal zone for the surface turbulent heat fluxes in Arctic on the basis of NCEP CFSR reanalysis

2021 ◽  
Vol 21 (2) ◽  
pp. 1-8
Author(s):  
J. Selivanova ◽  
P. Verezemskaya ◽  
N. Tilinina ◽  
S. Gulev ◽  
S. Dobrolyubov
Keyword(s):  
Sea Ice ◽  
Marginal Zone ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Turbulent Heat Fluxes

scholarly journals On the statistical properties of sea ice lead fraction and heat fluxes in the Arctic

2020 ◽  
Author(s):  
Einar Örn Ólason ◽  
Pierre Rampal ◽  
Véronique Dansereau
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Heat Fluxes ◽  
Statistical Properties ◽  
The Arctic ◽  
High Flux ◽  
Spatial Scaling ◽  
Arctic Sea ◽  
Multifractal Scaling ◽  
Probability Density Function Pdf

Abstract. In this paper we explore several statistical properties of the observed and simulated Arctic sea-ice lead-fraction, as well as the statistics of simulated Arctic ocean-atmosphere heat fluxes. We first show that the probability density function (PDF) and the monofractal spatial scaling of the observed lead fraction in the Central Arctic are both well represented by our model, neXtSIM. Given that the heat flux through leads may be up to two orders of magnitude larger than that through unbroken ice we then explore the statistical properties (PDF and spatial scaling) of the heat fluxes simulated by neXtSIM. We demonstrate that the modelled heat fluxes present a multifractal scaling in the Central Arctic, where heat fluxes through leads dominate the high-flux tail of the PDF. In the Central Arctic, the high-flux tail of the PDF is dominated by an exponential decay, which we attribute to the presence of coastal polynyas. Finally, we show that the scaling of simulated lead fraction and heat fluxes depend weakly on the model resolution and discuss the role sub-grid scale parameterisations of the ice heterogeneity may have in improving this result.

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