A Boundary Layer Parameterization for a General Model.

Abstract

A two-layer model of soil hydrology is developed from the basic soil moisture transport equations. The thin upper layer responds to short term evaporation. A thick lower layer includes the root zone and longer term water storage. The model is tested against a high-resolution soil hydrology model. Simple transpiration and canopy interception models are also included in the surface water budget. A surface energy balance is employed. Fluxes from the surface to the atmosphere are formulated with a stability-dependent bulk aerodynamic relationship and a stability dependent Penman relationship. The latter is evaluated with the Wangara data set. The model of the atmospheric boundary layer uses a stability-dependent, height dependent eddy diffusivity which provides for countergradient convective transport. Boundary layer growth is modelled with a bulk Richardson number which is generalized to include purely convective boundary layer growth. The model development emphasizes self-consistency and reduction of the number of velocity scales compared to previous models of this type.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1984
Accession Number
ADA144224

Entities

People

  • Hsi-An Pan
  • I. Troen
  • J. Paumier
  • L. Mahrt

Organizations

  • Oregon State University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Atmospheric Sciences
  • Boundary Layer
  • Diurnal Variations
  • Geography
  • Geometry
  • Heat Energy
  • Latent Heat
  • Meteorology
  • Richardson Number
  • Soil Models
  • Specific Heat
  • Surface Properties
  • Turbulence
  • United States
  • Vegetables
  • Weather Forecasting

Fields of Study

  • Environmental science

Readers

  • Agricultural Chemistry/Soil Science
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Plasma Physics / Magnetohydrodynamics

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference