Tropospheric Anthropogenic Aerosols and Climate

Massachusetts Institute Of Technology, Cambridge MA

Investigators

Abstract

This project seeks to quantify the climate responses and feedbacks to the direct and indirect effects of tropospheric anthropogenic aerosols and natural aerosols converted by anthropogenic pollutants. The investigators will continue to develop a size- and mixing-resolving aerosol model interactively coupled with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM), an effort previously supported by NSF. In this study they will: (1) include new anthropogenic aerosol types to better describe the chemical and physical transfer of aerosols across the whole size and mixing spectra; (2) include important chemical conversions of "natural aerosols" of dust and sea salt by anthropogenic pollutants; and (3) fully couple the aerosol model with a chemistry module and a 2-moment cloud microphysics module in the new version of CCSM. The investigators will examine aerosol-caused climate responses and feedbacks, either occurring locally or remotely from regions of high aerosol loading, and reveal the aerosol effects on the hydrologic cycle including cloud, precipitation, surface water and heat budget. Specifically, they will: (1) define aerosol perturbations on major dynamic processes and circulation; (2) search for representative diagnostics (also suitable for other models) to identify such mechanistic alterations by aerosols; (3) examine the key factors of major feedbacks; (4) understand climate responses as functions of aerosol composition and size distributions; and (5) compare climate response to aerosol forcing and that of long-lived greenhouse gases. The model performance will be evaluated using available surface and satellite data, and a Kalman-filter-based inverse modeling tool will be used to optimize the emission inventories particularly of absorbing aerosols. If successful, this project will advance our knowledge of climate feedbacks and responses to aerosol forcing, making important contributions to the next generation of models to predict not only the future climate but also the state of the environment and ecosystems. The results of this project will be useful for climate-related policy decisions, as well as global environment and air quality studies. The project is based on a community model framework and the model developed by this program will be provided to the community. Postdocs and graduate students will be trained in the project.