Understanding the Dynamic Land-Atmosphere System: Multiple Equilibrium States and Climate Variability

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Several modeling studies indicate that terrestrial biosphere-atmosphere interactions may give rise to the existence of multiple equilibria in the Earth's climate system. However, diagnosing whether multiple equilibrium states exist in global climate system models and why they exist where they do is extremely challenging; the impact of multiple equilibria on the long-term variability and changes of regional-global climates is not well understood. The research objectives of this project are to two-fold: first, to understand the mechanisms responsible for the existence of multiple biosphere-atmosphere equilibria in certain climate models and over certain regions; second, to understand the natural variability of regional climate systems that do possess multiple equilibrium states.Intellectual merit. Based on a conceptual dynamical model for vegetation-precipitation interactions, the PI develops four hypotheses. These hypotheses will be evaluated using a global circulation model developed by the National Center for Atmospheric Research and models that will be derived from it by changing the quantification of certain properties or changing the parameterization of certain processes within the model. Completion of this work will offer new insights into:1. The existence of multiple equilibrium states in the global biosphere-atmosphere system as simulated by global general circulation models, and 2. An improved understanding of climate variability, climate changes, and their model dependence.Broader impacts. The research will provide a better understanding about how a system with multiple equilibria behaves, which may increase the ability of affected populations to adapt to and mitigate the impact of potential climate transitions between different equilibria. This project provides learning experiences and training for undergraduate and graduate-level students in the field of climate system modeling and climate-vegetation interactions.