Analyzing the Arctic Feedback Mechanism between Sea Ice and Low-Level Clouds Using 34 Years of Satellite Observations

2020 ◽  
Vol 33 (17) ◽  
pp. 7479-7501
Author(s):  
Daniel Philipp ◽  
Martin Stengel ◽  
Bodo Ahrens
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Large Scale ◽  
The Arctic ◽  
Turbulent Heat ◽  
Arctic Amplification ◽  
Surface Warming ◽  
Low Level ◽  
Gc Analysis ◽  
Csi Feedback

AbstractSatellite-based cloud, radiation flux, and sea ice records covering 34 years are used 1) to investigate autumn cloud cover trends over the Arctic, 2) to assess its relation with declining sea ice using Granger causality (GC) analysis, and 3) to discuss the contribution of the cloud–sea ice (CSI) feedback to Arctic amplification. This paper provides strong evidence for a positive CSI feedback with the capability to contribute to autumnal Arctic amplification. Positive low-level cloud fractional cover (CFClow) trends over the Arctic ice pack are found in October and November (ON) with magnitudes of up to about +9.6% per decade locally. Statistically significant anticorrelations between sea ice concentration (SIC) and CFClow are observed in ON over melting zones, suggesting an association. The GC analysis indicated a causal two-way interaction between SIC and CFClow. Interpreting the resulting F statistic and its spatial distribution as a relation strength proxy, the influence of SIC on CFClow is likely stronger than the reverse. ERA-Interim reanalysis data suggest that ON CFClow is impacted by sea ice melt through surface–atmosphere coupling via turbulent heat and moisture fluxes. Due to weak solar insolation in ON, net cloud radiative forcing (CRF) exerts a warming effect on the Arctic surface. Increasing CFClow induces a large-scale surface warming trend reaching magnitudes of up to about +8.3 W m−2 per decade locally. Sensitivities of total CRF to CFClow ranges between +0.22 and +0.66 W m−2 per percent CFClow. Increasing surface warming can cause a melt season lengthening and hinders formation of perennial ice.

Pan-Arctic and regional trends of reflectance, clouds and fluxes: implications for Arctic Amplification

2021 ◽  
Author(s):  
Luca Lelli ◽  
Narges Khosravi ◽  
Marco Vountas ◽  
John Burrows
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
The Arctic ◽  
Arctic Amplification ◽  
Sea Ice Extent ◽  
Simple Assumption ◽  
Spectral Reflectivity ◽  
Surface Warming ◽  
Cloud Properties ◽  
Regional Trends

<p>It is now well known that the sea ice extent in the Artic has been shrinking in the past three decades in the period known as the Arctic Amplification. A simple assumption would be that if the sea ice extent has been reduced, then the spectral reflectance at the top of the atmosphere - R<sub>TOA</sub> - would have also decreased across the Arctic. On the other hand, Arctic reflectivity also largely depends on the presence of clouds, shielding the underlying surface, and on changes of their optical and physical properties. Thus, the assessment of trends of spectral reflectivity and cloud properties are essential to understand those forcings and feedbacks considered drivers of Arctic Amplification as well as the interactions between the components of the Arctic cryosphere. In the reported study we observationally tackle the stated problem investigating changes of R<sub>TOA</sub> at selected wavelengths making use of spaceborne measurements of the Global Ozone Monitoring Experiment (GOME onboard ERS-2 and MetOp A/B/C) and of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY onboard Envisat) for the period 1995-2018. We complement this record with cloud properties and fluxes at top of the atmosphere and at the surface, inferred from measurements of the post-meridiem orbits of the Advanced Very High Resolution Radiometer (AVHRR onboard POES). Although the Pan-Arctic reflectivity has decreased, the analysis of regional trends shows distinct areas where the reflectivity trends diverge. While darkening areas can be attributed to seasonal sea ice decline, an increase of Arctic brightness over sea ice free regions can be largely attributed to changes in the optical properties of clouds. While the multiyear mean of the radiative forcing by clouds points to a TOA cooling and a surface warming, its trends exhibit opposite tendencies. In the last two decades, the cloud radiative effect at TOA is expected to warm the lower latitudes (below 75 N) and to cool the circumpolar belt, while an opposite trend at BOA, amounting to 5 W m<sup>-2 </sup>per decade, cools the lower Arctic latitudes and warms the permanent sea ice region, this effect being more pronounced in spring months (April to June) than in summer months (July to September).</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.

