scholarly journals First records of winter sea ice concentration in the southwest Pacific sector of the Southern Ocean

2015 ◽  
Vol 30 (11) ◽  
pp. 1525-1539 ◽  
Author(s):  
Alexander J. Ferry ◽  
Xavier Crosta ◽  
Patrick G. Quilty ◽  
David Fink ◽  
William Howard ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Sea Ice Concentration ◽  
Southwest Pacific ◽  
Ice Concentration

scholarly journals DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations

2021 ◽  
pp. 1-6
Author(s):  
Hao Luo ◽  
Qinghua Yang ◽  
Longjiang Mu ◽  
Xiangshan Tian-Kunze ◽  
Lars Nerger ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Southern Ocean ◽  
Sea Ice ◽  
Coupled Model ◽  
Sea Ice Concentration ◽  
Model Free ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
Data Assimilation System ◽  
Assimilation System

Abstract To improve Antarctic sea-ice simulations and estimations, an ensemble-based Data Assimilation System for the Southern Ocean (DASSO) was developed based on a regional sea ice–ocean coupled model, which assimilates sea-ice thickness (SIT) together with sea-ice concentration (SIC) derived from satellites. To validate the performance of DASSO, experiments were conducted from 15 April to 14 October 2016. Generally, assimilating SIC and SIT can suppress the overestimation of sea ice in the model-free run. Besides considering uncertainties in the operational atmospheric forcing data, a covariance inflation procedure in data assimilation further improves the simulation of Antarctic sea ice, especially SIT. The results demonstrate the effectiveness of assimilating sea-ice observations in reconstructing the state of Antarctic sea ice, but also highlight the necessity of more reasonable error estimation for the background as well as the observation.

scholarly journals Modeling the effect of Ross Ice Shelf melting on the Southern Ocean in quasi-equilibrium

2018 ◽  
Vol 12 (9) ◽  
pp. 3033-3044 ◽  
Author(s):  
Xiying Liu
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Ross Sea ◽  
Global Ocean ◽  
Freshwater Flux ◽  
Quasi Equilibrium ◽  
Ice Shelf ◽  
Sea Ice Concentration ◽  
Ross Ice Shelf ◽  
Ice Concentration

Abstract. To study the influence of basal melting of the Ross Ice Shelf (BMRIS) on the Southern Ocean (ocean southward of 35∘ S) in quasi-equilibrium, numerical experiments with and without the BMRIS effect were performed using a global ocean–sea ice–ice shelf coupled model. In both experiments, the model started from a state of quasi-equilibrium ocean and was integrated for 500 years forced by CORE (Coordinated Ocean-ice Reference Experiment) normal-year atmospheric fields. The simulation results of the last 100 years were analyzed. The melt rate averaged over the entire Ross Ice Shelf is 0.25 m a−1, which is associated with a freshwater flux of 3.15 mSv (1 mSv = 103 m3 s−1). The extra freshwater flux decreases the salinity in the region from 1500 m depth to the sea floor in the southern Pacific and Indian oceans, with a maximum difference of nearly 0.005 PSU in the Pacific Ocean. Conversely, the effect of concurrent heat flux is mainly confined to the middle depth layer (approximately 1500 to 3000 m). The decreased density due to the BMRIS effect, together with the influence of ocean topography, creates local differences in circulation in the Ross Sea and nearby waters. Through advection by the Antarctic Circumpolar Current, the flux difference from BMRIS gives rise to an increase of sea ice thickness and sea ice concentration in the Ross Sea adjacent to the coast and ocean water to the east. Warm advection and accumulation of warm water associated with differences in local circulation decrease sea ice concentration on the margins of sea ice cover adjacent to open water in the Ross Sea in September. The decreased water density weakens the subpolar cell as well as the lower cell in the global residual meridional overturning circulation (MOC). Moreover, we observe accompanying reduced southward meridional heat transport at most latitudes of the Southern Ocean.

scholarly journals NEMO-ICB (v1.0): interactive icebergs in the NEMO ocean model globally configured at coarse and eddy-permitting resolution

