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1
Tokay, Ali, Paul G. Bashor, and Katherine R. Wolff. "Error Characteristics of Rainfall Measurements by Collocated Joss–Waldvogel Disdrometers." Journal of Atmospheric and Oceanic Technology 22, no. 5 (May 1, 2005): 513–27. http://dx.doi.org/10.1175/jtech1734.1.
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Abstract Error characteristics of rainfall measurements were studied using six collocated Joss–Waldvogel (JW) disdrometers that are located at NASA’s Wallops Flight Facility. The six disdrometer means of rain rate R, reflectivity Z, and differential reflectivity ZDR, for a given minute were considered as a reference. The maximum deviations of R, Z, and ZDR from the mean in a rain event were 0.6 mm h−1, 1.3 dB, and 0.05 dB, respectively. Rainfall statistics were then examined between disdrometer pairs. The root-mean-square (rms) difference of R, Z, and ZDR between paired disdrometers in a rain event were as high as 3.2 mm h−1, 3.7 dB, and 0.3 dB, respectively. The rms difference of R and ZDR were even higher when the disdrometer observations were stratified based on reflectivity intervals. The differences in disdrometer rainfall measurements have a potential impact when the disdrometers are considered as calibration tools for vertically pointing and scanning radars. The differences between the disdrometer measurements also result in differences in coefficients and exponents of the derived relations between radar parameters and rain rate. Among the four different relations between radar parameters and rain rate, the absolute difference in rain rate |ΔR| from two different JW disdrometers was highest in R(ZH, ZDR) and lowest in R(KDP, ZDR). The other two relations were R(Z) and R(KDP). The |ΔR| increases with increasing horizontally polarized reflectivity ZH, and differential specific phase KDP in both single- and dual-parameter rainfall estimators, while the |ΔR| increases with decreasing ZDR in dual-parameter rainfall estimators. Several sources of JW disdrometer malfunctions were also presented. The hardware problems were the leading cause for the malfunction of the JW disdrometers, as identified by the manufacturer. A single JW disdrometer could have inherent measurement errors that can only be identified in the presence of collocated (preferably two) rain-measuring instruments.
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Adirosi, Elisa, Nicoletta Roberto, Mario Montopoli, Eugenio Gorgucci, and Luca Baldini. "Influence of Disdrometer Type on Weather Radar Algorithms from Measured DSD: Application to Italian Climatology." Atmosphere 9, no. 9 (September 18, 2018): 360. http://dx.doi.org/10.3390/atmos9090360.
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Relations for retrieving precipitation and attenuation information from radar measurements play a key role in radar meteorology. The uncertainty in such relations highly affects the precipitation and attenuation estimates. Weather radar algorithms are often derived by applying regression methods to precipitation measurements and radar observables simulated from datasets of drop size distributions (DSD) using microphysical and electromagnetic assumptions. DSD datasets can be derived from theoretical considerations or obtained from experimental measurements collected throughout the years by disdrometers. Although the relations obtained from experimental disdrometer datasets can be generally considered more representative of a specific climatology, the measuring errors, which depend on the specific type of disdrometer used, introduce an element of uncertainty to the final retrieval algorithms. Eventually, data quality checks and filtering procedures applied to disdrometer measurements play an important role. In this study, we pursue two main goals: (i) evaluate two different techniques for establishing weather radar algorithms from measured DSD, and (ii) investigate to what extent dual-polarization radar algorithms derived from experimental DSD datasets are influenced by the different error structures introduced by the various disdrometer types (namely 2D video disdrometer, first and second generation of OTT Parsivel disdrometer, and Thies Clima disdrometer) used to collect the data. Furthermore, weather radar algorithms optimized for Italian climatology are presented and discussed.
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Raupach, T. H., and A. Berne. "Correction of raindrop size distributions measured by Parsivel disdrometers, using a two-dimensional video disdrometer as a reference." Atmospheric Measurement Techniques 8, no. 1 (January 16, 2015): 343–65. http://dx.doi.org/10.5194/amt-8-343-2015.
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Abstract. The raindrop size distribution (DSD) quantifies the microstructure of rainfall and is critical to studying precipitation processes. We present a method to improve the accuracy of DSD measurements from Parsivel (particle size and velocity) disdrometers, using a two-dimensional video disdrometer (2DVD) as a reference instrument. Parsivel disdrometers bin raindrops into velocity and equivolume diameter classes, but may misestimate the number of drops per class. In our correction method, drop velocities are corrected with reference to theoretical models of terminal drop velocity. We define a filter for raw disdrometer measurements to remove particles that are unlikely to be plausible raindrops. Drop concentrations are corrected such that on average the Parsivel concentrations match those recorded by a 2DVD. The correction can be trained on and applied to data from both generations of OTT Parsivel disdrometers, and indeed any disdrometer in general. The method was applied to data collected during field campaigns in Mediterranean France for a network of first- and second-generation Parsivel disdrometers, and on a first-generation Parsivel in Payerne, Switzerland. We compared the moments of the resulting DSDs to those of a collocated 2DVD, and the resulting DSD-derived rain rates to collocated rain gauges. The correction improved the accuracy of the moments of the Parsivel DSDs, and in the majority of cases the rain rate match with collocated rain gauges was improved. In addition, the correction was shown to be similar for two different climatologies, suggesting its general applicability.
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Tokay, Ali, and Paul G. Bashor. "An Experimental Study of Small-Scale Variability of Raindrop Size Distribution." Journal of Applied Meteorology and Climatology 49, no. 11 (November 1, 2010): 2348–65. http://dx.doi.org/10.1175/2010jamc2269.1.
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Abstract An experimental study of small-scale variability of raindrop size distributions (DSDs) has been carried out at Wallops Island, Virginia. Three Joss–Waldvogel disdrometers were operated at a distance of 0.65, 1.05, and 1.70 km in a nearly straight line. The main purpose of the study was to examine the variability of DSDs and its integral parameters of liquid water content, rainfall, and reflectivity within a 2-km array: a typical size of Cartesian radar pixel. The composite DSD of rain events showed very good agreement among the disdrometers except where there were noticeable differences in midsize and large drops in a few events. For consideration of partial beam filling where the radar pixel was not completely covered by rain, a single disdrometer reported just over 10% more rainy minutes than the rainy minutes when all three disdrometers reported rainfall. Similarly two out of three disdrometers reported 5% more rainy minutes than when all three were reporting rainfall. These percentages were based on a 1-min average, and were less for longer averaging periods. Considering only the minutes when all three disdrometers were reporting rainfall, just over one quarter of the observations showed an increase in the difference in rainfall with distance. This finding was based on a 15-min average and was even less for shorter averaging periods. The probability and cumulative distributions of a gamma-fitted DSD and integral rain parameters between the three disdrometers had a very good agreement and no major variability. This was mainly due to the high percentage of light stratiform rain and to the number of storms that traveled along the track of the disdrometers. At a fixed time step, however, both DSDs and integral rain parameters showed substantial variability. The standard deviation (SD) of rain rate was near 3 mm h−1, while the SD of reflectivity exceeded 3 dBZ at the longest separation distance. These standard deviations were at 6-min average and were higher at shorter averaging periods. The correlations decreased with increasing separation distance. For rain rate, the correlations were higher than previous gauge-based studies. This was attributed to the differences in data processing and the difference in rainfall characteristics in different climate regions. It was also considered that the gauge sampling errors could be a factor. In this regard, gauge measurements were simulated employing existing disdrometer dataset. While a difference was noticed in cumulative distribution of rain occurrence between the simulated gauge and disdrometer observations, the correlations in simulated gauge measurements did not differ from the disdrometer measurements.
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Raupach, T. H., and A. Berne. "Correction of raindrop size distributions measured by Parsivel disdrometers, using a two-dimensional-video-disdrometer as a reference." Atmospheric Measurement Techniques Discussions 7, no. 8 (August 19, 2014): 8521–79. http://dx.doi.org/10.5194/amtd-7-8521-2014.