scholarly journals Sensitivity of CAM5-Simulated Arctic Clouds and Radiation to Ice Nucleation Parameterization

2013 ◽  
Vol 26 (16) ◽  
pp. 5981-5999 ◽  
Author(s):  
Shaocheng Xie ◽  
Xiaohong Liu ◽  
Chuanfeng Zhao ◽  
Yuying Zhang
Keyword(s):  
Radiative Forcing ◽  
Large Scale ◽  
Arctic Region ◽  
Atmospheric Model ◽  
Ice Nucleation ◽  
The Arctic ◽  
Liquid Water Path ◽  
Arctic Clouds ◽  
Water Path ◽  
Low Level

Abstract Sensitivity of Arctic clouds and radiation in the Community Atmospheric Model, version 5, to the ice nucleation process is examined by testing a new physically based ice nucleation scheme that links the variation of ice nuclei (IN) number concentration to aerosol properties. The default scheme parameterizes the IN concentration simply as a function of ice supersaturation. The new scheme leads to a significant reduction in simulated IN concentration at all latitudes while changes in cloud amounts and properties are mainly seen at high- and midlatitude storm tracks. In the Arctic, there is a considerable increase in midlevel clouds and a decrease in low-level clouds, which result from the complex interaction among the cloud macrophysics, microphysics, and large-scale environment. The smaller IN concentrations result in an increase in liquid water path and a decrease in ice water path caused by the slowdown of the Bergeron–Findeisen process in mixed-phase clouds. Overall, there is an increase in the optical depth of Arctic clouds, which leads to a stronger cloud radiative forcing (net cooling) at the top of the atmosphere. The comparison with satellite data shows that the new scheme slightly improves low-level cloud simulations over most of the Arctic but produces too many midlevel clouds. Considerable improvements are seen in the simulated low-level clouds and their properties when compared with Arctic ground-based measurements. Issues with the observations and the model–observation comparison in the Arctic region are discussed.

Ice microphysics of low-level ice clouds in the Arctic: Satellite analysis

2021 ◽  
Author(s):  
Iris Papakonstantinou-Presvelou ◽  
Johannes Quaas
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Arctic Region ◽  
Open Ocean ◽  
The Arctic ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Low Level ◽  
Level Ice ◽  
Satellite Analysis

<p>This study investigates low-level ice clouds in the Arctic and their potential relation to the surface aerosols. These aerosols or ice nucleating particles (INPs), are necessary for the heterogeneous nucleation of ice in temperatures above -38°C. Several studies in the past have investigated the sources of INPs and their nucleating behavior with response to the temperature. According to these studies, it has been suggested that a marine source of INPs coming from sea spray is able to nucleate ice in temperatures close to -5<sup>o</sup>C. What we do here is a large-scale comparison of boundary-layer ice clouds over open ocean and sea ice, over the whole Arctic region for the time period of 2006-2016. We use for this purpose a satellite-retrieved quantity, the ice crystal number concentration (N<sub>i</sub>), which we investigate in relation to the temperature. We study clouds with regard to the region and season they form and we examine their coupling to the surface. Our findings show - contrary to previous expectation - enhanced ice crystal numbers over sea ice compared to open ocean, in temperatures above -10<sup>o</sup>C. In lower temperatures this difference still persists for the lower Arctic latitudes (<70<sup>o</sup>N), especially for clouds that are coupled to the surface.</p>

scholarly journals Mechanism of seasonal Arctic sea ice evolution and Arctic amplification

2016 ◽  
Vol 10 (5) ◽  
pp. 2191-2202 ◽  
Author(s):  
Kwang-Yul Kim ◽  
Benjamin D. Hamlington ◽  
Hanna Na ◽  
Jinju Kim
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Turbulent Heat Flux ◽  
Sea Surface ◽  
The Arctic ◽  
Turbulent Heat ◽  
Arctic Amplification ◽  
Atmospheric Column ◽  
The Arctic Ocean

Abstract. Sea ice loss is proposed as a primary reason for the Arctic amplification, although the 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 loss in the Arctic Ocean and the Arctic amplification. While sea ice loss is widespread over much of the perimeter of the Arctic Ocean in summer, sea ice remains thin in winter only in the Barents–Kara seas. Excessive turbulent heat flux through the sea surface exposed to air due to sea ice reduction warms the atmospheric column. Warmer air increases the downward longwave radiation and subsequently surface air temperature, which facilitates sea surface remains to be free of ice. 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.

