Comparison of Phytoplankton Communities Between Melt Ponds and Open Water in the Central Arctic Ocean

2019 ◽  
Vol 18 (3) ◽  
pp. 573-579
Author(s):  
Tianzhen Zhang ◽  
Yanpei Zhuang ◽  
Haiyan Jin ◽  
Ke Li ◽  
Zhongqian Ji ◽  
...  
2004 ◽  
Vol 91 (1-4) ◽  
pp. 131-141 ◽  
Author(s):  
E. Keith Bigg ◽  
Caroline Leck ◽  
Lars Tranvik

2016 ◽  
Vol 7 ◽  
Author(s):  
Mar Fernández-Méndez ◽  
Kendra A. Turk-Kubo ◽  
Pier L. Buttigieg ◽  
Josephine Z. Rapp ◽  
Thomas Krumpen ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jang-Mu Heo ◽  
Seong-Su Kim ◽  
Sung-Ho Kang ◽  
Eun Jin Yang ◽  
Ki-Tae Park ◽  
...  

AbstractThe western Arctic Ocean (WAO) has experienced increased heat transport into the region, sea-ice reduction, and changes to the WAO nitrous oxide (N2O) cycles from greenhouse gases. We investigated WAO N2O dynamics through an intensive and precise N2O survey during the open-water season of summer 2017. The effects of physical processes (i.e., solubility and advection) were dominant in both the surface (0–50 m) and deep layers (200–2200 m) of the northern Chukchi Sea with an under-saturation of N2O. By contrast, both the surface layer (0–50 m) of the southern Chukchi Sea and the intermediate (50–200 m) layer of the northern Chukchi Sea were significantly influenced by biogeochemically derived N2O production (i.e., through nitrification), with N2O over-saturation. During summer 2017, the southern region acted as a source of atmospheric N2O (mean: + 2.3 ± 2.7 μmol N2O m−2 day−1), whereas the northern region acted as a sink (mean − 1.3 ± 1.5 μmol N2O m−2 day−1). If Arctic environmental changes continue to accelerate and consequently drive the productivity of the Arctic Ocean, the WAO may become a N2O “hot spot”, and therefore, a key region requiring continued observations to both understand N2O dynamics and possibly predict their future changes.


2021 ◽  
Vol 13 (12) ◽  
pp. 2283
Author(s):  
Hyangsun Han ◽  
Sungjae Lee ◽  
Hyun-Cheol Kim ◽  
Miae Kim

The Arctic sea ice concentration (SIC) in summer is a key indicator of global climate change and important information for the development of a more economically valuable Northern Sea Route. Passive microwave (PM) sensors have provided information on the SIC since the 1970s by observing the brightness temperature (TB) of sea ice and open water. However, the SIC in the Arctic estimated by operational algorithms for PM observations is very inaccurate in summer because the TB values of sea ice and open water become similar due to atmospheric effects. In this study, we developed a summer SIC retrieval model for the Pacific Arctic Ocean using Advanced Microwave Scanning Radiometer 2 (AMSR2) observations and European Reanalysis Agency-5 (ERA-5) reanalysis fields based on Random Forest (RF) regression. SIC values computed from the ice/water maps generated from the Korean Multi-purpose Satellite-5 synthetic aperture radar images from July to September in 2015–2017 were used as a reference dataset. A total of 24 features including the TB values of AMSR2 channels, the ratios of TB values (the polarization ratio and the spectral gradient ratio (GR)), total columnar water vapor (TCWV), wind speed, air temperature at 2 m and 925 hPa, and the 30-day average of the air temperatures from the ERA-5 were used as the input variables for the RF model. The RF model showed greatly superior performance in retrieving summer SIC values in the Pacific Arctic Ocean to the Bootstrap (BT) and Arctic Radiation and Turbulence Interaction STudy (ARTIST) Sea Ice (ASI) algorithms under various atmospheric conditions. The root mean square error (RMSE) of the RF SIC values was 7.89% compared to the reference SIC values. The BT and ASI SIC values had three times greater values of RMSE (20.19% and 21.39%, respectively) than the RF SIC values. The air temperatures at 2 m and 925 hPa and their 30-day averages, which indicate the ice surface melting conditions, as well as the GR using the vertically polarized channels at 23 GHz and 18 GHz (GR(23V18V)), TCWV, and GR(36V18V), which accounts for atmospheric water content, were identified as the variables that contributed greatly to the RF model. These important variables allowed the RF model to retrieve unbiased and accurate SIC values by taking into account the changes in TB values of sea ice and open water caused by atmospheric effects.


2021 ◽  
Author(s):  
Jesse R. Farmer ◽  
Daniel M. Sigman ◽  
Julie Granger ◽  
Ona M. Underwood ◽  
François Fripiat ◽  
...  

AbstractSalinity-driven density stratification of the upper Arctic Ocean isolates sea-ice cover and cold, nutrient-poor surface waters from underlying warmer, nutrient-rich waters. Recently, stratification has strengthened in the western Arctic but has weakened in the eastern Arctic; it is unknown if these trends will continue. Here we present foraminifera-bound nitrogen isotopes from Arctic Ocean sediments since 35,000 years ago to reconstruct past changes in nutrient sources and the degree of nutrient consumption in surface waters, the latter reflecting stratification. During the last ice age and early deglaciation, the Arctic was dominated by Atlantic-sourced nitrate and incomplete nitrate consumption, indicating weaker stratification. Starting at 11,000 years ago in the western Arctic, there is a clear isotopic signal of Pacific-sourced nitrate and complete nitrate consumption associated with the flooding of the Bering Strait. These changes reveal that the strong stratification of the western Arctic relies on low-salinity inflow through the Bering Strait. In the central Arctic, nitrate consumption was complete during the early Holocene, then declined after 5,000 years ago as summer insolation decreased. This sequence suggests that precipitation and riverine freshwater fluxes control the stratification of the central Arctic Ocean. Based on these findings, ongoing warming will cause strong stratification to expand into the central Arctic, slowing the nutrient supply to surface waters and thus limiting future phytoplankton productivity.


1999 ◽  
Vol 26 (8) ◽  
pp. 1011-1014 ◽  
Author(s):  
Nadia Buraglio ◽  
Ala A. Aldahan ◽  
Göran Possnert

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