Skip to main content
ORNL DAAC HomeNASA Home

DAAC Home > Get Data > NASA Projects > Atmospheric Tomography Mission (ATom) > User guide

ATom: Global Modeling Initiative (GMI) Chemical Transport Model (CTM) output

Documentation Revision Date: 2021-10-29

Dataset Version: 1

Summary

This dataset contains Global Modeling Initiative (GMI) Chemical Transport Model (CTM) outputs from the four Atom campaigns. GMI simulations of the ATom flight periods have a horizontal resolution of 1.0 x 1.25 degrees, with output every 15 minutes. The ICARTT files are generated by spatially and temporally interpolating the output to the ATom flight track. Vertical interpolation is linear in log-pressure. The netCDF files provide three-dimensional (3D) GMI simulation output for the region surrounding the flight track every 15 minutes at the original model resolution. GMI is a 3-D CTM that includes full chemistry for both the troposphere and stratosphere. GMI simulates the concentrations of many of the species measured during ATom.

There are 48 data files in ICARTT (*.ict) format and 48 data files in netCDF format (*.nc) included in this dataset.

Figure 1. NASA's DC-8 flying laboratory. All four ATom campaigns were conducted with DC-8.

Citation

Strode, S.A., S.D. Steenrod, J.M. Nicely, J. Liu, M.R. Damon, and S.E. Strahan. 2021. ATom: Global Modeling Initiative (GMI) Chemical Transport Model (CTM) output. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1897

Table of Contents

  1. Dataset Overview
  2. Data Characteristics
  3. Application and Derivation
  4. Quality Assessment
  5. Data Acquisition, Materials, and Methods
  6. Data Access
  7. References

Dataset Overview

This dataset contains Global Modeling Initiative (GMI) Chemical Transport Model (CTM) outputs from the four Atom campaigns. GMI simulations of the ATom flight periods have a horizontal resolution of 1.0 x 1.25 degrees, with output every 15 minutes. The ICARTT files are generated by spatially and temporally interpolating the output to the ATom flight track. Vertical interpolation is linear in log-pressure. The netCDF files provide three-dimensional (3D) GMI simulation output for the region surrounding the flight track every 15 minutes at the original model resolution. GMI investigations support the development and integration of a state-of-the-art modular 3D CTM that includes full chemistry for both the troposphere and stratosphere. The GMI model is involved in the assessment of the impacts of atmospheric composition change due to anthropogenic emissions of gases and aerosols, such as those from aircraft, biomass burning, fossil fuel combustion, and production of ozone-depleting substances. GMI studies investigate changes in stratospheric ozone and the roles of long-range transport and changing emissions on air quality.

ProjectAtmospheric Tomography Mission

The Atmospheric Tomography Mission (ATom) was a NASA Earth Venture Suborbital-2 mission. It studied the impact of human-produced air pollution on greenhouse gases and on chemically reactive gases in the atmosphere. ATom deployed an extensive gas and aerosol payload on the NASA DC-8 aircraft for systematic, global-scale sampling of the atmosphere, profiling continuously from 0.2 to 12 km altitude. Flights occurred in each of four seasons over a 4-year period.

Related Publications

Hall, S.R., K. Ullmann, M.J. Prather, C.M. Flynn, L.T. Murray, A.M. Fiore, G. Correa, S.A. Strode, S.D. Steenrod, J.-F. Lamarque, J. Guth, B. Josse, J. Flemming, V. Huijnen, N.L. Abraham, and A.T. Archibald. 2018. Cloud impacts on photochemistry: building a climatology of photolysis rates from the Atmospheric Tomography mission. Atmospheric Chemistry and Physics 18:16809–16828. https://doi.org/10.5194/acp-18-16809-2018

Prather, M.J., C.M. Flynn, X. Zhu, S.D. Steenrod, S.A. Strode, A.M. Fiore, G. Correa, L.T. Murray, and J.-F. Lamarque. 2018. How well can global chemistry models calculate the reactivity of short-lived greenhouse gases in the remote troposphere, knowing the chemical composition. Atmospheric Measurement Techniques 11:2653–2668. https://doi.org/10.5194/amt-11-2653-2018

Prather, M.J., X. Zhu, C.M. Flynn, S.A. Strode, J.M. Rodriguez, S.D. Steenrod, J. Liu, J.-F. Lamarque, A.M. Fiore, L.W. Horowitz, J. Mao, L.T. Murray, D.T. Shindell, and S.C. Wofsy. 2017. Global atmospheric chemistry – which air matters. Atmospheric Chemistry and Physics 17:9081–9102. https://doi.org/10.5194/acp-17-9081-2017

Related Datasets

Wofsy, S.C., S. Afshar, H.M. Allen, E.C. Apel, E.C. Asher, B. Barletta, et al. 2021. ATom: Merged Atmospheric Chemistry, Trace Gases, and Aerosols, Version 2. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1925

  • Data from all ATom instruments and all four flight campaigns, including aircraft location and navigation data, merged to several different time bases.

Wofsy, S.C., and ATom Science Team. 2018. ATom: Aircraft Flight Track and Navigational Data. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1613

  • Flightpath (location and altitude) data for each of the four campaigns provided in KML and CSV format.

Data Characteristics

Spatial Coverage: Global. Flights circumnavigate the globe, primarily over the oceans

Spatial Resolution: Point measurements

Temporal Coverage: Periodic flights occurred during each campaign

Deployment Date Range
ATom-1 July 29 - August 23, 2016
ATom-2 January 26 - February 21, 2017
ATom-3 September 28 - October 28, 2017
ATom-4 April 24 - May 21, 2018

Temporal Resolution: 10 seconds

Data File Information

There are 48 data files in ICARTT (*.ict) format and 48 data files in netCDF format (*.nc) included in this dataset that contain GMI model outputs along the flight track. Data files conform to the ICARTT File Format Standards V1.1. The files are named GMI _DC8_YYYYMMDD_R#.ext, where YYYYMMDD is the start date (in UTC time) of the flight, R#  is the file version or revision number, and ext is the file extension.

Data File Details

Missing data are represented by -99999.

Table 1. Variables and descriptions for files named GMI _DC8_YYYYMMDD_R#.ict.

Name Units Description
UTC_Start Seconds Start time of observation in seconds from 0000 UTC
UTC_Stop Seconds Stop time of observation in seconds from 0000 UTC
Lat Decimal degrees Latitude
Lon Decimal degrees Longitude
StaticPressure_GMI hPa, Pressure
TroposphereIndicator_GMI 0 or 1 Presence (1) or absence (0) of current location being inside troposphere
StaticTemperature_GMI Kelvin Temperature
CH2O_GMI Parts per billion by volume Formaldehyde abundance
CH4_GMI Parts per billion by volume Methane abundance
CO_GMI Parts per billion by volume Carbon monoxide abundance
H2_GMI Parts per billion by volume Hydrogen abundance
CHOOH_GMI Parts per billion by volume Methyl hydroperoxide abundance
HNO3_GMI Parts per billion by volume Nitric acid abundance
HNO4_GMI Parts per billion by volume Pernitric acid abundance
H2O_GMI Parts per billion by volume Water abundance
HO2_GMI Parts per billion by volume Perhydroxyl radical abundance
H2O2_GMI Parts per billion by volume Hydrogen peroxide abundance
CH3OH_GMI Parts per billion by volume Methanol abundance
CH3OOH_GMI Parts per billion by volume Methyl hydroperoxide abundance
N2O_GMI Parts per billion by volume Nitrous oxide abundance
NO_GMI Parts per billion by volume Nitric oxide abundance
NO2_GMI Parts per billion by volume Nitrogen dioxide abundance
N2O5_GMI Parts per billion by volume Dinitrogen Pentoxide abundance
O3_GMI Parts per billion by volume Ozone abundance
OH_GMI Parts per billion by volume Hydroxyl radical abundance
CH3Br_GMI Parts per billion by volume Methyl bromide abundance
CH3Cl_GMI Parts per billion by volume Methyl chloride abundance
CFC11_GMI Parts per billion by volume CFC11 abundance
CFC12_GMI Parts per billion by volume Freon 12 abundance
CFC113_GMI Parts per billion by volume CFC113 (C2Cl3F3) abundance
CFC114_GMI Parts per billion by volume CFC114 (C2Cl2F4) abundance
CFC115_GMI Parts per billion by volume CFC115 (C2ClF5) abundance
HCFC22_GMI Parts per billion by volume HCFC22 (CClF2H) abundance
HCFC141b_GMI Parts per billion by volume HCFC141b (C2Cl2FH3) abundance
HCFC142b_GMI Parts per billion by volume HCFC142b (C2ClF2H3) abundance
H1202_GMI Parts per billion by volume Halon 1202 abundance
H1211_GMI Parts per billion by volume Halon 1211 abundance
H1301_GMI Parts per billion by volume Halon 1301 abundance
H2402_GMI Parts per billion by volume Halon 2402
CH3CHO_GMI Parts per billion by volume Acetaldehyde abundance
C4-C5Alkanes_GMI Parts per billion by volume C4-C5Alkanes abundance
Ethane_GMI Parts per billion by volume Ethane abundance
Propane_GMI Parts per billion by volume Propane abundance
Ethanol_GMI Parts per billion by volume Ethanol abundance
C2H5OOH_GMI Parts per billion by volume Ethylhydroperoxide abundance
Isoprene_GMI Parts per billion by volume Isoprene abundance
MAC_GMI Parts per billion by volume Methacrolein (C4H6O) abundance
CH3CO3_GMI Parts per billion by volume Peroxyacetyl radical (C2H3O3) abundance
MEK_GMI Parts per billion by volume Methyl ethyl ketone (C4H8O) abundance
MVK_GMI Parts per billion by volume Methyl vinyl ketone (C4H6O) abundance
PAN_GMI Parts per billion by volume Peroxyacetyl nitrate (C2H3NO5) abundance
MPAN_GMI Parts per billion by volume Peroxymethacryloyl nitrate (C4H5O5N) abundance
PPN_GMI Parts per billion by volume Peroxypropionyl nitrate (C3H5O5N) abundance
Propene_GMI Parts per billion by volume Propene abundance
C4andC5Alkylnitrates_GMI Parts per billion by volume C4 and C5 Alkynitrates abundance
C3toCnAldehydes_GMI Parts per billion by volume >C2 aldehydes (C3H6O) abundance
Acetone_GMI Parts per billion by volume Acetone abundance

Table 2. Variables and descriptions for files named GMI _DC8_YYYYMMDD_R#.nc.

