Global scale inversions from MOPITT CO and MODIS AOD
Gaubert, B., Edwards, D. P., Anderson, J. L., Arellano, A. F., Barré, J., et al. (2023). Global scale inversions from MOPITT CO and MODIS AOD. Remote Sensing, doi:10.3390/rs15194813
| Title | Global scale inversions from MOPITT CO and MODIS AOD |
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| Author(s) | Benjamin Gaubert, David P. Edwards, Jeffrey L. Anderson, Avelino F. Arellano, Jérôme Barré, Rebecca R. Buchholz, Sabine Darras, Louisa K. Emmons, David Fillmore, Claire Granier, James W. Hannigan, Ivan Ortega, Kevin Raeder, Antonin Soulié, Wenfu Tang, Helen M. Worden, Daniel Ziskin |
| Abstract | Top-down observational constraints on emissions flux estimates from satellite observations of chemical composition are subject to biases and errors stemming from transport, chemistry and prior emissions estimates. In this context, we developed an ensemble data assimilation system to optimize the initial conditions for carbon monoxide (CO) and aerosols, while also quantifying the respective emission fluxes with a distinct attribution of anthropogenic and wildfire sources. We present the separate assimilation of CO profile v9 retrievals from the Measurements of Pollution in the Troposphere (MOPITT) instrument and Aerosol Optical Depth (AOD), collection 6.1, from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. This assimilation system is built on the Data Assimilation Research Testbed (DART) and includes a meteorological ensemble to assimilate weather observations within the online Community Atmosphere Model with Chemistry (CAM-chem). Inversions indicate an underestimation of CO emissions in CAMS-GLOB-ANT_v5.1 in China for 2015 and an overestimation of CO emissions in the Fire INventory from NCAR (FINN) version 2.2, especially in the tropics. These emissions increments are consistent between the MODIS AOD and the MOPITT CO-based inversions. Additional simulations and comparison with in situ observations from the NASA Atmospheric Tomography Mission (ATom) show that biases in hydroxyl radical (OH) chemistry dominate the CO errors. |
| Publication Title | Remote Sensing |
| Publication Date | Oct 3, 2023 |
| Publisher's Version of Record | https://dx.doi.org/10.3390/rs15194813 |
| OpenSky Citable URL | https://n2t.net/ark:/85065/d7g44vb6 |
| OpenSky Listing | View on OpenSky |
| CISL Affiliations | TDD, DARES |