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Title: Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes: Part I. Comprehensive model evaluation and trend analysis for 2006 and 2011

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at the surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2more » but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM 2.5, and PM 10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less
 [1] ;  [2] ;  [3] ;  [3] ;  [4] ;  [4]
  1. North Carolina State Univ., Raleigh, NC (United States)
  2. North Carolina State Univ., Raleigh, NC (United States); Collaborative Innovation Center for Regional Environmental Quality, Beijing (China)
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  4. Collaborative Innovation Center for Regional Environmental Quality, Beijing (China); Tsinghua Univ., Beijing (China)
Publication Date:
Grant/Contract Number:
AC05-76RL01830; AC02-05CH11231
Accepted Manuscript
Journal Name:
Additional Journal Information:
Journal Volume: 3; Journal Issue: 3; Journal ID: ISSN 2225-1154 CLIMC9
Multidisciplinary Digital Publishing Institute
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
58 GEOSCIENCES; 54 ENVIRONMENTAL SCIENCES; WRF-CAM5; East Asia; coupled climate-chemistry modeling; model evaluation; trend analysis
OSTI Identifier: