Deciphering Doppler Radar velocity data Though Doppler radars have been around since the mid-twentieth century, scientists are still working to better understand the data they provide. The Swedish Meteorological and Hydrological Institute has made a breakthrough in this field. Climate Change and Environment © PhotoDisc Doppler radar is based on discoveries made by an Austrian scientist, Christian Doppler, in the middle nineteenth century. Also known simply as weather radar, Doppler radar provides information about winds and precipitation. Weather forecasting has benefited greatly from its contribution. Velocities above a certain cut-off point, the Nyquist velocity, must be deduced using special mathematical techniques known as de-aliasing. The Swedish Meteorological and Hydrological Institute (SMHI) has discovered an improved de-aliasing algorithm whereby the radar velocities are mapped onto a torus, a three-dimensional ring. The new technique has several advantages over existing methods. For one, errors associated with multiple folding are avoided. Secondly, the new technique does not require input from other measuring equipment or a forecasting model. The new de-aliasing algorithm can be applied to generate super-observations, conglomerations of different types of data describing the state of the atmosphere. These super-observations are then used in Numerical Weather Prediction (NWP), greatly improving the accuracy of the forecasting models into which they are fed. The theory was put to the test in the Nordic Weather Radar Network (NORDRAD). The technical limitations of the Finnish radars made them a prime candidate for the new de-aliasing algorithm. Data collected with a Doppler radar in Vantaa, Finland during an intense storm in the winter of 1999 was used as a test case scenario. The results were encouraging and additional testing is planned with data from other seasons. The long-term outlook is for operational implementation with the SMHI's HIgh Resolution Limited Area Model (HIRLAM).
