Articles | Volume 24, issue 9
https://doi.org/10.5194/acp-24-5315-2024
https://doi.org/10.5194/acp-24-5315-2024
Research article
 | 
07 May 2024
Research article |  | 07 May 2024

Potential of using CO2 observations over India in a regional carbon budget estimation by improving the modelling system

Vishnu Thilakan, Dhanyalekshmi Pillai, Jithin Sukumaran, Christoph Gerbig, Haseeb Hakkim, Vinayak Sinha, Yukio Terao, Manish Naja, and Monish Vijay Deshpande

Related authors

Evaluating the meteorological transport model ensemble for accounting uncertainties in carbon flux estimation over India
Thara Anna Mathew, Aparnna Ravi, Dhanyalekshmi Pillai, Lekshmi Saradambal, Jithin S. Kumar, Manoj M. Gopalakrishnan, and Vishnu Thilakan
EGUsphere, https://doi.org/10.5194/egusphere-2023-2334,https://doi.org/10.5194/egusphere-2023-2334, 2024
Short summary
Spatiotemporal variations in terrestrial biospheric CO2 fluxes of India derived from MODIS, OCO-2 and TROPOMI satellite observations and a diagnostic terrestrial vegetation model
Aparnna Ravi, Dhanyalekshmi Pillai, Christoph Gerbig, Stephen Sitch, Sönke Zaehle, Vishnu Thilakan, and Chandra Shekhar Jha
EGUsphere, https://doi.org/10.5194/egusphere-2023-817,https://doi.org/10.5194/egusphere-2023-817, 2023
Preprint archived
Short summary
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
Atmos. Chem. Phys., 22, 15287–15312, https://doi.org/10.5194/acp-22-15287-2022,https://doi.org/10.5194/acp-22-15287-2022, 2022
Short summary
Towards monitoring CO2 source-sink distribution over India via inverse modelling: Quantifying the fine-scale spatiotemporal variability of atmospheric CO2 mole fraction
Vishnu Thilakan, Dhanyalekshmi Pillai, Christoph Gerbig, Michal Galkowski, Aparnna Ravi, and Thara Anna Mathew
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-392,https://doi.org/10.5194/acp-2021-392, 2021
Revised manuscript not accepted
Short summary

Related subject area

Subject: Gases | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Tracing the origins of stratospheric ozone intrusions: direct vs. indirect pathways and their impacts on Central and Eastern China in spring–summer 2019
Kai Meng, Tianliang Zhao, Yongqing Bai, Ming Wu, Le Cao, Xuewei Hou, Yuehan Luo, and Yongcheng Jiang
Atmos. Chem. Phys., 24, 12623–12642, https://doi.org/10.5194/acp-24-12623-2024,https://doi.org/10.5194/acp-24-12623-2024, 2024
Short summary
Flow-dependent observation errors for greenhouse gas inversions in an ensemble Kalman smoother
Michael Steiner, Luca Cantarello, Stephan Henne, and Dominik Brunner
Atmos. Chem. Phys., 24, 12447–12463, https://doi.org/10.5194/acp-24-12447-2024,https://doi.org/10.5194/acp-24-12447-2024, 2024
Short summary
Observational and model evidence for a prominent stratospheric influence on variability in tropospheric nitrous oxide
Cynthia D. Nevison, Qing Liang, Paul A. Newman, Britton B. Stephens, Geoff Dutton, Xin Lan, Roisin Commane, Yenny Gonzalez, and Eric Kort
Atmos. Chem. Phys., 24, 10513–10529, https://doi.org/10.5194/acp-24-10513-2024,https://doi.org/10.5194/acp-24-10513-2024, 2024
Short summary
Estimation of Canada's methane emissions: inverse modelling analysis using the Environment and Climate Change Canada (ECCC) measurement network
Misa Ishizawa, Douglas Chan, Doug Worthy, Elton Chan, Felix Vogel, Joe R. Melton, and Vivek K. Arora
Atmos. Chem. Phys., 24, 10013–10038, https://doi.org/10.5194/acp-24-10013-2024,https://doi.org/10.5194/acp-24-10013-2024, 2024
Short summary
Spatiotemporal source apportionment of ozone pollution over the Greater Bay Area
Yiang Chen, Xingcheng Lu, and Jimmy C. H. Fung
Atmos. Chem. Phys., 24, 8847–8864, https://doi.org/10.5194/acp-24-8847-2024,https://doi.org/10.5194/acp-24-8847-2024, 2024
Short summary

Cited articles

Agustí-Panareda, A., Diamantakis, M., Massart, S., Chevallier, F., Muñoz-Sabater, J., Barré, J., Curcoll, R., Engelen, R., Langerock, B., Law, R. M., Loh, Z., Morguí, J. A., Parrington, M., Peuch, V.-H., Ramonet, M., Roehl, C., Vermeulen, A. T., Warneke, T., and Wunch, D.: Modelling CO2 weather – why horizontal resolution matters, Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, 2019. a
Agustí-Panareda, A., Barré, J., Massart, S., Inness, A., Aben, I., Ades, M., Baier, B. C., Balsamo, G., Borsdorff, T., Bousserez, N., Boussetta, S., Buchwitz, M., Cantarello, L., Crevoisier, C., Engelen, R., Eskes, H., Flemming, J., Garrigues, S., Hasekamp, O., Huijnen, V., Jones, L., Kipling, Z., Langerock, B., McNorton, J., Meilhac, N., Noël, S., Parrington, M., Peuch, V.-H., Ramonet, M., Razinger, M., Reuter, M., Ribas, R., Suttie, M., Sweeney, C., Tarniewicz, J., and Wu, L.: Technical note: The CAMS greenhouse gas reanalysis from 2003 to 2020, Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, 2023. a, b
Bhardwaj, P., Naja, M., Kumar, R., and Chandola, H. C.: Seasonal, interannual, and long-term variabilities in biomass burning activity over South Asia, Environ. Sci. Pollut. Res., 23, 4397–4410, https://doi.org/10.1007/s11356-015-5629-6, 2016. a
Bhuvan: Indian Geo-Platform of ISRO, https://bhuvan-app3.nrsc.gov.in/data/download/index.php, last access: 12 December 2022. a
Boadh, R., Satyanarayana, A., Rama Krishna, T., and Madala, S.: Sensitivity of PBL schemes of the WRF-ARW model in simulating the boundary layer flow parameters for their application to air pollution dispersion modeling over a tropical station, Atmósfera, 29, 61–81, https://doi.org/10.20937/ATM.2016.29.01.05, 2016. a
Download
Short summary
This study investigates the usability of CO2 mixing ratio observations over India to infer regional carbon sources and sinks. We demonstrate that a high-resolution modelling system can represent the observed CO2 variations reasonably well by improving the transport and flux variations at a fine scale. Future carbon data assimilation systems can thus benefit from these recently available CO2 observations when fine-scale variations are adequately represented in the models.
Altmetrics
Final-revised paper
Preprint