scholarly journals Supplementary material to "Multi-year Downscaling Application of Online Coupled WRFCMAQ over East Asia for Regional Climate and Air Quality Modeling: Model Evaluation and Aerosol Direct Effects"

2016 ◽  
Author(s):  
Chaopeng Hong ◽  
Qiang Zhang ◽  
Yang Zhang ◽  
Youhua Tang ◽  
Daniel Tong ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Model Evaluation ◽  
Regional Climate ◽  
Air Quality Modeling ◽  
Direct Effects ◽  
Quality Modeling ◽  
Supplementary Material

scholarly journals Multi-year Downscaling Application of Online Coupled WRFCMAQ over East Asia for Regional Climate and Air Quality Modeling: Model Evaluation and Aerosol Direct Effects

2016 ◽  
Author(s):  
Chaopeng Hong ◽  
Qiang Zhang ◽  
Yang Zhang ◽  
Youhua Tang ◽  
Daniel Tong ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Model Evaluation ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Air Quality Modeling ◽  
Meteorological Variables ◽  
Direct Effects ◽  
Modeling Framework ◽  
Quality Modeling

Abstract. In this study, a regional coupled climate-chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional online coupled Weather Research and Forecasting – Community Multiscale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over East Asia for a multiyear climatological application during 2006–2010 driven with CESM downscaling data under Representative Concentration Pathway 4.5 (RCP 4.5) as well as a short-term air quality application in representative months in 2013 driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the online coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2-m temperature (T2) in this study compared with the Coupled Model Inter-comparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2.5 in winter and O3 in summer in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2.5 concentrations in China, WRF-CMAQ was able to capture the high PM2.5 concentrations in urban areas. In general, the online coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled modeling system with direct aerosol feedbacks predicted aerosol optical depth relatively well and significantly reduced the overprediction in downward shortwave radiation at the surface (SWDOWN) over polluted regions in China. The performance of cloud variables was not as good as other meteorological variables, and underpredictions of cloud fraction resulted in overpredictions of SWDOWN and underpredictions of shortwave and longwave cloud forcing. The importance of climate-chemistry interactions was demonstrated via the impacts of aerosol direct effects on climate and air quality. The aerosol effects on climate and air quality in East Asia were more significant than in other regions because of higher aerosol loadings that resulted from severe regional pollution, which indicates the need for applying online-coupled models over East Asia for regional climate and air quality modeling and to study the important climate-chemistry interactions.

scholarly journals Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects

2017 ◽  
Vol 10 (6) ◽  
pp. 2447-2470 ◽  
Author(s):  
Chaopeng Hong ◽  
Qiang Zhang ◽  
Yang Zhang ◽  
Youhua Tang ◽  
Daniel Tong ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Model Evaluation ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Air Quality Modeling ◽  
Meteorological Variables ◽  
Direct Effects ◽  
Modeling Framework ◽  
Quality Modeling

Abstract. In this study, a regional coupled climate–chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional two-way coupled Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006–2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5), along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2) in this study (with a mean bias of −0.6 °C) compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB) of 6.4 % in 2013) and O3 in summer (with an NMB of 18.2 % in 2013) in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled modeling system with direct aerosol feedbacks predicted aerosol optical depth relatively well and significantly reduced the overprediction in downward shortwave radiation at the surface (SWDOWN) over polluted regions in China. The performance of cloud variables was not as good as other meteorological variables, and underpredictions of cloud fraction resulted in overpredictions of SWDOWN and underpredictions of shortwave and longwave cloud forcing. The importance of climate–chemistry interactions was demonstrated via the impacts of aerosol direct effects on climate and air quality. The aerosol effects on climate and air quality in east Asia (e.g., SWDOWN and T2 decreased by 21.8 W m−2 and 0.45 °C, respectively, and most pollutant concentrations increased by 4.8–9.5 % in January over China's major cities) were more significant than in other regions because of higher aerosol loadings that resulted from severe regional pollution, which indicates the need for applying online-coupled models over east Asia for regional climate and air quality modeling and to study the important climate–chemistry interactions. This work established a baseline for WRF-CMAQ simulations for a future period under the RCP4.5 climate scenario, which will be presented in a future paper.

Regional Air Quality Modeling System (RAQMS) predictions of the tropospheric ozone budget over east Asia

2003 ◽  
Vol 108 (D21) ◽  
Author(s):  
R. B. Pierce ◽  
J. A. Al-Saadi ◽  
T. Schaack ◽  
A. Lenzen ◽  
T. Zapotocny ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Tropospheric Ozone ◽  
Air Quality Modeling ◽  
Quality Modeling ◽  
Regional Air Quality

scholarly journals Air Quality Modeling for of a Strong Dust Event in East Asia in March 2010

2012 ◽  
Vol 12 (4) ◽  
pp. 615-628 ◽  
Author(s):  
Xiao Han ◽  
Cui Ge ◽  
Jinhua Tao ◽  
Meigen Zhang ◽  
Renjian Zhang
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Air Quality Modeling ◽  
Dust Event ◽  
Quality Modeling

scholarly journals Air quality modeling with WRF-Chem v3.5 in East Asia: sensitivity to emissions and evaluation of simulated air quality

2016 ◽  
Vol 9 (3) ◽  
pp. 1201-1218 ◽  
Author(s):  
Min Zhong ◽  
Eri Saikawa ◽  
Yang Liu ◽  
Vaishali Naik ◽  
Larry W. Horowitz ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Model Performance ◽  
Air Quality Modeling ◽  
Performance Criteria ◽  
Air Quality Model ◽  
Quality Model ◽  
Provincial Level ◽  
Mixing Ratios ◽  
Quality Modeling

Abstract. We conducted simulations using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.5 to study air quality in East Asia at a spatial resolution of 20 km  ×  20 km. We find large discrepancies between two existing emissions inventories: the Regional Emission Inventory in ASia version 2 (REAS) and the Emissions Database for Global Atmospheric Research version 4.2 (EDGAR) at the provincial level in China, with maximum differences of up to 500 % for CO emissions, 190 % for NO, and 160 % for primary PM10. Such discrepancies in the magnitude and the spatial distribution of emissions for various species lead to a 40–70 % difference in surface PM10 concentrations, 16–20 % in surface O3 mixing ratios, and over 100 % in SO2 and NO2 mixing ratios in the polluted areas of China. WRF-Chem is sensitive to emissions, with the REAS-based simulation reproducing observed concentrations and mixing ratios better than the EDGAR-based simulation for July 2007. We conduct additional model simulations using REAS emissions for January, April, July, and October of 2007 and evaluate simulations with available ground-level observations. The model results illustrate clear regional variations in the seasonal cycle of surface PM10 and O3 over East Asia. The model meets the air quality model performance criteria for both PM10 (mean fractional bias, MFB ⩽ ±60 %) and O3 (MFB ⩽ ±15 %) at most of the observation sites, although the model underestimates PM10 over northeastern China in January. The model predicts the observed SO2 well at sites in Japan, while it tends to overestimate SO2 in China in July and October. The model underestimates observed NO2 in all 4 months. Our study highlights the importance of constraining emissions at the provincial level for regional air quality modeling over East Asia. Our results suggest that future work should focus on the improvement of provincial-level emissions especially estimating primary PM, SO2, and NOx.

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