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  • 1
    Publication Date: 2024-04-20
    Description: This dataset includes melt pond fraction (MPF) over Arctic sea ice during 2000-2019. The spatial coverage of this data is north of 60 °N. The MPF data is projected on a polar stereographic grid with a spatial resolution of 12.5 km and a temporal resolution of 8-day intervals from May 9 to September 6, which is archived in the NetCDF format. This dataset was jointly developed by the Beijing Normal University, University at Albany-State University of New York, and Sun Yat-sen University. Large-scale temporal and spatial distribution of melt ponds over Arctic sea ice have implications for surface albedo, heat and mass balance of sea ice, freshwater in the upper ocean, and primary productivity of ice algae and phytoplankton. We retrieved the MPF data based on a robust ensemble-based deep neural network along with the surface reflectance of 7 bands from MOD09A1 (MODIS surface reflectance 8-Day L3 version 6) as the input and the MPF observations from multiple sources as the target. The validation results show that the retrieved MPF is in good agreement with the in-situ measurements (the details can be found at Ding et al., 2020).
    Keywords: Arctic; Arctic sea ice; Binary Object; DATE/TIME; Melt pond fraction; MODIS; pan-Arctic
    Type: Dataset
    Format: text/tab-separated-values, 319 data points
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  • 2
    Publication Date: 2024-02-07
    Description: The Greenland high (GL-high) coincides with a local center of action of the summer North Atlantic Oscillation and is known to have significant influence on Greenland ice sheet melting and summer Arctic sea ice. However, the mechanism behind the influence on regional Arctic sea ice is not yet clear. In this study, using reanalysis datasets and satellite observations, the influence of the GL-high in early summer on Arctic sea ice variability, and the mechanism behind it, are investigated. In response to an intensified GL-high, sea ice over the Beaufort Sea shows significant decline in both concentration and thickness from June through September. This decline in sea ice is primarily due to thermodynamic and mechanical redistribution processes. Firstly, the intensified GL-high increases subsidence over the Canadian Basin, leading to an increase in surface air temperature by adiabatic heating, and a substantial decrease in cloud cover and thus increased downward shortwave radiation. Secondly, the intensified GL-high increases easterly wind frequency and wind speed over the Beaufort Sea, pushing sea ice over the Canadian Basin away from the coastlines. Both processes contribute to an increase in open water areas, amplifying ice–albedo feedback and leading to sea ice decline. The mechanism identified here differs from previous studies that focused on northward moisture and heat transport and the associated increase in downward longwave radiation over the Arctic. The impact of the GL-high on the regional sea ice (also Arctic sea ice extent) can persist from June into fall, providing an important source for seasonal prediction of Arctic sea ice. The GL-high has an upward trend and reached a record high in 2012 that coincided with a record minimum summer Arctic sea ice extent, and has strong implications for summer Arctic sea ice changes.
    Type: Article , PeerReviewed
    Format: text
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  • 3
    Publication Date: 2024-02-07
    Description: Flow of dense shelf water provide an efficient mechanism for pumping CO 2 to the deep ocean along the continental shelf slope, particularly around the Antarctic bottom water (AABW) formation areas where much of the global bottom water is formed. However, the contribution of the formation of AABW to sequestering anthropogenic carbon ( C ant ) and its consequences remain unclear. Here, we show prominent transport of C ant (25.0 ± 4.7 Tg C yr −1 ) into the deep ocean (〉2,000 m) in four AABW formation regions around Antarctica based on an integrated observational data set (1974–2018). This maintains a lower C ant in the upper waters than that of other open oceans to sustain a stronger CO 2 uptake capacity (16.9 ± 3.8 Tg C yr −1 ). Nevertheless, the accumulation of C ant can further trigger acidification of AABW at a rate of −0.0006 ± 0.0001 pH unit yr −1 . Our findings elucidate the prominent role of AABW in controlling the Southern Ocean carbon uptake and storage to mitigate climate change, whereas its side effects (e.g., acidification) could also spread to other ocean basins via the global ocean conveyor belt. Plain Language Summary The Southern Ocean is thought to uptake and store a large amount of anthropogenic CO 2 ( C ant ), but little attention has been paid to the Antarctic coastal regions in the south of 60°S, mainly due to the lack of observations. Based on an integrated data set, we discovered the deep penetration of C ant and a visible pattern of relatively high concentration of C ant along the AABW formation pathway, and the concentration of C ant along the shelf‐slope is higher than that of other marginal seas at low‐mid latitudes, implying a highly effective C ant transport in AABW formation areas. We also found strong upper‐layer CO 2 uptake and a significant acidification rate in the deep waters of the Southern Ocean due to the AABW‐driven CO 2 transport, which is 3 times faster than those in other deep oceans. It is therefore crucial to understand how the Antarctic shelf regions affect the global carbon cycle through the uptake and transport of anthropogenic CO 2 , which also drives acidification in the other ocean basins. Key Points We show evidence for the accumulation of C ant along the Antarctic shelf‐slope into the deep ocean The process of AABW formation drives C ant downward transport at 25.0 ± 4.7 Tg C yr −1 , sustaining the CO 2 uptake in the surface ocean This further triggers acidification of AABW at a rate of −0.0006 ± 0.0001 pH unit yr −1 , which is faster than in other deep oceans
    Type: Article , PeerReviewed
    Format: text
    Format: text
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  • 4
    Publication Date: 2024-02-07
    Description: In recent decades, Arctic summer sea ice extent (SIE) has shown a rapid decline overlaid with large interannual variations, both of which are influenced by geopotential height anomalies over Greenland (GL-high) and the central Arctic (CA-high). In this study, we find that SIE along coastal Siberia (Sib-SIE) and Alaska (Ala-SIE) accounts for about 65% and 21% of the Arctic SIE interannual variability, respectively. Variability in Ala-SIE is related to the GL-high, whereas variability in Sib-SIE is related to the CA-high. A decreased Ala-SIE is associated with decreased cloud cover and increased easterly winds along the Alaskan coast, promoting ice-albedo feedback. A decreased Sib-SIE is associated with a significant increase in water vapor and downward longwave radiation (DLR) along the Siberian coast. The years 2012 and 2020 with minimum recorded ASIE are used as examples. Compared to climatology, summer 2012 is characterized by a significantly enhanced GL-high with major sea ice loss along the Alaskan coast, while summer 2020 is characterized by an enhanced CA-high with sea ice loss focused along the Siberian coast. In 2012, the lack of cloud cover along the Alaskan coast contributed to an increase in incoming solar radiation, amplifying ice-albedo feedback there; while in 2020 the opposite occurs with an increase in cloud cover along the Alaskan coast, resulting in a slight increase in sea ice there. Along the Siberian coast, increased DLR in 2020 plays a dominant role in sea ice loss and increased cloud cover and water vapor both contribute to the increased DLR.
    Type: Article , PeerReviewed
    Format: text
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