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A sensitivity theory for the equilibrium boundary layer over land

T. Cronin

Published 2013 in Journal of Advances in Modeling Earth Systems

ABSTRACT

Due to the intrinsic complexities associated with modeling land‐atmosphere interactions, global models typically use elaborate land surface and boundary layer physics parameterizations. Unfortunately, it is difficult to use elaborate models, by themselves, to develop a deeper understanding of how land surface parameters affect the coupled land‐atmosphere system. At the same time, it is also increasingly important to gain a deeper understanding of the role of changes in land cover, land use, and ecosystem function as forcings and feedbacks in past and future climate change. To improve the foundation of our understanding, we outline a framework for boundary layer climate sensitivity based on surface energy balance; just as global climate sensitivity is based on top‐of‐atmosphere energy balance. We develop an analytic theory for the boundary layer climate sensitivity of an idealized model of a diurnally averaged well‐mixed boundary layer over land. This analytic sensitivity theory identifies changes in the properties of the land surface—including moisture availability, albedo, and aerodynamic roughness—as forcings, and identifies strong negative feedbacks associated with the surface fluxes of latent and sensible heat. We show that our theory can explain nearly all of the sensitivity of the Betts (2000) full system of equations. Favorable comparison of the theory and the simulation results from a two‐column radiative convective model suggests that the theory may be broadly useful for unifying our understanding of how changes in land use or ecosystem function may affect climate change.

PUBLICATION RECORD

  • Publication year

    2013

  • Venue

    Journal of Advances in Modeling Earth Systems

  • Publication date

    2013-12-01

  • Fields of study

    Geology, Physics, Environmental Science

  • Identifiers
    DOI 10.1002/jame.20048
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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