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FLEXPART Influence Functions for ACT-America, 2016-2017

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Documentation Revision Date: 2022-12-29

Dataset Version: 1

Summary

This dataset contains a set of Lagrangian particle dispersion simulations of carbon dioxide concentrations using the FLEXible PARTicle (FLEXPART) model. FLEXPART quantified the source-receptor relationships, so-called "influence functions", in a backward mode. The simulations were constructed for five Atmospheric Carbon and Transport America (ACT-America) deployments over the eastern U.S. that occurred in 2016-2019. Each receptor of the influence function is the 30-second or 10-minute interval along flight tracks, characterized by a box with boundaries between the maximum and minimum latitude/longitude as well as between the maximum and minimum altitudes during the interval. Each receptor box released 5,000 particles and simulated their transport and dispersion backward for 10 or 20 days. The simulations were driven by 27-km meteorology provided by the WRF-Chem simulation or by ERA-Interim data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Background levels of carbon dioxide were obtained from CarbonTracker and OCO-2 v9 MIP. The data are provided in netCDF and FLEXPART binary formats.

This dataset includes a total of 745 files in Zip archive format. Three archives hold background CO2 values in netCDF format. The remaining archives hold simulation output in netCDF and FLEXPART binary format (n=742 simulations). 

Figure 1. Flight paths for five airborne campaigns of ACT-America that provided receptor locations and CO2 measurements for these FLEXPART simulations. Flights were concentrated on three study areas: the northeast, south-central, and mid-west regions of the United States.

Citation

Cui, Y.Y., A.R. Jacobson, S. Feng, D. Wesloh, Z.R. Barkley, L. Zhang, T. Gerken, K. Keller, D.F. Baker, and K.J. Davis. 2022. FLEXPART Influence Functions for ACT-America, 2016-2017. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2018

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 a set of Lagrangian particle dispersion simulations of carbon dioxide concentrations using the FLEXible PARTicle (FLEXPART) model. FLEXPART quantified the source-receptor relationships, so-called "influence functions", in a backward mode. The simulations were constructed for five Atmospheric Carbon and Transport America (ACT-America) deployments over the eastern U.S. that occurred in 2016-2017. Each receptor of the influence function is the 30-second or 10-minute interval along flight tracks, characterized by a box with boundaries between the maximum and minimum latitude/longitude as well as between the maximum and minimum altitudes during the interval. Each receptor box released 5,000 particles and simulated their transport and dispersion backward for 10 or 20 days. The simulations were driven by 27-km meteorology provided by the WRF-Chem simulation or by ERA-Interim data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Background levels of carbon dioxide were obtained from CarbonTracker and OCO-2 v9 MIP.  

Project: Atmospheric Carbon and Transport - America

The ACT-America, or Atmospheric Carbon and Transport - America, project is a NASA Earth Venture Suborbital-2 mission to study the transport and fluxes of atmospheric carbon dioxide and methane across three regions in the eastern United States. Flight campaigns measured transport of greenhouse gases by continental-scale weather systems. Ground-based measurements of greenhouse gases were also collected. Project goals include better estimates of greenhouse gas sources and sinks which are required for climate management and for prediction of future climate.

Related Dataset

Feng, S., T. Lauvaux, Z.R. Barkley, K.J. Davis, M.P. Butler, A. Deng, B. Gaudet, and D. Stauffer. 2021. ACT-America: WRF-Chem Baseline Simulations for North America, 2016-2019. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1884

  • This dataset employed the WRF-Chem model discussed in the Quality Assurance Section of this document.

Related Publications

Cui, Y. Y., Jacobson, A. R., Feng, S., Wesloh, D., Barkley, Z. R., Zhang, L., et al. (2021). Evaluation of CarbonTracker's inverse estimates of North American net ecosystem exchange of CO2 from different observing systems using ACT-America airborne observations. Journal of Geophysical Research: Atmospheres 126:e2020JD034406. https://doi.org/10.1029/2020JD034406

Cui, Y. Y., Zhang, L., Jacobson, A. R., Johnson, M. S., Philip, S., Baker, D., et al. (2022). Evaluating global atmospheric inversions of terrestrial net ecosystem exchange CO2 over North America on seasonal and sub-continental scales. Geophysical Research Letters 49:e2022GL100147. https://doi.org/10.1029/2022GL100147 

Acknowledgement

This work was supported by NASA's ACT-America project (grant NNX15AG76G).

