scholarly journals Inversion of long-lived trace gas emissions using combined Eulerian and Lagrangian chemical transport models

2011 ◽  
Vol 11 (5) ◽  
pp. 14689-14717 ◽  
Author(s):  
M. Rigby ◽  
A. J. Manning ◽  
R. G. Prinn

Abstract. We present a method for estimating emissions of long-lived trace gases from a sparse global network of high-frequency observatories, using both a global Eulerian chemical transport model and Lagrangian particle dispersion model. Emissions are derived in a single step after determining sensitivities of the observations to initial conditions, the high-resolution emissions field close to observation points, and larger regions further from the measurements. This method has the several advantages over inversions using one type of model alone, in that: high-resolution simulations can be carried out in limited domains close to the measurement sites, with lower resolution being used further from them; the influence of errors due to aggregation of emissions close to the measurement sites can be minimized; assumptions about boundary conditions to the Lagrangian model do not need to be made, since the entire emissions field is estimated; any combination of appropriate models can be used, with no code modification. Because the sensitivity to the entire emissions field is derived, the estimation can be carried out using traditional statistical methods without the need for multiple steps in the inversion. We demonstrate the utility of this approach by determining global SF6 emissions using measurements from the Advanced Global Atmospheric Gases Experiment (AGAGE) between 2007 and 2009. The global total and large-scale patterns of the derived emissions agree well with previous studies, whilst allowing emissions to be determined at higher resolution than has previously been possible, and improving the agreement between the modeled and observed mole fractions at some sites.

2011 ◽  
Vol 11 (18) ◽  
pp. 9887-9898 ◽  
Author(s):  
M. Rigby ◽  
A. J. Manning ◽  
R. G. Prinn

Abstract. We present a method for estimating emissions of long-lived trace gases from a sparse global network of high-frequency observatories, using both a global Eulerian chemical transport model and Lagrangian particle dispersion model. Emissions are derived in a single step after determining sensitivities of the observations to initial conditions, the high-resolution emissions field close to observation points, and larger regions further from the measurements. This method has the several advantages over inversions using one type of model alone, in that: high-resolution simulations can be carried out in limited domains close to the measurement sites, with lower resolution being used further from them; the influence of errors due to aggregation of emissions close to the measurement sites can be minimized; assumptions about boundary conditions to the Lagrangian model do not need to be made, since the entire emissions field is estimated; any combination of appropriate models can be used, with no code modification. Because the sensitivity to the entire emissions field is derived, the estimation can be carried out using traditional statistical methods without the need for multiple steps in the inversion. We demonstrate the utility of this approach by determining global SF6 emissions using measurements from the Advanced Global Atmospheric Gases Experiment (AGAGE) between 2007 and 2009. The global total and large-scale patterns of the derived emissions agree well with previous studies, whilst allowing emissions to be determined at higher resolution than has previously been possible, and improving the agreement between the modeled and observed mole fractions at some sites.


2011 ◽  
Vol 4 (3) ◽  
pp. 2047-2080 ◽  
Author(s):  
A. Ganshin ◽  
T. Oda ◽  
M. Saito ◽  
S. Maksyutov ◽  
V. Valsala ◽  
...  

Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e., a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.


2012 ◽  
Vol 5 (1) ◽  
pp. 231-243 ◽  
Author(s):  
A. Ganshin ◽  
T. Oda ◽  
M. Saito ◽  
S. Maksyutov ◽  
V. Valsala ◽  
...  

Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA), comprising a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e. a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.


2017 ◽  
Vol 17 (14) ◽  
pp. 8757-8770 ◽  
Author(s):  
Roghayeh Ghahremaninezhad ◽  
Ann-Lise Norman ◽  
Betty Croft ◽  
Randall V. Martin ◽  
Jeffrey R. Pierce ◽  
...  

