scholarly journals Spatial distribution of enhanced BrO and its relation to meteorological parameters in Arctic and Antarctic sea ice regions

2020 ◽  
Vol 20 (20) ◽  
pp. 12285-12312
Author(s):  
Sora Seo ◽  
Andreas Richter ◽  
Anne-Marlene Blechschmidt ◽  
Ilias Bougoudis ◽  
John Philip Burrows
Keyword(s):  
Spatial Distribution ◽  
Sea Ice ◽  
Spatial Patterns ◽  
Air Temperature ◽  
Meteorological Parameters ◽  
High Surface ◽  
Surface Air Temperature ◽  
Meteorological Conditions ◽  
The Arctic ◽  
Antarctic Sea Ice

Abstract. Satellite observations have shown large areas of elevated bromine monoxide (BrO) covering several thousand square kilometres over the Arctic and Antarctic sea ice regions in polar spring. These enhancements of total BrO columns result from increases in stratospheric or tropospheric bromine amounts or both, and their occurrence may be related to local meteorological conditions. In this study, the spatial distribution of the occurrence of total BrO column enhancements and the associated changes in meteorological parameters are investigated in both the Arctic and Antarctic regions using 10 years of Global Ozone Monitoring Experiment-2 (GOME-2) measurements and meteorological model data. Statistical analysis of the data presents clear differences in the meteorological conditions between the 10-year mean and episodes of enhanced total BrO columns in both polar sea ice regions. These differences show pronounced spatial patterns. In general, atmospheric low pressure, cold surface air temperature, high surface-level wind speed, and low tropopause heights were found during periods of enhanced total BrO columns. In addition, spatial patterns of prevailing wind directions related to the BrO enhancements are identified in both the Arctic and Antarctic sea ice regions. The relevance of the different meteorological parameters on the total BrO column is evaluated based on a Spearman rank correlation analysis, finding that tropopause height and surface air temperature have the largest correlations with the total BrO vertical column density. Our results demonstrate that specific meteorological parameters can have a major impact on the BrO enhancement in some areas, but in general, multiple meteorological parameters interact with each other in their influence on BrO columns.

scholarly journals Spatial distribution of enhanced BrO and its relation to meteorological parameters in Arctic and Antarctic sea ice regions

2019 ◽  
Author(s):  
Sora Seo ◽  
Andreas Richter ◽  
Anne-Marlene Blechschmidt ◽  
Ilias Bougoudis ◽  
John Philip Burrows
Keyword(s):  
Spatial Distribution ◽  
Sea Ice ◽  
Spatial Patterns ◽  
Air Temperature ◽  
Meteorological Parameters ◽  
High Surface ◽  
Surface Air Temperature ◽  
Meteorological Conditions ◽  
The Arctic ◽  
Antarctic Sea Ice

Abstract. Satellite observations have shown large areas of elevated BrO covering several thousand km2 over the Arctic and Antarctic sea ice region in polar spring. These enhancements of total BrO columns result from increases in stratospheric or tropospheric bromine amounts or both, and their occurrence may be related to local meteorological conditions. In this study, the spatial distribution of the occurrence of total BrO column enhancements and the associated changes in meteorological parameters are investigated in both the Arctic and Antarctic regions using 10 years of GOME-2 measurements in combination with meteorological model data. Statistical analysis of the data presents clear differences in the meteorological conditions between the 10 year mean and episodes of enhanced total BrO columns in both polar sea ice regions. These differences show pronounced spatial patterns. In general, atmospheric low pressure, cold surface air temperature, high surface-level wind speed and low tropopause heights were found during periods of enhanced total BrO columns. In addition, spatial patterns of prevailing wind directions related to the BrO enhancements are identified in both the Arctic and Antarctic sea ice region. The relevance of the different meteorological parameters for the total BrO column is evaluated based on a Spearman rank correlation analysis, finding that tropopause height and surface air temperature have the largest correlations with the total BrO vertical column density. Our results demonstrate that specific meteorological parameters can have a major impact on the BrO enhancement in some areas, but in general, multiple meteorological parameters interact with each other in their influence on BrO columns.

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.

scholarly journals Projected Changes in Daily Variability and Seasonal Cycle of Near-Surface Air Temperature over the Globe during the Twenty-First Century

2019 ◽  
Vol 32 (24) ◽  
pp. 8537-8561 ◽  
Author(s):  
Jiao Chen ◽  
Aiguo Dai ◽  
Yaocun Zhang
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Seasonal Cycle ◽  
Surface Air Temperature ◽  
First Century ◽  
The Arctic ◽  
Boreal Summer ◽  
High Latitudes ◽  
Low Latitudes ◽  
Twenty First Century

