DOI: 10.7280/d1b12h
title: Deconstruction of tropospheric chemical reactivity using aircraft measurements: the Atmospheric Tomography Mission (ATom) data

description: The NASA Atmospheric Tomography Mission (ATom) completed four seasonal
 deployments (August 2016, February 2017, October 2017, May 2018), each
 with regular 0.2–12 km profiling by transecting the remote Pacific Ocean
 and Atlantic Ocean basins. Additional data were also acquired for the
 Southern Ocean, the Arctic basin, and two flights over Antarctica. ATom in
 situ measurements provide a near-complete chemical characterization of the
 ∼ 140 000 10 s (80 m by 2 km) air parcels measured along the flight path.
 This paper presents the Modeling Data Stream (MDS), a continuous
 gap-filled record of the 10 s parcels containing the chemical species
 needed to initialize a gas-phase chemistry model for the budgets of
 tropospheric ozone and methane. Global 3D models have been used to
 calculate the Reactivity Data Stream (RDS), which is comprised of the
 chemical reactivities (production and loss) for methane, ozone, and carbon
 monoxide, through 24 h integration of the 10 s parcels. These parcels
 accurately sample tropospheric heterogeneity and allow us to partially
 deconstruct the spatial scales and variability that define tropospheric
 chemistry from composition to reactions. This paper provides a first look
 at and analysis of the up-to-date MDS and RDS data including all four
 deployments (Prather et al., 2023, https://doi.org/10.7280/D1B12H).
 ATom's regular profiling of the ocean basins allows for weighted
 averages to build probability densities for the key species and
 reactivities presented here. These statistics provide climatological
 metrics for global chemistry models, e.g., the large-scale pattern of
 ozone and methane loss in the lower troposphere and the more sporadic
 hotspots of ozone production in the upper troposphere. The profiling
 curtains of reactivity also identify meteorologically variable and hence
 deployment-specific hotspots of photochemical activity. Added calculations
 of the sensitivities of the production and loss terms relative to each
 species emphasize the few dominant species that control the ozone and
 methane budgets and whose statistical patterns should be key
 model–measurement metrics. From the sensitivities, we also derive
 linearized lifetimes of ozone and methane on a parcel-by-parcel basis and
 average over the basins, providing an observational basis for these
 previously model-only diagnostics. We had found that most model
 differences in the ozone and methane budgets are caused by the models
 calculating different climatologies for the key species such as O3, CO,
 H2O, NOx, CH4, and T, and thus these ATom measurements make a substantial
 contribution to the understanding of model differences and even
 identifying model errors in global tropospheric chemistry.
description: The Modeling Data Stream (MDS) is
 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 during ATom deployments 1–4. The MDS is merged
 observations and gap-filled (see published paper) with 10 s (2 km) average
 data, see Wofsy et al. (2018, 2021) and Thompson et al. (2022). The
 Reactivity Data Stream (RDS) is derived from the MDS using the UCI
 chemistry model in a manner described in Prather et al. (2017; 2018). See
 related papers and dataset DOIs below.  An earlier version of the MDS
 (MDS-0) was used to calculate RDS with six independent chemsitry models,
 and these results are shown in the published paper.  The MDS-0 and RDS-0
 versions and other previous versions are not archived here because there
 were too many errors in the MDS, and so the RDS results should not be used
 further.  If a next-generation multi-model comparison of the calculated
 reactivities is organized, it is recommended that the MDS-3 data be
 used.
description: The data sets are in standard, readable NetCDF format and they
 contain the metadata needed to use them. I have inserted the NetCDF
 display listing of the contents in the README file because it is useful
 for the user to be able to see what is in the datasets before downloading
 them. This should help them find the correct data.