scholarly journals Global sensitivity analysis of GEOS-Chem modeled ozone and hydrogen oxides during the INTEX campaigns

2018 ◽  
Vol 18 (4) ◽  
pp. 2443-2460 ◽  
Author(s):  
Kenneth E. Christian ◽  
William H. Brune ◽  
Jingqiu Mao ◽  
Xinrong Ren
Keyword(s):  
Transport Model ◽  
Chemical Transport ◽  
Specific Model ◽  
Atmospheric Composition ◽  
Chemical Transport Model ◽  
Global Sensitivity ◽  
Mixing Ratios ◽  
Making Sense ◽  
Transport Experiment ◽  
Sensitivity Method

Abstract. Making sense of modeled atmospheric composition requires not only comparison to in situ measurements but also knowing and quantifying the sensitivity of the model to its input factors. Using a global sensitivity method involving the simultaneous perturbation of many chemical transport model input factors, we find the model uncertainty for ozone (O3), hydroxyl radical (OH), and hydroperoxyl radical (HO2) mixing ratios, and apportion this uncertainty to specific model inputs for the DC-8 flight tracks corresponding to the NASA Intercontinental Chemical Transport Experiment (INTEX) campaigns of 2004 and 2006. In general, when uncertainties in modeled and measured quantities are accounted for, we find agreement between modeled and measured oxidant mixing ratios with the exception of ozone during the Houston flights of the INTEX-B campaign and HO2 for the flights over the northernmost Pacific Ocean during INTEX-B. For ozone and OH, modeled mixing ratios were most sensitive to a bevy of emissions, notably lightning NOx, various surface NOx sources, and isoprene. HO2 mixing ratios were most sensitive to CO and isoprene emissions as well as the aerosol uptake of HO2. With ozone and OH being generally overpredicted by the model, we find better agreement between modeled and measured vertical profiles when reducing NOx emissions from surface as well as lightning sources.

scholarly journals Global sensitivity analysis of GEOS-Chem modeled ozone and hydrogen oxides during the INTEX campaigns

2017 ◽  
Author(s):  
Kenneth E. Christian ◽  
William H. Brune ◽  
Jingqiu Mao ◽  
Xinrong Ren
Keyword(s):  
Transport Model ◽  
Specific Model ◽  
Atmospheric Composition ◽  
Chemical Transport Model ◽  
Global Sensitivity ◽  
Mixing Ratios ◽  
Making Sense ◽  
Sensitivity Method ◽  
Lightning Nox

Abstract. Making sense of modeled atmospheric composition requires not just comparison to in situ measurements, but also knowing and quantifying the sensitivity of the model to its input factors. Using a global sensitivity method involving the simultaneous perturbation of many chemical transport model input factors, we find the model uncertainty for ozone (O3), hydroxyl radical (OH), and hydroperoxyl radical (HO2) mixing ratios and apportion this uncertainty to specific model inputs for the DC-8 flight tracks corresponding to the NASA INTEX campaigns of 2004 and 2006. In general, when uncertainties in modeled and measured quantities are accounted for, we find agreement between modeled and measured oxidant mixing ratios with the exception of ozone during the Houston flights of the INTEX-B campaign and HO2 for the flights over the northernmost Pacific Ocean during INTEX-B. For ozone and OH, modeled mixing ratios were most sensitive to a bevy of emissions, notably lightning NOx, various surface NOx sources, and isoprene. HO2 mixing ratios were most sensitive to CO and isoprene emissions as well as the aerosol uptake of HO2. With ozone and OH being generally over predicted by the model, we find better agreement between modeled and measured vertical profiles when reducing NOx emissions from surface as well as lightning sources.

scholarly journals Global sensitivity analysis of the GEOS-Chem chemical transport model: Ozone and hydrogen oxides during ARCTAS (2008)

2016 ◽  
Author(s):  
Kenneth E. Christian ◽  
William H. Brune ◽  
Jingqiu Mao
Keyword(s):  
Aerosol Particle ◽  
Transport Model ◽  
Chemical Transport ◽  
Sensitivity Analyses ◽  
Chemical Transport Model ◽  
Global Sensitivity ◽  
Particle Uptake ◽  
Mixing Ratios ◽  
The North ◽  
Input Variables

