Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data
<p>A Lagrangian particle dispersion model, the FLEXible PARTicle dispersion chemical transport model (FLEXPART CTM), is used to simulate global three-dimensional fields of trace gas abundance. These fields are constrained with surface observation data through nudging, a data assimilation m...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-11-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://www.geosci-model-dev.net/11/4469/2018/gmd-11-4469-2018.pdf |
| _version_ | 1818214908846669824 |
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| author | C. D. Groot Zwaaftink S. Henne R. L. Thompson E. J. Dlugokencky T. Machida J.-D. Paris M. Sasakawa A. Segers C. Sweeney A. Stohl |
| author_facet | C. D. Groot Zwaaftink S. Henne R. L. Thompson E. J. Dlugokencky T. Machida J.-D. Paris M. Sasakawa A. Segers C. Sweeney A. Stohl |
| author_sort | C. D. Groot Zwaaftink |
| collection | DOAJ |
| description | <p>A Lagrangian particle dispersion
model, the FLEXible PARTicle dispersion chemical transport model (FLEXPART
CTM), is used to simulate global three-dimensional fields of trace gas
abundance. These fields are constrained with surface observation data through
nudging, a data assimilation method, which relaxes model fields to observed
values. Such fields are of interest to a variety of applications, such as
inverse modelling, satellite retrievals, radiative forcing models and
estimating global growth rates of greenhouse gases. Here, we apply this
method to methane using 6 million model particles filling the global model
domain. For each particle, methane mass tendencies due to emissions (based on
several inventories) and loss by reaction with OH, Cl and O(<sup>1</sup>D), as
well as observation data nudging were calculated. Model particles were
transported by mean, turbulent and convective transport driven by 1° × 1° ERA-Interim meteorology. Nudging is applied at 79 surface
stations, which are mostly included in the World Data Centre for Greenhouse
Gases (WDCGG) database or the Japan–Russia Siberian Tall Tower Inland
Observation Network (JR-STATION) in Siberia. For simulations of 1 year
(2013), we perform a sensitivity analysis to show how nudging settings affect
modelled concentration fields. These are evaluated with a set of independent
surface observations and with vertical profiles in North America from the
National Oceanic and Atmospheric Administration (NOAA) Earth System Research
Laboratory (ESRL), and in Siberia from the Airborne Extensive Regional
Observations in SIBeria (YAK-AEROSIB) and the National Institute for
Environmental Studies (NIES). FLEXPART CTM results are also compared to
simulations from the global Eulerian chemistry Transport Model version 5
(TM5) based on optimized fluxes. Results show that nudging strongly improves
modelled methane near the surface, not only at the nudging locations but also
at independent stations. Mean bias at all surface locations could be reduced
from over 20 to less than 5 ppb through nudging. Near the surface, FLEXPART
CTM, including nudging, appears better able to capture methane molar mixing
ratios than TM5 with optimized fluxes, based on a larger bias of over 13 ppb
in TM5 simulations. The vertical profiles indicate that nudging affects model
methane at high altitudes, yet leads to little improvement in the model
results there. Averaged from 19 aircraft profile locations in North America
and Siberia, root mean square error (RMSE) changes only from 16.3 to
15.7 ppb through nudging, while the mean absolute bias increases from 5.3 to
8.2 ppb. The performance for vertical profiles is thereby similar to TM5
simulations based on TM5 optimized fluxes where we found a bias of 5 ppb and
RMSE of 15.9 ppb. With this rather simple model setup, we thus provide
three-dimensional methane fields suitable for use as boundary conditions in
regional inverse modelling as a priori information for satellite retrievals
and for more accurate estimation of mean mixing ratios and growth rates. The
method is also applicable to other long-lived trace gases.</p> |
| first_indexed | 2024-12-12T06:27:40Z |
| format | Article |
| id | doaj.art-47cfd248aebd4557803da933e14006e5 |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-12-12T06:27:40Z |
