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Title: Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

Current climate models still have large uncertainties 24 in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land-surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature MEGAN (MEGAN v2.1) is coupled within the land surface parameterization CLM4 in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implement, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a standalone vegetation map that differs from what is used by land surface parameterizations. This improved modeling framework is used to investigate the impact of two land surface parameterizations, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted during Junemore » of 2010 provide an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface parameterizations do influence the simulated BVOCs, but that impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover datasets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry, and consequently secondary organic aerosol formation.« less
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Resource Type:
Journal Article
Resource Relation:
Journal Name: Geoscientific Model Development, 9(5):1959-1976
Research Org:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
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Country of Publication:
United States