Abstract
Abstract. Here we present the online meteorology and chemistry adjoint and tangent linear model, WRFPLUS-Chem (Weather Research and Forecasting plus chemistry), which incorporates modules to treat boundary layer mixing, emission, aging, dry deposition, and advection of black carbon aerosol. We also develop land surface and surface layer adjoints to account for coupling between radiation and vertical mixing. Model performance is verified against finite difference derivative approximations. A second-order checkpointing scheme is created to reduce computational costs and enable simulations longer than 6 h. The adjoint is coupled to WRFDA-Chem, in order to conduct a sensitivity study of anthropogenic and biomass burning sources throughout California during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. A cost-function weighting scheme was devised to reduce the impact of statistically insignificant residual errors in future inverse modeling studies. Results of the sensitivity study show that, for this domain and time period, anthropogenic emissions are overpredicted, while wildfire emission error signs vary spatially. We consider the diurnal variation in emission sensitivities to determine at what time sources should be scaled up or down. Also, adjoint sensitivities for two choices of land surface model (LSM) indicate that emission inversion results would be sensitive to forward model configuration. The tools described here are the first step in conducting four-dimensional variational data assimilation in a coupled meteorology–chemistry model, which will potentially provide new constraints on aerosol precursor emissions and their distributions. Such analyses will be invaluable to assessments of particulate matter health and climate impacts.
Highlights
Fine particulate matter impacts human health (Schwartz et al, 2007; Krewski et al, 2009) and climate (Myhre et al, 2013)
Atmospheric climate forcing from aerosols is potentially large, and highly uncertain owing to a complex spatial–temporal distribution of concentration, mixing state, and particle size for multiple species, each emitted from varying precursor sources, both anthropogenic and natural (Textor et al, 2006; Schulz et al, 2006)
The color bar has been saturated at ±5 × 10−3, the full range of sensitivities are from −2.3×10−3 to +7.1×10−3 and −4.9×10−3 to +11.3×10−3 for anthropogenic and biomass burning emissions, respectively
Summary
Fine particulate matter impacts human health (Schwartz et al, 2007; Krewski et al, 2009) and climate (Myhre et al, 2013). Depending on the species and quality of records, a nation’s annual aerosol precursor and primary emissions have uncertainties anywhere between 7 % and a factor of 4, with larger variation on seasonal to diurnal scales for particular sectors (Streets et al, 2003; Suutari et al, 2001). Over these shorter timescales, aerosols impact meteorology through the semidirect (Hansen et al, 1997; Koch and Del Genio, 2010) and indirect (Twomey, 1977; Lohmann and Feichter, 2005) cloud effects, which are both dependent on aerosol vertical profiles (e.g., Samset et al, 2013) governed by mixing. NWP-chemistry models account for moisture and temperature perturbations to dynamics due to aerosol microphysics
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
