Solar Flux Initialization Schemes for Distributed Surface Energy Budget Modeling

Abstract

Abstract : It is a well-established fact that the state of the ground is driven in a large part by the downwelling solar and IR fluxes. Models developed to predict the state of the ground depend critically on these fluxes for initialization. When measured solar and infrared fluxes are not available they must be computed. We have compared the ground temperatures as computed by the thermal model SWOETHERM using different solar flux initialization schemes. These initialization schemes used measured solar flux values obtained during the Smart Weapons Operability Enhancement (SWOE) field programs, and calculated solar flux values from a semi-empirical model (Shapiro's model). a plane parallel model (MODTRAN), and ARL's AIM (Atmospheric Illumination Module) model. We investigated the response of the surface temperature to different solar flux initialization schemes while all other environmental parameters were held constant. We found that for clear skies all schemes resulted in nearly identical surface temperatures. For partly cloudy and cloudy skies only the AIM model can mimic the spatial variability observed with the measured solar fluxes. The Cloud Scene Simulation Model (CSSM) was used to determine the spatial variability of the clouds. The cloud distributions were then used by AIM to produce the variations of the surface solar loading. CSSM also has the capability to produce the temporal variations in the cloud fields for short periods of time. Thus, it would be possible to use CSSM and AIM to produce the temporal and spatial variations in the solar loading. Models like AIM frequently incur a large computational burden. In order to reduce the computational burden associated with AIM we have implemented several new procedures. Distributed energy budget models used to predict the state of the ground require distributed environmental parameters for initialization.