Technical Note: An open source library for processing weather radar data (&amp;lt;i&amp;gt;wradlib&amp;lt;/i&amp;gt;)

Heistermann, Maik; Jacobi, Stephan; Pfaff, Thomas

doi:10.5194/hess-17-863-2013

Cited by 132 publications

(77 citation statements)

References 30 publications

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“…However, there is a lack of accurate rainfall information for the majority of the land surface of the earth, notably from ground-based weather radars (Heistermann et al, 2013). Moreover, the number of reporting rain gauges is dramatically declining in Europe, South America, and Africa.…”

Section: Introductionmentioning

confidence: 99%

Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

2016

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Abstract. Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide ( ≈ 35 500 km 2 ) 15 min rainfall maps can be derived from the signal attenuations of approximately 2400 microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm. Moreover, the documented, modular, and user-friendly code (a package in the scripting language "R") is made available, including a 2-day data set of approximately 2600 commercial microwave links from the Netherlands. The purpose of this paper is to promote rainfall mapping utilising microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

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Section: Introductionmentioning

confidence: 99%

Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

2016

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“…All of these issues are amplified by the disconnect between satellite data and traditional gauge-based measurements, which have well-recognized problems of poor distribution, wind-induced undercatch, elevation bias in gauge placement, and numerous other measurement complications (Lorenz and Kunstmann, 2012;Steiner et al, 1999). While ground-based polarimetric radars offer high temporal and spatial resolutions, they are only generally available in developed countries (Heistermann et al, 2013), have relatively poor coverage in mountainous areas, and their merging with satellite observations has often proven cumbersome (Lee et al, 2015). Nevertheless, due to their spatial and temporal continuity, ground radar data are considered the gold standard where they do exist.…”

Section: Hydrology-specific Data Needsmentioning

confidence: 99%

The future of Earth observation in hydrology

McCabe

Rodell

Alsdorf

et al. 2017

Hydrol. Earth Syst. Sci.

349

282

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Abstract. In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smartphones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Startup companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions.With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via highaltitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such globalPublished by Copernicus Publications on behalf of the European Geosciences Union. The future of Earth observation in hydrology access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparen...

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“…The module is designed to operate using radar data, which allows for the full automatisation of the prognostic precipitation data retrieval process, with significantly increased data resolution and accuracy. For this purpose, the user may turn to the wradlib open source library for weather radar data processing [49].…”

Section: Precipitation Forecastmentioning

confidence: 99%

Pluvial Flood Risk Assessment Tool (PFRA) for Rainwater Management and Adaptation to Climate Change in Newly Urbanised Areas

Szewrański

Chruściński

Kazak

et al. 2018

Water

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Abstract:The aim of this research is to develop the Pluvial Flood Risk Assessment tool (PFRA) for rainwater management and adaptation to climate change in newly urbanised areas. PFRA allows pluvial hazard assessment, as well as pluvial flood risk mapping. The original model was created using ArcGIS software with the ArcHydro extension, and the script was written using the Python programming language. The PFRA model effectively combines information about land cover, soils, microtopography (LiDAR data), and projected hydro-meteorological conditions, which enables the identification of the spatial and temporal distribution of pluvial flood risks in newly developed areas. Further improvements to the PFRA concern the quantification of pluvial flood-related damages, the application of high resolution precipitation data, and the optimisation of coding.

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Technical Note: An open source library for processing weather radar data (<i>wradlib</i>)

Cited by 132 publications

References 30 publications

Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

The future of Earth observation in hydrology

Pluvial Flood Risk Assessment Tool (PFRA) for Rainwater Management and Adaptation to Climate Change in Newly Urbanised Areas

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