Interannual Variability of Deep-Layer Hydrologic Memory and Mechanisms of Its Influence on Surface Energy Fluxes

Abstract

Abstract The characteristics of deep-layer terrestrial memory are explored using observed soil moisture data and simulated soil temperature from the Illinois Climate Network stations. Both soil moisture and soil temperature are characterized by exponential decay in amplitude, linear lag in phase, and increasing persistence with depth. Using spectral analysis, four dominant low-frequency modes are identified in the soil moisture variability. These signals have periods of about 12, 17, 34, and 60 months, which correspond to annual cycle, (4/3) ENSO, quasi-biennial (QB) ENSO, and quasi-quadrennial (QQ) ENSO signals, respectively. For deep layers, the interannual modes are dominant over the annual cycle, and vice versa for the near-surface layer. There are inherently two mechanisms by which deep-layer moisture impacts the surface fluxes. First, its temporal variability sets the lower boundary condition for the transfer of moisture and heat fluxes from the surface. Second, this temporal variability influences the uptake of moisture by plant roots, resulting in the variability of the transpiration and, therefore, the entire energy balance. Initial results suggest that this second mechanism may be more predominant.