Comparison of three types of laser optical disdrometers under natural rainfall conditions

Johannsen, Lisbeth Lolk; Zambon, Nives; Strauß, Peter; Dostál, Tomáš; Neumann, Martin; Zumr, David; Cochrane, Thomas A.; Blöschl, Günter; Klik, Andreas

doi:10.1080/02626667.2019.1709641

Cited by 42 publications

(39 citation statements)

References 35 publications

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“…However, despite their spatial separation, both Parsivel disdrometers showed similar distributions with an overestimation of the velocity of the majority of drops (up to around a diameter of 1 mm) compared to the terminal velocity line. This distribution was also observed in other studies [41,43,60].…”

Section: Drop Size and Velocity Distributionssupporting

confidence: 89%

“…It may also suggest that rainfall intensity measurement between the PWS PE and the rain gauge may deviate more within events than can be seen from the daily comparison. This was shown by Johannsen et al [43], who found that the rain gauge often measured higher intensities than four collocated disdrometers at the minute-scale.…”

Section: Validation Of Site-specific Rainfall Kinetic Energy-intensitmentioning

confidence: 69%

“…Thus, a difference in measured rainfall events may explain some of the differences between the two devices. However, in Johannsen et al [43], the KE-I relationships of the PWS100 and Parsivel disdrometers were established for the same rainfall events and were shown to differ due to instrumental differences.…”

Section: Implications Of Disdrometer Differences For the Estimation Omentioning

confidence: 98%

“…Variations in rainfall measurements between disdrometers and between disdrometers and rain gauges have been observed [35,[39][40][41]. In addition, disdrometers have been shown to measure different drop size distributions even when located at the same site [38,42,43]. The drop size distribution varies naturally in time and space, but disdrometers situated next to each other showed different distributions, which would not be explained by this natural variation [39].…”

Section: Reference Equation Abbreviationmentioning

confidence: 99%

“…Wind may also have affected the degree of scatter of the KE-I points, as the velocity distribution has been found to broaden under windy conditions due to sub-and super-terminal drops [64]. Johannsen et al [43] observed the importance of the installation of a wind protection shield for the Thies, as the drop velocity of small drops was seen to increase for events without the wind protection shield installed.…”

Section: Filtering Of Dropsmentioning

confidence: 99%

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Impact of Disdrometer Types on Rainfall Erosivity Estimation

Johannsen

Zambon

Strauß³

et al. 2020

Water

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Soil erosion by water is affected by the rainfall erosivity, which controls the initial detachment and mobilization of soil particles. Rainfall erosivity is expressed through the rainfall intensity (I) and the rainfall kinetic energy (KE). KE–I relationships are an important tool for rainfall erosivity estimation, when direct measurement of KE is not possible. However, the rainfall erosivity estimation varies depending on the chosen KE–I relationship, as the development of KE–I relationships is affected by the measurement method, geographical rainfall patterns and data handling. This study investigated how the development of KE–I relationships and rainfall erosivity estimation is affected by the use of different disdrometer types. Rainfall data were collected in 1-min intervals from six optical disdrometers at three measurement sites in Austria, one site in Czech Republic and one site in New Zealand. The disdrometers included two disdrometers of each of the following types: the PWS100 Present Weather Sensor from Campbell Scientific, the Laser Precipitation Monitor from Thies Clima and the first generation Parsivel from OTT Hydromet. The fit of KE–I relationships from the literature varied among disdrometers and sites. Drop size and velocity distributions and developed KE–I relationships were device-specific and showed similarities for disdrometers of the same type across measurement sites. This hindered direct comparison of results from different types of disdrometers, even when placed at the same site. Thus, to discern spatial differences in rainfall characteristics the same type of measurement instrument should be used.

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Section: Drop Size and Velocity Distributionssupporting

confidence: 89%

Section: Validation Of Site-specific Rainfall Kinetic Energy-intensitmentioning

confidence: 69%

Section: Implications Of Disdrometer Differences For the Estimation Omentioning

confidence: 98%

Section: Reference Equation Abbreviationmentioning

confidence: 99%

Section: Filtering Of Dropsmentioning

confidence: 99%

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Impact of Disdrometer Types on Rainfall Erosivity Estimation

Johannsen

Zambon

Strauß³

et al. 2020

Water

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Quantifying the time‐specific kinetic energy of simulated rainfall using a dynamic rain gauge system

Wacha

Huang

O’Brien

et al. 2021

Agricultural & Env Letters

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Raindrop impact derives from the kinetic energy of falling raindrops. Determining the kinetic energy of rainfall requires the size distribution and terminal velocity of raindrops, which necessitates complex instrumentation. To avoid this, empirical relations have been developed that relate rainfall intensity and the rate of kinetic energy, i.e., time-specific kinetic energy (KE time ). In this study, a dynamic rain gauge system (DRGS) was used to quantify the KE time generated by a rainfall simulator without need of measuring raindrop size distributions or impact velocities. In a series of 10 rainfall tests, the KE time and rainfall intensity were 860.9 (±88.6) J m 2 h −1 and 72.1 (±1.9) mm h −1 , respectively. Estimated KE time was found to agree well with the power-law relation presented by Petrů and Kalibová for high-intensity simulated rainfall, which are the conditions when higher deviations occur. The DRGS may be a useful tool in quantifying the KE time of rainfall simulators in hopes to better understand raindrop impact mechanisms.

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Error investigation of rain retrievals from disdrometer data using triple colocation

Annella

Capozzi

Fusco

et al. 2022

Atmospheric Science Letters

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Assessing the uncertainty of precipitation measurements is a challenging problem because precipitation estimates are inevitably influenced by various errors and environmental conditions. A way to characterize the error structure of coincident measurements is to use the triple colocation (TC) statistical method. Unlike more typical approaches, where measures are compared in pairs and one of the two is assumed error‐free, TC has the enviable advantage to succeed in characterizing the uncertainties of co‐located measurements being compared to each other, without requiring the knowledge of the true value which is often unknown. However, TC requires to have at least three co‐located measuring systems and the compliance with several initial assumptions. In this work, for the first time, TC is applied to in‐situ measurements of rain precipitation acquired by three co‐located devices: a weighing rain gauge, a laser disdrometer and a bidimensional video disdrometer. Both parametric and nonparametric formulations of TC are implemented to derive the rainfall product precision associated with the three devices. While the parametric TC technique requires tighter constraints and explicit assumptions which may be violated causing some artifacts, the nonparametric formulation is more flexible and requires less strict constrains. For this reason, a comparison between the two TC formulations is also presented to investigate the impact of TC constrains and their possible violations. The results are obtained using a statistically robust dataset spanning a 1.5 year period collected in Switzerland and presented in terms of traditional metrics. According to triple colocation analysis, the two disdrometers outperform the classical weighing rain gauge and they have similar measurement error structure regardless of the integration time intervals.

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Comparison of three types of laser optical disdrometers under natural rainfall conditions

Cited by 42 publications

References 35 publications

Impact of Disdrometer Types on Rainfall Erosivity Estimation

Impact of Disdrometer Types on Rainfall Erosivity Estimation

Quantifying the time‐specific kinetic energy of simulated rainfall using a dynamic rain gauge system

Error investigation of rain retrievals from disdrometer data using triple colocation

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