scholarly journals Spatial Variability of Surface-Level State Variables over Arctic Sea Ice

2015 ◽  
Vol 28 (16) ◽  
pp. 6360-6380
Author(s):  
Edgar L Andreas ◽  
Rachel E. Jordan
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Air Temperature ◽  
Cloud Cover ◽  
Numerical Models ◽  
Grid Cell ◽  
Longwave Radiation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Surface Level

Abstract Numerical models of the atmosphere, oceans, and sea ice are divided into horizontal grid cells that can range in size from a few kilometers to hundreds of kilometers. In these models, many surface-level variables are assumed to be uniform over a grid cell. Using a year of in situ data from the experiment to study the Surface Heat Budget of the Arctic Ocean (SHEBA), the authors investigate the accuracy of this assumption of gridcell uniformity for the surface-level variables pressure, air temperature, wind speed, humidity, and incoming longwave radiation. The paper bases its analysis on three statistics: the monthly average and, for each season, the spatial correlation function and the spatial bias. For five SHEBA sites, which had a maximum separation of 12 km, the analysis supports the assumption of gridcell uniformity in pressure, air temperature, wind speed, and humidity in all seasons. In winter, when the incidence of fractional cloudiness is largest, the incoming longwave radiation may not be uniform over a grid cell. In other seasons, the bimodal distribution in cloud cover—either clear skies or total cloud cover—tends to homogenize the incoming radiation at scales of 12 km and less.

scholarly journals Mechanism of Seasonal Arctic Sea Ice Evolution and Arctic Amplification

2016 ◽  
Author(s):  
Kwang-Yul Kim ◽  
Benjamin D. Hamlington ◽  
Hanna Na ◽  
Jinju Kim
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
The Arctic ◽  
Turbulent Heat ◽  
Arctic Amplification ◽  
Ice Melting ◽  
Downward Longwave Radiation

Abstract. Sea ice melting is proposed as a primary reason for the Artic amplification, although physical mechanism of the Arctic amplification and its connection with sea ice melting is still in debate. In the present study, monthly ERA-interim reanalysis data are analyzed via cyclostationary empirical orthogonal function analysis to understand the seasonal mechanism of sea ice melting in the Arctic Ocean and the Arctic amplification. While sea ice melting is widespread over much of the perimeter of the Arctic Ocean in summer, sea ice remains to be thin in winter only in the Barents-Kara Seas. Excessive turbulent heat flux through the sea surface exposed to air due to sea ice melting warms the atmospheric column. Warmer air increases the downward longwave radiation and subsequently surface air temperature, which facilitates sea surface remains to be ice free. A 1 % reduction in sea ice concentration in winter leads to ~ 0.76 W m−2 increase in upward heat flux, ~ 0.07 K increase in 850 hPa air temperature, ~ 0.97 W m−2 increase in downward longwave radiation, and ~ 0.26 K increase in surface air temperature. This positive feedback mechanism is not clearly observed in the Laptev, East Siberian, Chukchi, and Beaufort Seas, since sea ice refreezes in late fall (November) before excessive turbulent heat flux is available for warming the atmospheric column in winter. A detailed seasonal heat budget is presented in order to understand specific differences between the Barents-Kara Seas and Laptev, East Siberian, Chukchi, and Beaufort Seas.

Spring Arctic Atmospheric Preconditioning: Do Not Rule Out Shortwave Radiation Just Yet

2018 ◽  
Vol 31 (11) ◽  
pp. 4225-4240 ◽  
Author(s):  
Joseph Sedlar
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Atmospheric Transport ◽  
High Surface ◽  
Longwave Radiation ◽  
Absolute Magnitude ◽  
Arctic Sea Ice ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Ice Melt

Abstract Springtime atmospheric preconditioning of Arctic sea ice for enhanced or buffered sea ice melt during the subsequent melt year has received considerable research focus. Studies have identified enhanced poleward atmospheric transport of moisture and heat during spring, leading to increased emission of longwave radiation to the surface. Simultaneously, these studies ruled out the role of shortwave radiation as an effective preconditioning mechanism because of relatively weak incident solar radiation, high surface albedo from sea ice and snow, and increased clouds during spring. These conclusions are derived primarily from atmospheric reanalysis, which may not always accurately represent the Arctic climate system. Here, top-of-atmosphere shortwave radiation observations from a state-of-the-art satellite sensor are compared with ERA-Interim reanalysis to examine similarities and differences in the springtime absorbed shortwave radiation (ASR) over the Arctic Ocean. Distinct biases in regional location and absolute magnitude of ASR anomalies are found between satellite-based measurements and reanalysis. Observations indicate separability between ASR anomalies in spring corresponding to anomalously low and high ice extents in September; the reanalysis fails to capture the full extent of this separability. The causes for the difference in ASR anomalies between observations and reanalysis are considered in terms of the variability in surface albedo and cloud presence. Additionally, biases in reanalysis cloud water during spring are presented and are considered for their impact on overestimating spring downwelling longwave anomalies. Taken together, shortwave radiation should not be overlooked as a contributing mechanism to springtime Arctic atmospheric preconditioning.

