Investigating the Relation of Arctic Tropospheric Bro Derived by Satellite Remote Sensing to Sea Ice Age and Meteorological Driving Mechanisms Under the Impact of Arctic Amplification

2020 ◽  
Author(s):  
Ilias Bougoudis ◽  
Anne-Marlene Blechschmidt ◽  
Andreas Richter ◽  
Sora Seo ◽  
John Burrows
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Air Temperature ◽  
Ice Age ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Arctic Amplification ◽  
German Research Foundation ◽  
The Impact

<p>Arctic Amplification, the rapid increase of air temperature in higher latitudes over the last decades, is expected to have drastic impacts on all the sub-systems of the Arctic ecosystem. Bromine Oxides play a key role in the atmospheric composition of the Arctic. During polar spring, bromine molecules are released from young sea ice covered regions.  A rapid chemical chain reaction starts, the -so called 'bromine explosion', which depletes ozone, alters the production of OH, and thereby eventually changes the oxidizing capacity of the troposphere. Halogens oxidize elemental to gaseous mercury, which may then be deposited and harm the ecosystem. Based on current literature, there is considerable uncertainty on the impact of Arctic Amplification on halogen evolution. On one hand, the melting of multi-year sea ice should result in formation of more young sea ice, which favors bromine release. On the other hand, BrO explosion events are triggered by low temperatures, an effect expected to be reduced due to Arctic Amplification. Moreover, changes of other meteorological drivers, such as cyclone frequency and wind speed may impact on BrO amounts in the Arctic troposphere.</p><p>In this study, a long-term time-series of tropospheric BrO derived from 4 UV-VIS instruments (GOME, SCIAMACHY, GOME-2A, GOME-2B) is used as a basis, in order to investigate the impact of Arctic Amplification on BrO amounts in the Arctic. The long-term BrO data is being compared to sea ice age (NSIDC) and meteorological (air temperature, mean sea level pressure, wind speed and boundary layer height from ERA-5 & ASR-2) data. Our results focus on determining the relation between tropospheric BrO and its drivers, and especially on how the drivers impact on the formation of BrO plumes. Different cases studies throughout the 22 years of the BrO dataset were performed and evaluated. The changes in the tropospheric BrO abundances come in general agreement with changes in the drivers of BrO explosion events.</p><p> </p><p>We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 268020496 – TRR 172, within the Transregional Collaborative Research Center “ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)³”.</p>

scholarly journals Long-term Time-series of Arctic Tropospheric BrO derived from UV-VIS Satellite Remote Sensing and its Relation to First Year Sea Ice

2020 ◽  
Author(s):  
Ilias Bougoudis ◽  
Anne-Marlene Blechschmidt ◽  
Andreas Richter ◽  
Sora Seo ◽  
John Philip Burrows ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ice Age ◽  
The Arctic ◽  
First Year ◽  
Arctic Amplification ◽  
Vertical Column ◽  
The Impact ◽  
Good Agreement

Abstract. Arctic Amplification describes the rapid increase of the air temperature in the past three decades in the Arctic, which impacts on physicochemical conditions, the ecosystem and biogeochemistry. Every polar spring, the BrO explosion, a series of chemical reactions that release bromine molecules to the troposphere occurs over sea ice covered regions. This autocatalytic mechanism depletes boundary layer and tropospheric ozone, thereby changes the oxidizing capacity of the atmosphere and facilitates the deposition of metals (e.g. Hg). In this study, we present a 22 year consolidated and consistent tropospheric BrO dataset, derived from four different UV-VIS satellite instruments and investigate the BrO evolution under the impact of Arctic Amplification. The retrieval data products from the different sensors are compared during periods of overlap and show good agreement. By studying the sensor merged time-series of tropospheric BrO vertical column densities, we find an increase in the magnitude of BrO explosion events under the impact of Arctic Amplification with an upward trend of about 1.5 % per year. Furthermore, the areas where BrO plumes frequently appear have changed, extending over larger regions in the Arctic during more recent years. Comparison to sea ice age data suggests that the reported changes in tropospheric BrO are linked in a complex way to the increase of first-year ice extent in the Arctic.

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>

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.

Exploring ice core sea ice proxies through process-based modelling

2020 ◽  
Author(s):  
Rachael Rhodes ◽  
Xin Yang ◽  
Eric Wolff
Keyword(s):  
Sea Ice ◽  
Atmospheric Chemistry ◽  
Ice Core ◽  
Ice Cores ◽  
Sea Salt ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Sea Salt Aerosol ◽  
Aerosol Emission ◽  
The Impact