Name Units Description
Acetone_GMI Volume mixing ratio Acetone abundance
ai_GMI Unitless Hybrid pressure edge term
AirMass_GMI Kg Mass
am_GMI Unitless Hybrid pressure term
bi_GMI Unitless Hybrid sigma edge term
bm_GMI Unitless Hybrid sigma term
C2H5OOH_GMI Volume mixing ratio Ethylhydroperoxide abundance
C3toCnAldehydes_GMI Volume mixing ratio >C2 aldehydes (C3H6O) abundance
C4andC5Alkylnitrates_GMI Volume mixing ratio C4 and C5 Alkynitrates abundance
C4-C5Alkanes_GMI Volume mixing ratio C4-C5Alkanes abundance
CFC11_GMI Volume mixing ratio CFC11 abundance
CFC113_GMI Volume mixing ratio CFC113 (C2Cl3F3) abundance
CFC114_GMI Volume mixing ratio CFC114 (C2Cl2F4) abundance
CFC115_GMI Volume mixing ratio CFC115 (C2ClF5) abundance
CFC12_GMI Volume mixing ratio Freon 12 abundance
CH2O_GMI Volume mixing ratio Formaldehyde abundance
CH3Br_GMI Volume mixing ratio Methyl bromide abundance
CH3CHO_GMI Volume mixing ratio Acetaldehyde abundance
CH3Cl_GMI Volume mixing ratio Methyl chloride abundance
CH3CO3_GMI Volume mixing ratio Peroxyacetyl radical (C2H3O3) abundance
CH3OH_GMI Volume mixing ratio Methanol abundance
CH3OOH_GMI Volume mixing ratio Methyl hydroperoxide abundance
CH4_GMI Volume mixing ratio Methane abundance
CHOOH_GMI Volume mixing ratio Methyl hydroperoxide abundance
CO_GMI Volume mixing ratio Carbon monoxide abundance
Ethane_GMI Volume mixing ratio Ethane abundance
Ethanol_GMI Volume mixing ratio Ethanol abundance
GridBoxArea_GMI Meters^2 Grid box area
GridBoxHeight_GMI Meters Grid box height
H1202_GMI Volume mixing ratio Halon 1202 abundance
H1211_GMI Volume mixing ratio Halon 1211 abundance
H1301_GMI Volume mixing ratio Halon 1301 abundance
H2_GMI Volume mixing ratio Hydrogen abundance
H2402_GMI Volume mixing ratio Halon 2402
H2O_GMI Volume mixing ratio Water abundance
H2O2_GMI Volume mixing ratio Hydrogen peroxide abundance
HCFC141b_GMI Volume mixing ratio HCFC141b (C2Cl2FH3) abundance
HCFC142b_GMI Volume mixing ratio HCFC142b (C2ClF2H3) abundance
HCFC22_GMI Volume mixing ratio HCFC22 (CClF2H) abundance
HNO3_GMI Volume mixing ratio Nitric acid abundance
HNO4_GMI Volume mixing ratio Pernitric acid abundance
HO2_GMI Volume mixing ratio Perhydroxyl radical abundance
Isoprene_GMI Volume mixing ratio Isoprene abundance
latitude Decimal degrees Latitude
longitude Decimal degrees Longitude
MAC_GMI Volume mixing ratio Methacrolein (C4H6O) abundance
MEK_GMI Volume mixing ratio Methyl ethyl ketone (C4H8O) abundance
model_levels Numeric Model level number
MPAN_GMI Volume mixing ratio Peroxymethacryloyl nitrate (C4H5O5N) abundance
MVK_GMI Volume mixing ratio Methyl vinyl ketone (C4H6O) abundance
N2O_GMI Volume mixing ratio Nitrous oxide abundance
N2O5_GMI Volume mixing ratio Dinitrogen Pentoxide abundance
NO_GMI Volume mixing ratio Nitric oxide abundance
NO2_GMI Volume mixing ratio Nitrogen dioxide abundance
O3_GMI Volume mixing ratio Ozone abundance
OH_GMI Volume mixing ratio Hydroxyl radical abundance
PAN_GMI Volume mixing ratio Peroxyacetyl nitrate (C2H3NO5) abundance
PPN_GMI Volume mixing ratio Peroxypropionyl nitrate (C3H5O5N) abundance
PressureTop_GMI hPa Pressure top
Propane_GMI Volume mixing ratio Propane abundance
Propene_GMI Volume mixing ratio Propene abundance
StaticPressure_GMI hPa Pressure
StaticTemperature_GMI Kelvin Temperature
SurfacePressure_GMI mb Surface Pressure
time Seconds Seconds since 0000 UTC
TropopausePressure mb Tropopause Pressure
TroposphereIndicator_GMI 0 or 1 Presence (1) or absence (0) of current location being inside troposphere

Application and Derivation

ATom builds the scientific foundation for mitigation of short-lived climate forcers, in particular, methane (CH4), tropospheric ozone (O3), and Black Carbon aerosols (BC).

ATom Science Questions

Tier 1

  • What are chemical processes that control the short-lived climate forcing agents CH4, O3, and BC in the atmosphere? How is the chemical reactivity of the atmosphere on a global scale affected by anthropogenic emissions? How can we improve chemistry-climate modeling of these processes?

Tier 2

  • Over large, remote regions, what are the distributions of BC and other aerosols important as short-lived climate forcers? What are the sources of new particles? How rapidly do aerosols grow to CCN-active sizes? How well are these processes represented in models?
  • What type of variability and spatial gradients occur over remote ocean regions for greenhouse gases (GHGs) and ozone depleting substances (ODSs)? How do the variations among air parcels help identify anthropogenic influences on photochemical reactivity, validate satellite data for these gases, and refine knowledge of sources and sinks?

