An optimal inverse method using doppler lidar measurements to estimate the surface sensible heat flux

• Main Author: Dunbar, Tyrone
• Published: University of Reading 2011
• Subjects: 621.3678
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558718

There is a growing need for measurements of surface fluxes which are rep- resentative of large, heterogenous surfaces, for example urban areas. This requires an instrument which makes measurements that have a large source area, but the source area of measurements made by traditional, surface- based in situ instruments are generally small compared to the surface area required. A solution to this problem is to use a remote sensing instru- ment, such as a Doppler lidar, which is able to make measurements with a potential source area of the order of 10s of km2. We describe a novel technique, in which measurements of turbulence made by a Doppler lidar in the convectively unstable daytime boundary layer are used with an optimal inverse method to make estimates of surface sensi- ble heat fluxes with a large source area. The optimal inverse method uses forward models which are based upon functions of the vertical velocity vari- ance derived from mixed layer similarity scaling theory. The optimal inverse method also provides a probabilistic error of the estimated heat flux, which incorporates both instrument and sampling errors. Testing of the optimal inverse method upon a simulated convective bound- ary layer generated by an LES provides confidence in the method, and also allows for a critical examination of the similarity functions used in the for- ward models. The optimal inverse method is then applied to a set of lidar data from the Chilbolton observatory, and the estimated heat fluxes are compared to those measured by a sonic anemometer at the same site. The results are correlated, but show a bias in which the heat fluxes estimated by the optimal inverse method are consistently lower than those estimated by the sonic anemometer. Possible reasons for this bias are explored; in partic- ular, the bias is larger in the morning when the lidar measurements appear to show that there is shear turbulence present in the transitional convective layer, rendering the forward models inappropriate. The lidar also measures large spikes of turbulence in the middle of the boundary layer which appear during the afternoon. The reasons for these phenomena are unclear, and further work is required to investigate whether or not they are site specific.