Abstract Increases in atmospheric greenhouse gases will not only raise Earth’s temperature but may also change its variability and seasonal cycle. Here CMIP5 model data are analyzed to quantify these changes in surface air temperature (Tas) and investigate the underlying processes. The models capture well the mean Tas seasonal cycle and variability and their changes in reanalysis, which shows decreasing Tas seasonal amplitudes and variability over the Arctic and Southern Ocean from 1979 to 2017. Daily Tas variability and seasonal amplitude are projected to decrease in the twenty-first century at high latitudes (except for boreal summer when Tas variability increases) but increase at low latitudes. The day of the maximum or minimum Tas shows large delays over high-latitude oceans, while it changes little at low latitudes. These Tas changes at high latitudes are linked to the polar amplification of warming and sea ice loss, which cause larger warming in winter than summer due to extra heating from the ocean during the cold season. Reduced sea ice cover also decreases its ability to cause Tas variations, contributing to the decreased Tas variability at high latitudes. Over low–midlatitude oceans, larger increases in surface evaporation in winter than summer (due to strong winter winds, strengthened winter winds in the Southern Hemisphere, and increased winter surface humidity gradients over the Northern Hemisphere low latitudes), coupled with strong ocean mixing in winter, lead to smaller surface warming in winter than summer and thus increased seasonal amplitudes there. These changes result in narrower (wider) Tas distributions over the high (low) latitudes, which may have important implications for other related fields.

scholarly journals An energy budget approach to understand the Arctic warming during the Last Interglacial

2021 ◽  
Author(s):  
Marie Sicard ◽  
Masa Kageyama ◽  
Sylvie Charbit ◽  
Pascale Braconnot ◽  
Jean-Baptiste Madeleine
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Air Temperature ◽  
Energy Budget ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Last Interglacial ◽  
Near Surface ◽  
Arctic Warming ◽  
The Arctic Ocean

Abstract. The Last Interglacial period (129–116 ka BP) is characterized by a strong orbital forcing which leads to a different seasonal and latitudinal distribution of insolation compared to the pre-industrial period. In particular, these changes amplify the seasonality of the insolation in the high latitudes of the northern hemisphere. Here, we investigate the Arctic climate response to this forcing by comparing the CMIP6 lig127k and pi-Control simulations performed with the IPSL-CM6A-LR model. Using an energy budget framework, we analyse the interactions between the atmosphere, ocean, sea ice and continents. In summer, the insolation anomaly reaches its maximum and causes a near-surface air temperature rise of 3.2 °C over the Arctic region. This warming is primarily due to a strong positive surface downwelling shortwave radiation anomaly over continental surfaces, followed by large heat transfers from the continents back to the atmosphere. The surface layers of the Arctic Ocean also receives more energy, but in smaller quantity than the continents due to a cloud negative feedback. Furthermore, while heat exchanges from the continental surfaces towards the atmosphere are strengthened, the ocean absorbs and stores the heat excess due to a decline in sea ice cover. However, the maximum near-surface air temperature anomaly does not peak in summer like insolation, but occurs in autumn with a temperature increase of 4.0 °C relative to the pre-industrial period. This strong warming is driven by a positive anomaly of longwave radiations over the Arctic ocean enhanced by a positive cloud feedback. It is also favoured by the summer and autumn Arctic sea ice retreat (−1.9 × 106 and −3.4 × 106 km2 respectively), which exposes the warm oceanic surface and allows heat stored by the ocean in summer and water vapour to be released. This study highlights the crucial role of the sea ice cover variations, the Arctic ocean, as well as changes in polar clouds optical properties on the Last Interglacial Arctic warming.

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.

scholarly journals Impact of Model Physics on Seasonal Forecasts of Surface Air Temperature in the Arctic

2017 ◽  
Vol 145 (3) ◽  
pp. 773-782 ◽  
Author(s):  
Qiong Yang ◽  
Muyin Wang ◽  
James E. Overland ◽  
Wanqiu Wang ◽  
Thomas W. Collow
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Ice Thickness ◽  
Seasonal Forecasts ◽  
Forecast System ◽  
Climate Forecast System ◽  
Sea Ice Thickness ◽  
Forecast Bias

The impacts of model physics and initial sea ice thickness on seasonal forecasts of surface energy budget and air temperature in the Arctic during summer were investigated based on Climate Forecast System, version 2 (CFSv2), simulations. The model physics changes include the enabling of a marine stratus cloud scheme and the removal of the artificial upper limit on the bottom heat flux from ocean to sea ice. The impact of initial sea ice thickness was examined by initializing the model with relatively realistic sea ice thickness generated by the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS). Model outputs were compared to that from a control run that did not impose physics changes and used Climate Forecast System Reanalysis (CFSR) sea ice thickness. After applying the physics modification to either sea ice thickness initialization, the simulated total cloud cover more closely resembled the observed monthly variations of total cloud cover except for the midsummer reduction. Over the Chukchi–Bering Seas, the model physics modification reduced the seasonal forecast bias in surface air temperature by 24%. However, the use of initial PIOMAS sea ice thickness alone worsened the surface air temperature predictions. The experiment with physics modifications and initial PIOMAS sea ice thickness achieves the best surface air temperature improvement over the Chukchi–Bering Seas where the area-weighted forecast bias was reduced by 71% from 1.05 K down to −0.3 K compared with the control run. This study supports other results that surface temperatures and sea ice characteristics are highly sensitive to the Arctic cloud and radiation formulations in models and need priority in model formulation and validation.

