2018
DOI: 10.5194/gmd-11-305-2018
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Errors and improvements in the use of archived meteorological data for chemical transport modeling: an analysis using GEOS-Chem v11-01 driven by GEOS-5 meteorology

Abstract: Abstract. Global simulations of atmospheric chemistry are commonly conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it incurs errors due to temporal averaging in the meteorological archive and the inability to reproduce the GCM transport algorithms exactly. The CTM simulation is also often conducted at coarser grid resolution than the parent GCM. Here… Show more

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Cited by 65 publications
(88 citation statements)
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References 49 publications
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“…However, Pai et al (2019) indicate that GEOS-Chem does not generally underestimate OA in the upper troposphere, although their comparisons with data are limited to below 10 km. The study by Yu et al (2018) indicates that intensification of simulated convection in the Asian monsoon region would raise aerosol concentrations (and SR values) in the simulated ATAL, similar to that achieved in limiting SO 2 scavenging (ModSim). Assuming lower lidar ratios to convert modeled extinction coefficient to SR does not solve the problem; the peak in simulated SR is intensified, but the vertical distribution (i.e., the shape) remains unaffected.…”
Section: 1029/2019jd031506mentioning
confidence: 71%
See 1 more Smart Citation
“…However, Pai et al (2019) indicate that GEOS-Chem does not generally underestimate OA in the upper troposphere, although their comparisons with data are limited to below 10 km. The study by Yu et al (2018) indicates that intensification of simulated convection in the Asian monsoon region would raise aerosol concentrations (and SR values) in the simulated ATAL, similar to that achieved in limiting SO 2 scavenging (ModSim). Assuming lower lidar ratios to convert modeled extinction coefficient to SR does not solve the problem; the peak in simulated SR is intensified, but the vertical distribution (i.e., the shape) remains unaffected.…”
Section: 1029/2019jd031506mentioning
confidence: 71%
“…Yu et al () demonstrated that remapping of meteorological data from the native cubed‐sphere grid of the parent GCM (GEOS‐5) to an equivalent‐resolution latitude‐longitude grid, and 3‐hr‐averaging of the fields, led to vertical transport errors of 20% in offline CTM (GEOS‐Chem) simulations of a surface‐source tracer, 222 Rn, compared to online 222 Rn simulations (their Figure 2). Yu et al () attributed this error, in part, to a loss of transient organized vertical motions. Further degradation of the spatial resolution of the meteorological data to 2° × 2.5° (as used in our study) led to 222 Rn concentrations biased 40% low in the upper troposphere, relative to online 222 Rn simulations (their Figure 3), due to further weakening of vertical transport via spatial averaging.…”
Section: Sensitivity To Wet Scavenging Efficiency Of So2mentioning
confidence: 99%
“…A comparison of modeled versus observed PBL:FT VOC concentration ratios over the southeastern US suggests that inadequate PBL ventilation in the model may play a role in driving the observed FT biases. Recent work has sought to improve CTM transport performance through improved spatial resolution (e.g., (Zhuang et al, 2018;Yu et al, 2016)), through use of a cubed-sphere rather than regular Cartesian grid (e.g., (Eastham et al, 2018;Yu et al, 2018)), and by integration into Atmos. Chem.…”
Section: Discussionmentioning
confidence: 99%
“…GEOS-Chem mercury simulations using this meteorological data have been extensively compared to wet deposition and concentration measurements over the region of interest. 8,57,58 Yu et al 63 have recently reported that the use of offline meteorological archives to drive chemical transport simulations such as GEOS-Chem may lead to vertical transport errors that bias surface concentrations of chemical tracers high, and upper troposphere concentrations low. Consequently, these simulations may underestimate the extent of global mercury transport and its contribution to Great Lakes mercury deposition.…”
Section: Meteorologymentioning
confidence: 99%