Drivers of (non-)linear Eocene surface warming in the DeepMIP ensemble

2021 ◽  
Author(s):  
Sebastian Steinig ◽  
Jiang Zhu ◽  
Ran Feng ◽  
Keyword(s):  
Temperature Gradient ◽  
Heat Transport ◽  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Large Scale ◽  
Surface Albedo ◽  
Early Eocene ◽  
Meridional Heat Transport ◽  
Surface Warming ◽  
Global Mean

<p>The early Eocene greenhouse represents the warmest interval of the Cenozoic and therefore provides a unique opportunity to understand how the climate system operates under elevated atmospheric CO<sub>2</sub> levels similar to those projected for the end of the 21st century. Early Eocene geological records indicate a large increase in global mean surface temperatures compared to present day (by ~14°C) and a greatly reduced meridional temperature gradient (by ~30% in SST). However, reproducing these large-scale climate features at reasonable CO<sub>2</sub> levels still poses a challenge for current climate models. Recent modelling studies indicate an important role for shortwave (SW) cloud feedbacks to drive increases in climate sensitivity with global warming, which helps to close the gap between simulated and reconstructed Eocene global warmth and temperature gradient. Nevertheless, the presence of such state-dependent feedbacks and their relative strengths in other models remain unclear.</p><p>In this study, we perform a systematic investigation of the simulated surface warming and the underlying mechanisms in the recently published DeepMIP ensemble. The DeepMIP early Eocene simulations use identical paleogeographic boundary conditions and include six models with suitable output: CESM1.2_CAM5, GFDL_CM2.1, HadCM3B_M2.1aN, IPSLCM5A2, MIROC4m and NorESM1_F. We advance previous energy balance analysis by applying the approximate partial radiative perturbation (APRP) technique to quantify the individual contributions of surface albedo, cloud and non-cloud atmospheric changes to the simulated Eocene top-of-the-atmosphere SW flux anomalies. We further compare the strength of these planetary albedo feedbacks to changes in the longwave atmospheric emissivity and meridional heat transport in the warm Eocene climate. Particular focus lies in the sensitivity of the feedback strengths to increasing global mean temperatures in experiments at a range of atmospheric CO<sub>2</sub> concentrations between x1 to x9 preindustrial levels.</p><p>Preliminary results indicate that all models that provide data for at least 3 different CO<sub>2</sub> levels show an increase of the equilibrium climate sensitivity at higher global mean temperatures. This is associated with an increase of the overall strength of the positive SW cloud feedback with warming in those models. This nonlinear behavior seems to be related to both a reduction and optical thinning of low-level clouds, albeit with intermodel differences in the relative importance of the two mechanisms. We further show that our new APRP results can differ significantly from previous estimates based on cloud radiative forcing alone, especially in high-latitude areas with large surface albedo changes. We also find large intermodel variability and state-dependence in meridional heat transport modulated by changes in the atmospheric latent heat transport. Ongoing work focuses on the spatial patterns of the climate feedbacks and the implications for the simulated meridional temperature gradients.</p>

scholarly journals Cryospheric Impacts of Soviet River Diversion Schemes

1984 ◽  
Vol 5 ◽  
pp. 61-68 ◽  
Author(s):  
T. Holt ◽  
P. M. Kelly ◽  
B. S. G. Cherry
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
River Discharge ◽  
Large Scale ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
The Arctic Ocean ◽  
The Impact

Soviet plans to divert water from rivers flowing into the Arctic Ocean have led to research into the impact of a reduction in discharge on Arctic sea ice. We consider the mechanisms by which discharge reductions might affect sea-ice cover and then test various hypotheses related to these mechanisms. We find several large areas over which sea-ice concentration correlates significantly with variations in river discharge, supporting two particular hypotheses. The first hypothesis concerns the area where the initial impacts are likely to which is the Kara Sea. Reduced riverflow is associated occur, with decreased sea-ice concentration in October, at the time of ice formation. This is believed to be the result of decreased freshening of the surface layer. The second hypothesis concerns possible effects on the large-scale current system of the Arctic Ocean and, in particular, on the inflow of Atlantic and Pacific water. These effects occur as a result of changes in the strength of northward-flowing gradient currents associated with variations in river discharge. Although it is still not certain that substantial transfers of riverflow will take place, it is concluded that the possibility of significant cryospheric effects and, hence, large-scale climate impact should not be neglected.

