The impact of local orography on the treatment of radiative transfer within a road surface temperature model

The Impact of Local Orography on the Treatment of Radiative Transfer within a Road Surface Temperature Model.

W.P.Hopwood.

United Kingdom Meteorological Office. London Road, Bracknell. RG12 2SZ. United Kingdom.

The U.K. Meteorological Office (UKMO) has, for nearly a decade, provided operational short range forecasts via a Mesoscale model for aggregated areas/grid-boxes of the order of 12km x 12km. Data from this model has been used to drive a Road Surface Temperature Model (RST) to provide advice to road maintainence engineers as part of their anti-icing policies. It has been accepted that the Mesoscale model resolution is still too coarse to accurately forecast conditions that are dominated by strong local forcing e.g. overnight fog or frost, and the projected future increases in computer power suggest it will be a decade before truly site-specific forecasts will be achievable from 3D models. Therefore a high vertical resolution local or site-specific 1D model that could capture the flow features unique to a particular location situated anywhere within a Mesoscale grid-box was developed. This site-specific model contains the same physical parametrizations as the UKMO Unified Model with improvements to the treatment of the surface exchange and soil. The large-scale flow and forcing are defined by coupling to the operational Mesoscale model, yet its local flow and forcing is provided by interaction with the surface characteristics (heterogeneity) found within the upwind fetch of the chosen site. Data from this site-specific model has then be used to drive the RST. A first version of the model has been running since October 1996 and these changes have already provided a significant improvement in site-specific forecast skill over the Mesoscale model.

Although the site-specific model describes the impact of local orography on the flow profile it does not simulate the impact of physical presence of local orography on the site-specific radiation budget, i.e. local shading, and hence on the data used to drive the RST model. In addition the radiation budget in the RST model does not include this impact. This paper will describe the sensitivity of RST model simulations to errors in driving data and in the RST model's radiation budget due to local shading. Objective assessment of the predictive impact of accounting for local shading will also be presented via results from a 3 month verification trial that took place in the winter of 1998 at 2 nearby sites, one in a valley and one on a ridge.