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Nonlinearity and multivariate dependencies in land-atmosphere coupling
  • Hsin Hsu,
  • Paul A Dirmeyer
Hsin Hsu
George Mason University

Corresponding Author:[email protected]

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Paul A Dirmeyer
George Mason University
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Abstract

Most studies of land-atmosphere coupling have focused on bivariate linear statistics like correlation. However, more complex dependencies exist, including nonlinear relationships between components of land-atmosphere coupling and the transmutability of relationships between soil moisture and surface heat fluxes under different environmental conditions. In this study, a technique called multivariate mutual information, based on information theory, is used to quantify how surface heat fluxes depend on both surface energy and wetness conditions, i.e. net radiation and soil moisture, across the globe by season using reanalysis data. Such interdependency is then decomposed into linear and nonlinear contributions, which are further decomposed as different components explainable as the unique contribution from individual land surface conditions, redundant contributions shared by both land surface conditions, and the synergistic contribution from the coaction of net radiation and soil moisture. The dependency linearly contributed from soil moisture bears a similar global pattern to previously identified hot spots of coupling. The linear unique contributions of net radiation and soil moisture are mainly nonoverlapping, which suggests two separate regimes are governed by either energy or water limitations. These patterns persist when the nonlinearity is superimposed, thus reinforcing the validity of the land-atmospheric coupling hot spot paradigm and the spatial division of energy-limited as well as water-limited regions. Nevertheless, strong nonlinear relationships are detected, particularly over subtropical regions. Synergistic components are found across the globe, implying widespread multidimensional physical relationships among net radiation, soil moisture, and surface heat fluxes that previously had only been inferred locally.
Feb 2021Published in Water Resources Research volume 57 issue 2. 10.1029/2020WR028179