Abstract. Vertical distributions of atmospheric dimethyl sulfide (DMS(g)) were sampled aboard the research aircraft Polar 6 near Lancaster Sound, Nunavut, Canada, in July 2014 and on pan-Arctic flights in April 2015 that started from Longyearbyen, Spitzbergen, and passed through Alert and Eureka, Nunavut, and Inuvik, Northwest Territories. Larger mean DMS(g) mixing ratios were present during April 2015 (campaign mean of 116  ±  8 pptv) compared to July 2014 (campaign mean of 20  ±  6 pptv). During July 2014, the largest mixing ratios were found near the surface over the ice edge and open water. DMS(g) mixing ratios decreased with altitude up to about 3 km. During April 2015, profiles of DMS(g) were more uniform with height and some profiles showed an increase with altitude. DMS reached as high as 100 pptv near 2500 m. Relative to the observation averages, GEOS-Chem (www.geos-chem.org) chemical transport model simulations were higher during July and lower during April. Based on the simulations, more than 90 % of the July DMS(g) below 2 km and more than 90 % of the April DMS(g) originated from Arctic seawater (north of 66° N). During April, 60 % of the DMS(g), between 500 and 3000 m originated from Arctic seawater. During July 2014, FLEXPART (FLEXible PARTicle dispersion model) simulations locate the sampled air mass over Baffin Bay and the Canadian Arctic Archipelago 4 days back from the observations. During April 2015, the locations of the air masses 4 days back from sampling were varied: Baffin Bay/Canadian Archipelago, the Arctic Ocean, Greenland and the Pacific Ocean. Our results highlight the role of open water below the flight as the source of DMS(g) during July 2014 and the influence of long-range transport (LRT) of DMS(g) from further afield in the Arctic above 2500 m during April 2015.


2020 ◽  
Author(s):  
Shamil Maksyutov ◽  
Tomohiro Oda ◽  
Makoto Saito ◽  
Rajesh Janardanan ◽  
Dmitry Belikov ◽  
...  

Abstract. We developed a high-resolution surface flux inversion system based on the global Lagrangian–Eulerian coupled tracer transport model composed of National Institute for Environmental Studies Transport Model (NIES-TM) and FLEXible PARTicle dispersion model (FLEXPART). The inversion system is named NTFVAR (NIES-TM-FLEXPART-variational) as it applies variational optimisation to estimate surface fluxes. We tested the system by estimating optimized corrections to natural surface CO2 fluxes to achieve best fit to atmospheric CO2 data collected by the global in-situ network, as a necessary step towards capability of estimating anthropogenic CO2 emissions. We employ the Lagrangian particle dispersion model (LPDM) FLEXPART to calculate the surface flux footprints of CO2 observations at a 0.1° × 0.1° spatial resolution. The LPDM is coupled to a global atmospheric tracer transport model (NIES-TM). Our inversion technique uses an adjoint of the coupled transport model in an iterative optimization procedure. The flux error covariance operator is being implemented via implicit diffusion. Biweekly flux corrections to prior flux fields were estimated for the years 2010–2012 from in-situ CO2 data included in the Observation Package (ObsPack) dataset. High-resolution prior flux fields were prepared using Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) for fossil fuel combustion, Global Fire Assimilation System (GFAS) for biomass burning, the Vegetation Integrative SImulator for Trace gases (VISIT) model for terrestrial biosphere exchange and Ocean Tracer Transport Model (OTTM) for oceanic exchange. The terrestrial biospheric flux field was constructed using a vegetation mosaic map and separate simulation of CO2 fluxes at daily time step by the VISIT model for each vegetation type. The prior flux uncertainty for terrestrial biosphere was scaled proportionally to the monthly mean Gross Primary Production (GPP) by the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD17 product. The inverse system calculates flux corrections to the prior fluxes in the form of a relatively smooth field multiplied by high-resolution patterns of the prior flux uncertainties for land and ocean, following the coastlines and vegetation productivity gradients. The resulting flux estimates improve fit to the observations at continuous observations sites, reproducing both the seasonal variation and short-term concentration variability, including high CO2 concentration events associated with anthropogenic emissions. The use of high-resolution atmospheric transport in global CO2 flux inversion has the advantage of better resolving the transport from the mix of the anthropogenic and biospheric sources in densely populated continental regions and shows potential for better separation between fluxes from terrestrial ecosystems and strong localised sources such as anthropogenic emissions and forest fires. Further improvements in the modelling system are needed as the posterior fit is better than that by the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker only for a fraction of the monitoring sites, mostly at coastal and island locations experiencing mix of background and local flux signals.


