scholarly journals Measurements of open-water arctic ocean noise directionality and transport velocity

2021 ◽  
Vol 150 (3) ◽  
pp. 1954-1966
Author(s):  
Aaron M. Thode ◽  
Robert G. Norman ◽  
Alexander S. Conrad ◽  
Ludovic Tenorio-Hallé ◽  
Susanna B. Blackwell ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Open Water ◽  
Ocean Noise ◽  
Transport Velocity

scholarly journals N2O dynamics in the western Arctic Ocean during the summer of 2017

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jang-Mu Heo ◽  
Seong-Su Kim ◽  
Sung-Ho Kang ◽  
Eun Jin Yang ◽  
Ki-Tae Park ◽  
...  
Keyword(s):  
Arctic Ocean ◽  
Environmental Changes ◽  
Chukchi Sea ◽  
Hot Spot ◽  
Open Water ◽  
Northern Region ◽  
The Arctic ◽  
Western Arctic Ocean ◽  
Deep Layers ◽  
Western Arctic

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.

scholarly journals Retrieval of Summer Sea Ice Concentration in the Pacific Arctic Ocean from AMSR2 Observations and Numerical Weather Data Using Random Forest Regression

2021 ◽  
Vol 13 (12) ◽  
pp. 2283
Author(s):  
Hyangsun Han ◽  
Sungjae Lee ◽  
Hyun-Cheol Kim ◽  
Miae Kim
Keyword(s):  
Random Forest ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Open Water ◽  
The Arctic ◽  
Atmospheric Effects ◽  
Sea Ice Concentration ◽  
Air Temperatures ◽  
The Pacific ◽  
Ice Concentration

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.

Changes in phytoplankton concentration now drive increased Arctic Ocean primary production

Science ◽  
2020 ◽  
Vol 369 (6500) ◽  
pp. 198-202 ◽  
Author(s):  
K. M. Lewis ◽  
G. L. van Dijken ◽  
K. R. Arrigo
Keyword(s):  
Sea Ice ◽  
Primary Production ◽  
Arctic Ocean ◽  
Open Water ◽  
Water Area ◽  
The Arctic ◽  
Carbon Export ◽  
Phytoplankton Primary Production ◽  
Open Water Area ◽  
The Arctic Ocean

Historically, sea ice loss in the Arctic Ocean has promoted increased phytoplankton primary production because of the greater open water area and a longer growing season. However, debate remains about whether primary production will continue to rise should sea ice decline further. Using an ocean color algorithm parameterized for the Arctic Ocean, we show that primary production increased by 57% between 1998 and 2018. Surprisingly, whereas increases were due to widespread sea ice loss during the first decade, the subsequent rise in primary production was driven primarily by increased phytoplankton biomass, which was likely sustained by an influx of new nutrients. This suggests a future Arctic Ocean that can support higher trophic-level production and additional carbon export.

scholarly journals The Arctic Ocean Multi-Year Ice Balance, 1979-82

1990 ◽  
Vol 14 ◽  
pp. 252-255 ◽  
Author(s):  
D.A. Rothrock ◽  
D.R. Thomas
Keyword(s):  
Arctic Ocean ◽  
Open Water ◽  
Measurement Model ◽  
The Arctic ◽  
First Year ◽  
Independent Data ◽  
Self Consistent ◽  
Buoy Data ◽  
Parameter Values ◽  
Self Consistency

A method of determining the temporally varying “state” of the ice cover (the concentrations of three surface types: open water, first-year ice, and multi-year ice) is presented. The methodology is that of Kalman smoothing: a physical model and a measurement model are used to blend satellite passive microwave data and buoy data to give an optimal estimate of the ice state. The estimates are optimal only to the degree that model parameter values are known and assumptions about variances are met. Uncertainty about these values and assumptions, and lack of independent data with which to compare results,leaves self-consistency as the most important test of results. A four-year record (1979-82) of the estimated Arctic Ocean ice balance is presented and shown to be self-consistent. Results are discussed in terms of the Arctic multi-year ice balance, which may be an important factor in the interaction ofocean, sea ice and climate because of its relationship to the minimum summer ice extent. The estimated area of multi-year ice decreases each year, but the decrease is small and insignificant based on four years of results. Furthermore, the observed decrease may be due to instrument drift or changes in the multi-year ice signature.

Growth of Wave Height with Retreating Ice Cover in the Arctic

2020 ◽  
Author(s):  
Changlong Guan ◽  
Jingkai Li
Keyword(s):  
Arctic Ocean ◽  
Surface Waves ◽  
Wave Height ◽  
Open Water ◽  
Ice Cover ◽  
Wave Climate ◽  
Least Square ◽  
The Arctic ◽  
The Arctic Ocean ◽  
Wave Heights

