Relative contributions of internal atmospheric variability and surface processes to the interannual variations in wintertime Arctic surface air temperatures

2021 ◽  
pp. 1-48
Author(s):  
Fengmin Wu ◽  
Wenkai Li ◽  
Peng Zhang ◽  
Wei Li
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Surface Air Temperature ◽  
Surface Processes ◽  
The Arctic ◽  
Interannual Variations ◽  
Atmospheric Variability ◽  
Near Surface ◽  
Atmospheric Circulations ◽  
Downward Longwave Radiation

AbstractSuperimposed on a warming trend, Arctic winter surface air temperature (SAT) exhibits substantial interannual variability, whose underlying mechanisms are unclear, especially regarding the role of sea-ice variations and atmospheric processes. Here, atmospheric reanalysis data and idealized atmospheric model simulations are used to reveal the mechanisms by which sea-ice variations and atmospheric anomalous conditions affect interannual variations in wintertime Arctic SAT. Results show that near-surface interannual warming in the Arctic is accompanied by comparable warming throughout large parts of the Arctic troposphere and large-scale anomalous atmospheric circulation patterns. Within the Arctic, changes in large-scale atmospheric circulations due to internal atmospheric variability explain a substantial fraction of interannual variation in SAT and tropospheric temperatures, which lead to an increase in moisture and downward longwave radiation, with the rest likely coming from sea ice-related and other surface processes. Arctic winter sea-ice loss allows the ocean to release more heat and moisture, which enhances Arctic warming; however, this effect on SAT is confined to the ice-retreat area and has a limited influence on large-scale atmospheric circulations.

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.

Arctic Sea Ice Reemergence: The Role of Large-Scale Oceanic and Atmospheric Variability*

2015 ◽  
Vol 28 (14) ◽  
pp. 5477-5509 ◽  
Author(s):  
Mitchell Bushuk ◽  
Dimitrios Giannakis ◽  
Andrew J. Majda
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Spring Sea Ice ◽  
Phase Relationships

Abstract Arctic sea ice reemergence is a phenomenon in which spring sea ice anomalies are positively correlated with fall anomalies, despite a loss of correlation over the intervening summer months. This work employs a novel data analysis algorithm for high-dimensional multivariate datasets, coupled nonlinear Laplacian spectral analysis (NLSA), to investigate the regional and temporal aspects of this reemergence phenomenon. Coupled NLSA modes of variability of sea ice concentration (SIC), sea surface temperature (SST), and sea level pressure (SLP) are studied in the Arctic sector of a comprehensive climate model and in observations. It is found that low-dimensional families of NLSA modes are able to efficiently reproduce the prominent lagged correlation features of the raw sea ice data. In both the model and observations, these families provide an SST–sea ice reemergence mechanism, in which melt season (spring) sea ice anomalies are imprinted as SST anomalies and stored over the summer months, allowing for sea ice anomalies of the same sign to reappear in the growth season (fall). The ice anomalies of each family exhibit clear phase relationships between the Barents–Kara Seas, the Labrador Sea, and the Bering Sea, three regions that compose the majority of Arctic sea ice variability. These regional phase relationships in sea ice have a natural explanation via the SLP patterns of each family, which closely resemble the Arctic Oscillation and the Arctic dipole anomaly. These SLP patterns, along with their associated geostrophic winds and surface air temperature advection, provide a large-scale teleconnection between different regions of sea ice variability. Moreover, the SLP patterns suggest another plausible ice reemergence mechanism, via their winter-to-winter regime persistence.

Observed Atmospheric Coupling between Barents Sea Ice and the Warm-Arctic Cold-Siberian Anomaly Pattern

2016 ◽  
Vol 29 (2) ◽  
pp. 495-511 ◽  
Author(s):  
Svetlana A. Sorokina ◽  
Camille Li ◽  
Justin J. Wettstein ◽  
Nils Gunnar Kvamstø
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Barents Sea ◽  
Winter Season ◽  
Surface Air Temperature ◽  
Turbulent Heat Flux ◽  
Turbulent Heat ◽  
Atmospheric Variability ◽  
Atmospheric Flow ◽  
Anomaly Pattern

Abstract The decline in Barents Sea ice has been implicated in forcing the “warm-Arctic cold-Siberian” (WACS) anomaly pattern via enhanced turbulent heat flux (THF). This study investigates interannual variability in winter [December–February (DJF)] Barents Sea THF and its relationship to Barents Sea ice and the large-scale atmospheric flow. ERA-Interim and observational data from 1979/80 to 2011/12 are used. The leading pattern (EOF1: 33%) of winter Barents Sea THF variability is relatively weakly correlated (r = 0.30) with Barents Sea ice and appears to be driven primarily by atmospheric variability. The sea ice–related THF variability manifests itself as EOF2 (20%, r = 0.60). THF EOF2 is robust over the entire winter season, but its link to the WACS pattern is not. However, the WACS pattern emerges consistently as the second EOF (20%) of Eurasian surface air temperature (SAT) variability in all winter months. When Eurasia is cold, there are indeed weak reductions in Barents Sea ice, but the associated THF anomalies are on average negative, which is inconsistent with the proposed direct atmospheric response to sea ice variability. Lead–lag correlation analyses on shorter time scales support this conclusion and indicate that atmospheric variability plays an important role in driving observed variability in Barents Sea THF and ice cover, as well as the WACS pattern.