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Abstract. The raindrop size distribution (DSD) quantifies the micro-structure of rainfall and is critical to studying precipitation processes. We present a method to improve the accuracy of DSD measurements from Parsivel disdrometers, using a two-dimensional-video-disdrometer (2DVD) as a reference instrument. Parsivel disdrometers bin recorded raindrops into velocity and equivolume diameter classes, but may mis-estimate the number of drops per class. We define a filter for raw disdrometer measurements to remove particles that are unlikely to be plausible raindrops. In our correction method, drop velocities are corrected with reference to theoretical models of terminal drop velocity. Non-plausible measurements are removed. Lastly, drop concentrations are corrected such that on average the Parsivel concentrations match those recorded by a 2DVD. The correction can be trained on and applied to data from both generations of Parsivel disdrometers. The method was applied to data collected during field campaigns in Mediterranean France, for a network of first and second generation Parsivel disdrometers. We compared the moments of the resulting DSDs to those of a collocated 2DVD, and the resulting DSD-derived rain rates to collocated rain gauges. The correction vastly improved the accuracy of the moments of the Parsivel DSDs, and in the majority of cases the rain rate match with collocated rain gauges was improved.
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Lewandowski, Piotr A., William E. Eichinger, Anton Kruger, and Witold F. Krajewski. "Lidar-Based Estimation of Small-Scale Rainfall: Empirical Evidence." Journal of Atmospheric and Oceanic Technology 26, no. 3 (March 1, 2009): 656–64. http://dx.doi.org/10.1175/2008jtecha1122.1.
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Abstract A significant scale gap between radar and in situ measurements of rainfall using rain gauges and disdrometers indicates a pressing need for improved knowledge of rainfall variability at the spatial scales below those of today’s operational radar rainfall products, that is, ∼1–4 km. Lidar technology has the potential to fulfill this need, but there has been inconsistency in the literature pertaining to quantitative observations of rain using lidar. Several publications have stated that light scattering properties of raindrops could not be correlated with rain rates, while other papers have demonstrated the existence of such relationships. This note provides empirical evidence in support of the latter claim. The authors conducted a simple experiment using a near-horizontal-pointing elastic lidar to observe rain in Iowa City, Iowa, in the fall of 2005. The lidar signal was used to estimate rainfall quantities that were subsequently compared with independent estimates of the same quantities obtained from an optical disdrometer that was placed about 370 m from the lidar, ∼10 m below the lidar beam. To perform the conversion from the raw lidar signal, the authors used an optical geometry-based procedure to estimate optical extinction data. A theoretical relationship between extinction coefficients and rain rates was derived based on a theoretical drop size distribution. The parameters of the relationship were found through a best-fit procedure using lidar and disdrometer data. The results show that the lidar-derived rain rates correspond to those obtained from the optical disdrometer with a root-mean-square difference of 55%. The authors conclude that although a great deal remains to be done to improve the inversion algorithm, lidar measurements of rain are possible and warrant further studies. Lidars deployed in conjunction with disdrometers can provide high spatial (<5 m) and temporal (<1 min disdrometer, ∼1 s lidar) resolution data over a relatively long distance for rainfall measurements (1–2 km in the case of the University of Iowa lidar).
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Johannsen, Lisbeth Lolk, Nives Zambon, Peter Strauss, Tomas Dostal, Martin Neumann, David Zumr, Thomas A. Cochrane, and Andreas Klik. "Impact of Disdrometer Types on Rainfall Erosivity Estimation." Water 12, no. 4 (March 28, 2020): 963. http://dx.doi.org/10.3390/w12040963.
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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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Gires, Auguste, Philippe Bruley, Anne Ruas, Daniel Schertzer, and Ioulia Tchiguirinskaia. "Disdrometer measurements under Sense-City rainfall simulator." Earth System Science Data 12, no. 2 (April 14, 2020): 835–45. http://dx.doi.org/10.5194/essd-12-835-2020.
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Abstract. The Hydrology, Meteorology and Complexity Laboratory of École des Ponts ParisTech (http://hmco.enpc.fr, last access: 24 March 2020) and the Sense-City consortium (http://sense-city.ifsttar.fr/, last access: 24 March 2020) made available a dataset of optical disdrometer measurements stemming from a campaign that took place in September 2017 under the rainfall simulator of the Sense-City climatic chamber, which is located near Paris. Two OTT Parsivel2 disdrometers were used. The size and velocity of drops falling through the sampling area of the devices of roughly a few tens of square centimetres are computed by disdrometers. This enables the estimation of the drop size distribution and the further study of rainfall microphysics or kinetic energy for example. Raw data – basically a matrix containing a number of drops according to classes of size and velocity, along with more aggregated ones such as rain rate and drop size distribution with filtering – are available. The dataset is publicly available at https://doi.org/10.5281/zenodo.3347051(Gires et al., 2019).
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Adirosi, Elisa, Eugenio Gorgucci, Luca Baldini, and Ali Tokay. "Evaluation of Gamma Raindrop Size Distribution Assumption through Comparison of Rain Rates of Measured and Radar-Equivalent Gamma DSD." Journal of Applied Meteorology and Climatology 53, no. 6 (June 2014): 1618–35. http://dx.doi.org/10.1175/jamc-d-13-0150.1.
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AbstractTo date, one of the most widely used parametric forms for modeling raindrop size distribution (DSD) is the three-parameter gamma. The aim of this paper is to analyze the error of assuming such parametric form to model the natural DSDs. To achieve this goal, a methodology is set up to compare the rain rate obtained from a disdrometer-measured drop size distribution with the rain rate of a gamma drop size distribution that produces the same triplets of dual-polarization radar measurements, namely reflectivity factor, differential reflectivity, and specific differential phase shift. In such a way, any differences between the values of the two rain rates will provide information about how well the gamma distribution fits the measured precipitation. The difference between rain rates is analyzed in terms of normalized standard error and normalized bias using different radar frequencies, drop shape–size relations, and disdrometer integration time. The study is performed using four datasets of DSDs collected by two-dimensional video disdrometers deployed in Huntsville (Alabama) and in three different prelaunch campaigns of the NASA–Japan Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) ground validation program including the Hydrological Cycle in Mediterranean Experiment (HyMeX) special observation period (SOP) 1 field campaign in Rome. The results show that differences in rain rates of the disdrometer DSD and the gamma DSD determining the same dual-polarization radar measurements exist and exceed those related to the methodology itself and to the disdrometer sampling error, supporting the finding that there is an error associated with the gamma DSD assumption.
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Frech, Michael, Martin Hagen, and Theo Mammen. "Monitoring the Absolute Calibration of a Polarimetric Weather Radar." Journal of Atmospheric and Oceanic Technology 34, no. 3 (March 2017): 599–615. http://dx.doi.org/10.1175/jtech-d-16-0076.1.
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AbstractThe absolute calibration of a dual-polarization radar of the German Weather Service is continuously monitored using the operational birdbath scan and collocated disdrometer measurements at the Hohenpeissenberg observatory. The goal is to measure the radar reflectivity constant Z better than ±1 dB. The assumption is that a disdrometer measurement close to the surface can be related to the radar measurement at the first far-field range bin. This is verified using a Micro Rain Radar (MRR). The MRR data fill the gap between the measurement near the surface and the far-field range bin at 650 m. Using data from the first half of the warm season in 2014, a bias in radar calibration of 1.8 dB is found. Data from only stratiform precipitation events are considered. After adjusting the radar calibration and using an independent data sample, very good agreement is found between the radar, the MRR, and the disdrometer with a bias in smaller than 1 dB. The bias in is not captured with the classic one-point calibration, which is performed twice a day using a built-in test signal generator. This is attributed to the fact that the characterization of the transmit and receive path is not accurate enough. Solar interferences during the operational scanning are used to characterize the receiver. There, the bias found is small, about 0.2 dB, so that bias based on the comparison of the radar with external sensors is attributed to the transmit path. The representativeness of the disdrometer measurements are assessed using two additional disdrometers located within 200-m distance.
