scholarly journals Sensitivity of chemistry-transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

2016 ◽  
Vol 9 (5) ◽  
pp. 1683-1695 ◽  
Author(s):  
Sajeev Philip ◽  
Randall V. Martin ◽  
Christoph A. Keller
Keyword(s):  
Carbon Monoxide ◽  
Nitrogen Oxides ◽  
Spatial Resolution ◽  
Transport Model ◽  
Transport Models ◽  
Chemistry Transport Model ◽  
Simulation Accuracy ◽  
Transport Operator ◽  
Computational Expense ◽  
Simulation Error

Abstract. Chemistry-transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemistry-transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to operator duration. Subsequently, we compare the species simulated with operator durations from 10 to 60 min as typically used by global chemistry-transport models, and identify the operator durations that optimize both computational expense and simulation accuracy. We find that longer continuous transport operator duration increases concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production with longer transport operator duration. Longer chemical operator duration decreases sulfate and ammonium but increases nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by up to a factor of 5 from fine (5 min) to coarse (60 min) operator duration. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, secondary inorganic aerosols, ozone and carbon monoxide with a finer temporal or spatial resolution taken as “truth”. Relative simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) operator duration. Chemical operator duration twice that of the transport operator duration offers more simulation accuracy per unit computation. However, the relative simulation error from coarser spatial resolution generally exceeds that from longer operator duration; e.g., degrading from 2°  ×  2.5° to 4°  ×  5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different operator durations in offline chemistry-transport models. We encourage chemistry-transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

scholarly journals Sensitivity of chemical transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

2015 ◽  
Vol 8 (11) ◽  
pp. 9589-9616
Author(s):  
S. Philip ◽  
R. V. Martin ◽  
C. A. Keller
Keyword(s):  
Spatial Resolution ◽  
Temporal Resolution ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
Simulation Accuracy ◽  
Chemical Transport Models ◽  
Order Of Magnitude ◽  
Simulation Error

Abstract. Chemical transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemical transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to temporal resolution. Subsequently, we compare the tracers simulated with operator durations from 10 to 60 min as typically used by global chemical transport models, and identify the timesteps that optimize both computational expense and simulation accuracy. We found that longer transport timesteps increase concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production at longer transport timesteps. Longer chemical timesteps decrease sulfate and ammonium but increase nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by an order of magnitude from fine (5 min) to coarse (60 min) temporal resolution. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, ozone, carbon monoxide and secondary inorganic aerosols with a finer temporal or spatial resolution taken as truth. Simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) temporal resolution. Chemical timesteps twice that of the transport timestep offer more simulation accuracy per unit computation. However, simulation error from coarser spatial resolution generally exceeds that from longer timesteps; e.g. degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different temporal resolutions in offline chemical transport models. We encourage the chemical transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

scholarly journals Representing the effects of stratosphere–troposphere exchange on 3-D O<sub>3</sub> distributions in chemistry transport models using a potential vorticity-based parameterization

2016 ◽  
Vol 16 (17) ◽  
pp. 10865-10877 ◽  
Author(s):  
Jia Xing ◽  
Rohit Mathur ◽  
Jonathan Pleim ◽  
Christian Hogrefe ◽  
Jiandong Wang ◽  
...  
Keyword(s):  
Potential Vorticity ◽  
Transport Model ◽  
Model Performance ◽  
Surface Concentration ◽  
Weather Research And Forecasting ◽  
Regional Models ◽  
Transport Models ◽  
Reference Case ◽  
Chemistry Transport Model ◽  
Spatially Varying