2014 ◽  
Vol 7 (4) ◽  
pp. 5661-5698 ◽  
Author(s):  
R. Marsh ◽  
V. O. Ivchenko ◽  
N. Skliris ◽  
S. Alderson ◽  
G. R. Bigg ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Ocean Model ◽  
Coastal Current ◽  
Density Gradients ◽  
Surface Salinity ◽  
Sea Ice Concentration ◽  
Freshwater Forcing ◽  
Ice Concentration ◽  
The Antarctic

Abstract. NEMO-ICB features interactive icebergs in the NEMO ocean model. Simulations with coarse (2°) and eddy-permitting (0.25°) global configurations of NEMO-ICB are undertaken to evaluate the influence of icebergs on sea-ice, hydrography and transports, through comparison with control simulations in which the equivalent iceberg mass flux is applied as coastal runoff, the default forcing in NEMO. Comparing a short (14 year) spin-up of the 0.25° model with a computationally cheaper 105 year spin-up of the 2° configuration, calving, drift and melting of icebergs is evidently near equilibrium in the shorter simulation, justifying closer examination of iceberg influences in the eddy-permitting configuration. Freshwater forcing due to iceberg melt is most pronounced in southern high latitudes, where it is locally dominant over precipitation. Sea ice concentration and thickness in the Southern Ocean are locally increased with icebergs, by up to ~ 8 and ~ 25% respectively. Iceberg melting reduces surface salinity by ~ 0.2 psu around much of Antarctica, with compensating increases immediately adjacent to Antarctica, where coastal runoff is suppressed. Discernible effects on salinity and temperature extend to 1000 m. At many locations and levels, freshening and cooling indicate a degree of density compensation. However, freshening is a dominant influence on upper ocean density gradients across much of the high-latitude Southern Ocean, leading to weaker meridional density gradients, a reduced eastward transport tendency, and hence an increase of ~ 20% in westward transport of the Antarctic Coastal Current.

scholarly journals Assimilation of sea surface temperature, sea ice concentration and sea ice drift in a model of the Southern Ocean

2015 ◽  
Vol 93 ◽  
pp. 22-39 ◽  
Author(s):  
Alexander Barth ◽  
Martin Canter ◽  
Bert Van Schaeybroeck ◽  
Stéphane Vannitsem ◽  
François Massonnet ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Sea Ice Concentration ◽  
Ice Drift ◽  
Ice Concentration ◽  
Sea Ice Drift

scholarly journals Sea Ice Concentration and Sea Ice Extent Mapping with L-Band Microwave Radiometry and GNSS-R Data from the FFSCat Mission Using Neural Networks

2021 ◽  
Vol 13 (6) ◽  
pp. 1139
Author(s):  
David Llaveria ◽  
Juan Francesc Munoz-Martin ◽  
Christoph Herbert ◽  
Miriam Pablos ◽  
Hyuk Park ◽  
...  
Keyword(s):  
Sea Ice ◽  
Microwave Radiometer ◽  
Cost Effective ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Neural Network Approach ◽  
Ice Concentration ◽  
L Band ◽  
Moderate Cost

CubeSat-based Earth Observation missions have emerged in recent times, achieving scientifically valuable data at a moderate cost. FSSCat is a two 6U CubeSats mission, winner of the ESA S3 challenge and overall winner of the 2017 Copernicus Masters Competition, that was launched in September 2020. The first satellite, 3Cat-5/A, carries the FMPL-2 instrument, an L-band microwave radiometer and a GNSS-Reflectometer. This work presents a neural network approach for retrieving sea ice concentration and sea ice extent maps on the Arctic and the Antarctic oceans using FMPL-2 data. The results from the first months of operations are presented and analyzed, and the quality of the retrieved maps is assessed by comparing them with other existing sea ice concentration maps. As compared to OSI SAF products, the overall accuracy for the sea ice extent maps is greater than 97% using MWR data, and up to 99% when using combined GNSS-R and MWR data. In the case of Sea ice concentration, the absolute errors are lower than 5%, with MWR and lower than 3% combining it with the GNSS-R. The total extent area computed using this methodology is close, with 2.5% difference, to those computed by other well consolidated algorithms, such as OSI SAF or NSIDC. The approach presented for estimating sea ice extent and concentration maps is a cost-effective alternative, and using a constellation of CubeSats, it can be further improved.

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.

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