My doctoral research used climate data assimilation to reconstruct past climates.
Data assimilation methods are statistical frameworks that integrate climate model
simulations with observational products and natural climate archives. Synthesizing
these data sources provides a more complete understanding of Earth's climate than a
single source alone. My work used these methods to examine baseline climate dynamics,
in order to better understand future climate change.
More specifically, I specialized in the development and application of
Kalman filter,
particle filter,
and optimal sensor
assimilation techniques.
