Aerosol predictions and their links to weather forecasts through online interactive atmospheric modeling and data assimilation Pablo Enrique Saide Peralta , University of Iowa Follow http://www.lib.uiowa.edu/sc/contact/

[摘要] Atmospheric particles represent a component of air pollution that has been identified as a major contributor to adverse health effects and mortality. Aerosols also interact with solar radiation and clouds perturbing the atmosphere and generating responses in a wide range of scales, such as changes to severe weather and climate. Thus, being able to accurately predict aerosols and its effects on atmospheric properties is of upmost importance. This thesis presents a collection of studies with the global objective to advance in science and operations the use of WRF-Chem, a regional model able to provide weather and atmospheric chemistry predictions and simultaneously representing aerosol effects on climate. Different strategies are used to obtain accurate predictions, including finding an adequate model configuration for each application (e.g., grid resolution, parameterizations choices, processes modeled), using accurate forcing elements (e.g., weather and chemical boundary conditions, emissions), and developing and applying data assimilation techniques for different observational sources. Several environments and scales are simulated, including complex terrain at a city scale, meso-scale over the southeast US for severe weather applications, and regional simulations over the three subtropical persistent stratocumulus decks (off shore California and southeast Pacific and Atlantic) and over North America. Model performance is evaluated against a large spectrum of observations, including field experiments and ground based and satellite measurements. Overall, very positive results were obtained with the WRF-Chem system once it had been configured properly and the inputs chosen. Also, data assimilation of aerosol and cloud satellite observations contributed to improve model performance even further. The model is proven to be an excellent tool for forecasting applications, both for local and long range transported pollution. Also, advances are made to better understand aerosol effects on climate and its uncertainties. Aerosols are found to generate important perturbations, ranging from changes in cloud properties over extensive regions, up to playing a role in increasing the likelihood of tornado occurrence and intensity. Future directions are outline to keep advancing in better predictions of aerosols and its feedbacks.