ATom: Merged Atmospheric Chemistry, Trace Gases, and Aerosols

Wofsy, S.C.; Afshar, Shahrara; Allen, Hannah M.; Apel, E. C.; Asher, Elizabeth; Barletta, B.; Bent, J. D.; Bian, Huisheng; Biggs, Brenna; Blake, D. R.; Blake, N. J.; Bourgeois, Ilann; Brock, C. A.; Brune, W. H.; Budney, J.; Bui, T. P.; Butler, Amy H.; Campuzano‐Jost, P.; Chang, Cecilia S.; Chin, Mian; Commane, R.; Correa, Gustavo; Crounse, J. D.; Cullis, Patrick; Daube, Bruce C.; Day, D. A.; Dean‐Day, Jonathan M.; Dibb, Jack E.; DiGangi, J. P.; Diskin, G. S.; Dollner, Maximilian; Elkins, James W.; Erdesz, Frank; Fiore, Arlene M.; Flynn, Clare M.; Froyd, K. D.; Gesler, D.W.; Hall, S. R.; Hanisco, T. F.; Hannun, Reem A.; Hills, A. J.; Hintsa, E. J.; Hoffman, Alicia; Hornbrook, R. S.; Huey, L. G.; Hughes, S.; Jiménez, José; Johnson, B. J.; Katich, Joseph M.; Keeling, Ralph F.; Kim, M.J.; Kupc, Agnieszka; Lait, Leslie R.; Lamarque, Jean‐François; Liu, J.; McKain, Kathryn; McLaughlin, Richard J.; Meinardi, Simone; Miller, David O.; Montzka, S. A.; Moore, F. L.; Morgan, Eric J.; Murphy, D. M.; Murray, Lee T.; Nault, Benjamin A.; Neuman, J. A.; Newman, Paul A.; Nicely, Julie M.; Pan, Xiaohua; Paplawsky, W.; Peischl, J.; Prather, MJ; Price, Derek J.; Ray, E. A.; Reeves, J. M.; Richardson, M.; Rollins, A. W.; Rosenlof, K. H.; Ryerson, T. B.; Scheuer, Eric; Schill, Gregory P.; Schroder, Jason C.; Schwarz, J. P.; Clair, J. M. St; Steenrod, Stephen D.; Stephens, B. B.; Strode, Sarah A.; Sweeney, C.; Tanner, D.; Teng, Alex; Thames, A. B.; Thompson, C. Ray; Ullmann, Kirk; Veres, P. R.; Vizenor, N.; Wagner, Nick; Watt, A.; Weber, R. J.; Weinzierl, Bernadett; Wennberg, P. O.; Williamson, C.; Wilson, J. C.; Wolfe, G. M.; Woods, C.; Zeng, Linghan

doi:10.3334/ornldaac/1581

Cited by 53 publications

(42 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A previous comparison of clear MOPITT and TROPOMI total CO column retrievals showed good agreement between the two datasets(Martínez-Alonso et al, 2020). In that same study, cloudy TROPOMI CO retrievals over bodies of water were also validated with respect to ATom (Atmospheric Tomography mission;Wofsy et al, 2018) aircraft profiles. The results showed that the e null (null-space error) of the profile scaling retrieval over water is very small (2.16 %).…”

mentioning

confidence: 70%

Evaluation of MOPITT and TROPOMI carbon monoxide retrievals using AirCore in situ vertical profiles

