10th European Conference on Radar in Meteorology and Hydrology (ERAD 2018) : 1-6 July 2018, Ede-Wageningen, The Netherlands

Vos, Lotte de; Leijnse, H.; Uijlenhoet, R.

doi:10.18174/454537

Cited by 14 publications

(26 citation statements)

References 234 publications

(389 reference statements)

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“…Villarini et al (2008) found a similar nugget parameter of 0.51 for 1 min accumulations, though with far larger values at higher accumulation intervals. The nuggets found by Krajewski et al (2003) (0.95-0.97 for 15 min and longer), Ciach & Krajewski (2006) (0.995 and higher for 1 min and longer), Tokay &Öztürk (2012) (0.97 and higher for 5 min and longer) and Peleg et al (2013) (0.92 and higher for 1 min and longer), are all considerably higher than the nugget parameters found here. This is not surprising as the gauges in the networks evaluated in those papers are carefully controlled and of higher sensor quality than typical PWSs.…”

Section: Amsterdam Weather Station Spatial Correlationscontrasting

confidence: 62%

“…Fortunately, many telecom operators have successfully been convinced as shown by the large number of studies on CML datasets from many international locations, e.g. in Italy (Alberoni et al, 2018), Brazil (Rios Gaona et al, 2018), Pakistan (Sohail Afzal et al, 2018), Burkina Faso (Doumounia et al, 2014), Germany (Chwala et al, 2018), Israel (Liberman et al, 2014), and many others.…”

Section: Commercial Microwave Linksmentioning

confidence: 99%

“…The accuracy of CML rainfall observations has been explored by Leijnse et al (2008); Zinevich et al (2010); Overeem et al (2011); Chwala et al (2012) (among others), which is helpful in establishing the potential for operational use of this technique. Because it is possible to log power levels in real time, this technique allows for real-time rainfall monitoring (Chwala et al, 2016;Andersson et al, 2017;Chwala et al, 2018). Messer & Sendik (2015), Uijlenhoet et al (2018), and Chwala & Kunstmann (2019) provide reviews on the details and background of this technique.…”

Section: Commercial Microwave Linksmentioning

confidence: 99%

“…In most cases, there is no information available on the PWS type, the installation setup, maintenance of the sensor or data postprocessing while transferring measurements to the online platform. Bell et al (2013) examine the potential improvement on the UK's observational network with the real-time and local weather measurements of air temperature, relative humidity and pressure collected from WunderMap. The most critical issue was found to be the estimation of data quality.…”

Section: Ochoamentioning

confidence: 99%

“…The relationship in Eq. 2.2 is sensitive to rainfall extremes (Habib et al, 2001a), climatic regimes (Krajewski et al, 2003) and seasonality (Van de Beek et al, 2011;Tokay &Öztürk, 2012) as well as strongly dependent on time interval (Krajewski et al, 2003;Ciach & Krajewski, 2006;Van de Beek et al, 2011;Tokay &Öztürk, 2012;Van de Beek et al, 2012;Peleg et al, 2013). For the PWS dataset in Amsterdam, correlograms are constructed and compared with spatial dependencies found in literature.…”

Section: Station Measurement Qualitymentioning

confidence: 99%

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Rainfall monitoring with opportunistic sensors

Vos¹

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Propositions 1. Understanding uncertainties in high-quantity low-quality observations is only of interest to scientists. (this thesis) 2. Opportunistic sensors cannot replace traditional dedicated rainfall sensing techniques. (this thesis) 3. Faulty scientific hypotheses are not necessarily disproven by accurate observations.4. If a scientist makes a discovery, but is not able to communicate it to other scientists, there has been no scientific advancement. The idea that academic success is measured by how busy youare is a misconception, particularly destructive to young scientists. The large-scale educational exchange between strangers viainternet is a proof of altruism. 7. Everyone's opinion matters, but only opinions of informed individuals should matter in decision making. Propositions belonging to the thesis, entitledRainfall monitoring with opportunistic sensors Lotte de Vos

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Section: Amsterdam Weather Station Spatial Correlationscontrasting

confidence: 62%

Section: Commercial Microwave Linksmentioning

confidence: 99%

Section: Commercial Microwave Linksmentioning

confidence: 99%

Section: Ochoamentioning

confidence: 99%

Section: Station Measurement Qualitymentioning

confidence: 99%

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Rainfall monitoring with opportunistic sensors

Vos¹

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The GPM Ground Validation Program

Petersen

Kirstetter

Wang

et al. 2020

Advances in Global Change Research

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High‐Resolution Simulation Study Exploring the Potential of Radars, Crowdsourced Personal Weather Stations, and Commercial Microwave Links to Monitor Small‐Scale Urban Rainfall

Vos

Raupach

Leijnse

et al. 2018

Water Resources Research

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Many applications in urban areas require high-resolution rainfall measurements. Typical operational weather radars can provide rainfall intensities at 1-km 2 grid cells every 5 min. Opportunistic sensing with commercial microwave links yields path-averaged rainfall intensities (typically 0.1-10 km) within urban areas. Additionally, large amounts of urban in situ rainfall measurements from amateur weather observers are obtainable in real-time. The accuracy of these three techniques is evaluated for an urban study area of 20 × 20 km, taking into account their respective network layouts and sampling characteristics. We use two simulated rainfall events described in terms of drop size distributions on a 100-m grid and with a temporal resolution of 30 s. Accurate radar rainfall estimation with the Z-R relationship relies heavily on an appropriate choice of parameters, and a dual-polarization strategy is more suitable for higher intensities. Under ideal measurement conditions, the weather station network is the most promising, with a Pearson correlation coefficient above 0.86 and a relative bias below 4% for 100-m rainfall estimates at 5-min resolution. Microwave link rainfall observations contain the largest error, shown by a consistently larger coefficient of variation. The accuracy of all techniques improves when considering rainfall at larger scales, especially by increasing time intervals, with the strongest improvements found for microwave links for which errors are largely caused by their temporal sampling. Sparser networks are examined, showing that the decline in measurement accuracy only becomes significant when the link and station network density are reduced to less than half their levels in Amsterdam.

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10th European Conference on Radar in Meteorology and Hydrology (ERAD 2018) : 1-6 July 2018, Ede-Wageningen, The Netherlands

Cited by 14 publications

References 234 publications

Rainfall monitoring with opportunistic sensors

Rainfall monitoring with opportunistic sensors

The GPM Ground Validation Program

High‐Resolution Simulation Study Exploring the Potential of Radars, Crowdsourced Personal Weather Stations, and Commercial Microwave Links to Monitor Small‐Scale Urban Rainfall

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