Real-time data acquisition of commercial microwave link networks for hydrometeorological applications

Chwala, Christian; Keis, Felix; Kunstmann, Harald

doi:10.5194/amt-9-991-2016

Cited by 70 publications

(60 citation statements)

References 12 publications

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“…The accuracy of such relationships has been subsequently investigated in many studies (Doumounia et al, ; Rayitsfeld et al, ). Results show that while quantitative precipitation estimates from CMLs might be regionally biased, possibly due to antenna wetting and systematic disturbances from the built environment, they could match reasonably well with precipitation observations overall (Chwala et al, ; Fencl, Rieckermann, Sykora, et al, ; Fencl, Rieckermann, Vojtěch, ; Mercier et al, ; Rios Gaona et al, ). This implies that the use of communication networks to estimate precipitation is promising, as it provides an important supplement to traditional measurements using ground gauges and radars (Fencl et al, ; Gosset et al, ).…”

Section: Review Of Crowdsourcing Data Acquisition Methods Usedmentioning

confidence: 52%

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

Zheng

Tao

Maier

et al. 2018

Reviews of Geophysics

113

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Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional sources, particularly due to its relatively low implementation cost and ability to increase the spatial and/or temporal resolution of data significantly. Given the proliferation of different crowdsourcing methods in geophysics and the promise they have shown, it is timely to assess the state of the art in this field, to identify potential issues and map out a way forward. In this paper, crowdsourcing‐based data acquisition methods that have been used in seven domains of geophysics, including weather, precipitation, air pollution, geography, ecology, surface water, and natural hazard management, are discussed based on a review of 162 papers. In addition, a novel framework for categorizing these methods is introduced and applied to the methods used in the seven domains of geophysics considered in this review. This paper also features a review of 93 papers dealing with issues that are common to data acquisition methods in different domains of geophysics, including the management of crowdsourcing projects, data quality, data processing, and data privacy. In each of these areas, the current status is discussed and challenges and future directions are outlined.

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Section: Review Of Crowdsourcing Data Acquisition Methods Usedmentioning

confidence: 52%

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

Zheng

Tao

Maier

et al. 2018

Reviews of Geophysics

113

View full text Add to dashboard Cite

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“…In order to derive reasonable precipitation information, it is therefore necessary to identify the disturbances caused by rain events. In the simulation studies presented in this article, two approaches are applied to the time series of transmitted and received signal levels (TRSL) acquired with the method described by Chwala et al (2016). The first procedure stdev after Schleiss and Berne (2010) calculates the standard deviation s within a moving time window along the TRSL.…”

Section: CMLmentioning

confidence: 99%

“…Hence, it is applicable in most inhabited areas around the globe (Overeem et al 2013). Furthermore, the required CML data can be made available in real time Chwala et al (2016), allowing the application of this technique with operational tools for warning of precipitation and floods. It can advantageously complement the existing networks of rain gauges and radar, but it can also be used in areas where station networks are very coarse or non-existent.…”

Section: Introductionmentioning

confidence: 99%

“…Overeem et al (2013) demonstrated that processing algorithms are capable of providing real-time rainfall maps for an entire country, in this case the Netherlands. Chwala et al (2016) implemented a system to acquire and distribute the required CML data in real time. From a case study in Prague, Czech Republic, Fencl et al (2015) concluded that the CLM captures the spatiotemporal rainfall variability with a positive bias and emphasized its potential to improve runoff predictions.…”

Section: Introductionmentioning

confidence: 99%

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Potential of commercial microwave link network derived rainfall for river runoff simulations

Smiatek

Keis

Chwala

et al. 2017

Environ. Res. Lett.

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Commercial microwave link networks allow for the quantification of path integrated precipitation because the attenuation by hydrometeors correlates with rainfall between transmitter and receiver stations. The networks, operated and maintained by cellphone companies, thereby provide completely new and country wide precipitation measurements. As the density of traditional precipitation station networks worldwide is significantly decreasing, microwave link derived precipitation estimates receive increasing attention not only by hydrologists but also by meteorological and hydrological services. We investigate the potential of microwave derived precipitation estimates for streamflow prediction and water balance analyses, exemplarily shown for an orographically complex region in the German Alps (River Ammer). We investigate the additional value of link derived rainfall estimations combined with station observations compared to station and weather radar derived values. Our river runoff simulation system employs a distributed hydrological model at 100 Â 100 m grid resolution. We analyze the potential of microwave link derived precipitation estimates for two episodes of 30 days with typically moderate river flow and an episode of extreme flooding. The simulation results indicate the potential of this novel precipitation monitoring method: a significant improvement in hydrograph reproduction has been achieved in the extreme flooding period that was characterized by a large number of local strong precipitation events. The present rainfall monitoring gauges alone were not able to correctly capture these events.

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“…For instance, Messer et al (2012), and Overeem et al (2016b) , and 0.1 to 2.1 km per km 2 , respectively. Fencl et al (2015), and Messer et al (2012) provide 1-min rainfall estimates, whereas 1-s retrievals are obtained by Chwala et al (2016), and Doumounia et al (2014).…”

mentioning

confidence: 99%

Rainfall retrieval with commercial microwave links in São Paulo, Brazil

Gaona¹,

Overeem²,

Raupach³

et al. 2017

Preprint

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Abstract. In the last decade there has been a growing interest from the hydrometeorological community regarding rainfall estimation from commercial microwave link (CML) networks. Path-averaged rainfall intensities can be retrieved from the signal attenuation between cell phone towers. Although this technique is still in development, it offers great opportunities for the retrieval of rainfall rates at high spatiotemporal resolutions very close to the Earth's surface. Rainfall measurements at high spatiotemporal resolutions are highly valued in urban hydrology, for instance, given the large impact that flash floods exert on 5 society. Flash floods are triggered by intense rainfall events that develop over short time scales.Here, we present one of the first evaluations of this measurement technique for a subtropical climate. Rainfall estimation for subtropical climates is highly relevant, since many countries with few surface rainfall observations are located in such areas.The test bed of the current study is the Brazilian city of São Paulo. The open-source algorithm RAINLINK was applied to retrieve rainfall intensities from (power) attenuation measurements. The performance of RAINLINK estimates was evaluated 10 for 5 of the 250 CML in the São Paulo metropolitan area for which we received data, for 81 days between October 2014 and January 2015. We evaluated the retrieved rainfall intensities and accumulations from CML against those from a dense automatic gauge network. Results were found to be promising and encouraging, especially for short links, for which high correlations (> 0.9) and low biases (∼30% and lower) were obtained.

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Real-time data acquisition of commercial microwave link networks for hydrometeorological applications

Cited by 70 publications

References 12 publications

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

Potential of commercial microwave link network derived rainfall for river runoff simulations

Rainfall retrieval with commercial microwave links in São Paulo, Brazil

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