Abstract

Abstract. Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.

Highlights

  • In 2003 the International Group on Urban Rainfall (IGUR) under the IWA/IAHR Joint Committee on Urban Drainage initiated joint work on the status and development on using radar rainfall data within the context of urban drainage

  • Germann and Joss (2001), Berne et al (2004), Bruni et al (2015), and Ochoa-Rodriguez et al (2015) suggested applying climatological variograms to characterize the spatial structure of rainfall fields and investigating the spatial resolution requirements in order to resolve the spatial structure of rainfall fields in a sufficient way for urban hydrological applications

  • This paper summarized literature findings from the last decade in three key research areas: temporal and spatial radar rainfall resolution in relation to their use in urban hydrology, radar rainfall data adjustment and quality, and use of radar data for rainfall nowcasting and online applications

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Summary

Introduction

In 2003 the International Group on Urban Rainfall (IGUR) under the IWA/IAHR Joint Committee on Urban Drainage initiated joint work on the status and development on using radar rainfall data within the context of urban drainage. Searching for ”hydrology” in general in the aforementioned databases shows a somewhat linear growth from 1980 to 2015 (not shown), whereas the increase in the number of publications within “radar + urban drainage” and “radar + urban hydrology” is more exponential, which indicates a faster growth with regards to the latter This significant growth covers both an increase in applications of weather radar data in urban hydrology, and continuous improvement and development of methods, algorithms, instrumentation, etc., for estimating rainfall from radar data. These form the starting basis of this paper, which aims to provide a review of the major technical developments during the past decade, with particular focus on the most ground-breaking applications and cases, from where updated recommendations are distilled for the applications of radar rainfall data in urban hydrology. We focus on new developments in applications of radar in urban hydrology, and start the discussion from the temporal and spatial resolution needs

Temporal resolution
Spatial resolution
Projection of data
Reflectivity–rain rate conversion
Bias adjustment against ground observations
Operational radar rainfall products
2.1.10 Dynamic adjustment in real time
2.1.11 Choosing adjustment procedures for hydrological modelling
Nowcasting of radar rainfall
The value of radar rainfall for urban hydrology
Re-analysis of damaging extreme events
Urban water management
Nowcasting and operational warning
Operational real-time control
Summary and recommendations
Radar resolution
Radar data adjustment and rainfall data quality
Findings
Nowcasting of rainfall and online applications
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