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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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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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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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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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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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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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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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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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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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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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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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Larsen, Michael L., and Katelyn A. O'Dell. "Sampling variability effects in drop-resolving disdrometer observations." Journal of Geophysical Research: Atmospheres 121, no. 19 (October 10, 2016): 11,777–11,791. http://dx.doi.org/10.1002/2016jd025491.
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Testik, F. Y., and M. K. Rahman. "High-Speed Optical Disdrometer for Rainfall Microphysical Observations." Journal of Atmospheric and Oceanic Technology 33, no. 2 (February 2016): 231–43. http://dx.doi.org/10.1175/jtech-d-15-0098.1.
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AbstractA high-speed optical disdrometer (HOD) that was developed for measuring rainfall microphysical quantities, including raindrop shape, size distribution, and fall velocity/acceleration, is the subject of this paper. The main components of the HOD are a high-speed video camera, a light-emitting diode (LED) light, and a sensing unit to detect raindrops passing through the camera view frame. The high-speed video camera is directed at the LED light to capture the silhouettes of the backlit drops when triggered by a raindrop that is detected within a specified focal depth by the sensing unit. The use of a sensing unit enables the confinement of a measurement volume around the camera focal plane. This innovative operation principle ensures the capture of sharp images of raindrop silhouettes, which are then digitally processed to provide accurate information on various raindrop characteristics. The measurement capabilities of the HOD were evaluated through both laboratory and field tests. In the laboratory tests, high-precision spherical lenses with known diameters and water drops of different sizes generated for a known volume of water were used. In the field tests, the HOD was evaluated against a reference rain gauge in a number of rain events. These tests demonstrated the precise accuracy of HOD measurements and the HOD’s technological readiness for field deployment for various applications. It is expected that the HOD will play an important role in generating new insights on raindrop dynamics and related research through its unique measurement capability of providing sequential high-speed images of raindrops.
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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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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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Kalina, Evan A., Katja Friedrich, Scott M. Ellis, and Donald W. Burgess. "Comparison of Disdrometer and X-Band Mobile Radar Observations in Convective Precipitation." Monthly Weather Review 142, no. 7 (June 27, 2014): 2414–35. http://dx.doi.org/10.1175/mwr-d-14-00039.1.
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Abstract Microphysical data from thunderstorms are sparse, yet they are essential to validate microphysical schemes in numerical models. Mobile, dual-polarization, X-band radars are capable of providing a wealth of data that include radar reflectivity, drop shape, and hydrometeor type. However, X-band radars suffer from beam attenuation in heavy rainfall and hail, which can be partially corrected with attenuation correction schemes. In this research, the authors compare surface disdrometer observations to results from a differential phase-based attenuation correction scheme. This scheme is applied to data recorded by the National Oceanic and Atmospheric Administration (NOAA) X-band dual-polarized (NOXP) mobile radar, which was deployed during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2). Results are presented from five supercell thunderstorms and one squall line (183 min of data). The median disagreement (radar–disdrometer) in attenuation-corrected reflectivity Z and differential reflectivity ZDR is just 1.0 and 0.19 dB, respectively. However, two data subsets reveal much larger discrepancies in Z (ZDR): 5.8 (1.6) dB in a hailstorm and −13 (−0.61) dB when the radar signal quality index (SQI) is less than 0.8. The discrepancies are much smaller when disdrometer and S-band Weather Surveillance Radar-1988 Doppler (WSR-88D) Z are compared, with differences of −1.5 dB (hailstorm) and −0.66 dB (NOXP SQI < 0.8). A comparison of the hydrometeor type retrieved from disdrometer and NOXP radar data is also presented, in which the same class is assigned 63% of the time.
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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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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.
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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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Zhang, Guifu, Juanzhen Sun, and Edward A. Brandes. "Improving Parameterization of Rain Microphysics with Disdrometer and Radar Observations." Journal of the Atmospheric Sciences 63, no. 4 (April 1, 2006): 1273–90. http://dx.doi.org/10.1175/jas3680.1.