scholarly journals Impacts of Arctic Sea Ice on Cold Season Atmospheric Variability and Trends Estimated from Observations and a Multi-model Large Ensemble

2021 ◽  
pp. 1-64
Author(s):  
Yu-Chiao Liang ◽  
Claude Frankignoul ◽  
Young-Oh Kwon ◽  
Guillaume Gastineau ◽  
Elisa Manzini ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
General Circulation ◽  
Cold Season ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atmospheric Variability ◽  
Large Ensemble ◽  
Near Surface ◽  
Arctic Sea

AbstractTo examine the atmospheric responses to Arctic sea-ice variability in the Northern Hemisphere cold season (October to following March), this study uses a coordinated set of large-ensemble experiments of nine atmospheric general circulation models (AGCMs) forced with observed daily-varying sea-ice, sea-surface temperature, and radiative forcings prescribed during the 1979-2014 period, together with a parallel set of experiments where Arctic sea ice is substituted by its climatology. The simulations of the former set reproduce the near-surface temperature trends in reanalysis data, with similar amplitude, and their multi-model ensemble mean (MMEM) shows decreasing sea-level pressure over much of the polar cap and Eurasia in boreal autumn. The MMEM difference between the two experiments allows isolating the effects of Arctic sea-ice loss, which explain a large portion of the Arctic warming trends in the lower troposphere and drives a small but statistically significant weakening of the wintertime Arctic Oscillation. The observed interannual co-variability between sea-ice extent in the Barents-Kara Seas and lagged atmospheric circulation is distinguished from the effects of confounding factors based on multiple regression, and quantitatively compared to the co-variability in MMEMs. The interannual sea-ice decline followed by a negative North Atlantic Oscillation-like anomaly found in observations is also seen in the MMEM differences, with consistent spatial structure but much smaller amplitude. This result suggests that the sea-ice impacts on trends and interannual atmospheric variability simulated by AGCMs could be underestimated, but caution is needed because internal atmospheric variability may have affected the observed relationship.

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 Attribution of late summer early autumn Arctic sea ice decline in recent decades

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Lejiang Yu ◽  
Shiyuan Zhong ◽  
Timo Vihma ◽  
Bo Sun
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Atmospheric Circulations ◽  
Sea Ice Decline ◽  
Decadal Scale ◽  
Downward Longwave Radiation ◽  
Arctic Sea ◽  
Circulation Changes ◽  
Thermodynamic Processes

AbstractThe underlying mechanisms for Arctic sea ice decline can be categories as those directly related to changes in atmospheric circulations (often referred to as dynamic mechanisms) and the rest (broadly characterized as thermodynamic processes). An attribution analysis based on the self-organizing maps (SOM) method is performed to determine the relative contributions from these two types of mechanisms to the Arctic sea ice decline in August–October during 1979–2016. The daily atmospheric circulations represented by daily 500-hPa geopotential height anomalies are classified into 12 SOM patterns, which portray the spatial structures of the Arctic Oscillation and Arctic Dipole, and their transitions. Due to the counterbalance between the opposite trends among the circulation patterns, the net effect of circulation changes is small, explaining only 1.6% of the declining trend in the number of August–October sea ice days in the Arctic during 1979–2016. The majority of the trend (95.8%) is accounted for by changes in thermodynamic processes not directly related to changes in circulations, whereas for the remaining trend (2.6%) the contributions of circulation and non-circulation changes cannot be distinguished. The sea ice decline is closely associated with surface air temperature increase, which is related to increasing trends in atmospheric water vapor content, downward longwave radiation, and sea surface temperatures over the open ocean, as well as to decreasing trends in surface albedo. An analogous SOM analysis extending seasonal coverage to spring (April–October) for the same period supports the dominating role of thermodynamic forcing in decadal-scale Arctic sea ice loss.

Interannual Variations of Arctic Cloud Types in Relation to Sea Ice

2010 ◽  
Vol 23 (15) ◽  
pp. 4216-4232 ◽  
Author(s):  
Ryan Eastman ◽  
Stephen G. Warren
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Cloud Cover ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Interannual Variations ◽  
Total Cloud Cover ◽  
Sea Ice Extent ◽  
The Arctic Ocean ◽  
Precipitating Clouds

