Quantifying the complexity in mapping energy inputs and hydrologic state variables into land-surface fluxes

Abstract

This study explores the complexity (or disorder) in mapping energy (Rn) forcing to land surface fluxes of sensible heat (Hs), water vapor (LE), and carbon dioxide (or net ecosystem exchange, NEE) for different soil water states (θ). Specifically, we ask, does the vegetation act to increase or dissipate statistical entropy injected from Rn? We address this question using novel scalar complexity measures applied to a long-term time series record of Rn, θ, Hs, LE, and NEE collected over a uniform pine forest. This analysis is the first to demonstrate that vegetation dissipates scalar flux entropy injected through Rn. We also find that the entropy or disorder in scalar fluxes increases with increasing Rn and that the complexity in mapping Rn to scalar fluxes is reduced with increasing θ.