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Angulo-Martínez, Marta, Santiago Beguería, Borja Latorre, and María Fernández-Raga. "Comparison of precipitation measurements by OTT Parsivel<sup>2</sup> and Thies LPM optical disdrometers." Hydrology and Earth System Sciences 22, no. 5 (May 8, 2018): 2811–37. http://dx.doi.org/10.5194/hess-22-2811-2018.
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Abstract. Optical disdrometers are present weather sensors with the ability of providing detailed information on precipitation such as rain intensity, radar reflectivity or kinetic energy, together with discrete information on the particle size and fall velocity distribution (PSVD) of the hydrometeors. Disdrometers constitute a step forward towards a more complete characterization of precipitation, being useful in several research fields and applications. In this article the performance of two extensively used optical disdrometers, the most recent version of OTT Parsivel2 disdrometer and Thies Clima Laser Precipitation Monitor (LPM), is evaluated. During 2 years, four collocated optical disdrometers, two Thies Clima LPM and two OTT Parsivel2, collected up to 100 000 min of data and up to 30 000 min with rain in more than 200 rainfall events, with intensities peaking at 277 mm h−1 in 1 minute. The analysis of these records shows significant differences between both disdrometer types for all integrated precipitation parameters, which can be explained by differences in the raw PSVD estimated by the two sensors. Thies LPM recorded a larger number of particles than Parsivel2 and a higher proportion of small particles than OTT Parsivel2, resulting in higher rain rates and totals and differences in radar reflectivity and kinetic energy. These differences increased greatly with rainfall intensity. Possible causes of these differences, and their practical consequences, are discussed in order to help researchers and users in the choice of sensor, and at the same time pointing out limitations to be addressed in future studies.
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Friedrich, Katja, Stephanie Higgins, Forrest J. Masters, and Carlos R. Lopez. "Articulating and Stationary PARSIVEL Disdrometer Measurements in Conditions with Strong Winds and Heavy Rainfall." Journal of Atmospheric and Oceanic Technology 30, no. 9 (September 1, 2013): 2063–80. http://dx.doi.org/10.1175/jtech-d-12-00254.1.
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Abstract The influence of strong winds on the quality of optical Particle Size Velocity (PARSIVEL) disdrometer measurements is examined with data from Hurricane Ike in 2008 and from convective thunderstorms observed during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) in 2010. This study investigates an artifact in particle size distribution (PSD) measurements that has been observed independently by six stationary PARSIVEL disdrometers. The artifact is characterized by a large number concentration of raindrops with large diameters (>5 mm) and unrealistic fall velocities (<1 m s−1). It is correlated with high wind speeds and is consistently observed by stationary disdrometers but is not observed by articulating disdrometers (instruments whose sampling area is rotated into the wind). The effects of strong winds are further examined with a tilting experiment, in which drops are dripped through the PARSIVEL sampling area while the instrument is tilted at various angles, suggesting that the artifact is caused by particles moving at an angle through the sampling area. Most of the time, this effect occurs when wind speed exceeds 20 m s−1, although it was also observed when wind speed was as low as 10 m s−1. An alternative quality control is tested in which raindrops are removed when their diameters exceed 8 mm and they divert from the fall velocity–diameter relationship. While the quality control does provide more realistic reflectivity values for the stationary disdrometers in strong winds, the number concentration is reduced compared to the observations with an articulating disdrometer.
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Wood, N. B., T. S. L'Ecuyer, F. L. Bliven, and G. L. Stephens. "Characterization of video disdrometer uncertainties and impacts on estimates of snowfall rate and radar reflectivity." Atmospheric Measurement Techniques 6, no. 12 (December 20, 2013): 3635–48. http://dx.doi.org/10.5194/amt-6-3635-2013.
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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, &varphi;, that relates disdrometer-observed particle size to the true maximum dimension of the particle. Values and uncertainties for &varphi; 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 &varphi; owing to partially compensating effects on both the reflectivity and snowfall rate.
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Wood, N. B., T. S. L'Ecuyer, F. L. Bliven, and G. L. Stephens. "Characterization of disdrometer uncertainties and impacts on estimates of snowfall rate and radar reflectivity." Atmospheric Measurement Techniques Discussions 6, no. 4 (July 11, 2013): 6329–69. http://dx.doi.org/10.5194/amtd-6-6329-2013.
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Abstract. Estimates of snow microphysical properties obtained by analyzing collections of individual particles are often limited to short time scales 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 dBZ for reflectivity and 40–60% for snowfall rate, are highly correlated, and are substantial compared to expected observational uncertainties. 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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Checa-Garcia, R., A. Tokay, and F. J. Tapiador. "Binning effects on in-situ raindrop size distribution measurements." Atmospheric Measurement Techniques Discussions 7, no. 3 (March 7, 2014): 2339–79. http://dx.doi.org/10.5194/amtd-7-2339-2014.
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Abstract. This paper investigates the binning effects on drop size distribution (DSD) measurements obtained by Joss-Waldvogel disdrometer (JWD), Precipitation Occurrence Sensor System (POSS), Thies disdrometer (Thies), Parsivel OTT disdrometer, two-dimensional video disdrometer (2DVD) and optical spectro-pluviometer (OSP) instruments, therefore the evaluation comprises non-regular bin sizes and the effect of minimum and maximum measured sizes of drops. To achieve this goal, 2DVD measurements and simulated gamma size distributions were considered. The analysis of simulated gamma DSD binned according each instrument was performed to understand the role of discretisation and truncation effects together on the integral rainfall parameters and estimators of the DSD parameters. In addition, the drop-by-drop output of the 2DVD is binned to simulate the raw output of the other disdrometers which allowed us estimate sampling and binning effects on selected events from available dataset. From simulated DSD it has been found that binning effects exist in integral rainfall parameters and in the evaluation of DSD parameters of a gamma distribution. This study indicates that POSS and JWD exhibit underestimation of concentration and mean diameter due to binning. Thies and Parsivel report a positive bias for rainfall and reflectivity (reaching 5% for heavy rainfall intensity events). Regarding to DSD parameters, distributions of estimators for the shape and scale parameters were analyzed by moment, truncated moment and maximum likelihood methods. They reported noticeable differences between instruments for all methodologies of estimation applied. The measurements of 2DVD allow sampling error estimation of instruments with smaller capture areas than 2DVD. The results show that the instrument differences due to sampling were a~relevant uncertainty but that concentration, reflectivity and mass-weighted diameter were sensitive to binning.
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Fehlmann, Michael, Mario Rohrer, Annakaisa von Lerber, and Markus Stoffel. "Automated precipitation monitoring with the Thies disdrometer: biases and ways for improvement." Atmospheric Measurement Techniques 13, no. 9 (September 4, 2020): 4683–98. http://dx.doi.org/10.5194/amt-13-4683-2020.
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Abstract. The intensity and phase of precipitation at the ground surface can have important implications not only for meteorological and hydrological situations but also in terms of hazards and risks. In the field, Thies disdrometers are sometimes used to monitor the quantity and nature of precipitation with high temporal resolution and very low maintenance and thus provide valuable information for the management of meteorological and hydrological risks. Here, we evaluate the Thies disdrometer with respect to precipitation detection, as well as the estimation of precipitation intensity and phase at a pre-alpine site in Switzerland (1060 m a.s.l.), using a weighing precipitation gauge (OTT pluviometer) and a two-dimensional video disdrometer (2DVD) as a reference. We show that the Thies disdrometer is well suited to detect even light precipitation, reaching a hit rate of around 95 %. However, the instrument tends to systematically underestimate rainfall intensities by 16.5 %, which can be related to a systematic underestimation of the number of raindrops with diameters between 0.5 and 3.5 mm. During snowfall episodes, a similar underestimation is observed in the particle size distribution (PSD), which is, however, not reflected in intensity estimates, probably due to a compensation by snow density assumptions. To improve intensity estimates, we test PSD adjustments (to the 2DVD) and direct adjustments of the resulting intensity estimates (to the OTT pluviometer), the latter of which are able to successfully reduce the systematic deviations during rainfall in the validation period. For snowfall, the combination of the 2DVD and the OTT pluviometer seems promising as it allows for improvement of snow density estimates, which poses a challenge to all optical precipitation measurements. Finally, we show that the Thies disdrometer and the 2DVD agree well insofar as the distinction between rain and snowfall is concerned, such that an important prerequisite for the proposed correction methods is fulfilled. Uncertainties mainly persist during mixed-phase precipitation or low precipitation intensities, where the assignment of precipitation phase is technically challenging, but less relevant for practical applications. We conclude that the Thies disdrometer is suitable not only to estimate precipitation intensity but also to distinguish between rain and snowfall. The Thies disdrometer therefore seems promising for the improvement of precipitation monitoring and the nowcasting of discharge in pre-alpine areas, where considerable uncertainties with respect to these quantities are still posing a challenge to decision-making.
