Articles | Volume 22, issue 23
https://doi.org/10.5194/acp-22-15287-2022
https://doi.org/10.5194/acp-22-15287-2022
Research article
 | 
01 Dec 2022
Research article |  | 01 Dec 2022

Towards monitoring the CO2 source–sink distribution over India via inverse modelling: quantifying the fine-scale spatiotemporal variability in the atmospheric CO2 mole fraction

Vishnu Thilakan, Dhanyalekshmi Pillai, Christoph Gerbig, Michal Galkowski, Aparnna Ravi, and Thara Anna Mathew

Viewed

Total article views: 2,417 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,773 582 62 2,417 168 58 59
  • HTML: 1,773
  • PDF: 582
  • XML: 62
  • Total: 2,417
  • Supplement: 168
  • BibTeX: 58
  • EndNote: 59
Views and downloads (calculated since 24 Jun 2022)
Cumulative views and downloads (calculated since 24 Jun 2022)

Viewed (geographical distribution)

Total article views: 2,417 (including HTML, PDF, and XML) Thereof 2,353 with geography defined and 64 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
Short summary
This paper demonstrates how we can use atmospheric observations to improve the CO2 flux estimates in India. This is achieved by improving the representation of terrain, mesoscale transport, and flux variations. We quantify the impact of the unresolved variations in the current models on optimally estimated fluxes via inverse modelling and quantify the associated flux uncertainty. We illustrate how a parameterization scheme captures this variability in the coarse models.
Altmetrics
Final-revised paper
Preprint