<p>It is important to understand the magnitude and rate of past sea ice changes, as well as their timing relative to abrupt shifts in other components of Earth’s climate system. Furthermore, records of past sea ice over the last few centuries are urgently needed to assess the scale of natural (internal) variability over decadal timescales. By continuously recording past atmospheric composition, polar ice cores have the potential to document changing sea ice conditions if atmospheric chemistry is altered.  Sea salt aerosol, specifically sodium (Na), and bromine enrichment (Br<sub>enr</sub>, Br/Na enriched relative to seawater ratio) are two ice core sea ice proxies suggested following this premise.</p><p>Here we aim to move beyond a conceptual understanding of the controls on Na and Br<sub>enr</sub> in ice cores by using process-based modelling to test hypotheses. We present results of experiments using a 3D global chemical transport model (p-TOMCAT) that represents marine aerosol emission, transport and deposition. Critically, the complex atmospheric chemistry of bromine is also included. Three fundamental issues will be examined: 1) the partitioning of Br between gas and aerosol phases, 2) sea salt aerosol production from first-year versus multi-year sea ice, and 3) the impact of increased acidity in the atmosphere due to human activity in the Arctic.</p>

scholarly journals Long-term time series of Arctic tropospheric BrO derived from UV–VIS satellite remote sensing and its relation to first-year sea ice

2020 ◽  
Vol 20 (20) ◽  
pp. 11869-11892
Author(s):  
Ilias Bougoudis ◽  
Anne-Marlene Blechschmidt ◽  
Andreas Richter ◽  
Sora Seo ◽  
John Philip Burrows ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ice Age ◽  
The Arctic ◽  
First Year ◽  
Vertical Column ◽  
Chain Reactions ◽  
Heterogeneous Chain ◽  
Good Agreement

Abstract. Every polar spring, phenomena called bromine explosions occur over sea ice. These bromine explosions comprise photochemical heterogeneous chain reactions that release bromine molecules, Br2, to the troposphere and lead to tropospheric plumes of bromine monoxide, BrO. This autocatalytic mechanism depletes ozone, O3, in the boundary layer and troposphere and thereby changes the oxidizing capacity of the atmosphere. The phenomenon also leads to accelerated deposition of metals (e.g., Hg). In this study, we present a 22-year (1996 to 2017) consolidated and consistent tropospheric BrO dataset north of 70∘ N, derived from four different ultraviolet–visible (UV–VIS) satellite instruments (GOME, SCIAMACHY, GOME-2A and GOME-2B). The retrieval data products from the different sensors are compared during periods of overlap and show good agreement (correlations of 0.82–0.98 between the sensors). From our merged time series of tropospheric BrO vertical column densities (VCDs), we infer changes in the bromine explosions and thus an increase in the extent and magnitude of tropospheric BrO plumes during the period of Arctic warming. We determined an increasing trend of about 1.5 % of the tropospheric BrO VCDs per year during polar springs, while the size of the areas where enhanced tropospheric BrO VCDs can be found has increased about 896 km2 yr−1. We infer from comparisons and correlations with sea ice age data that the reported changes in the extent and magnitude of tropospheric BrO VCDs are moderately related to the increase in first-year ice extent in the Arctic north of 70∘ N, both temporally and spatially, with a correlation coefficient of 0.32. However, the BrO plumes and thus bromine explosions show significant variability, which also depends, apart from sea ice, on meteorological conditions.

The impact of denying sea ice information on the predictability of atmospheric processes over the Arctic and at mid-latitude regions

2020 ◽  
Author(s):  
Leandro Ponsoni ◽  
Daniela Flocco ◽  
François Massonnet ◽  
Steve Delhaye ◽  
Ed Hawkins ◽  
...  
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Model Comparison ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atmospheric Processes ◽  
Ice Conditions ◽  
The Impact

<p>In this work, we make use of an inter-model comparison and of a perfect model approach, in which model outputs are used as true reference states, to assess the impact that denying sea ice information has on the prediction of atmospheric processes, both over the Arctic and at mid-latitude regions. To do so, two long-term control runs (longer than 250 years) were generated with two state-of-the-art General Circulation Models (GCM), namely EC-Earth and HadGEM. From these two reference states, we have identified three different years in which the Arctic sea ice volume (SIV) was (i) maximum, (ii) minimum and (iii) a representative case for the mean state. By departing from each of these three dates (not necessarily the same for the two models), we generated a set of experiments in which the control runs are restarted both from original and climatological sea ice conditions. Here, climatological sea ice conditions are estimated as the time-average of sea ice parameters from the respective long-term control runs. The experiments are 1-year long and all of them start in January when ice is still thin, snow depth is small, air-ocean temperatures contrast the most and, therefore, the heat conductive flux in sea ice (at the surface) is nearly maximum. To robustly separate the response to degrading the initial sea ice state from background internal variability, each of the two counterfactual experiments (reference and climatological) consists of 50 ensembles members. Threstatedese ensembles are generated by adding small random perturbations to the sea surface temperature (EC-Earth) or to the air temperature (HadGEM) fields. Preliminary results reinforce the importance of having the right sea ice state for improving the (sub-)seasonal prediction of atmospheric parameters (e.g., 2m-temperature and geopotential) and circulation (e.g., Westerlies and Jet Stream) not only over the Arctic, but also at mid-latitude regions.</p>

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 An enhancement to sea ice motion and age products at the National Snow and Ice Data Center (NSIDC)

