Errors and uncertainty in radar estimates of precipitation result both from errors in the basic measurement of reflectivity and from attempts to relate this to the precipitation falling at the ground. If radar data are to be used to their full potential, it is essential that effective measures are taken to mitigate these problems. The automatic processing of radar data that forms part of the UK Met. Office's Nimrod system addresses a number of specific sources of error. These include the identification and removal of spurious echoes resulting from anomalous propagation of the radar beam, errors resulting from variations in the vertical profile of reflectivity and radar sensitivity errors. Routine verification of the surface precipitation estimates has been undertaken, largely through comparison with rain gauge observations, over a range of timescales, which has allowed the benefits of the quality control and correction processes to be quantified. Although the improvement derived varies according to the dominant synoptic situation, an average reduction in the root‐mean‐square difference between gauge and radar data of 30% can be achieved. Copyright © 2000 Royal Meteorological Society

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S m YA new method of correcting data from the United Kingdom operationd weather radar network is described. The physically based scheme is designed to produce estimates of instantaneous precipitation rate at the surface by compensating for the effects of the bright band, range and low-level orographic growth. In a preliminary study, the characteristic shape of the vertical profile of reflectivity factor was examined using a climatological dataset derived from rangeheight indication scans recorded by a high-resolution radar. The results were then used to construct an idealized reflectivity factor profile. In the correction procedure, the heights of significant turning points in the profile are diagnosed from relevant meteorological data at each radar pixel. The parametrized profile is weighted by the radar-beam power profile and the surface precipitation rate found by an iterative method in real-time. The scheme has some important advantages over the alternative correction strategies. Detailed quantitative evaluation in typical cases of mainly frontal rainfall over southern England suggested that root-mean-square errors in estimates of instantaneous precipitation rates over 5 km pixels were reduced to less than half compared to the same radar data subject to only a fixed range correction.

The use of precipitation estimates from weather radar for hydrological applications has been limited by the quantitative accuracy, reliability and resolution. The adoption of a more centralised approach to radar data processing, upgrades to telecommunications links and the installation of additional radars in the UK weather radar network have enabled some of these limitations to be addressed. The development of more flexible product generation software, which more fully exploits the resolution of the radar measured reflectivity, now provides for the mapping of precipitation on scales of 1 km and even below, thus approaching the resolution requirements for applications in urban hydrology. This paper describes the methods by which these high-resolution precipitation products are now generated. Illustrations of the products are given and their use in predicting flow using an urban drainage model is demonstrated. Issues affecting data quality, and the advantages and disadvantages of using radar products at high resolution are discussed.

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