Articles | Volume 15, issue 11
https://doi.org/10.5194/essd-15-5105-2023
https://doi.org/10.5194/essd-15-5105-2023
Data description paper
 | 
24 Nov 2023
Data description paper |  | 24 Nov 2023

Using machine learning to construct TOMCAT model and occultation measurement-based stratospheric methane (TCOM-CH4) and nitrous oxide (TCOM-N2O) profile data sets

Sandip S. Dhomse and Martyn P. Chipperfield

Related authors

Quantifying the tropospheric ozone radiative effect and its temporal evolution in the satellite era
Richard J. Pope, Alexandru Rap, Matilda A. Pimlott, Brice Barret, Eric Le Flochmoen, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Anne Boynard, Christian Retscher, Wuhu Feng, Richard Rigby, Sandip S. Dhomse, Catherine Wespes, and Martyn P. Chipperfield
Atmos. Chem. Phys., 24, 3613–3626, https://doi.org/10.5194/acp-24-3613-2024,https://doi.org/10.5194/acp-24-3613-2024, 2024
Short summary
Quantifying effects of long-range transport of NO2 over Delhi using back trajectories and satellite data
Ailish M. Graham, Richard J. Pope, Martyn P. Chipperfield, Sandip S. Dhomse, Matilda Pimlott, Wuhu Feng, Vikas Singh, Ying Chen, Oliver Wild, Ranjeet Sokhi, and Gufran Beig
Atmos. Chem. Phys., 24, 789–806, https://doi.org/10.5194/acp-24-789-2024,https://doi.org/10.5194/acp-24-789-2024, 2024
Short summary
Investigation of satellite vertical sensitivity on long-term retrieved lower tropospheric ozone trends
Richard J. Pope, Fiona M. O'Connor, Mohit Dalvi, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Brice Barret, Eric Le Flochmoen, Anne Boynard, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, Catherine Wespes, and Richard Rigby
EGUsphere, https://doi.org/10.5194/egusphere-2023-3109,https://doi.org/10.5194/egusphere-2023-3109, 2024
Short summary
Investigation of spatial and temporal variability in lower tropospheric ozone from RAL Space UV–Vis satellite products
Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, and Richard Rigby
Atmos. Chem. Phys., 23, 14933–14947, https://doi.org/10.5194/acp-23-14933-2023,https://doi.org/10.5194/acp-23-14933-2023, 2023
Short summary
Quantifying stratospheric ozone trends over 1984–2020: a comparison of ordinary and regularized multivariate regression models
Yajuan Li, Sandip S. Dhomse, Martyn P. Chipperfield, Wuhu Feng, Jianchun Bian, Yuan Xia, and Dong Guo
Atmos. Chem. Phys., 23, 13029–13047, https://doi.org/10.5194/acp-23-13029-2023,https://doi.org/10.5194/acp-23-13029-2023, 2023
Short summary