scholarly journals Relationship of the Extent of Antarctic and Arctic Ice with Temperature Changes, 1979–2020

2021 ◽  
Vol 496 (1) ◽  
pp. 66-71
Author(s):  
I. I. Mokhov ◽  
M. R. Parfenova
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Surface Air Temperature ◽  
Sharp Decrease ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Cross Wavelet Analysis

Abstract Quantitative estimates of the relationship between interannual variations in the extent of Antarctic and Arctic sea ice and changes in the surface air temperature in the Northern and Southern hemispheres are obtained using satellite, ground-based, and reanalysis data for the past four decades (1980–2019). It is shown that the previously noted general increase in the extent of Antarctic sea ice observed until recent years from satellite data (available only since the late 1970s) over the background global warming and a rapid decrease in the extent of Arctic sea ice is associated with a regional decrease in the surface temperature at Antarctic latitudes from the end of the 1970s. This is a result of regional manifestation of natural climate variations with periods of up to several decades against the background of global secular warming with a relatively weak temperature trend over the ocean in the Southern Hemisphere. Since 2016, a sharp decrease in the extent of Antarctic sea ice in the Southern Ocean has been observed. The results of the correlation and cross-wavelet analysis indicate significant coherence and negative correlation with the surface temperature of the extent of sea ice in recent decades, not only in the Arctic, but also in the Antarctic.

scholarly journals Prediction of Arctic temperature and sea ice using a high-resolution coupled model

2021 ◽  
pp. 1-62
Author(s):  
Le Chang ◽  
Jing-Jia Luo ◽  
Jiaqing Xue ◽  
Haiming Xu ◽  
Nick Dunstone
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Air Temperature ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Arctic Region ◽  
Warming Trend ◽  
Lower Atmosphere ◽  
The Arctic

AbstractUnder global warming, surface air temperature has risen rapidly and sea ice decreased markedly in the Arctic. These drastic climate changes have brought about various severe impacts on the vulnerable environment and ecosystem there. Thus, accurate prediction of Arctic climate becomes more important than before. Here we examine the seasonal to interannual predictive skills of 2-meter air temperature (2-m T) and sea ice cover (SIC) over the Arctic region (70°∼90°N) during 1980–2014 with a high-resolution global coupled model called the Met Office Decadal Prediction System version 3 (DePreSys3). The model captures well both the climatology and interannual variability of the Arctic 2-m T and SIC. Moreover, the anomaly correlation coefficient (ACC) of Arctic-averaged 2-m T and SIC shows statistically significant skills at lead times up to 16 months. This is mainly due to the contribution of strong decadal trends. In addition, it is found that the peak warming trend of Arctic 2-m T lags the maximum decrease trend of SIC by one month, in association with the heat flux forcing from the ocean surface to lower atmosphere. While the predictive skill is generally much lower for the detrended variations, we find a close relationship between the tropical Pacific El Niño–Southern Oscillation and the Arctic detrended 2-m T anomalies. This indicates potential seasonal to interannual predictability of the Arctic natural variations.

scholarly journals Snow Depth and Air Temperature Seasonality on Sea Ice Derived From Snow Buoy Measurements

2021 ◽  
Vol 8 ◽  
Author(s):  
Marcel Nicolaus ◽  
Mario Hoppmann ◽  
Stefanie Arndt ◽  
Stefan Hendricks ◽  
Christian Katlein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Weddell Sea ◽  
The Arctic ◽  
Validation Data ◽  
Antarctic Sea Ice

Snow depth on sea ice is an essential state variable of the polar climate system and yet one of the least known and most difficult to characterize parameters of the Arctic and Antarctic sea ice systems. Here, we present a new type of autonomous platform to measure snow depth, air temperature, and barometric pressure on drifting Arctic and Antarctic sea ice. “Snow Buoys” are designed to withstand the harshest environmental conditions and to deliver high and consistent data quality with minimal impact on the surface. Our current dataset consists of 79 time series (47 Arctic, 32 Antarctic) since 2013, many of which cover entire seasonal cycles and with individual observation periods of up to 3 years. In addition to a detailed introduction of the platform itself, we describe the processing of the publicly available (near real time) data and discuss limitations. First scientific results reveal characteristic regional differences in the annual cycle of snow depth: in the Weddell Sea, annual net snow accumulation ranged from 0.2 to 0.9 m (mean 0.34 m) with some regions accumulating snow in all months. On Arctic sea ice, the seasonal cycle was more pronounced, showing accumulation from synoptic events mostly between August and April and maxima in autumn. Strongest ablation was observed in June and July, and consistently the entire snow cover melted during summer. Arctic air temperature measurements revealed several above-freezing temperature events in winter that likely impacted snow stratigraphy and thus preconditioned the subsequent spring snow cover. The ongoing Snow Buoy program will be the basis of many future studies and is expected to significantly advance our understanding of snow on sea ice, also providing invaluable in situ validation data for numerical simulations and remote sensing techniques.

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.

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