Towards monitoring the CO<sub>2</sub> source–sink distribution over India via inverse modelling: quantifying the fine-scale spatiotemporal variability in the atmospheric CO<sub>2</sub> mole fraction

Abstract 2 sources and sinks over India through inverse methods calls for a comprehensive atmospheric monitoring system involving atmospheric transport models that make a realistic accounting of atmospheric CO2 variability along with a good coverage of ground-based monitoring stations. This study investigates the importance of representing fine-scale variability in atmospheric CO2 in models for the optimal use of observations through inverse modelling. The unresolved variability in atmospheric CO2 in coarse models is quantified by using WRF-Chem (Weather Research and Forecasting model coupled with Chemistry) simulations at a spatial resolution of 10 km × ∘ (∼ 2, respectively) compared to the measurement errors. The monthly averaged surface representation error reaches up to ∼ 2 variability in models over the Indian subcontinent to better understand processes regulating CO2 sources and sinks. The efficacy of a simple parameterization scheme is further demonstrated to capture these unresolved variations in coarse models.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Towards monitoring the CO2 source–sink distribution over India via inverse modelling: quantifying the fine-scale spatiotemporal variability in the atmospheric CO2 mole fraction ; volume:22 ; number:23 ; year:2022 ; pages:15287-15312 ; extent:26
Atmospheric chemistry and physics ; 22, Heft 23 (2022), 15287-15312 (gesamt 26)

Creator
Thilakan, Vishnu
Pillai, Dhanyalekshmi
Gerbig, Christoph
Gałkowski, Michał
Ravi, Aparnna
Anna Mathew, Thara

DOI
10.5194/acp-22-15287-2022
URN
urn:nbn:de:101:1-2022120804412428059461
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:33 AM CEST

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