Full textAbstract:
Abstract Disdrometer observations indicate that the raindrop size distribution (DSD) can be represented by a constrained-gamma (CG) distribution model. The model is used to retrieve DSDs from polarization radar measurements of reflectivity and differential reflectivity and to characterize rain microphysics and physical processes such as evaporation, accretion, and precipitation. The CG model parameterization is simplified to a single parameter for application in single-moment numerical models. This simplified parameterization is applied in the Variational Doppler Radar Analysis System (VDRAS) using Kessler-type parameterizations for model initialization and forecasting. Results are compared to those for the Marshall–Palmer (MP) DSD model. It is found that the simplified CG model parameterization better preserves the stratiform rain and produces better forecasts than the MP model parameterization.
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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.
Full textAbstract:
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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Thurai, Merhala, Viswanathan Bringi, David Wolff, David Marks, and Charanjit Pabla. "Testing the Drop-Size Distribution Based Separation of Stratiform and Convective Rain Using Radar and Disdrometer Data from a Midlatitude Coastal Region." Environmental Sciences Proceedings 4, no. 1 (November 13, 2020): 13. http://dx.doi.org/10.3390/ecas2020-08125.
Full textAbstract:
Stratiform and convective rain are associated with different microphysical processes and generally produce drop-size distributions (DSDs) with different characteristics. A previous study, using data from a tropical coastal location found that the two rain types could be separated in the NW–Dm space, where Dm is the mass-weighted mean diameter and NW is the normalized intercept parameter. The separation method has also been tested using data and observations from a midlatitude continental location with semiarid climate, and a subtropical continental location. In this paper, we investigate the same separation technique using data and observations from a midlatitude coastal region. Three-minute DSDs from disdrometer measurements were used for the NW versus Dm based classification and were compared with simultaneous observations from an S-band polarimetric radar 38 km away from the disdrometer site. Specifically, range-height indicator (RHI) scans over the disdrometer were used for confirmation. The results showed that there was no need to modify the separation criteria from previous studies. Scattering calculations using the three-minute DSDs were used to derive retrieval equations for Nw and Dm for the S-band radar and applied to the RHI scans to identify convective and stratiform rain regions. Two events are shown as illustrative examples.
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Zhang, Guifu, Sean Luchs, Alexander Ryzhkov, Ming Xue, Lily Ryzhkova, and Qing Cao. "Winter Precipitation Microphysics Characterized by Polarimetric Radar and Video Disdrometer Observations in Central Oklahoma." Journal of Applied Meteorology and Climatology 50, no. 7 (July 2011): 1558–70. http://dx.doi.org/10.1175/2011jamc2343.1.
Full textAbstract:
AbstractThe study of precipitation in different phases is important to understanding the physical processes that occur in storms, as well as to improving their representation in numerical weather prediction models. A 2D video disdrometer was deployed about 30 km from a polarimetric weather radar in Norman, Oklahoma, (KOUN) to observe winter precipitation events during the 2006/07 winter season. These events contained periods of rain, snow, and mixed-phase precipitation. Five-minute particle size distributions were generated from the disdrometer data and fitted to a gamma distribution; polarimetric radar variables were also calculated for comparison with KOUN data. It is found that snow density adjustment improves the comparison substantially, indicating the importance of accounting for the density variability in representing model microphysics.
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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.
Full textAbstract:
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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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.
Full textAbstract:
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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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.
Full textAbstract:
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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Defer, E., and M. Anagnostou. "Characterization of the precipitation in southwestern part of Greece with X-band Doppler radar, 2-D video disdrometer and rain gauges." Advances in Geosciences 7 (February 16, 2006): 121–25. http://dx.doi.org/10.5194/adgeo-7-121-2006.
