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  5. Comment on acp-2022-631

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Preprint
en
2022

Comment on acp-2022-631

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0 Files

en
2022
DOI: 10.5194/acp-2022-631-rc1

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Donald R Blake
Donald R Blake

University of California, Irvine

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Hao Guo
Clare M. Flynn
Michael J. Prather
+29 more

Abstract

Abstract. The NASA Atmospheric Tomography (ATom) mission built a photochemical climatology of air parcels based on in situ measurements with the NASA DC-8 aircraft along objectively planned profiling transects through the middle of the Pacific and Atlantic oceans. In this paper we present and analyze a data set of 10 s (2 km) merged and gap-filled observations of the key reactive species driving the chemical budgets of O3 and CH4 (O3, CH4, CO, H2O, HCHO, H2O2, CH3OOH, C2H6, higher alkanes, alkenes, aromatics, NOx, HNO3, HNO4, peroxyacetyl nitrate, and other organic nitrates), consisting of 146 494 distinct air parcels from ATom deployments 1 through 4. Six models calculated the O3 and CH4 photochemical tendencies from this modeling data stream for ATom 1. We find that 80 %–90 % of the total reactivity lies in the top 50 % of the parcels and 25 %–35 % in the top 10 %, supporting previous model-only studies that tropospheric chemistry is driven by a fraction of all the air. Surprisingly, the probability densities of species and reactivities averaged on a model scale (100 km) differ only slightly from the 2 km ATom 10 s data, indicating that much of the heterogeneity in tropospheric chemistry can be captured with current global chemistry models. Comparing the ATom reactivities over the tropical oceans with climatological statistics from six global chemistry models, we find generally good agreement with the reactivity rates for O3 and CH4. Models distinctly underestimate O3 production below 2 km relative to the mid-troposphere, and this can be traced to lower NOx levels than observed. Attaching photochemical reactivities to measurements of chemical species allows for a richer, yet more constrained-to-what-matters, set of metrics for model evaluation. This paper presents a corrected version of the paper published under the same authors and title (sans “corrected”) as https://doi.org/10.5194/acp-21-13729-2021.

How to cite this publication

Hao Guo, Clare M. Flynn, Michael J. Prather, Sarah A. Strode, Stephen D. Steenrod, L. K. Emmons, Forrest Lacey, Jean‐François Lamarque, Arlene M. Fiore, Gustavo Correa, Lee T. Murray, Glenn M. Wolfe, Jason M. St. Clair, Michelle Kim, John D. Crounse, Glenn S. Diskin, Joshua P. DiGangi, Bruce C. Daube, R. Commane, Kathryn McKain, Jeff Peischl, Thomas B. Ryerson, Chelsea R. Thompson, T. F. Hanisco, Donald R Blake, N. J. Blake, Eric C. Apel, Rebecca S. Hornbrook, James W. Elkins, Eric J. Hintsa, F. L. Moore, Steven C. Wofsy (2022). Comment on acp-2022-631. , DOI: https://doi.org/10.5194/acp-2022-631-rc1.

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Publication Details

Type

Preprint

Year

2022

Authors

32

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.5194/acp-2022-631-rc1

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