xarray.Dataset.argo.canyon_med

xarray.Dataset.argo.canyon_med#

Dataset.argo.canyon_med(**kwargs)#

Nutrients and Carbonate System Variables predictor with CANYON-MED

This is an implementation of the CANYON-MED method: a Regional Neural Network Approach to Estimate Water-Column Nutrient Concentrations and Carbonate System Variables in the Mediterranean Sea ([1], [2]).

When using this method, please cite the papers.

See also

canyon_med.predict(), canyon_med.input_list, canyon_med.output_list

Examples

Load data, they must contain oxygen measurements:

from argopy import DataFetcher
ArgoSet = DataFetcher(ds='bgc', mode='standard', params='DOXY', measured='DOXY').float(1902605)
ds = ArgoSet.to_xarray()

Once input data are loaded, make all or selected parameters predictions:

ds.argo.canyon_med.predict()
ds.argo.canyon_med.predict('PO4')
ds.argo.canyon_med.predict(['PO4', 'NO3'])

Notes

This Python implementation is largely inspired by work from Marine Fourrier (MarineFou) and Florian Ricour (fricour) from LOV.

First Python implementation was published here: euroargodev/CANYON-MED

References

[1]

Fourrier, M., Coppola, L., Claustre, H., D’Ortenzio, F., Sauzede, R., and Gattuso, J.-P. (2020). A Regional Neural Network Approach to Estimate Water-Column Nutrient Concentrations and Carbonate System Variables in the Mediterranean Sea: CANYON-MED. Frontiers in Marine Science 7. doi:10.3389/fmars.2020.00620.

[2]

Fourrier, M., Coppola, L., Claustre, H., D’Ortenzio, F., Sauzede, R., and Gattuso, J.-P. (2021). Corrigendum: A Regional Neural Network Approach to Estimate Water-Column Nutrient Concentrations and Carbonate System Variables in the Mediterranean Sea: CANYON-MED. Frontiers in Marine Science 8. doi:10.3389/fmars.2021.650509.