Articles | Volume 9, issue 7
https://doi.org/10.5194/amt-9-3165-2016
https://doi.org/10.5194/amt-9-3165-2016
Research article
 | 
21 Jul 2016
Research article |  | 21 Jul 2016

Characterization of anthropogenic methane plumes with the Hyperspectral Thermal Emission Spectrometer (HyTES): a retrieval method and error analysis

Le Kuai, John R. Worden, King-Fai Li, Glynn C. Hulley, Francesca M. Hopkins, Charles E. Miller, Simon J. Hook, Riley M. Duren, and Andrew D. Aubrey

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Cited articles

Alvarado, M. J., Payne, V. H., Mlawer, E. J., Uymin, G., Shephard, M. W., Cady-Pereira, K. E., Delamere, J. S., and Moncet, J.-L.: Performance of the Line-By-Line Radiative Transfer Model (LBLRTM) for temperature, water vapor, and trace gas retrievals: recent updates evaluated with IASI case studies, Atmos. Chem. Phys., 13, 6687–6711, https://doi.org/10.5194/acp-13-6687-2013, 2013.
Caulton, D. R., Shepson, P. B., Santoro, R. L., Sparks, J. P., Howarth, R. W., Ingraffea, A. R., Cambaliza, M. O., Sweeney, C., Karion, A., and Davis, K. J.: Toward a better understanding and quantification of methane emissions from shale gas development, P. Natl. Acad. Sci. USA, 111, 6237–6242, 2014.
Clough, S. A., Shephard, M. W., Worden, J., Brown, P. D., Worden, H. M., Luo, M., Rodgers, C. D., Rinsland, C. P., Goldman, A., and Brown, L.: Forward model and Jacobians for tropospheric emission spectrometer retrievals, IEEE T. Geosci. Remote, 44, 1308–1323, 2006.
Etheridge, D. M., Steele, L. P., Francey, R. J., and Langenfelds, R. L.: Atmospheric methane between 1000 AD and present: Evidence of anthropogenic emissions and climatic variability, J. Geophys. Res., 103, 15979–15993, https://doi.org/10.1029/98JD00923, 1998.
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Short summary
This paper describes the retrieval algorithm to estimate the lower tropospheric methane concentrations using Hyperspectral Thermal Emission Spectrometer (HyTES) airborne measurements. This project aims to map and detect methane plumes from the oil leaking or dairy emission. Our results demonstrate an example of the quantitative retrievals, imaged a big methane plume from storage tanks near Kern River Oil Field. The methane enhancement is well above the uncertainties of the estimates.