esmtools.carbon.temp_decomp_takahashi

esmtools.carbon.temp_decomp_takahashi(ds, time_dim='time', temperature='tos', pco2='spco2')[source]

Decompose surface pCO2 into thermal and non-thermal components.

Note

This expects cmorized variable names. You can pass keywords to change that or rename your variables accordingly.

Parameters:ds (xarray.Dataset) – Contains two variables: * tos (sea surface temperature in degC) * spco2 (surface pCO2 in uatm)
Returns:Decomposed thermal and non-thermal components.
Return type:decomp (xr.Dataset)

References

  • Takahashi, Taro, Stewart C. Sutherland, Colm Sweeney, Alain Poisson, Nicolas Metzl, Bronte Tilbrook, Nicolas Bates, et al. “Global Sea–Air CO2 Flux Based on Climatological Surface Ocean PCO2, and Seasonal Biological and Temperature Effects.” Deep Sea Research Part II: Topical Studies in Oceanography, The Southern Ocean I: Climatic Changes in the Cycle of Carbon in the Southern Ocean, 49, no. 9 (January 1,2002): 1601–22. https://doi.org/10/dmk4f2.

Examples

>>> from esmtools.carbon import temp_decomp_takahashi
>>> import numpy as np
>>> import xarray as xr
>>> t = xr.DataArray(np.random.randint(10, 25, size=(100, 10, 10)),
        dims=['time', 'lat', 'lon']).rename('tos')
>>> pco2 = xr.DataArray(np.random.randint(350, 400, size=(100, 10, 10)),
        dims=['time', 'lat', 'lon']).rename('spco2')
>>> ds = xr.merge([t, pco2])
>>> decomp = temp_decomp_takahashi(ds)