Articles | Volume 18, issue 20
https://doi.org/10.5194/gmd-18-7275-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-7275-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
15 Oct 2025
Development and technical paper |
| 15 Oct 2025
| 15 Oct 2025
PyESPERv1.0.0: a Python implementation of empirical seawater property estimation routines (ESPERs)
Cooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, Seattle, 98105, USA
NOAA Pacific Marine Environmental Laboratory, Seattle, 98115, USA
Brendan R. Carter
Cooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, Seattle, 98105, USA
NOAA Pacific Marine Environmental Laboratory, Seattle, 98115, USA
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GLODAP is a data product for ocean inorganic carbon and related biogeochemical variables measured by chemical analysis of water bottle samples at scientific cruises. GLODAPv2.2020 is the second update of GLODAPv2 from 2016. The data that are included have been subjected to extensive quality control, including systematic evaluation of measurement biases. This version contains data from 946 hydrographic cruises covering the world's oceans from 1972 to 2019.
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Short summary
The increasing availability of oceanographic physical and chemical data necessitates accompanying methods for optimizing use of these data. This project produced algorithms (PyESPERs) for estimating biogeochemical seawater properties in Python, a freely available coding language. These algorithms were based on empirical seawater property estimation routines (ESPERs), which were originally written in the proprietary MATLAB coding language and can be used in studies of marine carbonate chemistry.
The increasing availability of oceanographic physical and chemical data necessitates...
