The Fire-Land-Atmosphere Modeling and Evaluation for Southeast Asia (FLAMES) Project
Darla
K
Munroe, Ohio State University, munroe.9@osu.edu
(Presenting)
Catherine
A
Calder, Ohio State University, calder@stat.ohio-state.edu
Tao
Shi, Ohio State University, taoshi@stat.ohio-state.edu
Ningchuan
Xiao, Ohio State University, xiao.37@osu.edu
Scientists and policy makers have become increasingly concerned about the implications of the consistent brown haze covering Southeast Asia and the Indian Ocean in terms of human health and regional climate impacts. The emergence of this haze is due to increased atmospheric concentrations of carbonaceous aerosols, or small airborne particles, over the region. A large portion of these carbonaceous aerosols is generated by anthropogenic activities, including both shifting/swidden agriculture and fossil fuel combustion. This research project seeks to develop methodology to determine the relative contribution of these two types of emissions to the total aerosol burden over the region. We have developed a novel Bayesian hierarchical statistical framework for modeling aerosol optical depth data. This statistical framework draws on the space-time dependence structure of the aerosol transportation process, as estimated from the Model for OZone And Related chemical Tracers (MOZART) aerosol simulator. The process convolution, or moving-average, structure of this model readily accommodates the nonstationary and anisotropic behavior of aerosol transportation. The statistical model is fitted using a Markov chain Monte Carlo (MCMC) algorithm. To integrate spatial data necessary to the model, as well as in the display and visualization of model results, we are developing a web-based application in an AJAX framework to support dynamic querying and displaying of data and model output.
NASA Carbon Cycle & Ecosystems Active Awards Represented by this Poster: