Xiangshang Li
University of Houston
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Publication
Featured researches published by Xiangshang Li.
Atmospheric Chemistry and Physics | 2016
Xiangshang Li; Yunsoo Choi; Beata Czader; Anirban Roy; Hyuncheol Kim; Barry Lefer; Shuai Pan
Accurate meteorological fields are imperative for correct chemical transport modeling. Observation nudging, along with objective analysis, is generally considered a lowcost and effective technique to improve meteorological simulations. However, the meteorological impact of observation nudging on chemistry has not been well characterized. This study involved two simulations to analyze the impact of observation nudging on simulated meteorology and ozone concentrations during the 2013 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Texas campaign period, using the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models. The results showed improved correlations between observed and simulated parameters. For example, the index of agreement (IOA) improved by about 9 % for surface temperature and 6–11 % for surface zonal (U-WIND) and meridional (V-WIND) winds when observation nudging was employed. Analysis of a cold front event indicated that nudging improved the timing of wind transition during the front passage. Observation nudging also reduced the model biases for the planetary boundary layer height predictions. Additionally, the IOA for CMAQ simulated surface ozone improved by 6 % during the simulation period. The high-ozone episode on 25 September was a post-front ozone event in Houston. The small-scale morning wind shifts near the Houston Ship Channel combined with higher aloft ozone early morning likely caused the day’s ozone exceedance. While observation nudging did not recreate the wind shifts on that day and failed to reproduce the observed high ozone, analyses of surface and aircraft data found that observation nudging helped the model yield improved ozone predictions. In a 2 h period during the event, substantially better winds in the sensitivity case noticeably improved the ozone. The average IOA for ozone in the period increased from just over 0.4 to near 0.7. Further work on improving the capability of nudging to reproduce local meteorological events such as stagnations and wind reversals could enhance a chemical transport model’s skill for predicting high-ozone events.
Journal of Geophysical Research | 2013
Beata Czader; Xiangshang Li; Bernhard Rappenglueck
Atmospheric Environment | 2014
G.C. Cuchiara; Xiangshang Li; Jonas C. Carvalho; Bernhard Rappenglück
Atmospheric Environment | 2016
Amir Hossein Souri; Yunsoo Choi; Wonbae Jeon; Xiangshang Li; Shuai Pan; Lijun Diao; David A. Westenbarger
Atmospheric Chemistry and Physics | 2014
Beata Czader; Yunsoo Choi; Xiangshang Li; S. Alvarez; Barry Lefer
Atmospheric Research | 2016
Amir Hossein Souri; Yunsoo Choi; Xiangshang Li; Alexander Kotsakis; Xun Jiang
Atmospheric Environment | 2015
Shuai Pan; Yunsoo Choi; Anirban Roy; Xiangshang Li; Wonbae Jeon; Amir Hossein Souri
Atmospheric Research | 2016
Lijun Diao; Yunsoo Choi; Beata Czader; Xiangshang Li; Shuai Pan; Anirban Roy; Amir Hossein Souri; Mark Estes; Wonbae Jeon
Geoscientific Model Development | 2014
C.-S. M. Wilmot; Bernhard Rappenglück; Xiangshang Li; G.C. Cuchiara
Atmospheric Environment | 2014
Xiangshang Li; Bernhard Rappenglück