scholarly journals Relationships between Arctic Sea Ice and Clouds during Autumn

2008 ◽  
Vol 21 (18) ◽  
pp. 4799-4810 ◽  
Author(s):  
Axel J. Schweiger ◽  
Ron W. Lindsay ◽  
Steve Vavrus ◽  
Jennifer A. Francis
Keyword(s):  
Sea Ice ◽  
Cloud Cover ◽  
Cloud Amount ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Simultaneous Increase ◽  
Temperature Structure ◽  
Infrared Observation ◽  
Near Surface ◽  
Subsequent Decrease

Abstract The connection between sea ice variability and cloud cover over the Arctic seas during autumn is investigated by analyzing the 40-yr ECMWF Re-Analysis (ERA-40) products and the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) Polar Pathfinder satellite datasets. It is found that cloud cover variability near the sea ice margins is strongly linked to sea ice variability. Sea ice retreat is linked to a decrease in low-level cloud amount and a simultaneous increase in midlevel clouds. This pattern is apparent in both data sources. Changes in cloud cover can be explained by changes in the atmospheric temperature structure and an increase in near-surface temperatures resulting from the removal of sea ice. The subsequent decrease in static stability and deepening of the atmospheric boundary layer apparently contribute to the rise in cloud level. The radiative effect of this change is relatively small, as the direct radiative effects of cloud cover changes are compensated for by changes in the temperature and humidity profiles associated with varying ice conditions.

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 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 Fate of sea ice in the 'New Arctic': A database of daily Lagrangian Arctic sea ice parcel drift tracks with coincident ice and atmospheric conditions

2021 ◽  
Author(s):  
Sean Horvath ◽  
Linette Boisvert ◽  
Chelsea Parker ◽  
Melinda Webster ◽  
Patrick Taylor ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Mass Balance ◽  
Air Temperature ◽  
Snow Depth ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Ice Mass Balance ◽  
Temperature And Pressure

Abstract. Since the early 2000s, sea ice has experienced an increased rate of decline in thickness and extent and transitioned to a seasonal ice cover. This shift to thinner, seasonal ice in the 'New Arctic' is accompanied by a reshuffling of energy flows at the surface. Understanding the magnitude and nature of this reshuffling and the feedbacks therein remains limited. A novel database is presented that combines satellite observations, model output, and reanalysis data with daily sea ice parcel drift tracks produced in a Lagrangian framework. This dataset consists of daily time series of sea ice parcel locations, sea ice and snow conditions, and atmospheric states. Building on previous work, this dataset includes remotely sensed radiative and turbulent fluxes from which the surface energy budget can be calculated. Additionally, flags indicate when sea ice parcels travel within cyclones, recording distance and direction from the cyclone center. The database drift track was evaluated by comparison with sea ice mass balance buoys. Results show ice parcels generally remain within 100km of the corresponding buoy, with a mean distance of 82.6 km and median distance of 54 km. The sea ice mass balance buoys also provide recordings of sea ice thickness, snow depth, and air temperature and pressure which were compared to this database. Ice thickness and snow depth typically are less accurate than air temperature and pressure due to the high spatial variability of the former two quantities when compared to a point measurement. The correlations between the ice parcel and buoy data are high, which highlights the accuracy of this Lagrangian database in capturing the seasonal changes and evolution of sea ice. This database has multiple applications for the scientific community; it can be used to study the processes that influence individual sea ice parcel time series, or to explore generalized summary statistics and trends across the Arctic. Applications such as these may shed light on the atmosphere-snow-sea ice interactions in the changing Arctic environment.

scholarly journals Suppression of Arctic sea ice growth by winter clouds and snowfall

2021 ◽  
Author(s):  
Won-il Lim ◽  
Hyo-Seok Park ◽  
Andrew Stewart ◽  
Kyong-Hwan Seo
Keyword(s):  
Sea Ice ◽  
Longwave Radiation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Ice Growth ◽  
Downward Longwave Radiation ◽  
Arctic Sea ◽  
The Impact

Abstract The ongoing Arctic warming has been pronounced in winter and has been associated with an increase in downward longwave radiation. While previous studies have demonstrated that poleward moisture flux into the Arctic strengthens downward longwave radiation, less attention has been given to the impact of the accompanying increase in snowfall. Here, utilizing state-of-the art sea ice models, we show that typical winter snowfall anomalies of 1.0 cm, accompanied by positive downward longwave radiation anomalies of ~5 W m-2 can decrease sea ice thickness by around 5 cm in the following spring over the Eurasian Seas. This basin-wide ice thinning is followed by a shrinking of summer ice extent in extreme cases. In the winter of 2016–17, anomalously strong warm/moist air transport combined with ~2.5 cm increase in snowfall decreased spring ice thickness by ~10 cm and decreased the following summer sea ice extent by 5–30%. Projected future reductions in the thickness of Arctic sea ice and snow will amplify the impact of anomalous winter snowfall events on winter sea ice growth and seasonal sea ice thickness.