Abstract. Downward transport of ozone (O3) from the stratosphere can be a significant contributor to tropospheric O3 background levels. However, this process often is not well represented in current regional models. In this study, we develop a seasonally and spatially varying potential vorticity (PV)-based function to parameterize upper tropospheric and/or lower stratospheric (UTLS) O3 in a chemistry transport model. This dynamic O3–PV function is developed based on 21-year ozonesonde records from World Ozone and Ultraviolet Radiation Data Centre (WOUDC) with corresponding PV values from a 21-year Weather Research and Forecasting (WRF) simulation across the Northern Hemisphere from 1990 to 2010. The result suggests strong spatial and seasonal variations of O3 ∕ PV ratios which exhibits large values in the upper layers and in high-latitude regions, with highest values in spring and the lowest values in autumn over an annual cycle. The newly developed O3 ∕ PV function was then applied in the Community Multiscale Air Quality (CMAQ) model for an annual simulation of the year 2006. The simulated UTLS O3 agrees much better with observations in both magnitude and seasonality after the implementation of the new parameterization. Considerable impacts on surface O3 model performance were found in the comparison with observations from three observational networks, i.e., EMEP, CASTNET and WDCGG. With the new parameterization, the negative bias in spring is reduced from −20 to −15 % in the reference case to −9 to −1 %, while the positive bias in autumn is increased from 1 to 15 % in the reference case to 5 to 22 %. Therefore, the downward transport of O3 from upper layers has large impacts on surface concentration and needs to be properly represented in regional models.

scholarly journals HCOOH distributions from IASI for 2008–2014: comparison with ground-based FTIR measurements and a global chemistry-transport model

2016 ◽  
Author(s):  
M. Pommier ◽  
C. Clerbaux ◽  
P.-F. Coheur ◽  
E. Mahieu ◽  
J.-F. Müller ◽  
...  
Keyword(s):  
Transport Model ◽  
Positive Trend ◽  
Good Representation ◽  
La Réunion ◽  
Transport Models ◽  
Chemistry Transport Model ◽  
Biogenic Emission ◽  
Annual Cycles ◽  
Sources And Sinks ◽  
Mountainous Regions

Abstract. Formic acid (HCOOH) is one of the most abundant volatile organic compounds in the atmosphere. It is a major contributor to rain acidity in remote areas. There are however large uncertainties on its sources and sinks, and HCOOH is misrepresented by global chemistry-transport models. This work presents global distributions from 2008 to 2014 as derived from the measurements of the Infrared Atmospheric Sounding Interferometer (IASI), based on conversion factors between brightness temperature differences and representative retrieved total columns over seven regions: Africa N, Africa S, Amazonia, Atlantic, Australia, Pacific and Russia. The dependence of the thermal contrast is taking account in the conversion method. This conversion presents errors lower than 20 % for total columns ranging between 0.5 and 1 × 1016 molec/cm2 but reaches higher values, up to 78 %, for columns lower than 0.3 × 1016 molec/cm2. Signatures from biomass burning events are highlighted, such as in the Southern Hemisphere and in Russia, as well as biogenic emission sources, e.g. over Eastern US. A comparison between 2008 and 2014 with ground-based FTIR measurements obtained at 4 locations (Maido and Saint-Denis at La Réunion, Jungfraujoch and Wollongong) is shown. Although IASI columns are found to correlate well with FTIR data, a large bias (> 100 %) is found over the two sites at La Réunion. A better agreement is found at Wollongong with a negligible bias. The comparison also highlights the difficulty for IASI to retrieve the total columns over mountainous regions such as Jungfraujoch. A comparison of the retrieved columns with the global chemistry-transport model IMAGESv2 is also presented, showing the good representation of the seasonal and inter-annual cycles over America, Australia, Asia and Siberia. A global model underestimation of the distribution and a misrepresentation of the seasonal cycle over India are also noted. A small positive trend in the IASI columns is also observed over Australia, Amazonia and India over 2008–2014 (from 0.7 to 1.5 %/year), while a decrease of ~ 0.8 %/year is measured over Siberia.

scholarly journals A 60 yr record of atmospheric carbon monoxide reconstructed from Greenland firn air

2013 ◽  
Vol 13 (15) ◽  
pp. 7567-7585 ◽  
Author(s):  
V. V. Petrenko ◽  
P. Martinerie ◽  
P. Novelli ◽  
D. M. Etheridge ◽  
I. Levin ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Transport Model ◽  
Ice Core ◽  
Emission Inventories ◽  
Road Transportation ◽  
Atmospheric Measurements ◽  
Chemistry Transport Model ◽  
Atmospheric Carbon ◽  
Atmospheric Carbon Monoxide ◽  
Co Emission

Abstract. We present the first reconstruction of the Northern Hemisphere (NH) high latitude atmospheric carbon monoxide (CO) mole fraction from Greenland firn air. Firn air samples were collected at three deep ice core sites in Greenland (NGRIP in 2001, Summit in 2006 and NEEM in 2008). CO records from the three sites agree well with each other as well as with recent atmospheric measurements, indicating that CO is well preserved in the firn at these sites. CO atmospheric history was reconstructed back to the year 1950 from the measurements using a combination of two forward models of gas transport in firn and an inverse model. The reconstructed history suggests that Arctic CO in 1950 was 140–150 nmol mol−1, which is higher than today's values. CO mole fractions rose by 10–15 nmol mol−1 from 1950 to the 1970s and peaked in the 1970s or early 1980s, followed by a ≈ 30 nmol mol−1 decline to today's levels. We compare the CO history with the atmospheric histories of methane, light hydrocarbons, molecular hydrogen, CO stable isotopes and hydroxyl radicals (OH), as well as with published CO emission inventories and results of a historical run from a chemistry-transport model. We find that the reconstructed Greenland CO history cannot be reconciled with available emission inventories unless unrealistically large changes in OH are assumed. We argue that the available CO emission inventories strongly underestimate historical NH emissions, and fail to capture the emission decline starting in the late 1970s, which was most likely due to reduced emissions from road transportation in North America and Europe.

Source attribution of carbon monoxide and ozone over the Indian subcontinent using MOZART-4 chemistry transport model

2019 ◽  
Vol 227 ◽  
pp. 165-177 ◽  
Author(s):  
Yesobu Yarragunta ◽  
Shuchita Srivastava ◽  
D. Mitra ◽  
Eric Le Flochmoën ◽  
Brice Barret ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Transport Model ◽  
Indian Subcontinent ◽  
Source Attribution ◽  
Chemistry Transport Model

scholarly journals Development of a custom OMI NO<sub>2</sub> data product for evaluating biases in a regional chemistry transport model

2015 ◽  
Vol 15 (10) ◽  
pp. 5627-5644 ◽  
Author(s):  
G. Kuhlmann ◽  
Y. F. Lam ◽  
H. M. Cheung ◽  
A. Hartl ◽  
J. C. H. Fung ◽  
...  
Keyword(s):  
Hong Kong ◽  
Air Quality ◽  
High Resolution ◽  
Correlation Coefficient ◽  
Spatial Resolution ◽  
Transport Model ◽  
Satellite Observations ◽  
Surface Reflectance ◽  
Data Set ◽  
Chemistry Transport Model