<p>For the Arctic surface waves, one of the most uncontroversial viewpoints is that their escalation in the past few years is mainly caused by the ice extent reduction. Ice retreat enlarges the open water area, i.e., the effective fetch, and thus allows more wind input energy and available distance for wave evolution. This knowledge has been supported by a few previous studies on the Arctic waves which analyzed the correlation between time-series variations in wave height and ice coverage. However, from the perspective of space, the detailed relationship between retreating ice cover and increasing surface waves is not well studied. Hence, we performed such a study for the whole Arctic and its subregions, which will be helpful for a better understanding of the wave climate and for forecasting waves in the Arctic Ocean.</p><p>Wave data are produced by twelve-year (2007-2018) hindcasts of summer melt seasons (May-Sept.) and numerical tests with WAVEWATCH III. When a viscoelastic wave-ice model and a spherical multiple-cell grid are applied, simulated wave heights agree with available buoy data and previous research. After the validations, simulated significant wave heights over twelve-year summer melt seasons are used to demonstrate the detailed relationship between the escalation of wave height and reduction of ice extent for the whole Arctic and seven subregions. Through least square regression, we find that the mean wave height in the Arctic Ocean will increase by 0.071m (10<sup>6</sup>km<sup>2</sup>)<sup>-1</sup> when the ice extent is smaller than 9.4×10<sup>6</sup>km<sup>2</sup>, and roughly 51% is contributed by the enlarged fetch. By analyzing the nondimensional wave energy and comparing the simulated wave height with Wilson IV, we prove the swell is widespread during the summertime in the current Arctic Ocean. Furthermore, we also display the variations in probabilities of occurrence of large waves as ice-edge retreats in seven subregions. Assuming that an ice free period occurs in the Arctic in September, the model results show that the simulated mean wave height is approximately 1.6m and the large waves occur much more frequently, which mean that the growth rate of wave height will be higher if the minimum ice extent keeps reducing in the future.</p>

scholarly journals Approaching Freshet beneath Landfast Ice in Kugmallit Bay on the Canadian Arctic Shelf: Evidence from Sensor and Ground Truth Data

ARCTIC ◽  
2009 ◽  
Vol 61 (1) ◽  
pp. 76 ◽  
Author(s):  
Tony R. Walker ◽  
Jon Grant ◽  
Peter Jarvis
Keyword(s):  
Arctic Ocean ◽  
Ground Truth ◽  
Open Water ◽  
Early Spring ◽  
The Arctic ◽  
Ground Truth Data ◽  
The North ◽  
Landfast Ice ◽  
North American Arctic ◽  
Mackenzie River

The Mackenzie River is the largest river in the North American Arctic. Its huge freshwater and sediment load impacts the Canadian Beaufort Shelf, transporting large quantities of sediment and associated organic carbon into the Arctic Ocean. The majority of this sediment transport occurs during the freshet peak flow season (May to June). Mackenzie River-Arctic Ocean coupling has been widely studied during open water seasons, but has rarely been investigated in shallow water under landfast ice in Kugmallit Bay with field-based surveys, except for those using remote sensing. We observed and measured sedimentation rates (51 g m-2 d-1) and the concentrations of chlorophyll a (mean 2.2 ?g L-1) and suspended particulate matter (8.5 mg L-1) and determined the sediment characteristics during early spring, before the breakup of landfast ice in Kugmallit Bay. We then compared these results with comparable data collected from the same site the previous summer. Comparison of organic quality in seston and trapped material demonstrated substantial seasonal differences. The subtle changes in biological and oceanographic variables beneath landfast ice that we measured using sensors and field sampling techniques suggest the onset of a spring melt occurring hundreds of kilometres farther south in the Mackenzie Basin.

Seasonal methane and carbon dioxide emissions from the coastal nearshore of the Kolyma river, Siberia.

2021 ◽  
Author(s):  
Juri Palmtag ◽  
Cara Manning ◽  
Michael Bedington ◽  
Matthias Fuchs ◽  
Mathias Göckede ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Arctic Ocean ◽  
Carbon Dioxide Emissions ◽  
Open Water ◽  
The Arctic ◽  
Global Ocean ◽  
Nearshore Zone ◽  
Terrestrial Organic Matter ◽  
The Arctic Ocean ◽  
Kolyma River

<p>Arctic rivers deliver ≈11% of global river discharge into the Arctic Ocean, while this ocean represents only ≈1% of the global ocean volume. Ongoing climate warming across the Arctic, and specifically Siberia, has led to regional-scale changes in precipitation patterns, greater rates of permafrost thaw and active layer deepening, as well as enhanced riverbank and coastal erosion. Combined, these climatic and cryospheric perturbations have already resulted in increased freshwater discharge and changes to constituent loads (e.g. dissolved organic carbon - OC) supplied from land to the Arctic Ocean.</p><p>To date, the majority of studies examining terrestrial organic matter (OM) delivery to the Arctic Ocean have focused almost entirely on freshwater (riverine) or fully-marine environments and been conducted during late summer seasons – often due to logistical constraints. Despite this, an improved understanding of how OC is transformed, mineralised and released during transit through the highly reactive nearshore estuarine environment is critical for examining the fate and influence of terrestrial OM on the Arctic Ocean. Capturing seasonality over the open water period is also necessary to identify current OM fluxes to the ocean vs the atmosphere, and aid in constraining how future changes may modify them.</p><p>Here we focus upon carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) measurements collected during six repeated transects of the Kolyma River and nearshore zone (covering ~120 km) from 2019. Transects spanned almost the entirety of the riverine open water season (June to September). We use these results, in parallel with gas concentrations derived from prior studies, to develop and validate a simple box-model of gas emissions from the nearshore zone.</p><p>Observations and model‐derived output data reveal that more than 50% of the cumulative gross delivery of CH<sub>4</sub> and CO<sub>2</sub> to the coastal ocean occurred during the freshet period with dissolved CH<sub>4</sub> concentrations in surface water reaching 660 Nanomole per liter [nmol/l]. These results demonstrate the relevance of seasonal dynamics and its spatial variability which are needed in order to estimate greenhouse gas fluxes on an annual basis.</p><p>More accurate understanding of land-ocean carbon fluxes in the Arctic is therefore crucial to mitigate the effects of climate change and to support the decisions of policy makers.</p>

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