Related subject area

Domain: ESSD – Atmosphere | Subject: Atmospheric chemistry and physics
High-resolution physicochemical dataset of atmospheric aerosols over the Tibetan Plateau and its surroundings
Jianzhong Xu, Xinghua Zhang, Wenhui Zhao, Lixiang Zhai, Miao Zhong, Jinsen Shi, Junying Sun, Yanmei Liu, Conghui Xie, Yulong Tan, Kemei Li, Xinlei Ge, Qi Zhang, and Shichang Kang
Earth Syst. Sci. Data, 16, 1875–1900, https://doi.org/10.5194/essd-16-1875-2024,https://doi.org/10.5194/essd-16-1875-2024, 2024
Short summary
Introduction to the NJIAS Himawari-8/9 Cloud Feature Dataset for climate and typhoon research
Xiaoyong Zhuge, Xiaolei Zou, Lu Yu, Xin Li, Mingjian Zeng, Yilun Chen, Bing Zhang, Bin Yao, Fei Tang, Fengjiao Chen, and Wanlin Kan
Earth Syst. Sci. Data, 16, 1747–1769, https://doi.org/10.5194/essd-16-1747-2024,https://doi.org/10.5194/essd-16-1747-2024, 2024
Short summary
The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020
Honglin Pan, Jianping Huang, Jiming Li, Zhongwei Huang, Minzhong Wang, Ali Mamtimin, Wen Huo, Fan Yang, Tian Zhou, and Kanike Raghavendra Kumar
Earth Syst. Sci. Data, 16, 1185–1207, https://doi.org/10.5194/essd-16-1185-2024,https://doi.org/10.5194/essd-16-1185-2024, 2024
Short summary
PalVol v1: a proxy-based semi-stochastic ensemble reconstruction of volcanic stratospheric sulfur injection for the last glacial cycle (140 000–50 BP)
Julie Christin Schindlbeck-Belo, Matthew Toohey, Marion Jegen, Steffen Kutterolf, and Kira Rehfeld
Earth Syst. Sci. Data, 16, 1063–1081, https://doi.org/10.5194/essd-16-1063-2024,https://doi.org/10.5194/essd-16-1063-2024, 2024
Short summary
Ground- and ship-based microwave radiometer measurements during EUREC4A
Sabrina Schnitt, Andreas Foth, Heike Kalesse-Los, Mario Mech, Claudia Acquistapace, Friedhelm Jansen, Ulrich Löhnert, Bernhard Pospichal, Johannes Röttenbacher, Susanne Crewell, and Bjorn Stevens
Earth Syst. Sci. Data, 16, 681–700, https://doi.org/10.5194/essd-16-681-2024,https://doi.org/10.5194/essd-16-681-2024, 2024
Short summary

Cited articles

Arosio, C., Rozanov, A., Malinina, E., Eichmann, K.-U., von Clarmann, T., and Burrows, J. P.: Retrieval of ozone profiles from OMPS limb scattering observations, Atmos. Meas. Tech., 11, 2135–2149, https://doi.org/10.5194/amt-11-2135-2018, 2018. a
Baldwin, M. P., Gray, L. J., Dunkerton, T. J., Hamilton, K., Haynes, P. H., Randel, W. J., Holton, J. R., Alexander, M. J., Hirota, I., Horinouchi, T., Jones, D. B. A., Kinnersley, J. S., Marquardt, C., Sato, K., and Takahashi, M.: The quasi-biennial oscillation, Rev. Geophys., 39, 179–229, https://doi.org/10.1029/1999RG000073, 2001. a
Bândă, N., Krol, M., van Weele, M., van Noije, T., and Röckmann, T.: Analysis of global methane changes after the 1991 Pinatubo volcanic eruption, Atmos. Chem. Phys., 13, 2267–2281, https://doi.org/10.5194/acp-13-2267-2013, 2013. a
Bândă, N., Krol, M., van Weele, M., van Noije, T., Le Sager, P., and Röckmann, T.: Can we explain the observed methane variability after the Mount Pinatubo eruption?, Atmos. Chem. Phys., 16, 195–214, https://doi.org/10.5194/acp-16-195-2016, 2016. a
Bernath, P.: Atmospheric Chemistry Experiment (ACE): An overview, IEEE International Geoscience and Remote Sensing Symposium, 2, 147–160, http://eprints.whiterose.ac.uk/68898/ (last access: 10 January 2023), 2002. a
Download
Short summary
There are no long-term stratospheric profile data sets for two very important greenhouse gases: methane (CH4) and nitrous oxide (N2O). Along with radiative feedback, these species play an important role in controlling ozone loss in the stratosphere. Here, we use machine learning to fuse satellite measurements with a chemical model to construct long-term gap-free profile data sets for CH4 and N2O. We aim to construct similar data sets for other important trace gases (e.g. O3, Cly, NOy species).
Altmetrics
Final-revised paper
Preprint