scholarly journals Climate changes modulated the history of Arctic iodine during the Last Glacial Cycle

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Juan Pablo Corella ◽  
Niccolo Maffezzoli ◽  
Andrea Spolaor ◽  
Paul Vallelonga ◽  
Carlos A. Cuevas ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Radiative Forcing ◽  
Climate Changes ◽  
Ice Cores ◽  
The Arctic ◽  
Glacial Cycle ◽  
Ice Dynamics ◽  
Sea Ice Dynamics ◽  
Ultrafine Aerosol

AbstractIodine has a significant impact on promoting the formation of new ultrafine aerosol particles and accelerating tropospheric ozone loss, thereby affecting radiative forcing and climate. Therefore, understanding the long-term natural evolution of iodine, and its coupling with climate variability, is key to adequately assess its effect on climate on centennial to millennial timescales. Here, using two Greenland ice cores (NEEM and RECAP), we report the Arctic iodine variability during the last 127,000 years. We find the highest and lowest iodine levels recorded during interglacial and glacial periods, respectively, modulated by ocean bioproductivity and sea ice dynamics. Our sub-decadal resolution measurements reveal that high frequency iodine emission variability occurred in pace with Dansgaard/Oeschger events, highlighting the rapid Arctic ocean-ice-atmosphere iodine exchange response to abrupt climate changes. Finally, we discuss if iodine levels during past warmer-than-present climate phases can serve as analogues of future scenarios under an expected ice-free Arctic Ocean. We argue that the combination of natural biogenic ocean iodine release (boosted by ongoing Arctic warming and sea ice retreat) and anthropogenic ozone-induced iodine emissions may lead to a near future scenario with the highest iodine levels of the last 127,000 years.

scholarly journals Sea ice melt pond fraction estimation from dual-polarisation C-band SAR – Part 2: Scaling in situ to Radarsat-2

2014 ◽  
Vol 8 (1) ◽  
pp. 845-885 ◽  
Author(s):  
R. K. Scharien ◽  
K. Hochheim ◽  
J. Landy ◽  
D. G. Barber
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Temporal Frequency ◽  
Model Performance ◽  
Free Water ◽  
Light Transmittance ◽  
The Arctic ◽  
Ice Melt ◽  
Melt Pond

Abstract. Observed changes in the Arctic have motivated efforts to understand and model its components as an integrated and adaptive system at increasingly finer scales. Sea ice melt pond fraction, an important summer sea ice component affecting surface albedo and light transmittance across the ocean-sea ice–atmosphere interface, is inadequately parameterized in models due to a lack of large scale observations. In this paper, results from a multi-scale remote sensing program dedicated to the retrieval of pond fraction from satellite C-band synthetic aperture radar (SAR) are detailed. The study was conducted on first-year sea (FY) ice in the Canadian Arctic Archipelago during the summer melt period in June 2012. Approaches to retrieve the subscale FY ice pond fraction from mixed pixels in RADARSAT-2 imagery, using in situ, surface scattering theory, and image data are assessed. Each algorithm exploits the dominant effect of high dielectric free-water ponds on the VV/HH polarisation ratio (PR) at moderate to high incidence angles (about 40° and above). Algorithms are applied to four images corresponding to discrete stages of the seasonal pond evolutionary cycle, and model performance is assessed using coincident pond fraction measurements from partitioned aerial photos. A RMSE of 0.07, across a pond fraction range of 0.10 to 0.70, is achieved during intermediate and late seasonal stages. Weak model performance is attributed to wet snow (pond formation) and synoptically driven pond freezing events (all stages), though PR has utility for identification of these events when considered in time series context. Results demonstrate the potential of wide-swath, dual-polarisation, SAR for large-scale observations of pond fraction with temporal frequency suitable for process-scale studies and improvements to model parameterizations.

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