A detectable change in the air-sea CO2 flux estimate from sailboat measurements

This repository contains files and scripts used to generate figures for the paper titled "A detectable change in the air-sea CO2 flux estimate from sailboat measurements". The study quantifies the impact of pCO2 observations measured by the sailboat "Seaexplorer" on the air-sea CO2 flux estimate.
 Overview:
We used pCO2 measurements sourced from SOCAT (www.socat.info), along with other environmental variables. We applied the 2-step neural network method SOM-FFN (Landschützer et al., 2013) to reconstruct air-sea CO2 flux estimates.
Four sets of air-sea CO2 flux estimates were reconstructed, each with 40 ensemble members to account for random errors in the neural network. These are the four sets:
E1) fluxesA - Based on SOCATv2022 including Seaexplorer data
E2) fluxesB - Based on SOCATv2022 excluding Seaexplorer data.
E3) fluxesC - Based on SOCATv2022 data, including Seaexplorer data, but introducing a random uncertainty of ± 5 μatm to the Seaexplorer data.
E4) fluxesD - Based on SOCATv2022 data, including Seaexplorer data, but introducing a constant measurement offset of 5 μatm to the Seaexplorer data.
These air-sea CO2 flux density estimates are 4-dimensional, represented in mol C m-2 yr-1, with the following dimensions:
- Ensemble size of flux reconstructions (40)
- Time (months from 1982 to 2021, totaling 480 months)
- Latitude (1-degree intervals, totaling 180 latitudes)
- Longitude (1-degree intervals, totaling 360 longitudes)