Abstract. Developing predictive capability for future atmospheric oxidation capability requires a detailed analysis of model uncertainties and sensitivity of the modeled oxidation capacity to model input variables. Using oxidant mixing ratios modeled by the GEOS-Chem chemical transport model and measured on the NASA DC8 aircraft, uncertainty and global sensitivity analyses were performed on the GEOS-Chem chemical transport model for the modeled oxidants hydroxyl (OH), hydroperoxyl (HO2), and ozone (O3). The sensitivity of modeled OH, HO2, and ozone to modeled inputs perturbed simultaneously within their respective uncertainties were found for the period of NASA's Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) A &amp; B campaigns (2008) in the North American Arctic. For the spring deployment (ARCTAS-A), ozone is most sensitive to the photolysis rate of NO2, the NO2 + OH reaction rate, and various emissions, including methyl bromoform (CHBr3). OH and HO2 were overwhelmingly sensitive to aerosol particle uptake of HO2 with this one factor contributing upwards of 75 % of the uncertainty in HO2. For the summer deployment (ARCTAS-B), ozone was most sensitive to emissions factors, such as soil NOx and isoprene. OH and HO2 were most sensitive to biomass emissions and aerosol particle uptake of HO2. With modeled HO2 showing a factor of 2 underestimation compared to measurements in the lowest 2 kilometers of the troposphere, lower uptake rates (γHO2 < 0.04), regardless of whether or not the product of the uptake is H2O or H2O2, produced better agreement between modeled and measured HO2.

scholarly journals Global sensitivity analysis of the GEOS-Chem chemical transport model: ozone and hydrogen oxides during ARCTAS (2008)

2017 ◽  
Vol 17 (5) ◽  
pp. 3769-3784 ◽  
Author(s):  
Kenneth E. Christian ◽  
William H. Brune ◽  
Jingqiu Mao
Keyword(s):  
Aerosol Particle ◽  
Transport Model ◽  
Chemical Transport ◽  
Sensitivity Analyses ◽  
Chemical Transport Model ◽  
Oxidation Capacity ◽  
Global Sensitivity ◽  
Particle Uptake ◽  
Mixing Ratios ◽  
The North

Abstract. Developing predictive capability for future atmospheric oxidation capacity requires a detailed analysis of model uncertainties and sensitivity of the modeled oxidation capacity to model input variables. Using oxidant mixing ratios modeled by the GEOS-Chem chemical transport model and measured on the NASA DC-8 aircraft, uncertainty and global sensitivity analyses were performed on the GEOS-Chem chemical transport model for the modeled oxidants hydroxyl (OH), hydroperoxyl (HO2), and ozone (O3). The sensitivity of modeled OH, HO2, and ozone to model inputs perturbed simultaneously within their respective uncertainties were found for the flight tracks of NASA's Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) A and B campaigns (2008) in the North American Arctic. For the spring deployment (ARCTAS-A), ozone was most sensitive to the photolysis rate of NO2, the NO2 + OH reaction rate, and various emissions, including methyl bromoform (CHBr3). OH and HO2 were overwhelmingly sensitive to aerosol particle uptake of HO2 with this one factor contributing upwards of 75 % of the uncertainty in HO2. For the summer deployment (ARCTAS-B), ozone was most sensitive to emission factors, such as soil NOx and isoprene. OH and HO2 were most sensitive to biomass emissions and aerosol particle uptake of HO2. With modeled HO2 showing a factor of 2 underestimation compared to measurements in the lowest 2 km of the troposphere, lower uptake rates (γHO2 < 0. 055), regardless of whether or not the product of the uptake is H2O or H2O2, produced better agreement between modeled and measured HO2.

scholarly journals An evaluation of global organic aerosol schemes using airborne observations

2020 ◽  
Vol 20 (5) ◽  
pp. 2637-2665 ◽  
Author(s):  
Sidhant J. Pai ◽  
Colette L. Heald ◽  
Jeffrey R. Pierce ◽  
Salvatore C. Farina ◽  
Eloise A. Marais ◽  
...  
Keyword(s):  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Basis Set ◽  
Atmospheric Composition ◽  
Model Bias ◽  
Chemical Transport Model ◽  
Uptake Mechanism ◽  
Simple Scheme ◽  
Complex Scheme

