Abstract
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(1D), 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.
| Original language | English |
|---|---|
| Pages (from-to) | 4469-4487 |
| Number of pages | 19 |
| Journal | Geoscientific Model Development |
| Volume | 11 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 8 Nov 2018 |
Funding
We acknowledge the following people, institutes or projects for providing observations: AGAGE, Chris M. Harth and Ray Weiss at Scripps Institution of Oceanography (SIO), Ron Prinn at Massachusetts Institute of Technology (MIT), Paul B. Krummel at CSIRO Oceans & Atmosphere, Ray H. Wang at Georgia Institute of Technology, Simon O’Doherty and Kieran Stanley at the University of Bristol. AGAGE operations for the methane data used here were primarily supported by NASA grants to MIT (NNX11AF17G) and SIO (NNX11AF15G, NNX11AF16G). The operation of all UK DECC Network stations, TAC, RGL and TTA was funded by the UK Department of Business, Energy and Industrial Strategy (contract TRN1028/06/2015) with additional funding at Mace Head, Ireland and Ragged Point, Barbados, under NASA contract NNX16AC98G through MIT with a subaward 5710004056 to University of Bristol and NOAA contract RA-133R-15-CN-0008 for Ragged Point; Cathrine Lund Myhre (NILU); China Meteorological Administration; Climate Science Centre – CSIRO Oceans & Atmosphere; Agency for Meteorology, Climatology and Geophysics (BMKG); Dirección Meteorológica de Chile; EMEP; Environment and Climate Change Canada; Federal Environment Agency, Austria; Federal Environment Agency, Germany; Institute of Arctic and Alpine Research at the University of Colorado, Boulder, funded by US National Science Foundation grant AON 1108391; Italian National Agency for New Technology, Energy and the Environment; Izana Atmospheric Research Center; Meteorological State Agency of Spain; Japan Meteorological Agency, Korea Meteorological Administration; National Institute of Water & Atmospheric Research Ltd. (NIWA), New Zealand; Ricerca sul Sistema Energetico – RSE S.p.A.; South African Weather Service; Swiss Federal Laboratories for Materials Science and Technology (Empa); University of Malta and University of Urbino. This study was funded by the Norwegian Research Council as part of ICOS-Norway (project 245927) and was part of the Nordic Centre of Excellence eSTICC (eScience Tools for Investigating Climate Change in Northern High Latitudes) funded by Nordforsk (grant 57001). A large set of observations was used in our simulations. We thank all those involved in the EBAS and WDCGG efforts, and those who have contributed by operating sites, performing chemical analysis and making the data publicly available in the databases. We acknowledge the following people, institutes or projects for providing observations: AGAGE, Chris M. Harth and Ray Weiss at Scripps Institution of Oceanography (SIO), Ron Prinn at Massachusetts Institute of Technology (MIT), Paul B. Krummel at CSIRO Oceans & Atmosphere, Ray H. Wang at Georgia Institute of Technology, Simon O'Doherty and Kieran Stanley at the University of Bristol. AGAGE operations for the methane data used here were primarily supported by NASA grants to MIT (NNX11AF17G) and SIO (NNX11AF15G, NNX11AF16G). The operation of all UK DECC Network stations, TAC, RGL and TTA was funded by the UK Department of Business, Energy and Industrial Strategy (contract TRN1028/06/2015) with additional funding at Mace Head, Ireland and Ragged Point, Barbados, under NASA contract NNX16AC98G through MIT with a subaward 5710004056 to University of Bristol and NOAA contract RA-133R-15-CN-0008 for Ragged Point; Cathrine Lund Myhre (NILU); China Meteorological Administration; Climate Science Centre - CSIRO Oceans & Atmosphere; Agency for Meteorology, Climatology and Geophysics (BMKG); Dirección Meteorológica de Chile; EMEP; Environment and Climate Change Canada; Federal Environment Agency, Austria; Federal Environment Agency, Germany; Institute of Arctic and Alpine Research at the University of Colorado, Boulder, funded by US National Science Foundation grant AON 1108391; Italian National Agency for New Technology, Energy and the Environment; Izana Atmospheric Research Center; Meteorological State Agency of Spain; Japan Meteorological Agency, Korea Meteorological Administration; National Institute of Water & Atmospheric Research Ltd. (NIWA), New Zealand; Ricerca sul Sistema Energetico - RSE S.p.A.; South African Weather Service; Swiss Federal Laboratories for Materials Science and Technology (Empa); University of Malta and University of Urbino. This study was funded by the Norwegian Research Council as part of ICOS-Norway (project 245927) and was part of the Nordic Centre of Excellence eSTICC (eScience Tools for Investigating Climate Change in Northern High Latitudes) funded by Nordforsk (grant 57001).
Austrian Fields of Science 2012
- 105206 Meteorology