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Tokay, Ali, Leo Pio D’Adderio, David B. Wolff, and Walter A. Petersen. "Development and Evaluation of the Raindrop Size Distribution Parameters for the NASA Global Precipitation Measurement Mission Ground Validation Program." Journal of Atmospheric and Oceanic Technology 37, no. 1 (January 2020): 115–28. http://dx.doi.org/10.1175/jtech-d-18-0071.1.
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AbstractThe National Aeronautics and Space Administration Global Precipitation Measurement (GPM) mission ground validation program uses dual-polarization radar moments to estimate raindrop size distribution (DSD) parameters, the mass-weighted mean drop diameter Dmass, and normalized intercept parameter NW, to validate the GPM Core Observatory–derived DSD parameters. The disdrometer-based Dmass and NW are derived through empirical relationships between Dmass and differential reflectivity ZDR, and between NW, reflectivity ZH, and Dmass. This study employs large datasets collected from two-dimensional video disdrometers (2DVD) during six different field studies to derive the requisite empirical relationships. The uncertainty of the derived Dmass(ZDR) relationship is evaluated through comparisons of 2DVD-calculated and ZDR-estimated Dmass, where ZDR is calculated directly from 2DVD observations. Similarly, the uncertainty of the NW(ZH, Dmass) relationship is evaluated through 2DVD-calculated and Dmass and ZH-estimated NW, where Dmass and ZH are directly calculated from 2DVD observations. This study also presents the sensitivity of Dmass(ZDR) relationships to climate regime and to disdrometer type after developing three additional Dmass(ZDR) relationships from second-generation Particle Size Velocity (PARSIVEL2) disdrometer (P2) observations collected in the Pacific Northwest, in Iowa, and at Kwajalein Atoll in the tropical Pacific Ocean. The application of P2-derived Dmass(ZDR) relationship based on precipitation in the northwestern United States to P2 observations collected over the tropical ocean resulted in the highest error among comparisons of the three datasets.
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ONOMURA, Shiho, Kousuke SUZUKI, and Makoto NAKAYOSHI. "DEVELOPMENT OF IMAGE DISDROMETER." Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering) 75, no. 2 (2019): I_1159—I_1164. http://dx.doi.org/10.2208/jscejhe.75.2_i_1159.
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Fernandez-Raga, M., C. Palencia, C. Tomas, A. I. Calvo, A. Castro, and R. Fraile. "Rain research with disdrometers: a bibliometric review." Atmospheric Measurement Techniques Discussions 4, no. 5 (September 23, 2011): 6041–68. http://dx.doi.org/10.5194/amtd-4-6041-2011.
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Abstract. This study analyses the research on disdrometers based on published studies. To do so, a wide data base of bibliographic references has been used: the Web of Science (published by Thomson Reuters). The search was carried out for all of the articles whose "TOPIC" was disdrometer. The more than 300 articles found were analysed according to various criteria: countries with research using disdrometers; publication dates; evolution of the number of articles; concepts studied and research lines followed in each article; and finally, a bibliometric analysis of the more than 60 journals where these articles have been published. Since 1963, there has been an increase in the number of articles published on disdrometers, which in the last 20 yr has been more than ten times higher than the increase in the number of articles on meteorology.
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Tokay, Ali, Walter A. Petersen, Patrick Gatlin, and Matthew Wingo. "Comparison of Raindrop Size Distribution Measurements by Collocated Disdrometers." Journal of Atmospheric and Oceanic Technology 30, no. 8 (August 1, 2013): 1672–90. http://dx.doi.org/10.1175/jtech-d-12-00163.1.
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Abstract An impact-type Joss–Waldvogel disdrometer (JWD), a two-dimensional video disdrometer (2DVD), and a laser optical OTT Particle Size and Velocity (PARSIVEL) disdrometer (PD) were used to measure the raindrop size distribution (DSD) over a 6-month period in Huntsville, Alabama. Comparisons indicate event rain totals for all three disdrometers that were in reasonable agreement with a reference rain gauge. In a relative sense, hourly composite DSDs revealed that the JWD was more sensitive to small drops (<1 mm), while the PD appeared to severely underestimate small drops less than 0.76 mm in diameter. The JWD and 2DVD measured comparable number concentrations of midsize drops (1–3 mm) and large drops (3–5 mm), while the PD tended to measure relatively higher drop concentrations at sizes larger than 2.44 mm in diameter. This concentration disparity tended to occur when hourly rain rates and drop counts exceeded 2.5 mm h−1 and 400 min−1, respectively. Based on interactions with the PD manufacturer, the partially inhomogeneous laser beam is considered the cause of the PD drop count overestimation. PD drop fall speeds followed the expected terminal fall speed relationship quite well, while the 2DVD occasionally measured slower drops for diameters larger than 2.4 mm, coinciding with events where wind speeds were greater than 4 m s−1. The underestimation of small drops by the PD had a pronounced effect on the intercept and shape of parameters of gamma-fitted DSDs, while the overestimation of midsize and larger drops resulted in higher mean values for PD integral rain parameters.
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Smith, Paul L. "Sampling Issues in Estimating Radar Variables from Disdrometer Data." Journal of Atmospheric and Oceanic Technology 33, no. 11 (November 2016): 2305–13. http://dx.doi.org/10.1175/jtech-d-16-0040.1.
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AbstractSimulation of sampling from gamma-distributed raindrop populations demonstrates that significant biases and substantial errors can occur in estimates of polarimetric radar variables based on samples of raindrop populations obtained with disdrometers. Biases and RMS errors of 0.5 dB or more in estimates of differential reflectivity Zdr can occur with samples of even a few hundred drops; significant biases and errors also occur in estimates of reflectivity ZH or specific differential phase Kdp. The results indicate that very large samples would be required to obtain adequate representation of the population characteristics for many radar applications. They also suggest that greater attention is needed to the sample sizes in the disdrometer data used in developing polarimetric rainfall-rate estimators or hydrometeor classification algorithms.
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Ghada, Wael, Nicole Estrella, and Annette Menzel. "Machine Learning Approach to Classify Rain Type Based on Thies Disdrometers and Cloud Observations." Atmosphere 10, no. 5 (May 7, 2019): 251. http://dx.doi.org/10.3390/atmos10050251.
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Rain microstructure parameters assessed by disdrometers are commonly used to classify rain into convective and stratiform. However, different types of disdrometer result in different values for these parameters. This in turn potentially deteriorates the quality of rain type classifications. Thies disdrometer measurements at two sites in Bavaria in southern Germany were combined with cloud observations to construct a set of clear convective and stratiform intervals. This reference dataset was used to study the performance of classification methods from the literature based on the rain microstructure. We also explored the possibility of improving the performance of these methods by tuning the decision boundary. We further identified highly discriminant rain microstructure parameters and used these parameters in five machine-learning classification models. Our results confirm the potential of achieving high classification performance by applying the concepts of machine learning compared to already available methods. Machine-learning classification methods provide a concrete and flexible procedure that is applicable regardless of the geographical location or the device. The suggested procedure for classifying rain types is recommended prior to studying rain microstructure variability or any attempts at improving radar estimations of rain intensity.
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Lempio, G. E., K. Bumke, and A. Macke. "Measurement of solid precipitation with an optical disdrometer." Advances in Geosciences 10 (April 26, 2007): 91–97. http://dx.doi.org/10.5194/adgeo-10-91-2007.
