StraitFlux – Precise computations of Water Strait fluxes on various Modelling Grids
Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data is complicated by the distortion of the used curvilinear ocean model grids towards their displaced north poles. Combined with the large number of different grid type...
| Main Authors: | , , |
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| Format: | Article in Journal/Newspaper |
| Language: | English |
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Copernicus Publications
2024
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| Subjects: | |
| Online Access: | https://doi.org/10.5194/egusphere-2023-2883 https://noa.gwlb.de/receive/cop_mods_00070785 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00069115/egusphere-2023-2883.pdf https://egusphere.copernicus.org/preprints/2024/egusphere-2023-2883/egusphere-2023-2883.pdf |
| Summary: | Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data is complicated by the distortion of the used curvilinear ocean model grids towards their displaced north poles. Combined with the large number of different grid types, this has made the exact calculation of oceanic transports a challenging and time-consuming task. Use of data on standard latitude/longitude grids is not an option since transports computed from those are not mass consistent. We present two methods for transport calculations on grids with variously shifted north poles, different orientations, and different Arakawa partitions. The first method calculates net transports through arbitrary sections using line integrals, while the second method generates cross-sections of the vertical-horizontal planes of these sections using vector projection algorithms. Apart from the input data on the original model grids the user only needs to specify the start and end points of the required section to get the net transports (with both methods) and their integrand (for the second method). This allows to calculate oceanic fluxes through almost arbitrary sections, to compare them with observed oceanic volume and energy transports at available sections such as the RAPID array or at Fram strait and other Arctic gateways, or to compare them amongst reanalyses and to model integrations from the Coupled Model Intercomparison Projects (CMIP). We implemented our methods in a Python package called StraitFlux. This paper represents its scienfic documentation and demonstrates its application on outputs of multiple CMIP6 models and several ocean reanalyses. We also analyse the robustness and computational performance of the tools as well as the uncertainties of the results. The package is available on github and zenodo and can be installed using pypi. |
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