Retrieval of stratified atmospheric reflectivity and wind velocity using inverse methods: application to a VHF ST mini-radar

Abstract

Abstract The growing interest of measuring wind and turbulence in the lower atmosphere has led to the development of new radar systems. UHF radars, though being an interesting solution from a technical and logistical point of view, have some disadvantages due to their high sensitivity to Rayleigh scattering and interference from precipitations, birds and insects. The standard VHF ST radars were originally designed for high altitude investigations and are consequently not suited for low atmosphere soundings. This context makes it necessary to develop the new concept of a VHF ‘mini-radar’. But the simultaneous use of a small antenna in the VHF band, combined with a beam having a more grazing angle, results in an important mixing of the altitude contributions for each range, a problem which is non existent with previous ST radars. Consequently, the atmospheric reflectivity and wind velocity profiles cannot be directly obtained and have to be treated by other methods. In this context, the aim of the present work consists in the development of an appropriate inverse method. Two different classic methods are considered, the least squares method and the maximum entropy method. The ‘direct problem’ is first addressed, resulting in an integral description of the zeroth and first moments of the Doppler spectra. In order to perform various simulations to test the validity of the two proposed inverse methods in the particular case of the VHF miniradar, a model is built for the radar which includes a set of reference atmospheric profiles. The simulations give evidence for the validity of the inversion processes. The high robustness of the least squares method always leads to significant results. But its over-determined nature results in a poor vertical resolution for the inverted profiles. Consequently this method is not suited to retrieving strong gradients. The maximum entropy method is intrinsically much more appropriate in terms of vertical resolution and consequently leads to valuable results, but its high sensitivity to the data noise requires some additional constraints. The practical efficiency of the methods is tested with real data from the mini-radar, and the resulting retrieved profiles are compared to those obtained simultaneously using a conventional ST radar (the ‘Provence’ radar). As a result of a poor vertical resolution, the least squares method cannot provide a valid retrieval of the atmospheric profiles under real experimental conditions. Nevertheless, a preliminary inversion using the least squares method can be used as a constraint for initializing the maximum entropy inversion process. Although this processing appears to be very efficient for the reflectivity, the retrieved profiles reveal a smoothing effect which seems to be linked to a faulty radar antenna radiation model. In contrast, the retrieval of wind velocity seems to be more difficult and requires additional investigations.