Precipitation is a crucial part of the hydrological cycle and it plays an important role in water management activities. There is an increasing demand from the practitioners to use weather radar data to obtain precipitation information when traditional rain-gauge networks fail to provide the required data resolution in time and space. Although there have been a multitude of publications in the field of weather radar technology in the past decades, these are mainly published in some very specialised journals with a focus to serve the academic hydrologists and meteorologists, not practicing water engineers. The aim of this special issue of Water Management is to provide the information on the latest advances in weather radar technology, which is relevant to practicing water engineers. Ten peer reviewed papers have been selected from the submissions and they represent a good variation about weather radars and their applications.
Radar data quality has attracted the attention from both data providers and data users. This is especially important for real time applications. Collier's paper highlights that ‘The unpredictable nature of radar errors continues to discourage many operational hydrologists from using radar data quantitatively as input to models.1 The tendency has been to wait for all errors to be removed. Unfortunately it is unlikely that all errors will be removed for a very long time if at all’. To reassure the data users about quality issues, he has proposed a quality index based on ‘Peaks-Over-Threshold’ (POT) parameter for gauged catchments and a spectral analysis approach for ungauged catchments. The two methods would be useful for water engineers to assess radar data quality in real time flood forecasting operations. It is expected that the proposed schemes will be further validated and improved with more case studies. The paper from the Met Office (Harrison et al.)2 describes the quantitative precipitation estimation in the UK using weather radar, which documents the techniques to produce high resolution (1 km and 500 m) precipitation estimates from the UK network of 15 overlapping weather radars. It quantifies the improvement from the new compositing algorithms, and analyses the impact of the new data on urban hydrological modelling. It also discusses issues associated with the increased resolutions. The paper by Westcott assesses the differences between multi-sensor (radar + rain-gauge) and rain-gauge precipitation for midwest America.3 The quality assessment of the radar data is based on descriptive statistics such as the calculation of quartile ranges. It is found that the processing algorithm used to correct the radar data does not account for errors due to inadequate sampling or ‘overshooting’ of the radar, particularly in winter when stratiform precipitation is frequent. In summer during convective storms, multi-sensor precipitation data are most useful and less prone to error.
It should be noted that weather radars will not replace rain-gauge networks. Instead, they complement each other. A review of the Scottish rain-gauge network by McGregor and McDougall4 provides useful information about the combined networks of rain-gauges and weather radars. The paper evaluates the existing network against current user requirements for rainfall data, investigates the interaction between the rain-gauge and radar networks and informs recommendations for improvements to the network and associated rainfall data. One of the major advantages of weather radars over rain-gauges is their high spatial and temporal resolutions. This makes it possible to develop spatial-temporal rainfall models. The study by Segond and Onof illustrates such a model called Gaussian Displacement Spatial-Temporal Model.5 The model is developed from the rainfall data from three weather radars in the UK and has a potential to be used in flood risk management in urban areas. This is followed by a paper on urban runoff modelling based on Nexrad rainfall in the USA, over a small scale, heavily urbanised and high risk catchment.6 The authors conclude that radar data are better than single-point rain-gauge data in modelling the shape, timing and magnitude of catchment hydrographs. In another study, weather radar data have been applied to a rural catchment by Reichel et al.7 Their paper presents a framework for a radar-based flood forecasting model integrating radar rainfall data, geographical information systems, the hydrological model HEC-HMS and a short-term precipitation nowcasting system. Traditionally, weather radars have been mainly used in rainfall runoff modelling. The study by Dale and Stidson describes an interesting application of weather radar to predict the quality of bathing waters in Scotland.8 They have shown that radar data can be more effective than rain-gauge data in predicting both exceedance and non-exceedance of faecal coliform standards. Weather radars are now widely deployed in many countries in the world. The paper from China (Chen et al.) presents China's next generation weather radars based on the data quality assessment in Southern China.9 This study should provide useful information for practitioners to gain a broadening knowledge about weather radar technology application in developing countries. Last but not least, the paper by Neiman et al.10 demonstrates a water vapour flux tool for precipitation forecasting through analysing hourly radar wind observations and GPS water vapour measurements during four winters over the coastal area in northern California. Based on previous studies on multiple NOAA projects in this area, this work constructs an important framework for coastal weather research and forecasting.
It is impossible to cover all aspects of modern weather radar technology in one special issue. We hope these papers will provide useful information and leads for interested readers to explore and apply radar data in their future water management activities.
