My main research goal is to understand the spatial and temporal structure of climate feedback processes, how this structure will determine future climate change, and how it can be constrained from historical patterns of both anthropogenic change
and natural variability. This goal entails a complex series of problems that require a structured, hierarchical approach. I favor a research philosophy of building conceptual analytical models, testing them in large, complex numerical simulations,
and developing the statistical tools required to constrain the relevant physics in observational records and palaeoclimate proxies.
- Climate Sensitivity is arguably the single most used metric of the earth's response to anthropogenic greenhouse gases. I try to understand how spatial patterns of warming interact with radiative feedbacks to set both
the time-evolution and equilibrium value of climate sensitivity.
- Natural variability is often treated as a nuisance in attempts to identify anthropogenic components of climate change. However, the structure of internal variability encodes a wealth of information about the underlying physical processes.
I am particularly interested in the scale-dependence of the dominant radiative and air-sea feedback and forcing terms.
- Palaeoclimate archives offer a unique opportunity to stress-test our theories about how the climate operates under markedly different conditions than the present. I am particularly interested in the interplay between internal variability
and orbital forcing of past climates, and the coupling of sea level, volcanism, and the carbon cycle.
- I use General Circulation Models (GCMs) to test theoretical and statistical models under idealized "perfect information" scenarios. Given my interest in conceptual models and natural variability, I have an affinity for model hierarchies,
model ensembles, and idealized simulations.
- I often examine the Dynamics of the Climate System by treating Climate as a Dynamical System. Ideas from the control theory of dynamical systems make appearances.
- Working on the physics of natural variability means I deal with stochastic dynamics, which I examine by extensively using spectral analysis.
- The problems I approach typically involve several sources of evidence - such as data, proxies, and model output, and several layers of uncertainty - due to natural variability, observational error, and model error. Such problems are often best
approached in Bayesian frameworks.