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Abstract. A study about measurements of solid precipitation using an optical disdrometer is presented. The optical disdrometer is an improved version of the ODM 470 disdrometer. It allows to measure hydrometeors within a size range of 0.4 to 22 mm in diameter. The main advantage of this instrument is its ability to estimate accurately precipitation even under strong wind conditions (Großklaus, 1996). To measure solid precipitation a geometrical model was developed to determine the mean cross-sectional area of snow crystals for different predefined shapes and sizes. It serves to develop an algorithm, which relates the mean cross sectional area of snow crystals to their maximum dimension, liquid water content, and terminal velocity. The algorithm was applied to disdrometer measurements during winter 1999/2000 in Uppsala/Sweden. Resulting precipitation was compared to independent measurements of a Geonor gauge and to manual measurements. In terms of daily precipitation the disdrometer shows a reliable performance.
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Moisseev, Dmitri N., and V. Chandrasekar. "Examination of the μ–Λ Relation Suggested for Drop Size Distribution Parameters." Journal of Atmospheric and Oceanic Technology 24, no. 5 (May 1, 2007): 847–55. http://dx.doi.org/10.1175/jtech2010.1.
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Abstract Raindrop size distributions are often assumed to follow a three-parameter gamma distribution. Since rain intensity retrieval from radar observations is an underdetermined problem, there is great interest in finding physical correlations between the parameters of the gamma distribution. One of the more common approaches is to measure naturally occurring drop size distributions (DSDs) using a disdrometer and to find DSD parameters by fitting a gamma distribution to these observations. Often the method of moments is used to retrieve the parameters of a gamma distribution from disdrometer observations. In this work the effect of the method of moments and data filtering on the relation between the parameters of the DSD is investigated, namely, the shape μ and the slope Λ parameters. For this study the disdrometer observations were simulated. In these simulations the gamma distribution parameters Nw, D0, and μ were randomly selected from a wide range of values that are found in rainfall. Then, using simulated disdrometer measurements, DSD parameters were estimated using the method of moments. It is shown that the statistical errors associated with data filtering of disdrometer measurements might produce a spurious relation between μ and Λ parameters. It is also shown that three independent disdrometer measurements can be used to verify the existence of such a relation.
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Henson, William, Geoff Austin, and Harry Oudenhoven. "Development of an Inexpensive Raindrop Size Spectrometer." Journal of Atmospheric and Oceanic Technology 21, no. 11 (November 1, 2004): 1710–17. http://dx.doi.org/10.1175/jtech1665.1.
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Abstract The deployment of weather radar, notably in mountainous terrain with many microclimates, requires the use of several or even many drop size spectrometers to provide confidence in the quantitative relation between radar reflectivity and rainfall. While there are several different commercial disdrometers available they are all expensive, large, or fragile, which militates against multiple deployment in the field. The design brief was for a reasonably accurate and sensitive, low-cost and rugged disdrometer to support field work. A design based on piezoceramic disks normally used in hydrophones is described. Calibration and typical field results are presented.
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Chandrasekar, V., and Enrico G. Gori. "Multiple Disdrometer Observations of Rainfall." Journal of Applied Meteorology 30, no. 11 (November 1991): 1514–20. http://dx.doi.org/10.1175/1520-0450(1991)030<1514:mdoor>2.0.co;2.
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Demina, V. V., and V. A. Donchenko. "Calibration of a holographic disdrometer." Russian Physics Journal 35, no. 5 (May 1992): 474–76. http://dx.doi.org/10.1007/bf00558862.
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Jaffrain, Joël, and Alexis Berne. "Experimental Quantification of the Sampling Uncertainty Associated with Measurements from PARSIVEL Disdrometers." Journal of Hydrometeorology 12, no. 3 (June 1, 2011): 352–70. http://dx.doi.org/10.1175/2010jhm1244.1.
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Abstract The variability of the (rain)drop size distribution (DSD) in time and space is an intrinsic property of rainfall, which is of primary importance for various environmental fields such as remote sensing of precipitation, for example. DSD observations are usually collected using disdrometers deployed at the ground level. Like any other measurement of a physical process, disdrometer measurements are affected by noise and sampling effects. This uncertainty must be quantified and taken into account in further analyses. This paper addresses this issue for the Particle Size Velocity (PARSIVEL) optical disdrometer by using a large dataset corresponding to light and moderate rainfall and collected from two collocated PARSIVELs deployed during 15 months in Lausanne, Switzerland. The relative sampling uncertainty associated with quantities characterizing the DSD—namely the total concentration of drops Nt and the median-volume diameter D0—is quantified for different temporal resolutions. Similarly, the relative sampling uncertainty associated with the estimates of the most commonly used weighted moments of the DSD (i.e., the rain-rate R, the radar reflectivity at horizontal polarization Zh, and the differential reflectivity Zdr) is quantified as well for different weather radar frequencies. The relative sampling uncertainty associated with estimates of Nt is below 13% for time steps longer than 60 s. For D0, it is below 8% for D0 values smaller than 1 mm. The associated sampling uncertainty for estimates of R is on the order of 15% at a temporal resolution of 60 s. For Zh, the sampling uncertainty is below 9% for Zh values below 35 dBZ at a temporal resolution of 60 s. For Zdr values below 0.75 dB, the sampling uncertainty is below 36% for all temporal resolutions. These analyses provide relevant information for the accurate quantification of the variability of the DSD from disdrometer measurements.
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Capozzi, Vincenzo, Clizia Annella, Mario Montopoli, Elisa Adirosi, Giannetta Fusco, and Giorgio Budillon. "Influence of Wind-Induced Effects on Laser Disdrometer Measurements: Analysis and Compensation Strategies." Remote Sensing 13, no. 15 (August 2, 2021): 3028. http://dx.doi.org/10.3390/rs13153028.
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Nowadays, laser disdrometers constitute a very appealing tool for measuring surface precipitation properties, by virtue of their capability to estimate not only the rainfall amount and intensity, but also the number, the size and the velocity of falling drops. However, disdrometric measures are affected by various sources of error being some of them related to environmental conditions. This work presents an assessment of Thies Clima laser disdrometer performance with a focus on the relationship between wind and the accuracy of the disdrometer output products. The 10-min average rainfall rate and total rainfall accumulation obtained by the disdrometer are systematically compared with the collocated measures of a standard tipping bucket rain gauge, the FAK010AA sensor, in terms of familiar statistical scores. A total of 42 rainy events, collected in a mountainous site of Southern Italy (Montevergine observatory), are used to support our analysis. The results show that the introduction of a new adaptive filtering in the disdrometric data processing can reduce the impact of sampling errors due to strong winds and heavy rain conditions. From a quantitative perspective, the novel filtering procedure improves by 8% the precipitation estimates with respect to the standard approach widely used in the literature. A deeper examination revealed that the signature of wind speed on raw velocity-diameter spectrographs gradually emerges with the rise of wind strength, thus causing a progressive increase of the wrongly allocated hydrometeors (which reaches 70% for wind speed greater than 8 m s−1). With the aid of reference rain-gauge rainfall data, we designed a second simple methodology that makes use of a correction factor to mitigate the wind-induced bias in disdrometric rainfall estimates. The resulting correction factor could be applied as an alternative to the adaptive filtering suggested by this study and may be of practical use when dealing with disdrometric data processing.
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Jameson, A. R., M. L. Larsen, and A. B. Kostinski. "Disdrometer Network Observations of Finescale Spatial–Temporal Clustering in Rain." Journal of the Atmospheric Sciences 72, no. 4 (March 31, 2015): 1648–66. http://dx.doi.org/10.1175/jas-d-14-0136.1.
