Professor and Chair, Department of Atmospheric, Oceanic, and Earth Sciences
The Earth is a complex system with a wide range of physical and biological processes that drive a rich spectrum of variability. We experience that variability as the day-to-day changes in weather, the march of the seasons, the differences in climate from year to year and the trend in weather statistics that we have observed in the recent past. My research is intended to develop the highest fidelity models of the Earth system in order to test hypotheses about how predictable weather and climate may be, what processes contribute to that predictability, and how human influences or natural processes may change the statistics of weather over time.
■ NSF 1338427 / NOAA NA14OAR4310160 / NASA NNX14AM19G: predictability of climate from days to decades
■ NOAA NA18NWS4680045: improving subseasonal prediction by using a convection-allowing global coupled model
■ Innovim 18-GMU-01: attributes of predicting western U.S. hydrological response to tropical forcing during the winters of 2015-2016 and 2016-2017
■ ONR N00014-17-1-2136: an integration and evaluation framework for ESPC coupled models
■ Manganello, J., et al. (2018, April). Assessment of climatology and predictability of US Mid-Atlantic tropical cyclone landfalls in high-atmospheric-resolution seasonal prediction system. In EGU General Assembly Conference Abstracts (Vol. 20, p. 3957).
■ Kumar, S., et al. (2016). Twentieth century temperature trends in CMIP3, CMIP5, and CESM‐LE climate simulations: spatial‐temporal uncertainties, differences, and their potential sources. Journal of Geophysical Research: Atmospheres, 121(16), 9561-9575.