Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation

Abstract

An efficient time‐dependent equation for predicting ground surface temperature devised by Bhumralkar (1975) and Blackadar (1976) is tested against a 12‐layer soil model and compared with five other approximate methods in current use. It is found to be generally superior if diurnal forcing is present and very much superior to the use of the insulated surface assumption. An analogous method of predicting ground surface moisture content is presented which allows the surface to become moist quickly during rainfall or to become drier than the bulk soil while evaporation occurs. These improved methods are not of much relevance unless the main influences of a vegetation layer are included. An efficient one‐layer foliage parameterization is therefore developed that extends continuously from the case of no shielding of the ground by vegetation to complete shielding. It includes influences of both ground and foliage albedos and emissivities, net leaf area index, stomatal resistance, retained water on the foliage, and several other considerations. When it is tested against data for wheat measured by Penman and Long (1960), it appears quite adequate despite the many simplifying assumptions. The parameterization predicts that errors of up to a factor of 2 in evapotranspiration can be incurred by ignoring the presence of a vegetation layer.

Modelling the impact of urbanisation on regional climate in the Greater London Area

“…The model version applied here does not consider a direct anthropogenic heat flux from energy consumption. To solve the surface energy budget equation, the force restore method (Tiedke and Geleyn, 1975;Deardroff, 1978) is used. For the calculation of turbulent fluxes, several local and non-local first-order closures are implemented; for this study the Prandtl-Kolmogorov closure which solves a prognostic equation for the subgrid scale turbulent kinetic energy (TKE) and takes into account a local Richardson number and the mixing length has been employed.…”

OSIrIS: a physically based simulation tool to improve training in thermal infrared remote sensing over urban areas at high spatial resolution

“…Several solutions to Eq. 3 have been published: the finite difference method (Ciarlet & Lions 1990;Jakob 1949;Mitchell & Griffiths 1980) and the methods proposed by Bhumralkar (1975) and Deardorff (1978). Heat equation is a second-order equation that requires two boundary conditions: the energy flux balance at surface and the in-depth temperature.…”

Robust simulation of root zone soil moisture with assimilation of surface soil moisture data

“…The evolution of the surface thermal status is based on a "forcing" by the net energy exchange with the atmosphere (i.e., net radiation-sensible heat flux-latent heat flux) and a "restoring" action drawing the surface temperature toward the deep (or average) soil temperature [Bhumralkar, 1975;Blackadar, 1976;Deardorff, 1978 …”