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Abstract The spatial clustering of drops is a defining characteristic of rain on all scales from centimeters to kilometers. It is the physical basis for much of the observed variability in rain. The authors report here on the temporal–spatial 1-min counts using a network of 21 optical disdrometers over a small area near Charleston, South Carolina. These observations reveal significant differences between spatial and temporal structures (i.e., clustering) for different sizes of drops, which suggest that temporal observations of clustering cannot be used to infer spatial clustering simply using by an advection velocity as has been done in past studies. It is also shown that both spatial and temporal clustering play a role in rain variability depending upon the drop size. The more convective rain is dominated by spatial clustering while the opposite holds for the more stratiform rain. Like previous time series measurements by a single disdrometer but in contradiction with widely accepted drop size distribution power-law relations, it is also shown that there is a linear relation between 1-min averages of the rainfall rate R over the network and the average total number of drops Nt. However, the network (area) R–Nt relation differs from those derived strictly from time series observations by individual disdrometers. These differences imply that the temporal and spatial size distributions and their variabilities are not equivalent.
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Gires, Auguste, Ioulia Tchiguirinskaia, and Daniel Schertzer. "Two months of disdrometer data in the Paris area." Earth System Science Data 10, no. 2 (May 24, 2018): 941–50. http://dx.doi.org/10.5194/essd-10-941-2018.
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Abstract. The Hydrology, Meteorology, and Complexity laboratory of École des Ponts ParisTech (hmco.enpc.fr) has made a data set of optical disdrometer measurements available that come from a campaign involving three collocated devices from two different manufacturers, relying on different underlying technologies (one Campbell Scientific PWS100 and two OTT Parsivel2 instruments). The campaign took place in January–February 2016 in the Paris area (France). Disdrometers provide access to information on the size and velocity of drops falling through the sampling area of the devices of roughly a few tens of cm2. It enables the drop size distribution to be estimated and rainfall microphysics, kinetic energy, or radar quantities, for example, to be studied further. Raw data, i.e. basically a matrix containing a number of drops according to classes of size and velocity, along with more aggregated ones, such as the rain rate or drop size distribution with filtering, are available. Link to the data set: https://zenodo.org/record/1240168 (DOI: https://doi.org/10.5281/zenodo.1240168).
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Tapiador, F. J., A. Navarro, R. Moreno, A. Jiménez-Alcázar, C. Marcos, A. Tokay, L. Durán, et al. "On the Optimal Measuring Area for Pointwise Rainfall Estimation: A Dedicated Experiment with 14 Laser Disdrometers." Journal of Hydrometeorology 18, no. 3 (March 1, 2017): 753–60. http://dx.doi.org/10.1175/jhm-d-16-0127.1.
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Abstract Laser disdrometers measure the particle size distribution (PSD) of hydrometeors through a small cross-sectional (tens of square centimeters) surface. Such a limited area induces a sampling effect in the estimates of the PSD, which translates to error in the reflectivity–rain-rate (Z–R) relationship used for ground radar estimates of rainfall, estimates of kinetic energy of precipitation, and any other hydrometeorological application relying on particle size information. Here, the results of a dedicated experiment to estimate the extent of the effect of limited area sampling of rainfall are presented. Using 14 Parsivel, version 1 (Parsivel-1), disdrometers placed within 6 m2, it was found that the combined area of at least seven disdrometers is required for the estimates to start converging to a stable value. The results can be used to quantify the degree of over-/underestimation of precipitation parameters for a single instrument due to the limited collecting area effect. It has been found that a single disdrometer may underestimate instantaneous rain rate by 70%.
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Rivelli Zea, Lina, Stephen W. Nesbitt, Alfonso Ladino, Joseph C. Hardin, and Adam Varble. "Raindrop Size Spectrum in Deep Convective Regions of the Americas." Atmosphere 12, no. 8 (July 29, 2021): 979. http://dx.doi.org/10.3390/atmos12080979.
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This study compared drop size distribution (DSD) measurements on the surfaces, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter Dm, and normalized droplet concentration Nw) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader Nw distributions in Córdoba. The raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h−1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In the light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of Nw in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution.
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Tokay, Ali, David B. Wolff, and Walter A. Petersen. "Evaluation of the New Version of the Laser-Optical Disdrometer, OTT Parsivel2." Journal of Atmospheric and Oceanic Technology 31, no. 6 (June 1, 2014): 1276–88. http://dx.doi.org/10.1175/jtech-d-13-00174.1.
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Abstract A comparative study of raindrop size distribution measurements has been conducted at NASA’s Goddard Space Flight Center where the focus was to evaluate the performance of the upgraded laser-optical OTT Particle Size Velocity (Parsivel2; P2) disdrometer. The experimental setup included a collocated pair of tipping-bucket rain gauges, OTT Parsivel (P1) and P2 disdrometers, and Joss–Waldvogel (JW) disdrometers. Excellent agreement between the two collocated rain gauges enabled their use as a relative reference for event rain totals. A comparison of event total showed that the P2 had a 6% absolute bias with respect to the reference gauges, considerably lower than the P1 and JW disdrometers. Good agreement was also evident between the JW and P2 in hourly raindrop spectra for drop diameters between 0.5 and 4 mm. The P2 drop concentrations mostly increased toward small sizes, and the peak concentrations were mostly observed in the first three measurable size bins. The P1, on the other hand, underestimated small drops and overestimated the large drops, particularly in heavy rain rates. From the analysis performed, it appears that the P2 is an improvement over the P1 model for both drop size and rainfall measurements. P2 mean fall velocities follow accepted terminal fall speed relationships at drop sizes less than 1 mm. As a caveat, the P2 had approximately 1 m s−1 slower mean fall speed with respect to the terminal fall speed near 1 mm, and the difference between the mean measured and terminal fall speeds reduced with increasing drop size. This caveat was recognized as a software bug by the manufacturer and is currently being investigated.
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Tokay, Ali, Peter Hartmann, Alessandro Battaglia, Kenneth S. Gage, Wallace L. Clark, and Christopher R. Williams. "A Field Study of Reflectivity and Z–R Relations Using Vertically Pointing Radars and Disdrometers." Journal of Atmospheric and Oceanic Technology 26, no. 6 (June 1, 2009): 1120–34. http://dx.doi.org/10.1175/2008jtecha1163.1.
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Abstract Observations from a 16-month field study using two vertically pointing radars and a disdrometer at Wallops Island are analyzed to examine the consistency of the multi-instrument observations with respect to reflectivity and Z–R relations. The vertically pointing radars were operated at S and K bands and had a very good agreement in reflectivity at a gate centered on 175 and 177 m above ground level over a variety of storms. This agreement occurred even though the sampling volumes were of different size and even though the S band measured the reflectivity factor directly, whereas the K-band radar deduced it from attenuated K-band measurements. Indeed, the radar agreement in reflectivity at the collocated range gates was superior to that between the disdrometer and either radar. This is attributed in large part to the spatial separation of the disdrometer and radar sample volumes, although the lesser agreement observed in a prior collocated disdrometer–disdrometer comparison suggests the larger size of the radar sample volumes as well as the better overlap also play a role. Vertical variations in the observations were examined with the aid of the two radar profilers. As expected, the agreement between the disdrometer reflectivity and the reflectivity seen in the vertically pointing radars decreased with height. The effect of these vertical variations on determinations of Z–R relation coefficients was then examined, using a number of different methods for finding the best-fitting coefficients. The coefficient of the Z–R relation derived from paired disdrometer rain rate and radar reflectivity decreased with height, while the exponent of the Z–R relation increased with height. The coefficient and exponent of the Z–R relations also showed sensitivity to the choice of derivation method [linear and nonlinear least squares, fixed exponent, minimizing the root-mean-square difference (RMSD), and probability matching]. The influence of the time lag between the radar and disdrometer measurements was explored by examining the RMSD in reflectivity for paired measurements between 0- and 4-min lag. The no-lag conditions had the lowest RMSD up to 400 m, while 1-min lag gave the lowest RMSD at higher heights. The coefficient and exponent of the Z–R relations, on the other hand, did not have a significant change between no-lag- and 1-min-lag-based pairs.