Abstract. In this paper, we present the custom Hong Kong NO2 retrieval (HKOMI) for the Ozone Monitoring Instrument (OMI) on board the Aura satellite which was used to evaluate a high-resolution chemistry transport model (CTM) (3 km × 3 km spatial resolution). The atmospheric chemistry transport was modelled in the Pearl River Delta (PRD) region in southern China by the Models-3 Community Multiscale Air Quality (CMAQ) modelling system from October 2006 to January 2007. In the HKOMI NO2 retrieval, tropospheric air mass factors (AMFs) were recalculated using high-resolution ancillary parameters of surface reflectance, a priori NO2 and aerosol profiles, of which the latter two were taken from the CMAQ simulation. We tested the influence of the ancillary parameters on the data product using four different aerosol parametrizations. Ground-level measurements by the PRD Regional Air Quality Monitoring (RAQM) network were used as additional independent measurements. The HKOMI retrieval increases estimated tropospheric NO2 vertical column densities (VCD) by (+31 ± 38)%, when compared to NASA's standard product (OMNO2-SP), and improves the normalized mean bias (NMB) between satellite and ground observations by 26 percentage points from −41 to −15%. The individual influences of the parameters are (+11.4 ± 13.4)% for NO2 profiles, (+11.0 ± 20.9)% for surface reflectance and (+6.0 ± 8.4)% for the best aerosol parametrization. The correlation coefficient r is low between ground and satellite observations (r = 0.35). The low r and the remaining NMB can be explained by the low model performance and the expected differences when comparing point measurements with area-averaged satellite observations. The correlation between CMAQ and the RAQM network is low (r ≈ 0.3) and the model underestimates the NO2 concentrations in the northwestern model domain (Foshan and Guangzhou). We compared the CMAQ NO2 time series of the two main plumes with our best OMI NO2 data set (HKOMI-4). The model overestimates the NO2 VCDs by about 15% in Hong Kong and Shenzhen, while the correlation coefficient is satisfactory (r = 0.56). In Foshan and Guangzhou, the correlation is low (r = 0.37) and the model underestimates the VCDs strongly (NMB = −40%). In addition, we estimated that the OMI VCDs are also underestimated by about 10 to 20% in Foshan and Guangzhou because of the influence of the model parameters on the AMFs. In this study, we demonstrate that the HKOMI NO2 retrieval reduces the bias of the satellite observations and how the data set can be used to study the magnitude of NO2 concentrations in a regional model at high spatial resolution of 3 × 3 km2. The low bias was achieved with recalculated AMFs using updated surface reflectance, aerosol profiles and NO2 profiles. Since unbiased concentrations are important, for example, in air pollution studies, the results of this paper can be very helpful in future model evaluation studies.

scholarly journals Representing the effects of stratosphere-troposphere exchange on 3D O<sub>3</sub> distributions in chemistry transport models using a potential vorticity based parameterization

2016 ◽  
Author(s):  
Jia Xing ◽  
Rohit Mathur ◽  
Jonathan Pleim ◽  
Christian Hogrefe ◽  
Jiandong Wang ◽  
...  
Keyword(s):  
Potential Vorticity ◽  
Transport Model ◽  
Model Performance ◽  
Surface Concentration ◽  
Weather Research And Forecasting ◽  
Regional Models ◽  
Transport Models ◽  
Reference Case ◽  
Chemistry Transport Model ◽  
Spatially Varying

Abstract. Downward transport of ozone (O3) from the stratosphere can be a significant contributor to tropospheric O3 background levels. However, this process often is not well represented in current regional models. In this study, we develop a seasonally and spatially varying potential vorticity (PV)-based function to numerically assimilate upper tropospheric / lower stratospheric (UTLS) O3 in a chemistry transport model. This dynamic O3-PV function is parametrized based on 21-year ozonesonde records from World Ozone and Ultraviolet Radiation Data Centre (WOUDC) with corresponding PV values from a 21-year Weather Research and Forecasting (WRF) simulation across the northern hemisphere from 1990 to 2010. The result suggests strong spatial and seasonal variations of O3/PV ratios which exhibits large values in the upper layers and in high latitude regions, with highest values in spring and the lowest values in autumn over an annual cycle. The newly-developed O3/PV function was then applied in the Community Multiscale Air Quality (CMAQ) model for an annual simulation of the year 2006. The simulated UTLS O3 agrees much better with observations in both magnitude and seasonality after the implementation of the new function. Considerable impacts on surface O3 model performance were found in the comparison with observations from three observational networks, i.e., EMEP, CASTNET and WDCGG. With the new function, the negative bias in spring is reduced from −20 to −15 % in the reference case to −9 to −1 %, while the positive bias in autumn is increased from 1 to 15 % in the reference case to 5 to 22 %. Therefore, the downward transport of O3 from upper layers has large impacts on surface concentration and needs to be properly represented in regional models.

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