Abstract Sea ice extent and thickness may be affected by cloud changes, and sea ice changes may in turn impart changes to cloud cover. Different types of clouds have different effects on sea ice. Visual cloud reports from land and ocean regions of the Arctic are analyzed here for interannual variations of total cloud cover and nine cloud types, and their relation to sea ice. Over the high Arctic, cloud cover shows a distinct seasonal cycle dominated by low stratiform clouds, which are much more common in summer than winter. Interannual variations of cloud amounts over the Arctic Ocean show significant correlations with surface air temperature, total sea ice extent, and the Arctic Oscillation. Low ice extent in September is generally preceded by a summer with decreased middle and precipitating clouds. Following a low-ice September there is enhanced low cloud cover in autumn. Total cloud cover appears to be greater throughout the year during low-ice years. Multidecadal trends from surface observations over the Arctic Ocean show increasing cloud cover, which may promote ice loss by longwave radiative forcing. Trends are positive in all seasons, but are most significant during spring and autumn, when cloud cover is positively correlated with surface air temperature. The coverage of summertime precipitating clouds has been decreasing over the Arctic Ocean, which may promote ice loss.

scholarly journals Warm and moist atmospheric flow caused a record minimum July sea ice extent of the Arctic in 2020

2021 ◽  
Author(s):  
Yu Liang ◽  
Haibo Bi ◽  
Haijun Huang ◽  
Ruibo Lei ◽  
Xi Liang ◽  
...  
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Extreme Event ◽  
Longwave Radiation ◽  
Decisive Role ◽  
High Energy ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Atmospheric Flow ◽  
Downward Longwave Radiation

Abstract. The satellite observations unveiled that the July sea ice extent of the Arctic shrank to the lowest value in 2020 since 1979, with a major ice retreat in the Eurasian shelf seas including Kara, Laptev, and East Siberian Seas. Based on the ERA-5 reanalysis products, we explored the impacts of warm and moist air-mass transport on this extreme event. The results reveal that anomalously high energy and moisture converged into these regions in the spring months (April to June) of 2020, leading to a burst of high moisture content and warming within the atmospheric column. The convergence is accompanied by local enhanced downward longwave radiation and turbulent fluxes, which is favorable for initiating an early melt onset in the areas with severe ice loss. Once the melt begins, solar radiation played a decisive role in leading to further sea ice depletion due to ice-albedo positive feedback. The typical trajectories of the synoptic cyclones that occurred on the Eurasian side in spring 2020 agree well with the path of atmospheric flow. Assessments suggest that variations in characteristics of the spring cyclones are conducive to the severe melt of sea ice. We argue that large-scale atmospheric circulation and synoptic cyclones act in concert to trigger the exceptional poleward transport of total energy and moisture from April to June to cause this new record minimum of sea ice extent in the following July.

scholarly journals Trends, abrupt shifts and interannual variability of the Arctic Wintertime Seasonal Sea Ice from 1979 to 2019

2020 ◽  
pp. 1-13
Author(s):  
Guanghua Hao ◽  
Jie Su ◽  
Timo Vihma ◽  
Fei Huang
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Large Scale ◽  
Open Water ◽  
The Arctic ◽  
Atlantic Sector ◽  
Near Surface ◽  
The Pacific ◽  
Pressure Anomaly ◽  
Abrupt Shifts

Abstract The Arctic winter seasonal sea ice (WSSI) concentration from 1979 to 2019 is derived from passive microwave data. Based on Empirical Orthogonal Function (EOF) analysis, the WSSI time series includes regionally different trends, abrupt shifts and interannual variations. The time series of the first EOF mode (PC1) mainly represents the WSSI trend, which is characterized by an increase, particularly in the Pacific sector. PC1 confirms two abrupt shifts in WSSI in 1989 and 2007, with a variance of 31%. After 2007, the large-scale atmospheric circulation anomaly shows a strengthened wavenumber 3 structure at high latitudes associated with a mid-tropospheric low-pressure anomaly in central and western Siberia and a high-pressure anomaly in eastern Siberia in summer and autumn. These patterns have promoted the increased transport of moist static energy to the central Arctic and contributed to increased near-surface air temperatures that may enhance ice melting in summer and reduce ice growth in autumn and winter. The changes in ice melt and growth have had opposite effects in the Pacific and Atlantic sectors: WSSI has increased in the Pacific sector due to the replacement of multi-year ice by WSSI, and decreased in the Atlantic sector due to the replacement of WSSI by open water.

scholarly journals The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multiplatform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification

2019 ◽  
Vol 100 (5) ◽  
pp. 841-871 ◽  
Author(s):  
Manfred Wendisch ◽  
Andreas Macke ◽  
André Ehrlich ◽  
Christof Lüpkes ◽  
Mario Mech ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Aerosol Particles ◽  
Surface Air Temperature ◽  
Field Studies ◽  
Surface Processes ◽  
The Arctic ◽  
Arctic Amplification ◽  
Arctic Boundary Layer ◽  
Near Surface ◽  
Airborne Measurements

AbstractClouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, and surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) aircraft campaign and the Physical Feedbacks of Arctic Boundary Layer, Sea Ice, Cloud and Aerosol (PASCAL) ice breaker expedition. Both observational studies were performed in the framework of the German Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)3 project. They took place in the vicinity of Svalbard, Norway, in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft; the icebreaker Research Vessel (R/V) Polarstern; an ice floe camp including an instrumented tethered balloon; and the permanent ground-based measurement station at Ny-Ålesund, Svalbard, were employed to observe Arctic low- and mid-level mixed-phase clouds and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above the R/V Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns.

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