scholarly journals The Canadian atmospheric transport model for simulating greenhouse gas evolution on regional scales: GEM-MACH-GHG v.137-reg

2019 ◽  
Author(s):  
Jinwoong Kim ◽  
Saroja Polavarapu ◽  
Douglas Chan ◽  
Michael Neish
Keyword(s):  
Greenhouse Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Forecast Error ◽  
Regional Scale ◽  
The United States ◽  
Regional Model ◽  
Boreal Summer ◽  
Chemical Transport Model ◽  
Atmospheric Transport Model

Abstract. In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high spatio-temporal resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km × 10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations, based on comparisons to surface and aircraft observations. In addition, reduced bias and standard deviation of forecast error in boreal summer are obtained by the regional model. Better representation of model topography in the regional model reduces transport and representation errors significantly compared to the global model, especially in regions of complex topography, as revealed by the more precise and detailed structure of the CO2 diurnal cycle produced at observation sites and in model space. The new regional model will form the basis of a flux inversion system that estimates regional scale fluxes of GHGs over Canada.

scholarly journals The Canadian atmospheric transport model for simulating greenhouse gas evolution on regional scales: GEM–MACH–GHG v.137-reg

2020 ◽  
Vol 13 (1) ◽  
pp. 269-295
Author(s):  
Jinwoong Kim ◽  
Saroja M. Polavarapu ◽  
Douglas Chan ◽  
Michael Neish
Keyword(s):  
Greenhouse Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Forecast Error ◽  
Regional Scale ◽  
The United States ◽  
Regional Model ◽  
Boreal Summer ◽  
Spatiotemporal Resolution ◽  
Atmospheric Transport Model

Abstract. In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high-spatiotemporal-resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km×10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower-resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate the high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations based on comparisons to surface and aircraft observations. In addition, the bias and standard deviation of forecast error in boreal summer are reduced by the regional model. Better representation of model topography in the regional model results in improved simulation of the CO2 diurnal cycle compared to the global model at Walnut Grove, California. The new regional model will form the basis of a flux inversion system that estimates regional-scale fluxes of GHGs over Canada.

scholarly journals Assessment of an atmospheric transport model for annual inverse estimates of California greenhouse gas emissions

2017 ◽  
Vol 122 (3) ◽  
pp. 1901-1918 ◽  
Author(s):  
Justin E. Bagley ◽  
Seongeun Jeong ◽  
Xinguang Cui ◽  
Sally Newman ◽  
Jingsong Zhang ◽  
...  
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Gas Emissions ◽  
Atmospheric Transport Model

scholarly journals The CarboCount CH sites: characterization of a dense greenhouse gas observation network

2015 ◽  
Vol 15 (19) ◽  
pp. 11147-11164 ◽  
Author(s):  
B. Oney ◽  
S. Henne ◽  
N. Gruber ◽  
M. Leuenberger ◽  
I. Bamberger ◽  
...  
Keyword(s):  
Carbon Flux ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Regional Scale ◽  
Particle Dispersion ◽  
Observation Network ◽  
Simulated Surface ◽  
Swiss Plateau ◽  
Atmospheric Transport Model

Abstract. We describe a new rural network of four densely placed (< 100 km apart), continuous atmospheric carbon (CO2, CH4, and CO) measurement sites in north-central Switzerland and analyze its suitability for regional-scale (~ 100–500 km) carbon flux studies. We characterize each site for the period from March 2013 to February 2014 by analyzing surrounding land cover, observed local meteorology, and sensitivity to surface fluxes, as simulated with the Lagrangian particle dispersion model FLEXPART-COSMO (FLEXible PARTicle dispersion model-Consortium for Small-Scale Modeling). The Beromünster measurements are made on a tall tower (212 m) located on a gentle hill. At Beromünster, regional CO2 signals (measurement minus background) vary diurnally from −4 to +4 ppmv, on average, and are simulated to come from nearly the entire Swiss Plateau, where 50 % of surface influence is simulated to be within 130–260 km distance. The Früebüel site measurements are made 4 m above ground on the flank of a gently sloping mountain. Nearby (< 50 km) pasture and forest fluxes exert the most simulated surface influence, except during convective summertime days when the site is mainly influenced by the eastern Swiss Plateau, which results in summertime regional CO2 signals varying diurnally from −5 to +12 ppmv and elevated summer daytime CH4 signals (+30 ppbv above other sites). The Gimmiz site measurements are made on a small tower (32 m) in flat terrain. Here, strong summertime regional signals (−5 to +60 ppmv CO2) stem from large, nearby (< 50 km) crop and anthropogenic fluxes of the Seeland region, except during warm or windy days when simulated surface influence is of regional scale (< 250 km). The Lägern-Hochwacht measurements are made on a small tower (32 m) on top of the steep Lägern crest, where simulated surface influence is typically of regional scale (130–300 km) causing summertime regional signals to vary from −5 to +8 ppmv CO2. Here, considerable anthropogenic influence from the nearby industrialized region near Zurich causes the average wintertime regional CO2 signals to be 5 ppmv above the regional signals simultaneously measured at the Früebüel site. We find that the suitability of the data sets from our current observation network for regional carbon budgeting studies largely depends on the ability of the high-resolution (2 km) atmospheric transport model to correctly capture the temporal dynamics of the stratification of the lower atmosphere at the different sites. The current version of the atmospheric transport model captures these dynamics well, but it clearly reaches its limits at the sites in steep topography and at the sites that generally remain in the surface layer. Trace gas transport and inverse modeling studies will be necessary to determine the impact of these limitations on our ability to derive reliable regional-scale carbon flux estimates in the complex Swiss landscape.

scholarly journals The CarboCount CH sites: characterization of a dense greenhouse gas observation network

2015 ◽  
Vol 15 (9) ◽  
pp. 12911-12956 ◽  
Author(s):  
B. Oney ◽  
S. Henne ◽  
N. Gruber ◽  
M. Leuenberger ◽  
I. Bamberger ◽  
...  
Keyword(s):  
Carbon Flux ◽  
Temporal Dynamics ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Regional Scale ◽  
Observation Network ◽  
Simulated Surface ◽  
Swiss Plateau ◽  
The Impact ◽  
Atmospheric Transport Model

Abstract. We describe a new rural network of four densely placed (< 100 km apart), continuous atmospheric carbon (CO2, CH4, and CO) measurement sites in north-central Switzerland and analyze their suitability for regional-scale (~ 100 to 500 km) carbon flux studies. We characterize each site by analyzing surrounding land cover, observed local meteorology, and sensitivity to surface fluxes, as simulated with the Lagrangian particle dispersion model FLEXPART-COSMO. The Beromünster measurements are made on a tall tower (212 m) located on a gentle hill. At Beromünster, regional CO2 signals (measurement minus background) vary diurnally from −4 to +4 ppmv on average, and are simulated to come from nearly the entire Swiss Plateau, where 50% of surface influence is simulated to be within 130 to 260 km distance. The Früebüel site measurements are made 4 m above ground on the flank of a gently sloping mountain. Nearby (< 50 km) pasture and forest fluxes exert the most simulated surface influence, except during convective summertime days when the site is mainly influenced by the eastern Swiss Plateau, which results in summertime regional CO2 signals varying diurnally from −5 to +12 ppmv and elevated summer daytime CH4 signals (+30 ppbv above other sites). The Gimmiz site measurements are made on a small tower (32 m) in flat terrain. Here, strong summertime regional signals (−5 to +60 ppmv CO2) stem from large, nearby (< 50 km) crop and anthropogenic fluxes of the Seeland region, except during warm or windy days when simulated surface influence is of regional scale (< 250 km). The Lägern-Hochwacht measurements are made on a small tower (32 m) on top of the steep Lägern crest, where simulated surface influence is typically of regional scale (130 to 300 km) causing summertime regional signals to vary from −5 to +8 ppmv CO2. Here, considerable anthropogenic influence from the nearby industrialized region near Zurich cause the average wintertime regional CO2 signals to be 5 ppmv above the regional signals simultaneously measured at Früebüel site. We find that the suitability of the datasets from our current observation network for regional carbon budgeting studies largely depends on the ability of the high-resolution (2 km) atmospheric transport model to correctly capture the temporal dynamics of the stratification of the lower atmosphere at the different sites. The current version of the atmospheric transport model captures these dynamics well, but it clearly reaches its limits at the sites in steep topography, and at the sites that generally remain in the surface layer. Trace gas transport and inverse modeling studies will be necessary to determine the impact of these limitations on our ability to derive reliable regional-scale carbon flux estimates in the complex Swiss landscape.

scholarly journals Inverse modelling of CF<sub>4</sub> and NF<sub>3</sub> emissions in East Asia

2018 ◽  
Vol 18 (18) ◽  
pp. 13305-13320 ◽  
Author(s):  
Tim Arnold ◽  
Alistair J. Manning ◽  
Jooil Kim ◽  
Shanlan Li ◽  
Helen Webster ◽  
...  
Keyword(s):  
South Korea ◽  
East Asia ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Atmospheric Gases ◽  
Atmospheric Measurements ◽  
Small Uncertainty ◽  
Measurement Location ◽  
Atmospheric Transport Model ◽  
Good Agreement

Abstract. Decadal trends in the atmospheric abundances of carbon tetrafluoride (CF4) and nitrogen trifluoride (NF3) have been well characterised and have provided a time series of global total emissions. Information on locations of emissions contributing to the global total, however, is currently poor. We use a unique set of measurements between 2008 and 2015 from the Gosan station, Jeju Island, South Korea (part of the Advanced Global Atmospheric Gases Experiment network), together with an atmospheric transport model, to make spatially disaggregated emission estimates of these gases in East Asia. Due to the poor availability of good prior information for this study, our emission estimates are largely influenced by the atmospheric measurements. Notably, we are able to highlight emission hotspots of NF3 and CF4 in South Korea due to the measurement location. We calculate emissions of CF4 to be quite constant between the years 2008 and 2015 for both China and South Korea, with 2015 emissions calculated at 4.3±2.7 and 0.36±0.11 Gg yr−1, respectively. Emission estimates of NF3 from South Korea could be made with relatively small uncertainty at 0.6±0.07 Gg yr−1 in 2015, which equates to ∼1.6 % of the country's CO2 emissions. We also apply our method to calculate emissions of CHF3 (HFC-23) between 2008 and 2012, for which our results find good agreement with other studies and which helps support our choice in methodology for CF4 and NF3.

scholarly journals Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change

2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Multiple Linear Regression Model ◽  
The United States ◽  
Chemical Transport Model ◽  
Modes Of Variability ◽  
The Us ◽  
Cyclone Frequency

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

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