Articles | Volume 22, issue 2
https://doi.org/10.5194/bg-22-555-2025
https://doi.org/10.5194/bg-22-555-2025
Research article
 | 
30 Jan 2025
Research article |  | 30 Jan 2025

Seasonal and interannual variability in CO2 fluxes in southern Africa seen by GOSAT

Eva-Marie Metz, Sanam Noreen Vardag, Sourish Basu, Martin Jung, and André Butz

Data sets

ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V9r (https://oco2.gesdisc.eosdis.nasa.gov/data/GOSAT_TANSO_Level2/ACOS_L2_Lite_FP.9r/) OCO-2 Science Team et al. https://doi.org/10.5067/VWSABTO7ZII4

RemoTeC full-physics retrieval GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 version 2.4.0 operated at Heidelberg University A. Butz https://doi.org/10.5281/zenodo.5886662

CarbonTracker CT2022 (https://gml.noaa.gov/aftp/products/carbontracker/co2/CT2022/fluxes/monthly/ and https://gml.noaa.gov/aftp/products/carbontracker/co2/CT2022/molefractions/co2_total_monthly/) A. R. Jacobson et al. https://doi.org/10.25925/z1gj-3254

CAMS global inversion-optimised greenhouse gas fluxes and concentrations Copernicus Atmosphere Monitoring Service https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-greenhouse-gas-inversion

CAMS global biomass burning emissions based on fire radiative power (GFAS) Copernicus Atmosphere Monitoring Service https://ads.atmosphere.copernicus.eu/datasets/cams-global-fire-emissions-gfas

v10 Orbiting Carbon Observatory-2 model intercomparison project D. F. Baker et al. https://gml.noaa.gov/ccgg/OCO2_v10mip/

Global Fire Emissions Database, Version 4.1 (GFED4s) G. R. van der Werf et al. https://www.geo.vu.nl/~gwerf/GFED/GFED4/

Fire INventory from NCAR (FINN), Version 1.5 C. Wiedinmyer et al. https://www.acom.ucar.edu/Data/fire/

ERA5-Land monthly averaged data from 1950 to present (https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land-monthly-means) J. Muñoz Sabater https://doi.org/10.24381/cds.68d2bb30

Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach (http://fluxcom.org/CF-Download/) M. Jung et al. https://doi.org/10.5194/bg-17-1343-2020

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms (http://fluxcom.org/CF-Download/) G. Tramontana et al. https://doi.org/10.5194/bg-13-4291-2016

FLUXNET2015 ZA-Kru Skukuza (2000–2013) (https://fluxnet.org/data/fluxnet2015-dataset/) B. Scholes https://doi.org/10.18140/FLX/1440188

COCCON Version 2 dataset from atmospheric observatory of Gobabeb (Namibia) available at the EVDC Data Handling Facilities covering start date Jan 9th 2017 to end date Nov 27th 2020 (https://secondary-data-archive.nilu.no/evdc/ftir/coccon/gobabeb/version2) D. Dubravica et al. https://doi.org/10.48477/coccon.pf10.gobabeb.R02

MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V061 (https://search.earthdata.nasa.gov/search) M. Friedl and D. Sulla-Menashe https://doi.org/10.5067/MODIS/MCD12C1.061

L2 Daily Solar-Induced Fluorescence (SIF) from MetOp-A GOME-2, 2007–2018, V2 (https://search.earthdata.nasa.gov/) J. Joiner et al. https://doi.org/10.3334/ORNLDAAC/2292

Model code and software

ATMO-IUP-UHEI/MetzEtAl2024: v1.0.0 E.-M. Metz https://doi.org/10.5281/zenodo.12528504

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Short summary
We estimate CO2 fluxes in semiarid southern Africa from 2009 to 2018 based on satellite CO2 measurements and atmospheric inverse modeling. By selecting process-based vegetation models, which agree with the satellite CO2 fluxes, we find that soil respiration mainly drives the seasonality, whereas photosynthesis substantially influences the interannual variability. Our study emphasizes the need for better representation of the response of semiarid ecosystems to soil rewetting in vegetation models.
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