Decadal evaluation of regional climate, air quality, and their interactions using WRF/Chem Version 3.6.1

Abstract

Abstract. The Weather Research and Forecasting model with Chemistry (WRF/Chem) v3.6.1 with the Carbon Bond 2005 (CB05) gas-phase mechanism is evaluated for its first decadal application during 2001–2010 using the Representative Concentration Pathway (RCP 8.5) emissions to assess its capability and appropriateness for long-term climatological simulations. The initial and boundary conditions are downscaled from the modified Community Earth System Model/Community Atmosphere Model (CESM/CAM5) v1.2.2. The meteorological initial and boundary conditions are bias-corrected using the National Center for Environmental Protection's Final (FNL) Operational Global Analysis data. Climatological evaluations are carried out for meteorological, chemical, and aerosol-cloud-radiation variables against data from surface networks and satellite retrievals. The model performs very well for the 2 m temperature (T2) for the 10 year period with only a small cold bias of −0.3 °C. Biases in other meteorological variables including relative humidity at 2 m, wind speed at 10 m, and precipitation tend to be site- and season-specific; however, with the exception of T2, consistent annual biases exist for most of the years from 2001 to 2010. Ozone mixing ratios are slightly overpredicted at both urban and rural locations but underpredicted at rural locations. PM2.5 concentrations are slightly overpredicted at rural sites, but slightly underpredicted at urban/suburban sites. In general, the model performs relatively well for chemical and meteorological variables, and not as well for aerosol-cloud-radiation variables. Cloud-aerosol variables including aerosol optical depth, cloud water path, cloud optical thickness, and cloud droplet number concentration are generally underpredicted on average across the continental US. Overpredictions of several cloud variables over eastern US result in underpredictions of radiation variables and overpredictions of shortwave and longwave cloud forcing which are important climate variables. While the current performance is deemed to be acceptable, improvements to the bias-correction method for CESM downscaling and the model parameterizations of cloud dynamics and thermodynamics, as well as aerosol-cloud interactions can potentially improve model performance for long-term climate simulations.

Evaluating the sensitivity of fine particulate matter (PM<sub>2.5</sub>) simulations to chemical mechanism in Delhi

“…Aerosol processes are represented by the Modal Aerosol Dynamics for Europe/ Secondary Organic Aerosol Model (MADE/SORGAM) (Ahmadov et al, 2012) which uses modal aerosol size distribution, and includes an advanced secondary organic aerosol (SOA) treatment based on gas-particle partitioning and gas-phase oxidation in volatility bins. The CB05-MADE/SORGAM mechanism has also been coupled to existing model treatments of various feedback processes such as the aerosol semi-direct effect on photolysis rates of major gases and the aerosol indirect effect on cloud droplet number concentration and resulting impacts on shortwave radiation (Yahya et al, 2016).…”

“…The focus of the model evaluation was mainly to assess whether the model is able to effectively (NME) (the definition of those measures can be found in Yu et al, 2006, andZhang et al, 2006), and index of agreement (IOA) ranging from 0 to 1 (Yahya et al, 2016) with a value of 1 indicating a perfect agreement, is used to evaluate the perforation of different sets of the experiment. For evaluation, the observational data are paired up with the simulated data on an hourly basis for each site, and then observational data and simulated data are averaged out for all sites in Delhi, Haryana, Uttar Pradesh, and Rajasthan.…”