About the Group
The Atmospheric Modeling Group at the University of Rochester maintains high-performance computing resources dedicated to the development and application of cutting-edge models of atmospheric composition and climate.
Group members develop components for and perform simulations using a variety of global chemistry and climate models, employing both forward and inverse methods. Simulations are compared to satellite and other big data for interpretation and validation. Key tools include the GEOS-Chem global 3-D chemical transport model and the NASA Goddard Institute for Space Studies ModelE coupled chemistry-climate model.
Our research explores the nexus between atmospheric chemistry, climate science, and biogeochemical cycles. We are motivated by the following three major areas:
The World Health Organization recently classified air pollution as the leading cause of preventable death world-wide. Public policies informed by scientific research have greatly improved air quality in developed countries over recent decades. However, additional marginal improvements are increasingly difficult to achieve. Therefore, understanding the role of natural contributions and variability to surface air quality is increasingly relevant. Meanwhile, rapid population and economic growth in developing countries has deteriorated air quality for some of the world's most susceptible populations. Complicating everything is how air quality may change in a warming world. We seek to minimize these uncertainties and inform public health.
Climate change is one of the greatest challenges facing humanity today. Our group focuses on increasing understanding of the physical science basis of climate change. We are particularly interested in understanding how atmospheric chemistry may influence climate change, and how climate change in turn influences atmospheric chemistry. To evaluate our models and inform future prediction, we frequently turn to the past. We examine the interplay of atmospheric chemistry with climate variability in the recent past, as well as across major historical transitions such as the onset and retreat of Ice Ages. We collaborate with the U. Rochester Ice Core Lab and similar external groups to interpret these precious windows into the past.
Big Data Analysis
We live in an era of "Big Data", which presents unique challenges for scientific research. Atmospheric models were key motivators for creation of the first modern computers, and have pushed their limits ever since. In our group, individual model simulations regularly consume and produce Terabytes of data that must be explored and distilled into fundamental understanding. Furthermore, we regularly work with multi-Terabyte records of atmospheric composition from satellites. Our group is interested in identifying new methods, as well as applying existing numerical methods from other fields, to computationally process these data as efficiently as possible.
The University of Rochester Atmospheric Modeling Group may have opportunities available via the Ph.D. programs of the Dept. of Earth and Environmental Sciences or the Dept. of Physics and Astronomy. No previous programming experience is required. Given the highly interdisciplinary nature of group research, students from a wide variety of backgrounds will be considered. Successful applicants will be highly self-motivated and have demonstrated aptitude in prior research experiences.
The University of Rochester is committed to increasing and supporting groups presently underrepresented in STEM careers. Such applicants are especially encouraged to apply, and explore the programs and opportunities available through the David T. Kearns Center.
Further research opportunities may exist for M.S. students in the Goergen Institute for Data Science, and for undergraduate students interested in term-time or summer research.
Prospective students are encouraged to contact Dr. Murray via e-mail at email@example.com with any questions.