Online Sea-Ice Knowledge and Data Platform

Grosfeld, Klaus; Treffeisen, Renate; Asseng, Jölund; Bartsch, Annekathrin; Bräuer, Benny; Fritzsch, Bernd; Gerdes, Rüdiger; Hendricks, Stefan; Hiller, Wolfgang; Heygster, Georg; Krumpen, Thomas; Lemke, Peter; Melsheimer, Christian; Nicolaus, Marcel; Ricker, Robert; Weigelt, Marietta

doi:10.2312/polfor.2016.011

Cited by 18 publications

(9 citation statements)

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“…Starting from around 2050, except for SSP126, there are subsequent summers of a virtually ice-free Arctic ocean. The observed September sea-ice extent according to AWI's Sea Ice Portal (Grosfeld et al, 2016; derived from the University Bremen AMSR-ASI product; see Spreen et al, 2008) for 1979 to 2019 is shown (in purple) on top of AWI-CM outputs, confirming that AWI-CM sea-ice extent agrees well with observations both in terms of the average and in terms of the rate of sea ice decline. However, the September Arctic sea ice concentration is underestimated in AWI-CM simulations of the last 30 years as shown in section 4.5.…”

Section: Sea-ice Extentsupporting

confidence: 75%

“…Panels (c) and (d) same as (a) and (b) but for the Antarctic region. The purple line indicates the observed sea-ice extent from the sea ice portal meereisportal.de(Grosfeld et al, 2016). For comparison, observational National Snow and Ice Data Center (NSIDC)(Fetterer et al, 2017) and ERA5 reanalysis (Copernicus Climate Change Service [C3S], 2017;Hersbach et al, 2020) sea-ice extent are shown in inlays along with the ones from sea ice portal.…”

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confidence: 99%

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Simulations for CMIP6 With the AWI Climate Model AWI‐CM‐1‐1

Semmler

Danilov

Gierz

et al. 2020

J Adv Model Earth Syst

104

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The Alfred Wegener Institute Climate Model (AWI‐CM) participates for the first time in the Coupled Model Intercomparison Project (CMIP), CMIP6. The sea ice‐ocean component, FESOM, runs on an unstructured mesh with horizontal resolutions ranging from 8 to 80 km. FESOM is coupled to the Max Planck Institute atmospheric model ECHAM 6.3 at a horizontal resolution of about 100 km. Using objective performance indices, it is shown that AWI‐CM performs better than the average of CMIP5 models. AWI‐CM shows an equilibrium climate sensitivity of 3.2°C, which is similar to the CMIP5 average, and a transient climate response of 2.1°C which is slightly higher than the CMIP5 average. The negative trend of Arctic sea‐ice extent in September over the past 30 years is 20–30% weaker in our simulations compared to observations. With the strongest emission scenario, the AMOC decreases by 25% until the end of the century which is less than the CMIP5 average of 40%. Patterns and even magnitude of simulated temperature and precipitation changes at the end of this century compared to present‐day climate under the strong emission scenario SSP585 are similar to the multi‐model CMIP5 mean. The simulations show a 11°C warming north of the Barents Sea and around 2°C to 3°C over most parts of the ocean as well as a wetting of the Arctic, subpolar, tropical, and Southern Ocean. Furthermore, in the northern middle latitudes in boreal summer and autumn as well as in the southern middle latitudes, a more zonal atmospheric flow is projected throughout the year.

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Section: Sea-ice Extentsupporting

confidence: 75%

mentioning

confidence: 99%

Simulations for CMIP6 With the AWI Climate Model AWI‐CM‐1‐1

Semmler

Danilov

Gierz

et al. 2020

J Adv Model Earth Syst

104

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“…During summer and winter, Antarctic sea ice does not show a significant overall trend (Parkinson and DiGirolamo, 2021). Nevertheless, south and west of the Antarctic Peninsula, one region has shown a persistent decline (Grosfeld et al, 2013). In February 2020 weather stations recorded the hottest temperature on record for Antarctica, reaching 18.3 • C (64.9 • F) (Rocha Francelino et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Antarctic Glacial Meltwater Impacts the Diversity of Fungal Parasites Associated With Benthic Diatoms in Shallow Coastal Zones