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Zhang, Yun, Zuhang Wu, Lifeng Zhang, Yanqiong Xie, Yanbin Huang, and Hepeng Zheng. "Preliminary Study of Land–Sea Microphysics Associated with the East Asian Summer Monsoon Rainband and Its Application to GPM DPR." Journal of Atmospheric and Oceanic Technology 37, no. 7 (July 1, 2020): 1231–49. http://dx.doi.org/10.1175/jtech-d-19-0059.1.
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AbstractRaindrop size distribution (DSD) characteristics during the East Asian summer monsoon (EASM) were studied, using measurements from three OTT Particle Size Velocity (Parsivel) disdrometers in Nanjing, Chuzhou, and the northwestern Pacific (NWP), respectively. Western and eastern parts of the monsoon rainband were separated for a comparative study of the DSD variability. Along with disdrometer data, GPM Dual-Frequency Precipitation Radar (DPR), Fengyun-2E (FY-2E), MODIS, GPCP, ERA-Interim, and in situ radiosonde datasets are combined to illustrate the possible microphysical mechanisms for the significant DSD variability in two parts, in terms of convective intensity, cloud structure, and aerosol effects. The DSD characteristics of six rain-rate classes and two rainfall categories (convective and stratiform) were studied. The western part has larger mass-weighted mean diameter Dm while smaller normalized intercept log10(Nw) than the eastern part, and the convective clusters of the western part (land) could be identified more maritime-like than continental-like due to moisture transport from the tropical ocean, while that of the eastern part (sea) is between maritime-like and continental-like. Cross validation of GPM rainfall products are implemented based on surface disdrometer observations. DPR products manifest better performance over sea than land areas of the EASM rainband. Empirical Dm–Ze and Nw–Dm relations were also derived preliminarily to improve the GPM rain-retrieval algorithms in the EASM season.
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Michaelides, Silas, John Lane, and Takis Kasparis. "Effect of Vertical Air Motion on Disdrometer Derived Z-R Coefficients." Atmosphere 10, no. 2 (February 14, 2019): 77. http://dx.doi.org/10.3390/atmos10020077.
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For synoptic-scale motions the vertical velocity component is typically of the order of a few centimeters per second. In general, the vertical velocity is not measured directly but must be inferred from other meteorological fields that are measured directly. In the present study, a Joss–Waldvogel disdrometer was used in order to establish the drop size distributions (DSD) at Athalassa, Cyprus. Data from a radiosonde station co-located with the disdrometer were also collected which were subsequently used to derive estimates of vertical velocities. Meteorological fields, including vertical velocities, were extracted from an atmospheric reanalysis, for an area centered over the disdrometer and radiosonde station instrumentation. The disdrometer data were used to determine the Z-R disdrometer derived coefficients, A and b, where Z = A Rb. To model the vertical air effect on the Z-R disdrometer derived coefficients an idealistic notion of flux conservation of the DSD is adopted. This adjusted DSD (FCM-DSD) is based on the exponential DSD and is modified by the relationship between drop terminal velocity (D) and vertical air speed w . The FCM-DSD has a similar appearance to the popular gamma DSD for w < 0. A clear segregation is seen in the A-w plane for both data and model. The data points are also clearly segregated in the b- w plane, but the model points are on opposite sides of the w = 0 line. It is also demonstrated that vertical velocities can be extracted from radiosonde data if initial balloon volume is accurately measured, along with an accurate measurement of the mass of the complete radiosonde-balloon system. To accomplish this, vertical velocities from radiosonde data were compared to reanalysis vertical velocity fields. The resulting values of initial balloon volume are found to be within the range of measured values.
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Xie, Xinxin, Raquel Evaristo, Clemens Simmer, Jan Handwerker, and Silke Trömel. "Precipitation and microphysical processes observed by three polarimetric X-band radars and ground-based instrumentation during HOPE." Atmospheric Chemistry and Physics 16, no. 11 (June 10, 2016): 7105–16. http://dx.doi.org/10.5194/acp-16-7105-2016.
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Abstract. This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRRs) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol and KiXPol were continuously observing the central HOPE area near Forschungszentrum Jülich at a close distance, BoXPol observed the area from a distance of about 48.5 km. MRRs were deployed in the central HOPE area and one MRR close to BoXPol in Bonn, Germany. Seven disdrometers and three rain gauges providing point precipitation observations were deployed at five locations within a 5 km × 5 km region, while three other disdrometers were collocated with the MRR in Bonn. The daily rainfall accumulation at each rain gauge/disdrometer location estimated from the three X-band polarimetric radar observations showed very good agreement. Accompanying microphysical processes during the evolution of precipitation systems were well captured by the polarimetric X-band radars and corroborated by independent observations from the other ground-based instruments.
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Ekimov, Dmitry. "Digital holographic disdrometer for precipitation monitoring." Journal of Physics: Conference Series 1400 (November 2019): 066020. http://dx.doi.org/10.1088/1742-6596/1400/6/066020.
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Kruger, Anton, and Witold F. Krajewski. "Two-Dimensional Video Disdrometer: A Description." Journal of Atmospheric and Oceanic Technology 19, no. 5 (May 2002): 602–17. http://dx.doi.org/10.1175/1520-0426(2002)019<0602:tdvdad>2.0.co;2.
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Williams, Christopher R., Kenneth S. Gage, Wallace Clark, and Paul Kucera. "Monitoring the Reflectivity Calibration of a Scanning Radar Using a Profiling Radar and a Disdrometer." Journal of Atmospheric and Oceanic Technology 22, no. 7 (July 1, 2005): 1004–18. http://dx.doi.org/10.1175/jtech1759.1.
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Abstract This paper describes a method of absolutely calibrating and routinely monitoring the reflectivity calibration from a scanning weather radar using a vertically profiling radar that has been absolutely calibrated using a collocated surface disdrometer. The three instruments have different temporal and spatial resolutions, and the concept of upscaling is used to relate the small resolution volume disdrometer observations with the large resolution volume scanning radar observations. This study uses observations collected from a surface disdrometer, two profiling radars, and the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) scanning weather radar during the Texas–Florida Underflight-phase B (TEFLUN-B) ground validation field campaign held in central Florida during August and September 1998. The statistics from the 2062 matched profiling and scanning radar observations during this 2-month period indicate that the WSR-88D radar had a reflectivity 0.7 dBZ higher than the disdrometer-calibrated profiler, the standard deviation was 2.4 dBZ, and the 95% confidence interval was 0.1 dBZ. This study implies that although there is large variability between individual matched observations, the precision of a series of observations is good, allowing meaningful comparisons useful for calibration and monitoring.
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You, Cheol-Hwan, Mi-Young Kang, Dong-In Lee, and Jung-Tae Lee. "Approaches to radar reflectivity bias correction to improve rainfall estimation in Korea." Atmospheric Measurement Techniques 9, no. 5 (May 4, 2016): 2043–53. http://dx.doi.org/10.5194/amt-9-2043-2016.
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Abstract. Three methods for determining the reflectivity bias of single polarization radar using dual polarization radar reflectivity and disdrometer data (i.e., the equidistance line, overlapping area, and disdrometer methods) are proposed and evaluated for two low-pressure rainfall events that occurred over the Korean Peninsula on 25 August 2014 and 8 September 2012. Single polarization radar reflectivity was underestimated by more than 12 and 7 dB in the two rain events, respectively. All methods improved the accuracy of rainfall estimation, except for one case where drop size distributions were not observed, as the precipitation system did not pass through the disdrometer location. The use of these bias correction methods reduced the RMSE by as much as 50 %. Overall, the most accurate rainfall estimates were obtained using the overlapping area method to correct radar reflectivity.
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Liu, X. C., T. C. Gao, and L. Liu. "Effect of sampling variation on error of rainfall variables measured by optical disdrometer." Atmospheric Measurement Techniques Discussions 5, no. 6 (December 19, 2012): 8895–924. http://dx.doi.org/10.5194/amtd-5-8895-2012.
