Research Interests
Earth's climate is an archetypal nonlinear, chaotic system. Continuously responding to external forcing and internal feedbacks, the spectrum of temperature variability that begins for us as short-term weather extends continuously to geologic timescales in a series of power-law scaling regimes. The fluid nature of the atmosphere and oceans leads to similar power-law scaling in space, with isotropic turbulence at scales of centimeters to tens of kilometers giving way to the steeper rotation-constrained spectrum of geostrophic turbulence on planetary scales.
My research aims to understand rare events in the context of this rich spatiotemporal spectrum of climate variability, in which chance events are difficult to distinguish from structural changes in the system such as those due to greenhouse gas emissions. The unique challenges posed by this complexity have driven me to develop techniques to better link observations with theory and models of the climate's internal dynamics. My work is presently focused on developing stochastic methods to better quantify the distribution of temperature and to improve predictions of rare climate extremes such as heat waves and droughts, cold snaps and floods. Some further information on current and past research is provided by the links below.
My research aims to understand rare events in the context of this rich spatiotemporal spectrum of climate variability, in which chance events are difficult to distinguish from structural changes in the system such as those due to greenhouse gas emissions. The unique challenges posed by this complexity have driven me to develop techniques to better link observations with theory and models of the climate's internal dynamics. My work is presently focused on developing stochastic methods to better quantify the distribution of temperature and to improve predictions of rare climate extremes such as heat waves and droughts, cold snaps and floods. Some further information on current and past research is provided by the links below.
- Climate Variability and Extremes – predicting impactful weather events and understanding their changes through time.
- Spatiotemporal Statistics – detecting signals in the presence of random noise and the climate system's pacemakers (the diurnal, annual, and Milankovitch cycles).
- Quality Control and Data Assimilation – recovery, preservation, and interpretation of historical climate observations.
- Atmospheric Moisture Sources and Dynamics – tracking the origins of precipitation and recycling of fresh water by the terrestrial biosphere.