Data Characteristics

Spatial Coverage: Northern portion of western hemisphere

Spatial Resolution: 27 km as determined by meteorological drivers

Temporal Coverage: 2016-07-01 to 2019-08-01

Temporal Resolution: Hourly during 10-day or 20-day simulation

Study Area: Latitude and longitude are given in decimal degrees.

Site Northernmost Latitude Southernmost Latitude Westernmost Longitude Easternmost Longitude
Western hemisphere 70.10 -10.0 -170.0 5.0

Data File Information

This dataset includes a total of 745 files in Zip archive format. 

Three archives hold background CO2 values used in the simulations in netCDF format:

  • WRF-background.zip
  • ERA-back10d-rec10min-background.zip,
  • ERA-back10d-rec30s-background.zip

The remaining archives hold simulation output in netCDF and FLEXPART binary format (n=742 simulations). The naming convention for these Zip archives is <Meteorology>-back<time>-res<temporal resolution>-<date>-<platform>.zip, where

  • <Meteorology> is the source of meteorological drivers: "WRF" or "ERA"
  • <time> is the duration of the backwards simulation: 10 days ("10d") or 20 days ("20d")
  • <temporal resolution> is the averaging period of the receptor data along the ACT-America flight path: 10 minutes ("10min") or 30 seconds ("30s")
  • <date> is the date of the simulation as YYYYMMDD
  • <platform> is the NASA aircraft deployed for the flight: B200 ("b200") or C-130 ("c130")

Table 1. File names and descriptions.

Set Filename Number of archives Format Description Related Publication
1 WRF-background.zip 1 netCDF Background values of CO2 used for FLEXPART-WRF influence function simulations in Set 1 Cui et al., (2021)
WRF-back10d-rec30s-<date>-<b200|c130>.zip 208 netCDF Influence function simulations, backward for 10 days
WRF-back20d-rec30s-<date>-<b200|c130>.zip 169 FLEXPART binary Influence function simulations, backward for 20 days
2 ERA-back10d-rec10min-background.zip 1 netCDF Background values of CO2 used for FLEXPART-ERA influence function simulations in Set 2 from CarbonTracker CT2019B (Jacobson et al., 2020) Cui et al., (2022)
ERA-back10d-rec10min-<date>-<b200|c130>.zip 162 FLEXPART binary Influence function simulations using 10-min averaged receptor data
3 ERA-back10d-rec30s-background.zip 1 netCDF Background values of CO2 used for FLEXPART-ERA influence function simulations in Set 3 from CarbonTracker 2019B  See Cui et al., (2022) for methods.
ERA-back10d-rec30s-<date>-<b200|c130>.zip 203 FLEXPART binary Influence function simulations similar to Set 2 but at higher temporal resolution (using 30-s averaged receptor data)
Total:  745  

Datafile Details

Each archive holds a collection of files for the backward simulations. The naming convention for these individual files varies among archives but may include the name elements listed above along with these additional elements:

  • Date and time as YYYYMMDD_hhmmss or YYYYMMDDhhmmss
  • "CT" or "CT2019B" refer to background CO2 concentrations from CarbonTracker 2019B (https://gml.noaa.gov/ccgg/carbontracker/)
  • "27km" referring to the spatial resolution of the meteorological drivers at 27 km
  • NetCDF files have the suffix ".nc" while FLEXPART binary files have not suffix.

The archives holding FLEXPART binary files have additional files in plain text format (e.g., "dates", *.namelist) associated with the simulation runs.

Application and Derivation

These data may be used to study the sources and movement of greenhouse gasses and aerosols in the atmosphere as well as net ecosystem exchange of carbon. 

Quality Assessment

The FLEXPART simulations were compared to WRF-Chem simulations of CO2 mole fractions along the flight tracks using the same flux inputs, boundary conditions, and meteorological fields. There was close agreement between the FLEXPART and WRF-Chem simulations.

Data Acquisition, Materials, and Methods

Lagrangian particle dispersion simulations of carbon dioxide concentrations were created using the FLEXible PARTicle (FLEXPART) model (Brioude et al., 2013). FLEXPART quantified the source-receptor relationships, so-called "influence functions", in a backward mode. The simulations were constructed for five Atmospheric Carbon and Transport–America (ACT-America) deployments over the eastern U.S. that occurred in 2016-2019 (Davis et al., 2018; Figure 1). These ACT-America flights carried calibrated instruments for measuring in-situ atmospheric CO2 concentrations. The flights were conducted using two NASA aircraft, a B200 and a C-130, which facilitated concurrent sampling at different altitudes.