Abstract. Chemical transport models have historically struggled to accurately simulate the magnitude and variability of observed organic aerosol (OA), with previous studies demonstrating that models significantly underestimate observed concentrations in the troposphere. In this study, we explore two different model OA schemes within the standard GEOS-Chem chemical transport model and evaluate the simulations against a suite of 15 globally distributed airborne campaigns from 2008 to 2017, primarily in the spring and summer seasons. These include the ATom, KORUS-AQ, GoAmazon, FRAPPE, SEAC4RS, SENEX, DC3, CalNex, OP3, EUCAARI, ARCTAS and ARCPAC campaigns and provide broad coverage over a diverse set of atmospheric composition regimes – anthropogenic, biogenic, pyrogenic and remote. The schemes include significant differences in their treatment of the primary and secondary components of OA – a “simple scheme” that models primary OA (POA) as non-volatile and takes a fixed-yield approach to secondary OA (SOA) formation and a “complex scheme” that simulates POA as semi-volatile and uses a more sophisticated volatility basis set approach for non-isoprene SOA, with an explicit aqueous uptake mechanism to model isoprene SOA. Despite these substantial differences, both the simple and complex schemes perform comparably across the aggregate dataset in their ability to capture the observed variability (with an R2 of 0.41 and 0.44, respectively). The simple scheme displays greater skill in minimizing the overall model bias (with a normalized mean bias of 0.04 compared to 0.30 for the complex scheme). Across both schemes, the model skill in reproducing observed OA is superior to previous model evaluations and approaches the fidelity of the sulfate simulation within the GEOS-Chem model. However, there are significant differences in model performance across different chemical source regimes, classified here into seven categories. Higher-resolution nested regional simulations indicate that model resolution is an important factor in capturing variability in highly localized campaigns, while also demonstrating the importance of well-constrained emissions inventories and local meteorology, particularly over Asia. Our analysis suggests that a semi-volatile treatment of POA is superior to a non-volatile treatment. It is also likely that the complex scheme parameterization overestimates biogenic SOA at the global scale. While this study identifies factors within the SOA schemes that likely contribute to OA model bias (such as a strong dependency of the bias in the complex scheme on relative humidity and sulfate concentrations), comparisons with the skill of the sulfate aerosol scheme in GEOS-Chem indicate the importance of other drivers of bias, such as emissions, transport and deposition, that are exogenous to the OA chemical scheme.

scholarly journals Observing atmospheric formaldehyde (HCHO) from space: validation and intercomparison of six retrievals from four satellites (OMI, GOME2A, GOME2B, OMPS) with SEAC<sup>4</sup>RS aircraft observations over the southeast US

2016 ◽  
Vol 16 (21) ◽  
pp. 13477-13490 ◽  
Author(s):  
Lei Zhu ◽  
Daniel J. Jacob ◽  
Patrick S. Kim ◽  
Jenny A. Fisher ◽  
Karen Yu ◽  
...  
Keyword(s):  
Transport Model ◽  
Chemical Transport ◽  
Atmospheric Composition ◽  
Research Groups ◽  
Chemical Transport Model ◽  
Aircraft Observations ◽  
Volatile Organic ◽  
Mass Factor ◽  
The Mean ◽  
Southeast Us

Abstract. Formaldehyde (HCHO) column data from satellites are widely used as a proxy for emissions of volatile organic compounds (VOCs), but validation of the data has been extremely limited. Here we use highly accurate HCHO aircraft observations from the NASA SEAC4RS (Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) campaign over the southeast US in August–September 2013 to validate and intercompare six retrievals of HCHO columns from four different satellite instruments (OMI, GOME2A, GOME2B and OMPS; for clarification of these and other abbreviations used in the paper, please refer to Appendix A) and three different research groups. The GEOS-Chem chemical transport model is used as a common intercomparison platform. All retrievals feature a HCHO maximum over Arkansas and Louisiana, consistent with the aircraft observations and reflecting high emissions of biogenic isoprene. The retrievals are also interconsistent in their spatial variability over the southeast US (r  =  0.4–0.8 on a 0.5°  ×  0.5°  grid) and in their day-to-day variability (r  =  0.5–0.8). However, all retrievals are biased low in the mean by 20–51 %, which would lead to corresponding bias in estimates of isoprene emissions from the satellite data. The smallest bias is for OMI-BIRA, which has high corrected slant columns relative to the other retrievals and low scattering weights in its air mass factor (AMF) calculation. OMI-BIRA has systematic error in its assumed vertical HCHO shape profiles for the AMF calculation, and correcting this would eliminate its bias relative to the SEAC4RS data. Our results support the use of satellite HCHO data as a quantitative proxy for isoprene emission after correction of the low mean bias. There is no evident pattern in the bias, suggesting that a uniform correction factor may be applied to the data until better understanding is achieved.

scholarly journals An evaluation of global organic aerosol schemes using airborne observations

2019 ◽  
Author(s):  
Sidhant J. Pai ◽  
Colette L. Heald ◽  
Jeffrey R. Pierce ◽  
Salvatore C. Farina ◽  
Eloise A. Marais ◽  
...  
Keyword(s):  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Basis Set ◽  
Atmospheric Composition ◽  
Model Bias ◽  
Chemical Transport Model ◽  
Uptake Mechanism ◽  
Simple Scheme ◽  
Complex Scheme