2012 ◽  
Vol 5 (1) ◽  
pp. 309-346
Author(s):  
J. D. Silver ◽  
J. Brandt ◽  
M. Hvidberg ◽  
J. Frydendall

Abstract. Data assimilation is the process of combining real-world observations with a modelled geophysical field. The increasing abundance of satellite retrievals of atmospheric trace gases makes chemical data assimilation a powerful tool for improving air quality forecasts. We implemented a two-dimensional optimal interpolation (OI) algorithm to assimilate satellite-derived estimates of tropospheric NO2 column concentrations into the Danish Eulerian Hemispheric Model (DEHM, version V2007.0), a three-dimensional, European-scale, chemical transport model. In particular, we describe how we used observational data to estimate the background error covariance matrix, B. In the assimilation, the tropospheric column NO2 field was adjusted and the modelled NO2 profile was scaled accordingly; other species were only adjusted indirectly via changes to NO2 concentrations. We ran a number of experiments to compare different parameterisations of B; this involved varying the length scale used in B, the relative weighting of the background and observation errors, the errors assigned to observations and the influence of clustered observations. We assessed model performance by comparing the analysed fields to an independent set of observations: ground-based measurements of NO2 concentrations. Ozonosonde profiles were also used for verification. The analysed NO2 and O3 concentrations were more accurate than those from a reference simulation without assimilation, with lower bias for both species and improved correlation for NO2. The experiments showed that appropriately chosen parameters for the B matrix, estimated using innovation statistics, yielded more accurate surface NO2 concentrations. There was good agreement between the seasonally-averaged observed and modelled O3 profiles. The simple OI scheme was effective and computationally feasible in this context, where only a single species was assimilated and only a two-dimensional field was adjusted. However there are certain limitations to using this assimilation scheme for more highly multi-dimensional problems. Although forecast accuracy was not examined here, we discuss the potential for improving NO2 forecasts by using assimilation to generate initial conditions.


2015 ◽  
Vol 15 (23) ◽  
pp. 34091-34147 ◽  
Author(s):  
A. Gressent ◽  
B. Sauvage ◽  
D. Cariolle ◽  
M. Evans ◽  
M. Leriche ◽  
...  

Abstract. For the first time, a plume-in-grid approach is implemented in a chemical transport model (CTM) to parameterize the effects of the non-linear reactions occurring within high concentrated NOx plumes from lightning NOx emissions (LNOx) in the upper troposphere. It is characterized by a set of parameters including the plume lifetime, the effective reaction rate constant related to NOx-O3 chemical interactions and the fractions of NOx conversion into HNO3 within the plume. Parameter estimates were made using the DSMACC chemical box model, simple plume dispersion simulations and the mesoscale 3-D Meso-NH model. In order to assess the impact of the LNOx plume approach on the NOx and O3 distributions at large scale, simulations for the year 2006 were performed using the GEOS-Chem global model with a horizontal resolution of 2° × 2.5°. The implementation of the LNOx parameterization implies NOx and O3 decrease at large scale over the region characterized by a strong lightning activity (up to 25 and 8 %, respectively, over Central Africa in July) and a relative increase downwind of LNOx emissions (up to 18 and 2 % for NOx and O3, respectively, in July) are derived. The calculated variability of NOx and O3 mixing ratios around the mean value according to the known uncertainties on the parameter estimates is maximum over continental tropical regions with ΔNOx [−33.1; +29.7] ppt and ΔO3 [−1.56; +2.16] ppb, in January, and ΔNOx [−14.3; +21] ppt and ΔO3 [−1.18; +1.93] ppb, in July, mainly depending on the determination of the diffusion properties of the atmosphere and the initial NO mixing ratio injected by lightning. This approach allows (i) to reproduce a more realistic lightning NOx chemistry leading to better NOx and O3 distributions at the large scale and (ii) focus on other improvements to reduce remaining uncertainties from processes related to NOx chemistry in CTM.


2020 ◽  
Author(s):  
Bo Zhang ◽  
Hongyu Liu ◽  
James H. Crawford ◽  
Gao Chen ◽  
T. Duncan Fairlie ◽  
...  

Abstract. Radon-222 (222Rn) is a short-lived radioactive gas naturally emitted from land surfaces, and has long been used to assess convective transport in atmospheric models. In this study, we simulate 222Rn using the GEOS-Chem chemical transport model to improve our understanding of 222Rn emissions and surface concentration seasonality, and characterize convective transport associated with two Goddard Earth Observing System (GEOS) meteorological products, MERRA and GEOS-FP. We evaluate four global 222Rn emission scenarios by comparing model results with observations at 51 surface sites. The default emission scenario in GEOS-Chem yields a moderate agreement with surface observations globally ( 80 % data within a factor of 2), and reasonable agreement in Asia (close to 70 %). Further constraints on 222Rn emissions would require additional concentration and emission flux observations in the central U.S., Canada, Africa, and Asia. We also compare and assess convective transport in model simulations driven by MERRA and GEOS-FP using observed 222Rn vertical profiles in northern mid-latitude summer, and from three short-term airborne campaigns. While simulations with both GEOS products are able to capture the observed vertical gradient of 222Rn concentrations in the lower troposphere (0–4 km), neither correctly represents the level of convective detrainment, resulting in biases in the middle and upper troposphere. Compared with GEOS-FP, MERRA leads to stronger convective transport of 222Rn, which is partially compensated by its weaker large-scale vertical advection, resulting in similar global vertical distributions of 222Rn concentrations between the two simulations. This has important implications for using chemical transport models to interpret the transport of other trace species when these GEOS products are used as driving meteorology.