Full textAbstract:
Abstract. We document precipitation in the southwestern part of Greece with the National Observatory of Athens (NOA) X-band radar, NOA 2D video disdrometer and a network of rain gauges. The observations were collected between February and April 2004. Time evolution of the drop size distribution (DSD) is presented for the 9 March 2004 case where rain rate (computed on 1-min period) was measured up to 80 mm/h and reflectivity at the location of the disdrometer exceeded 40 dBZ. We then present the differences of DSD as function of the rain rate for the studied case as well as for the entire observations of the field experiment. It shows that higher the rain rate is, larger the range of the DSD and higher the concentration of the raindrops are.
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Chase, Randy J., Stephen W. Nesbitt, and Greg M. McFarquhar. "Evaluation of the Microphysical Assumptions within GPM-DPR Using Ground-Based Observations of Rain and Snow." Atmosphere 11, no. 6 (June 11, 2020): 619. http://dx.doi.org/10.3390/atmos11060619.
Full textAbstract:
The Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM-DPR) provides an opportunity to investigate hydrometeor properties. Here, an evaluation of the microphysical framework used within the GPM-DPR retrieval was undertaken using ground-based disdrometer measurements in both rain and snow with an emphasis on the evaluation of snowfall retrieval. Disdrometer measurements of rain show support for the two separate prescribed relations within the GPM-DPR algorithm between the precipitation rate (R) and the mass weighted mean diameter (
D
m
) with a mean absolute percent error (
M
A
P
E
) on R of
29%
and
47%
and a mean bias percentage (
M
B
P
) of
−
6%
and
−
20%
for the stratiform and convective relation, respectively. Ground-based disdrometer measurements of snow show higher MAPE and MBP values in the retrieval of R, at
77%
and
−
52%
, respectively, compared to the stratiform rain relation. An investigation using the disdrometer-measured fall velocity and mass in the calculation of R and
D
m
illustrates that the variability found in hydrometeor mass causes a poor correlation between R and
D
m
in snowfall. The results presented here suggest that
R
−
D
m
retrieval is likely not optimal in snowfall, and other retrieval techniques for R should be explored.
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Thurai, Merhala, Viswanathan Bringi, David Wolff, David Marks, and Charanjit Pabla. "Testing the Drop-Size Distribution-Based Separation of Stratiform and Convective Rain Using Radar and Disdrometer Data from a Mid-Latitude Coastal Region." Atmosphere 12, no. 3 (March 17, 2021): 392. http://dx.doi.org/10.3390/atmos12030392.
Full textAbstract:
Stratiform and convective rain are associated with different microphysical processes and generally produce drop-size distributions (DSDs) with different characteristics. Previous studies using data from (a) a tropical coastal location, (b) a mid-latitude continental location with semi-arid climate, and (c) a sub-tropical continental location, found that the two rain types could be separated in the NW–Dm space, where Dm is the mass-weighted mean diameter and NW is the normalized intercept parameter. In this paper, we investigate the same separation technique using data and observations from a mid-latitude coastal region. Three-minute DSDs from disdrometer measurements are used for the NW- versus Dm-based classification and are compared with simultaneous observations from an S-band polarimetric radar 38 km away from the disdrometer site. Specifically, RHI (range-height indicator) scans over the disdrometer were used for confirmation. Results show that there was no need to modify the separation criteria from previous studies. Three-minute DSDs from the same location were used as input to scattering calculations to derive retrieval equations for NW and Dm for the S-band radar using an improved technique and applied to the RHI scans to identify convective and stratiform rain regions. Two events are shown as illustrative examples.
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Battaglia, Alessandro, Elke Rustemeier, Ali Tokay, Ulrich Blahak, and Clemens Simmer. "PARSIVEL Snow Observations: A Critical Assessment." Journal of Atmospheric and Oceanic Technology 27, no. 2 (February 1, 2010): 333–44. http://dx.doi.org/10.1175/2009jtecha1332.1.
