Design and numerical simulation of an Arctic Ocean circulation and thermodynamic sea-ice model

1995 ◽  
Vol 12 (3) ◽  
pp. 289-310 ◽  
Author(s):  
Yu Rucong ◽  
Jin Xiangze ◽  
Zhang Xuehong
Keyword(s):  
Numerical Simulation ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Circulation ◽  
Arctic Ocean Circulation ◽  
Ice Model

scholarly journals Arctic Tides Drive Water Mixing and Sea Ice Loss

Eos ◽  
2016 ◽  
Vol 97 ◽  
Author(s):  
Lily Strelich
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Circulation ◽  
Water Mixing ◽  
Ice Volume ◽  
Arctic Ocean Circulation

Researchers model ice-ocean interaction to study how tides can influence Arctic Ocean circulation and sea ice volume.

scholarly journals Recent Sea Ice Decline Did Not Significantly Increase the Total Liquid Freshwater Content of the Arctic Ocean

2018 ◽  
Vol 32 (1) ◽  
pp. 15-32 ◽  
Author(s):  
Qiang Wang ◽  
Claudia Wekerle ◽  
Sergey Danilov ◽  
Dmitry Sidorenko ◽  
Nikolay Koldunov ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Ocean Circulation ◽  
General Circulation ◽  
The Arctic ◽  
Sea Ice Decline ◽  
The Arctic Ocean ◽  
Eurasian Basin ◽  
The Impact

Abstract The freshwater stored in the Arctic Ocean is an important component of the global climate system. Currently the Arctic liquid freshwater content (FWC) has reached a record high since the beginning of the last century. In this study we use numerical simulations to investigate the impact of sea ice decline on the Arctic liquid FWC and its spatial distribution. The global unstructured-mesh ocean general circulation model Finite Element Sea Ice–Ocean Model (FESOM) with 4.5-km horizontal resolution in the Arctic region is applied. The simulations show that sea ice decline increases the FWC by freshening the ocean through sea ice meltwater and modifies upper ocean circulation at the same time. The two effects together significantly increase the freshwater stored in the Amerasian basin and reduce its amount in the Eurasian basin. The salinification of the upper Eurasian basin is mainly caused by the reduction in the proportion of Pacific Water and the increase in that of Atlantic Water (AW). Consequently, the sea ice decline did not significantly contribute to the observed rapid increase in the Arctic total liquid FWC. However, the changes in the Arctic freshwater spatial distribution indicate that the influence of sea ice decline on the ocean environment is remarkable. Sea ice decline increases the amount of Barents Sea branch AW in the upper Arctic Ocean, thus reducing its supply to the deeper Arctic layers. This study suggests that all the dynamical processes sensitive to sea ice decline should be taken into account when understanding and predicting Arctic changes.

scholarly journals Simulation of Snow on Arctic Sea Ice Using a Coupled Snow–Ice Model

2010 ◽  
Vol 11 (1) ◽  
pp. 199-210 ◽  
Author(s):  
Yi-Ching Chung ◽  
Stéphane Bélair ◽  
Jocelyn Mailhot
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Snow Depth ◽  
Single Layer ◽  
Coupled System ◽  
The Arctic ◽  
Ice Thickness ◽  
The Arctic Ocean ◽  
Snow Model ◽  
Ice Model

Abstract The new Recherche Prévision Numérique (NEW-RPN) model, a coupled system including a multilayer snow thermal model (SNTHERM) and the sea ice model currently used in the Meteorological Service of Canada (MSC) operational forecasting system, was evaluated in a one-dimensional mode using meteorological observations from the Surface Heat Budget of the Arctic Ocean (SHEBA)’s Pittsburgh site in the Arctic Ocean collected during 1997/98. Two parameters simulated by NEW-RPN (i.e., snow depth and ice thickness) are compared with SHEBA’s observations and with simulations from RPN, MSC’s current coupled system (the same sea ice model and a single-layer snow model). Results show that NEW-RPN exhibits better agreement for the timing of snow depletion and for ice thickness. The profiles of snow thermal conductivity in NEW-RPN show considerable variability across the snow layers, but the mean value (0.39 W m−1 K−1) is within the range of reported observations for SHEBA. This value is larger than 0.31 W m−1 K−1, which is commonly used in single-layer snow models. Of particular interest in NEW-RPN’s simulation is the strong temperature stratification of the snowpack, which indicates that a multilayer snow model is needed in the SHEBA scenario. A sensitivity analysis indicates that snow compaction is also a crucial process for a realistic representation of the snowpack within the snow/sea ice system. NEW-RPN’s overestimation of snow depth may be related to other processes not included in the study, such as small-scale horizontal variability of snow depth and blowing snow processes.

GPU acceleration of the FESOM-2 ocean and sea-ice model

2021 ◽  
Author(s):  
Gijs van den Oord ◽  
Alessio Sclocco ◽  
Georges-Emmanuel Moulard ◽  
David Guibert ◽  
Dmitry Sidorenko ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ocean Circulation ◽  
Gpu Acceleration ◽  
Dominant Factor ◽  
Tracer Transport ◽  
Fortran Code ◽  
Mesh Resolution ◽  
Engineering Effort ◽  
Access Patterns ◽  
Ice Model

<p>FESOM-2 is a finite volume ocean circulation and sea ice model developed by the Alfred Wegener Institute (AWI). It solves the primitive equations using the hydrostatic and Bousinessq approximations on an unstructured grid, allowing seamless mesh resolution increase towards eddy-resolving scales in regions of high variability or along coast lines. FESOM-2 is a highly optimized MPI-parallel Fortran code that displays excellent scaling to tens of thousands of cores. In the context of ESiWACE-2 services, we have explored the benefits of GPU acceleration of FESOM-2 in a six-month engineering effort. We have determined the flux-corrected tracer transport, and in particular the advection of temperature and salinity, to be a dominant factor in the application profile and we have ported this routine to GPUs using both OpenACC and CUDA-C. We conclude that the memory access patterns in FESOM-2 are suitable to map onto GPU accelerators and that both strategies are viable options, giving significant speedups for tracer advection in high-resolution mesh configurations. We have benchmarked the ported application on Nvidia Kepler, Volta and Ampere architectures and observe that our tuned kernels can approach the peak memory bandwidth, and we also see that OpenACC offers a competitive performance with less development and maintenance effort. We conclude that an expansion of the OpenACC directives is the most promising road to utilize upcoming GPU-equipped exascale machines for FESOM-2.</p>

Sign in / Sign up

Export Citation Format

Share Document