Tropical Meteorology
Our team uses climate models, regional models, satellite and in situ observations, and theory to understand the phenomena of the Tropics. Phenomena of interest include the Madden-Julian oscillation, the boreal summer intraseasonal oscillation, easterly waves, El Nino-Southern oscillation, hurricanes, and the interactions among all of these.
Tropical-Extratropical Interactions
We seek to understand how and why tropical precipitation variations influence midlatitude weather, including pressure patterns, atmospheric blocking, atmospheric rivers, and other extreme events. Assessment of how well statistical models and dynamical models are able to predict midlatitude extremes based on the state of the tropical atmosphere is a key focus.
Ocean-Atmosphere Interactions
Interactions between the atmosphere and ocean have important but poorly understood impacts on climate and weather phenomenon in both the tropics and midlatitudes. We are using observations and models to understand the role of ocean coupling to disturbances like the Madden-Julian oscillation, boreal summer intraseasonal oscillation, and the midlatude atmosphere in the region of western boundary currents.
Climate Change
The Earth system will profoundly change in the future due to increased greenhouse gases in the atmosphere. These changes may not only impact North America, but also connections of North America to other parts of the globe. We are interested in how connections between the tropics and extratropics may change, including the implications for extreme events such as atmospheric rivers, droughts, and cold spells.
Diagnosis of Climate Models
The ability to predict future climate changes depends on having climate models that produce a reasonable climate for the correct reasons. However, our current generation of climate models is still characterized by notable biases that result from imperfect parameterization of physical processes. We are particularly interested in diagnosing tropical climate biases, providing model developers information to improve their models.