Significance

ATom delivers unique data and analysis to address the Science Mission Directorate objectives of acquiring “datasets that identify and characterize important phenomena in the changing Earth system” and “measurements that address weaknesses in current Earth system models leading to improvement in modeling capabilities.” ATom will provide unprecedented challenges to the CCMs used as policy tools for climate change assessments, with comprehensive data on atmospheric chemical reactivity at global scales, and will work closely with modeling teams to translate ATom data to better, more reliable CCMs. ATom provides extraordinary validation data for remote sensing.

Quality Assessment

Uncertainty information is not provided.

Data Acquisition, Materials, and Methods

Project Overview

ATom makes global-scale measurements of the chemistry of the atmosphere using the NASA DC-8 aircraft. Flights span the Pacific and Atlantic Oceans, nearly pole-to-pole, in continuous profiling mode, covering remote regions that receive long-range inputs of pollution from expanding industrial economies. The payload has proven instruments for in situ measurements of reactive and long-lived gases, diagnostic chemical tracers, and aerosol size, number, and composition, plus spectrally resolved solar radiation and meteorological parameters.

Combining distributions of aerosols and reactive gases with long-lived GHGs and ODSs enables disentangling of the processes that regulate atmospheric chemistry: emissions, transport, cloud processes, and chemical transformations. ATom analyzes measurements using customized modeling tools to derive daily averaged chemical rates for key atmospheric processes and to critically evaluate Chemistry-Climate Models (CCMs). ATom also differentiates between hypotheses for the formation and growth of aerosols over the remote oceans.

Global Modeling Initiative Chemical Transport Model

The Global Modeling Initiative (GMI) Chemical Transport Model (CTM) is part of the NASA Modeling Analysis and Prediction (MAP) program. The GMI CTM is used to assess the impacts of atmospheric circulation and composition change due to anthropogenic emissions, such as those from aircraft, biomass burning, fossil fuel combustion, and use of ozone-depleting substances (ODS). GMI studies investigate changes in stratospheric ozone and the roles of long-range transport and changing emissions on air quality.

GMI CTM simulations use a combined stratospheric-tropospheric chemical mechanism that has been adopted by the GEOS models. Updates to the GMI mechanism are first evaluated in the GMI CTM prior to adoption by GEOS. The GMI mechanism simulates the chemical interactions of NOx, HOx, VOCs, aerosols, and ozone. It includes 149 chemical species and approximately 400 reactions.

Additional information on the history, applications and publications related to GMI can be found on NASA’s GMI page.

Data Access

These data are available through the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

ATom: Global Modeling Initiative (GMI) Chemical Transport Model (CTM) output

Contact for Data Center Access Information:

References

Hall, S.R., K. Ullmann, M.J. Prather, C.M. Flynn, L.T. Murray, A.M. Fiore, G. Correa, S.A. Strode, S.D. Steenrod, J.-F. Lamarque, J. Guth, B. Josse, J. Flemming, V. Huijnen, N.L. Abraham, and A.T. Archibald. 2018. Cloud impacts on photochemistry: building a climatology of photolysis rates from the Atmospheric Tomography mission. Atmospheric Chemistry and Physics 18:16809–16828. https://doi.org/10.5194/acp-18-16809-2018

Prather, M.J., C.M. Flynn, X. Zhu, S.D. Steenrod, S.A. Strode, A.M. Fiore, G. Correa, L.T. Murray, and J.-F. Lamarque. 2018. How well can global chemistry models calculate the reactivity of short-lived greenhouse gases in the remote troposphere, knowing the chemical composition. Atmospheric Measurement Techniques 11:2653–2668. https://doi.org/10.5194/amt-11-2653-2018

Prather, M.J., X. Zhu, C.M. Flynn, S.A. Strode, J.M. Rodriguez, S.D. Steenrod, J. Liu, J.-F. Lamarque, A.M. Fiore, L.W. Horowitz, J. Mao, L.T. Murray, D.T. Shindell, and S.C. Wofsy. 2017. Global atmospheric chemistry – which air matters. Atmospheric Chemistry and Physics 17:9081–9102. https://doi.org/10.5194/acp-17-9081-2017