Martínez-Alonso

Aben

Baier

et al. 2022

Preprint

View full text Add to dashboard Cite

Abstract. AirCore in situ vertical profiles sample the atmosphere from near the surface to the lower stratosphere, making them ideal for the validation of satellite tropospheric trace gas data. Here we present intercomparison results of AirCore carbon monoxide (CO) measurements with respect to retrievals from MOPITT (Measurements of Pollution In The Troposphere; version 8) and TROPOMI (TROPOspheric Monitoring Instrument), onboard the NASA Terra and ESA Sentinel 5-Precursor satellites, respectively. Mean MOPITT/AirCore total column bias values and their standard deviation (0.0 ± 0.9, 0.3 ± 1.0, and 0.1 ± 1.0 for MOPITT thermal-infrared, near-infrared, and multispectral retrievals, respectively; all in units of 1017 molec cm-2) are similar to results obtained in MOPITT/NOAA aircraft flask data comparisons from this study and from previous validation efforts. MOPITT CO retrievals are systematically validated using in situ vertical profiles from a variety of aircraft campaigns. Because most aircraft vertical profiles do not sample the troposphere's entire vertical extent, they must be extended upwards in order to be usable in validation. Here we quantify for the first time the error introduced in MOPITT CO validation by the use of shorter aircraft vertical profiles extended upwards by analyzing validation results from AirCore CO vertical profiles. Our results indicate that the error is small, affects mostly upper tropospheric retrievals (at 300 hPa: ~ 2.6, 0.8, and 3.2 percent points for MOPITT thermal-infrared, near-infrared, and multispectral, respectively), and may have resulted in the overestimation of MOPITT retrieval biases in that region. TROPOMI can retrieve CO under both clear and cloudy conditions. The latter is achieved by quantifying interfering trace gases and parameters describing the cloud contamination of the measurements together with the CO column; then, the reference CO profiles used in the retrieval are scaled based on estimated above-cloud CO rather than on estimated total CO. We use AirCore measurements to evaluate the error introduced by this approach in cloudy TROPOMI retrievals over land after accounting for TROPOMI's vertical sensitivity to CO (relative bias and its standard deviation = 2.02 % ± 11.13 %). We also quantify the null-space error, which accounts for differences between the shape of TROPOMI reference profiles and that of AirCore true profiles (for TROPOMI cloudy enull = 0.98 % ± 2.32 %).

show abstract

mentioning

confidence: 70%

Evaluation of MOPITT and TROPOMI carbon monoxide retrievals using AirCore in situ vertical profiles

Martínez-Alonso

Aben

Baier

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The FIM-Chem v1 code and model configuration for chemical composition forecasts here are available at https: //doi.org/10.5281/zenodo.5044392 (Zhang et al, 2021). ATom-1 data are publicly available at the Oak Ridge National Laboratory Distributed Active Archive Center: https://daac.ornl.gov/ATOM/ guides/ATom_merge.html (last access: 13 January 2022) (DOI: https://doi.org/10.3334/ornldaac/1581, Wofsy et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…The Atmospheric Tomography Mission (ATom) studies the impact of human-produced air pollution on greenhouse gases and on chemically reactive gases in the atmosphere (Wofsy et al, 2018). ATom deploys instrumentation to sample the atmospheric composition, profiling the atmosphere in the 0.2 to 12 km altitude range.…”

Section: Observationsmentioning

confidence: 99%

Inline coupling of simple and complex chemistry modules within the global weather forecast model FIM (FIM-Chem v1)

et al. 2022

View full text Add to dashboard Cite

Abstract. The global Flow-following finite-volume Icosahedral Model (FIM), which was developed in the Global Systems Laboratory (GSL) of NOAA, has been coupled inline with aerosol and gas-phase chemistry schemes of different complexity using the chemistry and aerosol packages from WRF-Chem v3.7, named FIM-Chem v1. The three chemistry schemes include (1) the simple aerosol modules from the Goddard Chemistry Aerosol Radiation and Transport model that includes only simplified sulfur chemistry, black carbon (BC), organic carbon (OC), and sectional dust and sea salt modules (GOCART); (2) the photochemical gas phase of the Regional Atmospheric Chemistry Mechanism (RACM) coupled to GOCART to determine the impact of more realistic gas-phase chemistry on the GOCART aerosol simulations (RACM_GOCART); and (3) a further sophistication within the aerosol modules by replacing GOCART with a modal aerosol scheme that includes secondary organic aerosols (SOAs) based on the volatility basis set (VBS) approach (RACM_SOA_VBS). FIM-Chem is able to simulate aerosol, gas-phase chemical species, and SOA at various spatial resolutions with different levels of complexity and quantify the impact of aerosol on numerical weather prediction (NWP). We compare the results of RACM_GOCART and GOCART schemes which use the default climatological model fields for OH, H2O2, and NO3. We find significant reductions of sulfate that are on the order of 40 % to 80 % over the eastern US and are up to 40 % near the Beijing region over China when using the RACM_GOCART scheme. We also evaluate the model performance by comparing it with the Atmospheric Tomography Mission (ATom-1) aircraft measurements in the summer of 2016. FIM-Chem shows good performance in capturing the aerosol and gas-phase tracers. The model-predicted vertical profiles of biomass burning plumes and dust plumes off western Africa are also reproduced reasonably well.

