Ability of the 4-D-Var analysis of the GOSAT BESD XCO<SUB>2</SUB> retrievals to characterize atmospheric CO<SUB>2</SUB> at large and synoptic scales - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2015

Ability of the 4-D-Var analysis of the GOSAT BESD XCO2 retrievals to characterize atmospheric CO2 at large and synoptic scales

A. Agustí-Panareda
  • Fonction : Auteur
J. Heymann
  • Fonction : Auteur
M. Buchwitz
  • Fonction : Auteur
F. Chevallier
  • Fonction : Auteur
M. Reuter
  • Fonction : Auteur
M. Hilker
  • Fonction : Auteur
J. P. Burrows
  • Fonction : Auteur
F. Hase
  • Fonction : Auteur
F. Desmet
  • Fonction : Auteur
D. G. Feist
  • Fonction : Auteur
R. Kivi
  • Fonction : Auteur

Résumé

This study presents results from the European Centre for Medium-Range Weather Forecasts (ECMWF) carbon dioxide (CO2) analysis system where the atmospheric CO2 is controlled through the assimilation of column-average dry-air mole fractions of CO2 (XCO2) from the Greenhouse gases Observing Satellite (GOSAT). The analysis is compared to a free run simulation and they are both evaluated against XCO2 data from the Total Carbon Column Observing Network (TCCON). We show that the assimilation of the GOSAT XCO2 product from the Bremen Optimal Estimation DOAS (BESD) algorithm during the year 2013 provides XCO2 fields with an improved station-to-station bias deviation of 0.7 parts per million (ppm) compared to the free run (1.4 ppm) and an improved estimated precision of ~ 1 ppm compared to the used GOSAT data (3.4 ppm). We also show that the analysis has skill for synoptic situations in the vicinity of frontal systems where the GOSAT retrievals are sparse due to cloud contamination. We finally computed the 10 day forecast from each analysis at 00:00 UTC. Compared to its own analysis the CO2 forecast shows synoptic skill for the largest scale weather patterns even up to day 5 according to the anomaly correlation coefficient.
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Dates et versions

hal-04114755 , version 1 (02-06-2023)

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Citer

S. Massart, A. Agustí-Panareda, J. Heymann, M. Buchwitz, F. Chevallier, et al.. Ability of the 4-D-Var analysis of the GOSAT BESD XCO2 retrievals to characterize atmospheric CO2 at large and synoptic scales. 2023. ⟨hal-04114755⟩
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