Drought is a recurring extreme phenomenon in the climate system. Unlike most other natural hazards, droughts are a slowly developed process with timescales of a month or longer, for which our predictability ability is of critical importance toward seamless weather/climate modeling. Drought is also a complex extreme involving not only atmospheric changes but also perturbations to the land and biosphere conditions. Given these two features, drought is expected to bring significant changes in the abundance of both gaseous and aerosol species in the atmosphere, but few studies to date have investigated the nature and extent of such changes. This knowledge gap impedes our ability to predict air quality change in a warming climate that is widely projected to have more intense swings between droughts and floods. To fill this gap toward an improved understanding of drought impact on atmospheric composition, the proposed project will exploit the long-term comprehensive observations to conduct holistic analysis and derive quantitative characterization of the change of atmospheric aerosols and trace gases during the drought, and with that characterization and analysis, develop processed-based observational metrics to evaluate coupled chemistry-climate models. The scientific objectives of the proposed project are to: 1) Characterize the spatial and temporal anomaly of a variety of chemical species measured by the long-term networks associated with contemporary droughts (from the 1990s to the present) in the continental US, including co-variation of the anomalies among different species; 2) Develop observation-based hypotheses and process-level metrics from the synthesis of the multi-species changes associated with droughts; 3) Evaluate coupled chemistry-climate models using the process-level metrics as the benchmark and the observation-based hypothesis as the initial null hypothesis. To achieve the objectives, the proposed project will focus on the processes that can be more directly linked to the existing long-term observations and hence better constrained by these observations. The processes to be investigated include wet deposition, dust emissions, fire emissions, BVOC emissions, and surface radiation, and a three-step approach will be adopted. First, long-term surface observations will be analyzed to characterize the changes between drought and non-drought periods in wet deposition, surface radiation, PM10, PM2.5, O3, isoprene, and different aerosol components. Second, the observation-derived anomalies will be contrasted with modeled anomalies to develop process-level metrics to link with the aforementioned processes. Finally, an integrated comparison and contrast analysis will be conducted with advanced statistical techniques to study the impact of droughts on the analysis of atmospheric composition trend. The working hypothesis is that the abundance and covariation of different atmospheric species can be significantly altered during drought, and hence, analyzing the cross-associations of these anomalies and co-variations with drought characteristics (such as phase and severity) from long-term observations can provide a holistic constraint for process diagnosis and evaluation of chemistry-climate models for drought events. The proposed work is highly relevant to the solicitation that encourages exploration of factors influencing the gradient of the long-term trends of atmospheric composition, as well as patterns, anomalies, and extremes in the long-term trends.