| publishDate | 2018-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-47cfd248aebd4557803da933e14006e52022-12-22T00:34:43ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032018-11-01114469448710.5194/gmd-11-4469-2018Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation dataC. D. Groot Zwaaftink0S. Henne1R. L. Thompson2E. J. Dlugokencky3T. Machida4J.-D. Paris5M. Sasakawa6A. Segers7C. Sweeney8A. Stohl9Norwegian Institute for Air Research NILU, Kjeller, NorwayEmpa, Swiss Federal Laboratories for Materials Science and Technology, Air Pollution/Environmental Technology, Dübendorf, SwitzerlandNorwegian Institute for Air Research NILU, Kjeller, NorwayNOAA Earth System Research Laboratory, Boulder, CO, USANational Institute for Environmental Studies, Tsukuba, JapanLaboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, FranceNational Institute for Environmental Studies, Tsukuba, JapanNetherlands Organisation for Applied Scientific Research (TNO), Utrecht, the NetherlandsNOAA Earth System Research Laboratory, Boulder, CO, USANorwegian Institute for Air Research NILU, Kjeller, Norway<p>A Lagrangian particle dispersion model, the FLEXible PARTicle dispersion chemical transport model (FLEXPART CTM), is used to simulate global three-dimensional fields of trace gas abundance. These fields are constrained with surface observation data through nudging, a data assimilation method, which relaxes model fields to observed values. Such fields are of interest to a variety of applications, such as inverse modelling, satellite retrievals, radiative forcing models and estimating global growth rates of greenhouse gases. Here, we apply this method to methane using 6 million model particles filling the global model domain. For each particle, methane mass tendencies due to emissions (based on several inventories) and loss by reaction with OH, Cl and O(<sup>1</sup>D), as well as observation data nudging were calculated. Model particles were transported by mean, turbulent and convective transport driven by 1° × 1° ERA-Interim meteorology. Nudging is applied at 79 surface stations, which are mostly included in the World Data Centre for Greenhouse Gases (WDCGG) database or the Japan–Russia Siberian Tall Tower Inland Observation Network (JR-STATION) in Siberia. For simulations of 1 year (2013), we perform a sensitivity analysis to show how nudging settings affect modelled concentration fields. These are evaluated with a set of independent surface observations and with vertical profiles in North America from the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL), and in Siberia from the Airborne Extensive Regional Observations in SIBeria (YAK-AEROSIB) and the National Institute for Environmental Studies (NIES). FLEXPART CTM results are also compared to simulations from the global Eulerian chemistry Transport Model version 5 (TM5) based on optimized fluxes. Results show that nudging strongly improves modelled methane near the surface, not only at the nudging locations but also at independent stations. Mean bias at all surface locations could be reduced from over 20 to less than 5 ppb through nudging. Near the surface, FLEXPART CTM, including nudging, appears better able to capture methane molar mixing ratios than TM5 with optimized fluxes, based on a larger bias of over 13 ppb in TM5 simulations. The vertical profiles indicate that nudging affects model methane at high altitudes, yet leads to little improvement in the model results there. Averaged from 19 aircraft profile locations in North America and Siberia, root mean square error (RMSE) changes only from 16.3 to 15.7 ppb through nudging, while the mean absolute bias increases from 5.3 to 8.2 ppb. The performance for vertical profiles is thereby similar to TM5 simulations based on TM5 optimized fluxes where we found a bias of 5 ppb and RMSE of 15.9 ppb. With this rather simple model setup, we thus provide three-dimensional methane fields suitable for use as boundary conditions in regional inverse modelling as a priori information for satellite retrievals and for more accurate estimation of mean mixing ratios and growth rates. The method is also applicable to other long-lived trace gases.</p>https://www.geosci-model-dev.net/11/4469/2018/gmd-11-4469-2018.pdf |
| spellingShingle | C. D. Groot Zwaaftink S. Henne R. L. Thompson E. J. Dlugokencky T. Machida J.-D. Paris M. Sasakawa A. Segers C. Sweeney A. Stohl Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data Geoscientific Model Development |
| title | Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data |
| title_full | Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data |
| title_fullStr | Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data |
| title_full_unstemmed | Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data |
| title_short | Three-dimensional methane distribution simulated with FLEXPART 8-CTM-1.1 constrained with observation data |
| title_sort | three dimensional methane distribution simulated with flexpart 8 ctm 1 1 constrained with observation data |
| url | https://www.geosci-model-dev.net/11/4469/2018/gmd-11-4469-2018.pdf |
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