show abstract

“…Data Parsing. We used the 2-min merged ATom dataset in this study (34). We removed flight segments over the continental United States to limit the influence of regional emissions.…”

Section: Methodsmentioning

confidence: 99%

“…Instead, modeling studies often rely on ozonesonde-derived climatologies and satellite-based remote sensing observations to constrain tropospheric O 3 distributions and precursor sources (20,32,33). The recent NASA Atmospheric Tomography (ATom) mission provides global-scale and seasonally resolved in situ measurements of O 3 and CO and a comprehensive suite of trace gases and aerosol parameters, including tracers of BB and urban emissions (34). ATom sampled the remote troposphere from the Arctic to the Antarctic over the Pacific and Atlantic Oceans using repeated vertical profiles from ∼0.2 to ∼13 km in altitude during four seasonal deployments between 2016 and 2018 (Fig.…”

mentioning

confidence: 99%

Large contribution of biomass burning emissions to ozone throughout the global remote troposphere

Bourgeois

Peischl

Neuman

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Ozone is the third most important anthropogenic greenhouse gas after carbon dioxide and methane but has a larger uncertainty in its radiative forcing, in part because of uncertainty in the source characteristics of ozone precursors, nitrogen oxides, and volatile organic carbon that directly affect ozone formation chemistry. Tropospheric ozone also negatively affects human and ecosystem health. Biomass burning (BB) and urban emissions are significant but uncertain sources of ozone precursors. Here, we report global-scale, in situ airborne measurements of ozone and precursor source tracers from the NASA Atmospheric Tomography mission. Measurements from the remote troposphere showed that tropospheric ozone is regularly enhanced above background in polluted air masses in all regions of the globe. Ozone enhancements in air with high BB and urban emission tracers (2.1 to 23.8 ppbv [parts per billion by volume]) were generally similar to those in BB-influenced air (2.2 to 21.0 ppbv) but larger than those in urban-influenced air (−7.7 to 6.9 ppbv). Ozone attributed to BB was 2 to 10 times higher than that from urban sources in the Southern Hemisphere and the tropical Atlantic and roughly equal to that from urban sources in the Northern Hemisphere and the tropical Pacific. Three independent global chemical transport models systematically underpredict the observed influence of BB on tropospheric ozone. Potential reasons include uncertainties in modeled BB injection heights and emission inventories, export efficiency of BB emissions to the free troposphere, and chemical mechanisms of ozone production in smoke. Accurately accounting for intermittent but large and widespread BB emissions is required to understand the global tropospheric ozone burden.

show abstract

ATom: Merged Atmospheric Chemistry, Trace Gases, and Aerosols

Cited by 53 publications

References 0 publications

Evaluation of MOPITT and TROPOMI carbon monoxide retrievals using AirCore in situ vertical profiles

Evaluation of MOPITT and TROPOMI carbon monoxide retrievals using AirCore in situ vertical profiles

Inline coupling of simple and complex chemistry modules within the global weather forecast model FIM (FIM-Chem v1)

Large contribution of biomass burning emissions to ozone throughout the global remote troposphere

Contact Info

Product

Resources

About