Articles | Volume 16, issue 5
https://doi.org/10.5194/amt-16-1121-2023
https://doi.org/10.5194/amt-16-1121-2023
Research article
 | 
07 Mar 2023
Research article |  | 07 Mar 2023

A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm

Joshua L. Laughner, Sébastien Roche, Matthäus Kiel, Geoffrey C. Toon, Debra Wunch, Bianca C. Baier, Sébastien Biraud, Huilin Chen, Rigel Kivi, Thomas Laemmel, Kathryn McKain, Pierre-Yves Quéhé, Constantina Rousogenous, Britton B. Stephens, Kaley Walker, and Paul O. Wennberg

Data sets

ATom: Merged Atmospheric Chemistry, Trace Gases, and Aerosols S. C. Wofsy, S. Afshar, H. Allen, E. Apel, E. Asher, B. Barletta, J. Bent, H. Bian, B. Biggs, D. Blake, N. Blake, I. Bourgeois, C. Brock, W. Brune, J. Budney, T. Bui, A. Butler, P. Campuzano-Jost, C. Chang, M. Chin, R. Commane, G. Correa, J. Crounse, P. Cullis, B. Daube, D. Day, J. Dean-Day, J. Dibb, J. P. DiGangi, G. Diskin, M. Dollner, J. Elkins, F. Erdesz, A. Fiore, C. Flynn, K. Froyd, D. Gesler, S. Hall, T. Hanisco, R. Hannun, A. Hills, E. Hintsa, A. Hoffman, R. Hornbrook, L. Huey, S. Hughes, J. Jimenez, B. Johnson, J. Katich, R. Keeling, M. Kim, A. Kupc, L. Lait, K. McKain, R. Mclaughlin, S. Meinardi, D. Miller, S. Montzka, F. Moore, E. Morgan, D. Murphy, L. Murray, B. Nault, J. Neuman, P. Newman, J. Nicely, X. Pan, W. Paplawsky, J. Peischl, M. Prather, D. Price, E. Ray, J. Reeves, M. Richardson, A. Rollins, K. Rosenlof, T. Ryerson, E. Scheuer, G. Schill, J. Schroder, J. Schwarz, J. St. Clair, S. Steenrod, B. Stephens, S. Strode, C. Sweeney, D. Tanner, A. Teng, A. Thames, C. Thompson, K. Ullmann, P. Veres, N. Wagner, A. Watt, R. Weber, B. Weinzierl, P. Wennberg, C. Williamson, J. Wilson, G. Wolfe, C. Woods, L. Zeng, and N. Vieznor https://doi.org/10.3334/ORNLDAAC/1581

HIPPO Merged 10-Second Meteorology, Atmospheric Chemistry, and Aerosol Data, Version 1.0 S. C. Wofsy, B. Daube, R. Jimenez, E. Kort, J. V. Pittman, S. Park, R. Commane, B. Xiang, G. Santoni, D. J. Jacob, J. A. Fisher, C. A. Pickett-Heaps, H. Wang, K. J. Wecht, Q. Wang, B. B. Stephens, S. R. Shertz, A. Watt, P. Romashkin, T. Campos, J. Haggerty, W. A. Cooper, D. C. Rogers, S. Beaton, R. Hendershot, J. W. Elkins, D. W. Fahey, R. Gao, J. P. Schwarz, F. Moore, S. A. Montzka, A. E. Perring, D. Hurst, B. R. Miller, C. Sweeney, S. J. Oltmans, E. J. Hintsa, D. Nance, G. S. Dutton, L. A. Watts, J. R. Spackman, K. H. Rosenlof, E. Ray, B. Hall, M. Zondlo, M. Diao, R. F. Keeling, J. Bent, E. Atlas, R. Lueb, and M. J. Mahoney https://doi.org/10.3334/CDIAC/HIPPO_010

Multi-laboratory compilation of atmospheric carbon dioxide data for the period 1957-2018; obspack_co2_1_GLOBALVIEWplus_v5.0_2019_08_12 Cooperative Global Atmospheric Data Integration Project https://doi.org/10.25925/20190812

Multi-laboratory compilation of atmospheric methane data for the period 1957-2018; obspack_ch4_1_GLOBALVIEWplus_v2.0_2020-04-24 Cooperative Global Atmospheric Data Integration Project https://doi.org/10.25925/20200424

CO from 30-year specified dynamics run of the Canadian Middle Atmosphere Model Canadian Centre for Climate Modeling and Analysis https://climate-modelling.canada.ca/climatemodeldata/cmam/output/CMAM/CMAM30-SD/mon/atmosChem/vmrco/index.shtml

Atmospheric Chemistry Experiment SciSat Level 2 Processed Data, v3.5/v3.6. P. Bernath, C. Boone, J. Steffen, and J. Crouse https://doi.org/10.20383/102.0495

GEOS FP-IT data Goddard Earth Sciences Data Information Services Center (GES-DISC) https://gmao.gsfc.nasa.gov/GMAO_products/

CAMS global atmospheric composition forecasts Copernicus Atmosphere Monitoring Service (CAMS) https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-atmospheric-composition-forecasts?tab=overview

Model code and software

ginput v1.0.7b: GGG2020 prior profile software J. Laughner, A. Andrews, S. Roche, M. Kiel, and G. Toon https://doi.org/10.22002/D1.1880

WennbergLab/py-ginput: ginput v1.1.6 release J. Laughner https://doi.org/10.22002/D1.20285

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Short summary
Observations using sunlight to measure surface-to-space total column of greenhouse gases in the atmosphere need an initial guess of the vertical distribution of those gases to start from. We have developed an approach to provide those initial guess profiles that uses readily available meteorological data as input. This lets us make these guesses without simulating them with a global model. The profiles generated this way match independent observations well.