2020 ◽  
Vol 14 (5) ◽  
pp. 1519-1536 ◽  
Author(s):  
Mark A. Tschudi ◽  
Walter N. Meier ◽  
J. Scott Stewart
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Data Center ◽  
Ice Cover ◽  
Ice Age ◽  
The Arctic ◽  
Significant Shift ◽  
Positive Trend ◽  
The Impact ◽  
Snow And Ice

Abstract. A new version of sea ice motion and age products includes several significant upgrades in processing, corrects known issues with the previous version, and updates the time series through 2018, with regular updates planned for the future. First, we provide a history of these NASA products distributed at the National Snow and Ice Data Center. Then we discuss the improvements to the algorithms, provide validation results for the new (Version 4) and older versions, and intercompare the two. While Version 4 algorithm changes were significant, the impact on the products is relatively minor, particularly for more recent years. The changes in Version 4 reduce motion biases by ∼ 0.01 to 0.02 cm s−1 and error standard deviations by ∼ 0.3 cm s−1. Overall, ice speed increased in Version 4 over Version 3 by 0.5 to 2.0 cm s−1 over most of the time series. Version 4 shows a higher positive trend for the Arctic of 0.21 cm s−1 per decade compared to 0.13 cm s−1 per decade for Version 3. The new version of ice age estimates indicates more older ice than Version 3, especially earlier in the record, but similar trends toward less multiyear ice. Changes in sea ice motion and age derived from the product show a significant shift in the Arctic ice cover, from a pack with a high concentration of older ice to a sea ice cover dominated by first-year ice, which is more susceptible to summer melt. We also observe an increase in the speed of the ice over the time series ≥ 30 years, which has been shown in other studies and is anticipated with the annual decrease in sea ice extent.

scholarly journals An Investigation into the Impact of using Various Techniques to Estimate Arctic Surface Air Temperature Anomalies*

2015 ◽  
Vol 28 (5) ◽  
pp. 1743-1763 ◽  
Author(s):  
Emma M. A. Dodd ◽  
Christopher J. Merchant ◽  
Nick A. Rayner ◽  
Colin P. Morice
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Meteorological Station ◽  
The Arctic ◽  
Test Bed ◽  
Recent Climate ◽  
The Impact ◽  
Mean Square Errors

Abstract Time series of global and regional mean surface air temperature (SAT) anomalies are a common metric used to estimate recent climate change. Various techniques can be used to create these time series from meteorological station data. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice was investigated using reanalysis data as a test bed. Techniques that interpolated anomalies were found to result in smaller errors than noninterpolating techniques relative to the reanalysis reference. Kriging techniques provided the smallest errors in estimates of Arctic anomalies, and simple kriging was often the best kriging method in this study, especially over sea ice. A linear interpolation technique had, on average, root-mean-square errors (RMSEs) up to 0.55 K larger than the two kriging techniques tested. Noninterpolating techniques provided the least representative anomaly estimates. Nonetheless, they serve as useful checks for confirming whether estimates from interpolating techniques are reasonable. The interaction of meteorological station coverage with estimation techniques between 1850 and 2011 was simulated using an ensemble dataset comprising repeated individual years (1979–2011). All techniques were found to have larger RMSEs for earlier station coverages. This supports calls for increased data sharing and data rescue, especially in sparsely observed regions such as the Arctic.

scholarly journals Implications of all season Arctic sea-ice anomalies on the stratosphere

2012 ◽  
Vol 12 (5) ◽  
pp. 12423-12451
Author(s):  
D. Cai ◽  
M. Dameris ◽  
H. Garny ◽  
T. Runde
Keyword(s):  
Sea Ice ◽  
Boundary Conditions ◽  
Air Temperature ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Time Slice ◽  
Wave Radiation ◽  
Arctic Sea ◽  
The Impact

Abstract. In this study the impact of a substantially reduced Arctic sea-ice cover on the lower and middle stratosphere is investigated. For this purpose two simulations with fixed boundary conditions (the so-called time-slice mode) were performed with a Chemistry-Climate Model. A reference time-slice with boundary conditions representing the year 2000 is compared to a second sensitivity simulation in which the boundary conditions are identical apart from the polar sea-ice cover, which is set to represent the years 2089–2099. Three features of Arctic air temperature response have been identified which are worth to be discussed in detail. Firstly, tropospheric mean polar temperatures increase up to 7 K during winter. This warming is primarily driven by changes in outgoing long-wave radiation. Secondly, temperatures decrease significantly in the summer stratosphere caused by a decline in outgoing short-wave radiation, accompanied by a characteristic increase of ozone mixing ratios. Thirdly, there are short periods of statistical significant temperature anomalies in the winter stratosphere probably driven by modified planetary wave activity. Both the internal as well as the inter-annual variability of Arctic sea-ice content is related to Arctic climatic fields like surface air temperature, sea level pressure or precipitation, which are analogue with the variability of the Arctic Oscillation (AO)-index. In this study significant changes in the AO-index are detected in the course of winter. Neutral phases of AO appear more often. As expected, the dominating dynamical response of the stratosphere during winter turned out to be consistent to alterations in the tropospheric AO, although it is not statistically significant most of the time.

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