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Abstract. During the sampling process of precipitation particles by optical disdrometers, the randomness of particles and sampling variability has great impact on the accuracy of precipitation variables. Based on a marked point model of raindrop size distribution, the effect of sampling variation on drop size distribution and velocity distribution measurement using optical disdrometers are analyzed by Monte Carlo simulation. The results show that the samples number, rain rate, drop size distribution, and sampling size have different influences on the accuracy of rainfall variables. The relative errors of rainfall variables caused by sampling variation in a descending order as: water concentration, mean diameter, mass weighed mean diameter, mean volume diameter, radar reflectivity factor, and number density, which are independent with samples number basically; the relative error of rain variables are positively correlated with the margin probability, which is also positively correlated with the rain rate and the mean diameter of raindrops; the sampling size is one of the main factors that influence the margin probability, with the decreasing of sampling area, especially the decreasing of short side of sample size, the probability of margin raindrops is getting greater, hence the error of rain variables are getting greater, and the variables of median size raindrops have the maximum error. To ensure the relative error of rainfall variables measured by optical disdrometer less than 1%, the width of light beam should be at least 40 mm.
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Cao, Qing, Guifu Zhang, Edward Brandes, Terry Schuur, Alexander Ryzhkov, and Kyoko Ikeda. "Analysis of Video Disdrometer and Polarimetric Radar Data to Characterize Rain Microphysics in Oklahoma." Journal of Applied Meteorology and Climatology 47, no. 8 (August 1, 2008): 2238–55. http://dx.doi.org/10.1175/2008jamc1732.1.
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Abstract In this paper, data from three 2-dimensional video disdrometers (2DVDs) and an S-band polarimetric radar are used to characterize rain microphysics in Oklahoma. Sampling errors from the 2DVD measurements are quantified through side-by-side comparisons. In an attempt to minimize the sampling errors, a method of sorting and averaging based on two parameters (SATP) is proposed. The shape–slope (μ–Λ) relation of a constrained gamma (C-G) model is then refined for the retrieval of drop size distributions (DSDs) from polarimetric radar measurements. An adjustable term that is based on observed radar reflectivity and differential reflectivity is introduced to make the C-G DSD model more applicable. Radar retrievals using this improved DSD model are shown to provide good agreement with disdrometer observations and to give reasonable results, including in locations near the leading edge of convection where poorly sampled large drops are often observed.
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Lane, John E., Takis Kasparis, Philip T. Metzger, and W. Linwood Jones. "Spatial and Temporal Extrapolation of Disdrometer Size Distributions Based on a Lagrangian Trajectory Model of Falling Rain." Open Atmospheric Science Journal 3, no. 1 (June 25, 2009): 172–86. http://dx.doi.org/10.2174/1874282300903010172.
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Methodologies to improve disdrometer processing, loosely based on mathematical techniques common to the field of particle flow and fluid mechanics, are examined and tested. The inclusion of advection and vertical wind field estimates appears to produce significantly improved results in a Lagrangian hydrometeor trajectory model, in spite of very strict assumptions of noninteracting hydrometeors, constant vertical air velocity, and time independent advection during a radar scan time interval. Wind field data can be extracted from each radar elevation scan by plotting and analyzing reflectivity contours over the disdrometer site and by collecting the radar radial velocity data to obtain estimates of advection. Specific regions of disdrometer spectra (drop size versus time) often exhibit strong gravitational sorting signatures, from which estimates of vertical velocity can be extracted. These independent wind field estimates can be used as initial conditions to the Lagrangian trajectory simulation of falling hydrometeors.
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Lu, Junhui, Zhihong Yang, and Jianqiang Wang. "A membrane disdrometer based on membrane vibration." Measurement Science and Technology 26, no. 11 (October 14, 2015): 115103. http://dx.doi.org/10.1088/0957-0233/26/11/115103.
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Frasson, Renato Prata de Moraes, Luciana Kindl da Cunha, and Witold F. Krajewski. "Assessment of the Thies optical disdrometer performance." Atmospheric Research 101, no. 1-2 (July 2011): 237–55. http://dx.doi.org/10.1016/j.atmosres.2011.02.014.
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Van Den Broeke, Matthew. "Disdrometer, Polarimetric Radar, and Condensation Nuclei Observations of Supercell and Multicell Storms on 11 June 2018 in Eastern Nebraska." Atmosphere 11, no. 7 (July 21, 2020): 770. http://dx.doi.org/10.3390/atmos11070770.
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Disdrometer and condensation nuclei (CN) data are compared with operational polarimetric radar data for one multicell and one supercell storm in eastern Nebraska on 11 June 2018. The radar was located ~14.3 km from the instrumentation location and provided excellent observation time series with new low-level samples every 1–2 min. Reflectivity derived by the disdrometer and radar compared well, especially in regions with high number concentration of drops and reflectivity <45 dBZ. Differential reflectivity also compared well between the datasets, though it was most similar in the supercell storm. Rain rate calculated by the disdrometer closely matched values estimated by the radar when reflectivity and differential reflectivity were used to produce the estimate. Concentration of CN generally followed precipitation intensity for the leading convective cell, with evidence for higher particle concentration on the edges of the convective cell associated with outflow. The distribution of CN in the supercell was more complex and generally did not follow precipitation intensity.
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Schneebeli, M., J. Sakuragi, T. Biscaro, C. F. Angelis, I. Carvalho da Costa, C. Morales, L. Baldini, and L. A. T. Machado. "Observations of tropical rain with a polarimetric X-band radar: first results from the CHUVA campaign." Atmospheric Measurement Techniques Discussions 5, no. 1 (February 17, 2012): 1717–61. http://dx.doi.org/10.5194/amtd-5-1717-2012.
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Abstract. A polarimetric X-band radar has been deployed during one month (April 2011) for a field campaign in Fortaleza, Brazil, together with additional sensors like a Ka-band vertically pointing frequency modulated continuous wave (FMCW) radar and three laser disdrometers. The disdrometers as well as the FMCW radar are capable of measuring the rain drop size distributions (DSDs), hence making it possible to forward-model theoretical polarimetric X-band radar observables at the point where the instruments are located. This set-up allows to thoroughly test the accuracy of the X-band radar measurements as well as the algorithms that are used to correct the radar data for radome and rain attenuation. In the first campaign in Fortaleza it was found that radome attenuation dominantly affects the measurements. With an algorithm that is based on the self-consistency of the polarimetric observables, the radome induced reflectivity offset was estimated. Offset corrected measurements were then further corrected for rain attenuation with two different schemes. The performance of the post-processing steps is being analyzed by comparing the data with disdrometer-inferred polarimetric variables that were measured in a distance of 20 km to the radar.
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Conrick, Robert, Joseph P. Zagrodnik, and Clifford F. Mass. "Dual-Polarization Radar Retrievals of Coastal Pacific Northwest Raindrop Size Distribution Parameters Using Random Forest Regression." Journal of Atmospheric and Oceanic Technology 37, no. 2 (February 2020): 229–42. http://dx.doi.org/10.1175/jtech-d-19-0107.1.
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AbstractRadar retrievals of drop size distribution (DSD) parameters are developed and evaluated over the mountainous Olympic Peninsula of Washington State. The observations used to develop retrievals were collected during the 2015/16 Olympic Mountain Experiment (OLYMPEX) and included the NASA S-band dual-polarimetric (NPOL) radar and a collection of second-generation Particle Size and Velocity (PARSIVEL2) disdrometers over the windward slopes of the barrier. Nonlinear and random forest regressions are applied to the PARSIVEL2 data to develop retrievals for median volume diameter, liquid water content, and rain rate. Improvement in DSD retrieval accuracy, defined by the mean error of the retrieval relative to PARSIVEL2 observations, was achieved when using the random forest model when compared with nonlinear regression. Evaluation of disdrometer observations and the retrievals from NPOL indicate that the radar retrievals can accurately reproduce observed DSDs in this region, including the common wintertime regime of small but numerous raindrops that is important there. NPOL retrievals during the OLYMPEX period are further evaluated using two-dimensional video disdrometers (2DVD) and vertically pointing Micro Rain Radars. Results indicate that radar retrievals using random forests may be skillful in capturing DSD characteristics in the lowest portions of the atmosphere.