To provide receptor values for the influence functions, CO2 measurements were aggregated in 10-minute and 30-second intervals along the flights, excluding take-off and landing portions. Each receptor was characterized by a box with boundaries between the maximum and minimum latitude/longitude as well as between the maximum and minimum altitudes during the aggregation interval. Each receptor box released 1,000 to 5,000 particles, and their transport and dispersion were simulated backward for 10 or 20 days. 

Three sets of FLEXPART simulations were conducted (Table 1). In Set 1, simulations were driven by 27-km meteorology provided by the WRF-Chem simulation as described by Feng et al. (2019). Receptor measurements were aggregated to 30-second intervals. Each receptor box released 5,000 particles. The simulation time period was 10 days and 20 days backward from the receptor time. Background values of CO2 were obtained from CarbonTracker CT2019B (https://gml.noaa.gov/ccgg/carbontracker/; Jacobson et al., 2020).

In Set 2, simulations used FLEXPART version 3.1 (Pisso et al., 2019) driven by meteorology from ERA-interim reanalysis data (Dee et al., 2011). Receptor measurements were aggregated to 10-minute intervals. Each receptor box released 1,000 particles, and the simulation period was 10 days backward from the receptor time. Background values of CO2 were derived from OCO-2 v9 MIP global optimized CO2 mole fraction fields (https://gml.noaa.gov/ccgg/OCO2_v9mip). Set 3 employed the same methods as Set 2 except that receptor data were aggregated to 30-second intervals.

Detailed methods for Set 1 are available in Cui et al. (2021).  See Cui et al. (2022) for methods used for Set 2 and Set 3.

Data Access

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

FLEXPART Influence Functions for ACT-America, 2016-2017

Contact for Data Center Access Information:

References

Brioude, J., D. Arnold, A. Stohl, M. Cassiani, D. Morton, P. Seibert, W. Angevine, S. Evan, A. Dingwell, J.D. Fast, R.C. Easter, I. Pisso, J. Burkhart, and G. Wotawa. 2013. The Lagrangian particle dispersion model FLEXPART-WRF version 3.1. Geoscientific Model Development 6:1889–1904. https://doi.org/10.5194/gmd-6-1889-2013

Cui, Y. Y., Jacobson, A. R., Feng, S., Wesloh, D., Barkley, Z. R., Zhang, L., et al. (2021). Evaluation of CarbonTracker's inverse estimates of North American net ecosystem exchange of CO2 from different observing systems using ACT-America airborne observations. Journal of Geophysical Research: Atmospheres 126:e2020JD034406. https://doi.org/10.1029/2020JD034406

Cui, Y. Y., Zhang, L., Jacobson, A. R., Johnson, M. S., Philip, S., Baker, D., et al. (2022). Evaluating global atmospheric inversions of terrestrial net ecosystem exchange CO2 over North America on seasonal and sub-continental scales. Geophysical Research Letters 49:e2022GL100147. https://doi.org/10.1029/2022GL100147 

Davis, K.J., M.D. Obland, B. Lin, T. Lauvaux, C. O'Dell, B. Meadows, E.V. Browell, J.P. DiGangi, C. Sweeney, M.J. McGill, J.D. Barrick, A.R. Nehrir, M.M. Yang, J.R. Bennett, B.C. Baier, A. Roiger, S. Pal, T. Gerken, A. Fried, S. Feng, R. Shrestha, M.A. Shook, G. Chen, L.J. Campbell, Z.R. Barkley, and R.M. Pauly. 2018. ACT-America: L3 Merged In Situ Atmospheric Trace Gases and Flask Data, Eastern USA. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1593

Dee, D.P., S.M. Uppala, A.J. Simmons, P. Berrisford, P. Poli, S. Kobayashi, U. Andrae, M.A. Balmaseda, G. Balsamo, P. Bauer, P. Bechtold, A.C. M. Beljaars, L. van de Berg, J. Bidlot, N. Bormann, C. Delsol, R. Dragani, M. Fuentes, A.J. Geer, L. Haimberger, S.B. Healy, H. Hersbach, E.V. Hólm, L. Isaksen, P. Kållberg, M. Köhler, M. Matricardi, A.P. McNally, B.M. Monge-Sanz, J.-J. Morcrette, B.-K. Park, C. Peubey, P. de Rosnay, C. Tavolato, J.-N. Thépaut, and F. Vitart. 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society 137:553–597. https://doi.org/10.1002/qj.828