Full textAbstract:
Abstract The performance of the laser-optical Particle Size Velocity (PARSIVEL) disdrometer is evaluated to determine the characteristics of falling snow. PARSIVEL’s measuring principle is reexamined to detect its limitations and pitfalls when applied to solid precipitation. This study uses snow observations taken during the Canadian Cloudsat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Validation Project (C3VP) campaign, when two PARSIVEL instruments were collocated with a single two-dimensional disdrometer (2-DVD), which allows more detailed observation of snowflakes. When characterizing the snowflake size, PARSIVEL instruments inherently retrieve only one size parameter, which is approximately equal to the widest horizontal dimension (more accurately with large snowflakes) and that has no microphysical meaning. Unlike for raindrops, the equivolume PARSIVEL diameter—the PARSIVEL output variable—has no physical counterpart for snowflakes. PARSIVEL’s fall velocity measurement may not be accurate for a single snowflake particle. This is due to the internally assumed relationship between horizontal and vertical snow particle dimensions. The uncertainty originates from the shape-related factor, which tends to depart more and more from unity with increasing snowflake sizes and can produce large errors. When averaging over a large number of snowflakes, the correction factor is size dependent with a systematic tendency to an underestimation of the fall speed (but never exceeding 20%). Compared to a collocated 2-DVD for long-lasting events, PARSIVEL seems to overestimate the number of small snowflakes and large particles. The disagreement between PARSIVEL and 2-DVD snow measurements can only be partly ascribed to PARSIVEL intrinsic limitations (border effects and sizing problems), but it has to deal with the difficulties and drawbacks of both instruments in fully characterizing snow properties.
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Myagkov, Alexander, Stefan Kneifel, and Thomas Rose. "Evaluation of the reflectivity calibration of W-band radars based on observations in rain." Atmospheric Measurement Techniques 13, no. 11 (November 3, 2020): 5799–825. http://dx.doi.org/10.5194/amt-13-5799-2020.
Full textAbstract:
Abstract. This study presents two methods for evaluating the reflectivity calibration of W-band cloud radars. Both methods use natural rain as a reference target. The first approach is based on a self-consistency method of polarimetric radar variables, which is widely used in the precipitation radar community. As previous studies pointed out, the method cannot be directly applied to higher frequencies where non-Rayleigh scattering effects and attenuation have a nonnegligible influence on radar variables. The method presented here solves this problem by using polarimetric Doppler spectra to separate backscattering and propagational effects. New fits between the separated radar variables allow one to estimate the absolute radar calibration using a minimization technique. The main advantage of the self-consistency method is its lower dependence on the spatial variability in radar drop size distribution (DSD). The estimated uncertainty of the method is ±0.7 dB. The method was applied to three intense precipitation events, and the retrieved reflectivity offsets were within the estimated uncertainty range. The second method is an improvement on the conventional disdrometer-based approach, where reflectivity from the lowest range gate is compared to simulated reflectivity using surface disdrometer observations. The improved method corrects, first, for the time lag between surface DSD observations and the radar measurements at a certain range. In addition, the effect of evaporation of raindrops on their way towards the surface is mitigated. The disdrometer-based method was applied to 12 rain events observed by vertically pointed W-band radar and showed repeatable estimates of the reflectivity offsets at rain rates below 4 mm h−1 within ±0.9 dB. The proposed approaches can analogously be extended to Ka-band radars. Although very different in terms of complexity, both methods extend existing radar calibration evaluation approaches, which are inevitably needed for the growing cloud radar networks in order to provide high-quality radar observation to the atmospheric community.
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Anagnostou, Marios N., Emmanouil N. Anagnostou, Jothiram Vivekanandan, and Fred L. Ogden. "Comparison of Two Raindrop Size Distribution Retrieval Algorithms for X-Band Dual Polarization Observations." Journal of Hydrometeorology 9, no. 3 (June 1, 2008): 589–600. http://dx.doi.org/10.1175/2007jhm904.1.
