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Worldwide Evaluation of CAMS-EGG4 CO2 Data Re-Analysis at the Surface Level
Danilo Custódio1,2, Carlos Borrego3, Hélder Relvas3
1Helmholtz-Zentrum Hereon, Institute of Coastal Environmental Chemistry, Max-Planck-Str. 1, 21502 Geesthacht, Germany.
Toxics
|June 23, 2022
Summary
This study assessed global uncertainties in Copernicus Atmosphere Monitoring Service (CAMS) carbon dioxide (CO2) data. CAMS accurately captures CO2 trends in remote areas but shows significant biases in continental regions with high emissions.
Area of Science:
- Atmospheric chemistry and physics
- Earth system science
- Environmental monitoring
Background:
- The Copernicus Atmosphere Monitoring Service (CAMS) provides crucial data on atmospheric composition.
- Accurate carbon dioxide (CO2) measurements are vital for understanding climate change and emission sources.
- Global re-analysis products require rigorous validation against independent observations.
Purpose of the Study:
- To systematically evaluate global uncertainties and biases in the CAMS CO2 mixing ratio data product.
- To assess the performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) global greenhouse gas re-analysis (EGG4) against ground-based measurements.
- To identify regions and conditions where the CAMS CO2 product exhibits significant deviations from observations.
Main Methods:
- Comparison of CAMS global greenhouse gas re-analysis (EGG4) data with in situ ground-based measurements from over 160 global stations.
- Analysis of CO2 seasonal cycles, trends, and flux patterns at various scales (diurnal to interannual).
- Evaluation of model performance in remote, marine, and continental regions with varying CO2 flux profiles.
Main Results:
- CAMS CO2 re-analysis successfully captures general tracer distributions, seasonal cycles, and global trends.
- The model performs well in remote and marine environments with low CO2 fluxes.
- Significant weaknesses and biases were observed in continental areas with complex sources and high anthropogenic CO2 fluxes, with root-mean-square errors up to 70 ppmv.
Conclusions:
- The CAMS CO2 product demonstrates good compliance in regions with smooth variability but struggles with sharp flux changes in continental areas.
- Large uncertainties in continental regions with high anthropogenic emissions suggest issues with emission inventories and model parameterizations.
- The study provides a comprehensive uncertainty assessment for the CAMS CO2 product, highlighting areas for future improvement in regional CO2 estimation.