Feng, S., T. Lauvaux, K.J. Davis, K. Keller, Y. Zhou, C. Williams, A.E. Schuh, J. Liu, and I. Baker. 2019. Seasonal Characteristics of Model Uncertainties From Biogenic Fluxes, Transport, and Large-Scale Boundary Inflow in Atmospheric CO 2 Simulations Over North America. Journal of Geophysical Research: Atmospheres 124:14325–14346. https://doi.org/10.1029/2019jd031165

Feng, S., T. Lauvaux, Z.R. Barkley, K.J. Davis, M.P. Butler, A. Deng, B. Gaudet, and D. Stauffer. 2021. ACT-America: WRF-Chem Baseline Simulations for North America, 2016-2019. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1884

Jacobson, A.R, K.N. Schuldt, J.B. Miller, T. Oda, P. Tans, A. Andrews, J. Mund, L. Ott, G. J. Collatz, T. Aalto, S. Afshar, K. Aikin, S. Aoki, F. Apadula, B. Baier, P. Bergamaschi, A. Beyersdorf, S.C. Biraud, A. Bollenbacher, D. Bowling, G. Brailsford, J.B. Abshire, G. Chen, H. Chen, L. Chmura, Sites Climadat,A. Colomb, S. Conil, A. Cox, P. Cristofanelli, E. Cuevas, R. Curcoll, C.D. Sloop, K. Davis, S.D. Wekker, M. Delmotte, J.P. DiGangi, E. Dlugokencky, J. Ehleringer, J.W. Elkins, L. Emmenegger, M.L. Fischer, G. Forster, A. Frumau, M. Galkowski, L.V. Gatti, E. Gloor, T. Griffis, S. Hammer, L. Haszpra, J. Hatakka, M. Heliasz, A. Hensen, O. Hermanssen, E. Hintsa, J. Holst, D. Jaffe, A. Karion, S.R. Kawa, R. Keeling, P. Keronen, P. Kolari, K. Kominkova, E. Kort, P. Krummel, D. Kubistin, C. Labuschagne, R. Langenfelds, O. Laurent, T. Laurila, T. Lauvaux, B. Law, J. Lee, I. Lehner, M. Leuenberger, I. Levin, J. Levula, J. Lin,M. Lindauer, Z. Loh, M. Lopez, I.T. Luijkx, C. Lund Myhre, T. Machida, I. Mammarella, G. Manca, A. Manning, A. Manning, M.V. Marek, P. Marklund, M.Y. Martin, H. Matsueda, K. McKain, H. Meijer, F. Meinhardt, N. Miles, C.E. Miller, M. Molder, S. Montzka, F. Moore, J.-A. Morgui, S. Morimoto, B. Munger, J. Necki, S. Newman, S. Nichol, Y. Niwa, S. ODoherty, M. Ottosson-Lofvenius, B. Paplawsky, J. Peischl, O. Peltola, J.-M. Pichon, S. Piper, C. Plass-Dolmer, M. Ramonet, E. Reyes-Sanchez, S. Richardson, H. Riris, T. Ryerson, K. Saito, M. Sargent, M. Sasakawa, Y. Sawa, D. Say, B. Scheeren, M. Schmidt, A. Schmidt, M. Schumacher, P. Shepson, M. Shook, K. Stanley, M. Steinbacher, B. Stephens, C. Sweeney, K. Thoning, M. Torn, J. Turnbull, K. Tørseth, P.V.D. Bulk, D.V. Dinther, A. Vermeulen, B. Viner, G. Vitkova, S. Walker, D. Weyrauch, S. Wofsy, D. Worthy, D. Young, and M. Zimnoch. CarbonTracker CT2019B. https://doi.org/10.25925/20201008

Pisso, I., E. Sollum, H. Grythe, N.I. Kristiansen, M. Cassiani, S. Eckhardt, D. Arnold, D. Morton, R.L. Thompson, C.D. Groot Zwaaftink, N. Evangeliou, H. Sodemann, L. Haimberger, S. Henne, D. Brunner, J.F. Burkhart, A. Fouilloux, J. Brioude, A. Philipp, P. Seibert, and A. Stohl. 2019. The Lagrangian particle dispersion model FLEXPART version 10.4. Geoscientific Model Development 12:4955–4997. https://doi.org/10.5194/gmd-12-4955-2019