Analytical solutions to sampling effects in drop size distribution measurements during stationary rainfall: Estimation of bulk rainfall variables

Uijlenhoet, R.; Porrà, Josep M.; Sempere‐Torres, Daniel; Creutin, Jean‐Dominique

doi:10.1016/j.jhydrol.2005.11.043

Cited by 48 publications

(54 citation statements)

References 55 publications

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“…This may slightly influence the statistics of the measured DSDs. However, Uijlenhoet (1999) has shown that the distribution of rainfall intensities derived from the disdrometer closely follows the climatological distribution for the Netherlands. The small sampling area (20 cm 2 ) may also influence these statistics, as the measurement time interval should be rather large to collect enough drops.…”

Section: ) the De Bilt Filter Paper Datasetmentioning

confidence: 98%

“…We have used two separate datasets for this to ensure that the retrieval relations used are independent of the data to which they are applied. Because of the (usually) limited sampling area or volume, obtaining statistically robust measurements of DSDs is a challenge (e.g., Tokay et al 2005;Uijlenhoet et al 2006). Despite these limitations, measurements made by disdrometers are still valuable and will be used here.…”

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confidence: 99%

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Errors and Uncertainties in Microwave Link Rainfall Estimation Explored Using Drop Size Measurements and High-Resolution Radar Data

Leijnse

Uijlenhoet

Berne

2010

Journal of Hydrometeorology

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Microwave links can be used for the estimation of path-averaged rainfall by using either the path-integrated attenuation or the difference in attenuation of two signals with different frequencies and/or polarizations. Link signals have been simulated using measured time series of raindrop size distributions (DSDs) over a period of nearly 2 yr, in combination with wind velocity data and Taylor's hypothesis. For this purpose, Taylor's hypothesis has been tested using more than 1.5 yr of high-resolution radar data. In terms of correlation between spatial and temporal profiles of rainfall intensities, the validity of Taylor's hypothesis quickly decreases with distance. However, in terms of error statistics, the hypothesis is seen to hold up to distances of at least 10 km. Errors and uncertainties (mean bias error and root-mean-square error, respectively) in microwave link rainfall estimates due to spatial DSD variation are at a minimum at frequencies (and frequency combinations) where the power-law relation for the conversion to rainfall intensity is close to linear. Errors generally increase with link length, whereas uncertainties decrease because of the decrease of scatter about the retrieval relations because of averaging of spatially variable DSDs for longer links. The exponent of power-law rainfall retrieval relations can explain a large part of the variation in both bias and uncertainty, which means that the order of magnitude of these error statistics can be predicted from the value of this exponent, regardless of the link length.

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Section: ) the De Bilt Filter Paper Datasetmentioning

confidence: 98%

mentioning

confidence: 99%

Errors and Uncertainties in Microwave Link Rainfall Estimation Explored Using Drop Size Measurements and High-Resolution Radar Data

Leijnse

Uijlenhoet

Berne

2010

Journal of Hydrometeorology

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“…The number of particles Np i,tot in a particular size bin observed arriving in the disdrometer sample volume at a particular instant is typically taken to be a random deviate (Joss and Waldvogel, 1969) and contributes to sampling uncertainty in the calculated size distribution values. For rainfall, the number of particles observed in a given size bin by a volume sampling device like the SVI is often taken to be a Poisson-distributed random variable (Joss and Waldvogel, 1969;Gertzman and Atlas, 1977;Uijlenhoet et al, 2006). The same approach is taken here for snowfall, considering it to behave as a homogeneous Poisson process during the sampling time interval.…”

Section: B2 Sampling Uncertainties For D Svifi and N D Svifimentioning

confidence: 99%

“…The observed particles sizes D ij also vary and are distributed according to a probability density function defined by the size distribution (Uijlenhoet et al, 2006). The observed D ij form a sequence of random variables taken to be independent and identically distributed.…”

Section: B2 Sampling Uncertainties For D Svifi and N D Svifimentioning

confidence: 99%

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Characterization of video disdrometer uncertainties and impacts on estimates of snowfall rate and radar reflectivity

et al. 2013

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Abstract. Estimates of snow microphysical properties obtained by analyzing collections of individual particles are often limited to short timescales and coarse time resolution. Retrievals using disdrometer observations coincident with bulk measurements such as radar reflectivity and snowfall amounts may overcome these limitations; however, retrieval techniques using such observations require uncertainty estimates not only for the bulk measurements themselves, but also for the simulated measurements modeled from the disdrometer observations. Disdrometer uncertainties arise due to sampling and analytic errors and to the discrete, potentially truncated form of the reported size distributions. Imaging disdrometers such as the Snowflake Video Imager and 2-D Video Disdrometer provide remarkably detailed representations of snow particles, but view limited projections of their three-dimensional shapes. Particle sizes determined by such instruments underestimate the true dimensions of the particles in a way that depends, in the mean, on particle shape, also contributing to uncertainties. An uncertainty model that accounts for these uncertainties is developed and used to establish their contributions to simulated radar reflectivity and snowfall rate. Viewing geometry effects are characterized by a parameter, φ, that relates disdrometer-observed particle size to the true maximum dimension of the particle. Values and uncertainties for φ are estimated using idealized ellipsoidal snow particles. The model is applied to observations from seven snow events from the Canadian CloudSat/CALIPSO Validation Project (C3VP), a mid-latitude cold-season cloud and precipitation field experiment. Typical total uncertainties are 4 dB for reflectivity and 40-60 % for snowfall rate, are highly correlated, and are substantial compared to expected uncertainties for radar and precipitation gauge observations. The dominant sources of errors are viewing geometry effects and the discrete, truncated form of the size distributions. While modeled Ze-S relationships are strongly affected by assumptions about snow particle mass properties, such relationships are only modestly sensitive to φ owing to partially compensating effects on both the reflectivity and snowfall rate.

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Toward the camera rain gauge

Allamano

Croci

Laio

2015

Water Resources Research

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We propose a novel technique based on the quantitative detection of rain intensity from images, i.e., from pictures taken in rainy conditions. The method is fully analytical and based on the fundamentals of camera optics. A rigorous statistical framing of the technique allows one to obtain the rain rate estimates in terms of expected values and associated uncertainty. We show that the method can be profitably applied to real rain events, and we obtain promising results with errors of the order of 625%. A precise quantification of the method's accuracy will require a more systematic and long-term comparison with benchmark measures. The significant step forward with respect to standard rain gauges resides in the possibility to retrieve measures at very high temporal resolution (e.g., 30 measures per minute) at a very low cost. Perspective applications include the possibility to dramatically increase the spatial density of rain observations by exporting the technique to crowdsourced pictures of rain acquired with cameras and smartphones.

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Analytical solutions to sampling effects in drop size distribution measurements during stationary rainfall: Estimation of bulk rainfall variables

Cited by 48 publications

References 55 publications

Errors and Uncertainties in Microwave Link Rainfall Estimation Explored Using Drop Size Measurements and High-Resolution Radar Data

Errors and Uncertainties in Microwave Link Rainfall Estimation Explored Using Drop Size Measurements and High-Resolution Radar Data

Characterization of video disdrometer uncertainties and impacts on estimates of snowfall rate and radar reflectivity

Toward the camera rain gauge

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