2012 ◽  
Vol 5 (2) ◽  
pp. 1561-1626 ◽  
Author(s):  
O. A. Søvde ◽  
M. J. Prather ◽  
I. S. A. Isaksen ◽  
T. K. Berntsen ◽  
F. Stordal ◽  
...  

Abstract. We present here the global chemical transport model Oslo CTM3, an update of the Oslo CTM2. The update comprises a faster transport scheme, an improved wet scavenging scheme for large scale rain, updated photolysis rates and a new lightning parameterization. Oslo CTM3 is better parallelized and allows for stable, large time steps for advection, enabling more complex or high resolution simulations. Thorough comparisons between the Oslo CTM3, Oslo CTM2 and measurements are performed, and in general the Oslo CTM3 is found to reproduce measurements well. Inclusion of tropospheric sulfur chemistry and nitrate aerosols in CTM3 is shown to be important to reproduce tropospheric O3, OH and the CH4 lifetime well. Using the same meteorology to drive the two models, shows that some features related to transport are better resolved by the CTM3, such as polar cap transport, while features like transport close to the vortex edge are resolved better in the Oslo CTM2 due to its required shorter transport time step. The longer transport time steps in CTM3 result in larger errors e.g. near the jets, and when necessary, this can be remedied by using a shorter time step. An additional, more accurate and time consuming, treatment of polar cap transport is presented, however, both perform acceptably. A new treatment of the horizontal distribution of lightning is presented and found to compare well with measurements. Vertical distributions of lighting are updated, and tested against the old vertical distribution. The new profiles are found to produce more NOx in the tropical middle troposphere, and less at the surface and at high altitudes.


2011 ◽  
Vol 11 (12) ◽  
pp. 5783-5803 ◽  
Author(s):  
W. Feng ◽  
M. P. Chipperfield ◽  
S. Dhomse ◽  
B. M. Monge-Sanz ◽  
X. Yang ◽  
...  

Abstract. We investigate the performance of cloud convection and tracer transport in a global off-line 3-D chemical transport model. Various model simulations are performed using different meteorological (re)analyses (ERA-40, ECMWF operational and ECMWF Interim) to diagnose the updraft mass flux, convective precipitation and cloud top height. The diagnosed upward mass flux distribution from TOMCAT agrees quite well with the ECMWF reanalysis data (ERA-40 and ERA-Interim) below 200 hPa. Inclusion of midlevel convection improves the agreement at mid-high latitudes. However, the reanalyses show strong convective transport up to 100 hPa, well into the tropical tropopause layer (TTL), which is not captured by TOMCAT. Similarly, the model captures the spatial and seasonal variation of convective cloud top height although the mean modelled value is about 2 km lower than observed. The ERA-Interim reanalyses have smaller archived upward convective mass fluxes than ERA-40, and smaller convective precipitation, which is in better agreement with satellite-based data. TOMCAT captures these relative differences when diagnosing convection from the large-scale fields. The model also shows differences in diagnosed convection with the version of the operational analyses used, which cautions against using results of the model from one specific time period as a general evaluation. We have tested the effect of resolution on the diagnosed modelled convection with simulations ranging from 5.6° × 5.6° to 1° × 1°. Overall, in the off-line model, the higher model resolution gives stronger vertical tracer transport, however, it does not make a large change to the diagnosed convective updraft mass flux (i.e., the model results using the convection scheme fail to capture the strong convection transport up to 100 hPa as seen in the archived convective mass fluxes). Similarly, the resolution of the forcing winds in the higher resolution CTM does not make a large improvement compared to the archived mass fluxes. Including a radon tracer in the model confirms the importance of convection for reproducing observed midlatitude profiles. The model run using archived mass fluxes transports significantly more radon to the upper troposphere but the available data does not strongly discriminate between the different model versions.


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