et al. 2022

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Aquatic ecosystems are frequently overlooked as fungal habitats, although there is increasing evidence that their diversity and ecological importance are greater than previously considered. Aquatic fungi are critical and abundant components of nutrient cycling and food web dynamics, e.g., exerting top-down control on phytoplankton communities and forming symbioses with many marine microorganisms. However, their relevance for microphytobenthic communities is almost unexplored. In the light of global warming, polar regions face extreme changes in abiotic factors with a severe impact on biodiversity and ecosystem functioning. Therefore, this study aimed to describe, for the first time, fungal diversity in Antarctic benthic habitats along the salinity gradient and to determine the co-occurrence of fungal parasites with their algal hosts, which were dominated by benthic diatoms. Our results reveal that Ascomycota and Chytridiomycota are the most abundant fungal taxa in these habitats. We show that also in Antarctic waters, salinity has a major impact on shaping not just fungal but rather the whole eukaryotic community composition, with a diversity of aquatic fungi increasing as salinity decreases. Moreover, we determined correlations between putative fungal parasites and potential benthic diatom hosts, highlighting the need for further systematic analysis of fungal diversity along with studies on taxonomy and ecological roles of Chytridiomycota.

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“…River and sediment inputs to the Arctic Ocean have increased over past decades due to warming temperatures and changing atmospheric moisture patterns, and are expected to increase in the future as warming continues (Andreson et al, 2020;Wang et al, 2021). Higher temperatures have also led to declining summer sea ice cover (Grosfeld et al, 2015;Serreze et al, 2006), more extensive permafrost thaw (Biskaborn et al, 2019;IPCC, 2021), and faster rates of coastal erosion (Günther et al, 2013;Irrgang et al, 2022). There is also evidence of increasing pore water exchange rates from continental shelves (Kipp, Charette, et al, 2018;Kipp, Sanial, et al, 2018;Rutgers van der Loeff et al, 2018), which may be linked to increased wave action and vertical mixing on shelves associated with the diminishing ice cover (Carmack & Chapman, 2003;Rainville & Woodgate, 2009;Williams & Carmack, 2015).…”

Section: Discussionmentioning

confidence: 99%

Radium Inputs Into the Arctic Ocean From Rivers: A Basin‐Wide Estimate

et al. 2022

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Radium isotopes have been used to trace nutrient, carbon, and trace metal fluxes inputs from ocean margins. However, these approaches require a full accounting of radium sources to the coastal ocean including rivers. Here, we aim to quantify river radium inputs into the Arctic Ocean for the first time for 226Ra and to refine the estimates for 228Ra. Using new and existing data, we find that the estimated combined (dissolved plus desorbed) annual 226Ra and 228Ra fluxes to the Arctic Ocean are [7.0–9.4] × 1014 dpm y−1 and [15–18] × 1014 dpm y−1, respectively. Of these totals, 44% and 60% of the river 226Ra and 228Ra, respectively are from suspended sediment desorption, which were estimated from laboratory incubation experiments. Using Ra isotope data from 20 major rivers around the world, we derived global annual 226Ra and 228Ra fluxes of [7.4–17] × 1015 and [15–27] × 1015 dpm y−1, respectively. As climate change spurs rapid Arctic warming, hydrological cycles are intensifying and coastal ice cover and permafrost are diminishing. These river radium inputs to the Arctic Ocean will serve as a valuable baseline as we attempt to understand the changes that warming temperatures are having on fluxes of biogeochemically important elements to the Arctic coastal zone.

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Online Sea-Ice Knowledge and Data Platform

Cited by 18 publications

References 0 publications

Simulations for CMIP6 With the AWI Climate Model AWI‐CM‐1‐1

Simulations for CMIP6 With the AWI Climate Model AWI‐CM‐1‐1

Antarctic Glacial Meltwater Impacts the Diversity of Fungal Parasites Associated With Benthic Diatoms in Shallow Coastal Zones

Radium Inputs Into the Arctic Ocean From Rivers: A Basin‐Wide Estimate

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