Abstract. Chemical transport models have historically struggled to accurately simulate the magnitude and variability of observed organic aerosol (OA), with previous studies demonstrating that models significantly underestimate observed concentrations in the troposphere. In this study, we explore two different model OA schemes within the standard GEOS-Chem chemical transport model and evaluate the simulations against a suite of 15 globally-distributed airborne campaigns from 2008–2017. These include the ATom, KORUS-AQ, GoAmazon, FRAPPE, SEAC4RS, SENEX, DC3, CalNex, OP3, EUCAARI, ARCTAS and ARCPAC campaigns and provide broad coverage over a diverse set of atmospheric-composition regimes – anthropogenic, biogenic, pyrogenic and remote. The schemes include significant differences in their treatment of the primary and secondary components of OA – a simple scheme that models primary OA (POA) as non-volatile and takes a fixed-yield approach to secondary OA (SOA) formation, and a complex scheme that simulates POA as semi-volatile and uses a more sophisticated volatility basis set approach for non-isoprene SOA, with an explicit aqueous uptake mechanism to model isoprene SOA. Despite these substantial differences, both the simple and complex schemes perform comparably across the aggregate dataset in their ability to capture the observed variability (with an R2 of 0.41 and 0.44 respectively). The simple scheme displays greater skill in minimizing the overall model-bias (with a NMB of 0.04, compared to 0.29 for the complex scheme). Across both schemes, the model skill in reproducing observed OA is superior to previous model evaluations and approaches the fidelity of the sulfate simulation within GEOS-Chem. However, there are significant differences in model performance across different chemical source regimes, classified here into 7 categories. Higher-resolution nested regional simulations indicate that model resolution is an important factor in capturing variability in highly-localized campaigns, while also demonstrating the importance of well-constrained emissions inventories and local meteorology, particularly over Asia. A comparison of the POA loadings from the complex scheme with SOA loadings from the simple scheme (and vice versa) also suggests that a semi-volatile treatment of POA is superior to a non-volatile treatment. While this study identifies factors within the SOA schemes that likely contribute to OA model bias (such as a strong dependency of the bias in the complex scheme on relative humidity and sulfate concentrations), comparisons with the skill of the sulfate aerosol scheme in GEOS-Chem indicate the importance of other drivers of bias such as emissions, transport, and deposition that are exogenous to the OA chemical scheme.

scholarly journals Comparison between the assimilation of IASI Level 2 ozone retrievals and Level 1 radiances in a chemical transport model

2019 ◽  
Vol 12 (7) ◽  
pp. 3963-3984
Author(s):  
Emanuele Emili ◽  
Brice Barret ◽  
Eric Le Flochmoën ◽  
Daniel Cariolle
Keyword(s):  
Radiative Transfer ◽  
Prior Information ◽  
Transport Model ◽  
Chemical Transport ◽  
Atmospheric Composition ◽  
Chemical Transport Model ◽  
Level 1 ◽  
L1 And L2 ◽  
The Impact ◽  
Level 2

Abstract. The prior information used for Level 2 (L2) retrievals in the thermal infrared can influence the quality of the retrievals themselves and, therefore, their further assimilation in atmospheric composition models. In this study we evaluate the differences between assimilating L2 ozone profiles and Level 1 (L1) radiances from the Infrared Atmospheric Sounding Interferometer (IASI). We minimized potential differences between the two approaches by employing the same radiative transfer code (Radiative Transfer for TOVS, RTTOV) and a very similar setup for both the L2 retrievals (1D-Var) and the L1 assimilation (3D-Var). We computed hourly 3D-Var analyses assimilating L1 and L2 data in the chemical transport model MOCAGE and compared the resulting O3 fields among each other and against ozonesondes. We also evaluated the joint assimilation of limb measurements from the Microwave Limb Sounder (MLS) in combination with IASI to assess the impact of stratospheric O3 on tropospheric analyses. Results indicate that significant differences can arise between L2 and L1 assimilation, especially in regions where the L2 prior information is strongly biased (at low latitudes in this study). In these regions the L1 assimilation provides a better variability of the free-troposphere ozone column. L1 and L2 assimilation instead give very similar results at high latitudes, especially when MLS measurements are used to constrain the stratospheric O3 column. A critical analysis of the potential benefits and drawbacks of L1 assimilation is given in the conclusions. We also list remaining issues that are common to both the L1 and L2 approaches and that deserve further research.

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