scholarly journals Effect of retreating sea ice on Arctic cloud cover in simulated recent global warming

2015 ◽  
Vol 15 (12) ◽  
pp. 17527-17552 ◽  
Author(s):  
M. Abe ◽  
T. Nozawa ◽  
T. Ogura ◽  
K. Takata
Keyword(s):  
Global Warming ◽  
Sea Ice ◽  
General Circulation ◽  
Cloud Cover ◽  
Lower Troposphere ◽  
Cloud Fraction ◽  
Arctic Sea Ice ◽  
Thin Layers ◽  
The Arctic ◽  
Downward Longwave Radiation

Abstract. This study investigates the effect of sea ice reduction on Arctic cloud cover in historical simulations with the coupled atmosphere–ocean general circulation model MIROC5. During simulated global warming since the 1970s, the Arctic sea ice extent has reduced substantially, particularly in September. This simulated reduction is consistent with satellite observation results. However, the Arctic cloud cover increases significantly during October at grids with significant reductions in sea ice because of the enhanced heat and moisture flux from the underlying ocean. Cloud fraction increases in the lower troposphere. However, the cloud fraction in the surface thin layers just above the ocean decreases despite the increased moisture because the surface air temperature rises strikingly in the thin layers and the relative humidity decreases. As the cloud cover increases, the cloud radiative effect in surface downward longwave radiation (DLR) increases by approximately 40–60 % compared to a change in clear-sky surface DLR. These results suggest that an increase in the Arctic cloud cover as a result of a reduction in sea ice could further melt the sea ice and enhance the feedback processes of the Arctic amplification in future projections.

scholarly journals Seasonal co-variability of surface downwelling longwave radiation for the 1982–2009 period in the Arctic

2017 ◽  
Vol 14 ◽  
pp. 139-143 ◽  
Author(s):  
Mauro Boccolari ◽  
Flavio Parmiggiani
Keyword(s):  
Sea Ice ◽  
Spatial Patterns ◽  
Barents Sea ◽  
Longwave Radiation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Climate Oscillation ◽  
Main Technique ◽  
Downwelling Longwave Radiation

Abstract. Trends and variability of the Arctic sea ice extent depend on various physical processes, including those related to changes in radiative fluxes, which are associated with cloudiness and water vapour and, in turn, with the atmospheric moisture transport over the Arctic. Aim of this work was: (i) to extract seasonal spatial patterns of the co-variability between the sea ice concentration (SIC) and the surface downwelling longwave radiation (SDL) in the Arctic Ocean during the 1982–2009 period; and (ii) to estimate the correlation coefficients between these patterns and the indices associated to some climate oscillation modes (AO, NAO, PNA, PDO and AMO). Maximum Covariance Analysis (MCA) was the main technique used in this study. Among our results, we highlight two areas of maximum co-variability SIC/SDL centered over the Barents Sea in winter and over the Chukchi Sea in summer. In addition, some statistically significant correlations (at 95 %) between the spatial patterns of co-variability and climate oscillation indices were assessed, e.g. with PDO and AMO in November–January, with NAO and AMO in May–July, and with PNA in August–October.

scholarly journals Summertime changes in climate extremes over the peripheral Arctic regions after a sudden sea ice retreat

2021 ◽  
Author(s):  
Steve Delhaye ◽  
Thierry Fichefet ◽  
François Massonnet ◽  
David Docquier ◽  
Rym Msadek ◽  
...  
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Climate Extremes ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Maximum Surface ◽  
Temperature And Precipitation ◽  
Arctic Regions ◽  
Arctic Sea

Abstract. The retreat of Arctic sea ice is frequently considered as a possible driver of changes in climate extremes in the Arctic and possibly down to mid-latitudes. However, it is unclear how the atmosphere will respond to a near-total retreat of summer Arctic sea ice, a reality that might occur in the foreseeable future. This study explores this question by conducting sensitivity experiments with two global coupled climate models run at two different horizontal resolutions to investigate the change in temperature and precipitation extremes during summer over peripheral Arctic regions following a sudden reduction in summer Arctic sea ice cover. An increase in frequency and persistence of maximum surface air temperature is found in all peripheral Arctic regions during the summer when sea ice loss occurs. For each million km2 of Arctic sea ice extent reduction, the absolute frequency of days exceeding the surface air temperature of the climatological 90th percentile increases by ~4 % over the Svalbard area, and the duration of warm spells increases by ~1 day per month over the same region. Furthermore, we find that the 10th percentile of surface daily air temperature increases more than the 90th percentile, leading to a weakened diurnal cycle of surface air temperature. Finally, an increase in extreme precipitation, which is less robust (statistically speaking) than the increase in extreme temperatures, is found in all regions in summer. These findings suggest that a sudden retreat of summer Arctic sea ice clearly impacts the extremes in maximum surface air temperature and precipitation over the peripheral Arctic regions with the largest influence over inhabited islands such as Svalbard or Northern Canada. Nonetheless, even with a large sea ice reduction in regions close to the North Pole, the local precipitation response is relatively small compared to internal climate variability.

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