Full textAbstract:
Abstract In this study the authors evaluate two algorithms, the so-called beta (β) and constrained methods, proposed for retrieving the governing parameters of the “normalized” gamma drop size distribution (DSD) from dual-polarization radar measurements. The β method treats the drop axis ratio as a variable and computes drop shape and DSD parameters from radar reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase shift (KDP). The constrained method assumes that the axis-ratio relation is fixed and computes DSD parameters from ZH, ZDR, and an empirical relation between the DSD slope and shape parameters. The two techniques are evaluated for polarimetric X-band radar observations by comparing retrieved DSD parameters with disdrometer observations and examining simulated radar parameters for consistency. Error effects on the β method and constrained method retrievals are analyzed. The β approach is found to be sensitive to errors in KDP and to be less consistent with observations. Large retrieved β values are found to be associated with large retrieved DSD shape parameters and small median drop diameters. The constrained method provides reasonable rain DSD retrievals that agree better with disdrometer observations.
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Lam, Hong Yin, Jafri Din, and Siat Ling Jong. "Statistical and Physical Descriptions of Raindrop Size Distributions in Equatorial Malaysia from Disdrometer Observations." Advances in Meteorology 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/253730.
Full textAbstract:
This work investigates the physical characteristics of raindrop size distribution (DSD) in an equatorial heavy rain region based on three years of disdrometer observations carried out at Universiti Teknologi Malaysia’s (UTM’s) campus in Kuala Lumpur, Malaysia. The natural characteristics of DSD are deduced, and the statistical results are found to be in accordance with the findings obtained from others disdrometer measurements. Moreover, the parameters of the Gamma distribution and the normalized Gamma model are also derived by means of method of moment (MoM) and maximum likelihood estimation (MLE). Their performances are subsequently validated using the rain rate estimation accuracy: the normalized Gamma model with the MLE-generated shape parameterµwas found to provide better accuracy in terms of long-term rainfall rate statistics, which reflects the peculiarities of the local climatology in this heavy rain region. These results not only offer a better understanding of the microphysical nature of precipitation in this heavy rain region but also provide essential information that may be useful for the scientific community regarding remote sensing and radio propagation.
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Bukovčić, Petar, Dušan Zrnić, and Guifu Zhang. "Winter Precipitation Liquid–Ice Phase Transitions Revealed with Polarimetric Radar and 2DVD Observations in Central Oklahoma." Journal of Applied Meteorology and Climatology 56, no. 5 (May 2017): 1345–63. http://dx.doi.org/10.1175/jamc-d-16-0239.1.
Full textAbstract:
AbstractObservations and analysis of an ice–liquid phase precipitation event, collected with an S-band polarimetric KOUN radar and a two-dimensional video disdrometer (2DVD) in central Oklahoma on 20 January 2007, are presented. Using the disdrometer measurements, precipitation is classified either as ice pellets or rain/freezing rain. The disdrometer observations showed fast-falling and slow-falling particles of similar size. The vast majority (>99%) were fast falling with observed velocities close to those of raindrops with similar sizes. In contrast to the smaller particles (<1 mm in diameter), bigger ice pellets (>1.5 mm) were relatively easy to distinguish because their shapes differ from the raindrops. The ice pellets were challenging to detect by looking at conventional polarimetric radar data because of the localized and patchy nature of the ice phase and their occurrence close to the ground. Previously published findings referred to cases in which ice pellet areas were centered on the radar location and showed a ringlike structure of enhanced differential reflectivity ZDR and reduced copolar correlation coefficient ρhv and horizontal reflectivity ZH in PPI images. In this study, a new, unconventional way of looking at polarimetric radar data is introduced: slanted vertical profiles (SVPs) at low (0°–1°) radar elevations. From the analysis of the localized and patchy structures using SVPs, the polarimetric refreezing signature, reflected in local enhancement in ZDR and reduction in ZH and ρhv, became much more evident. Model simulations of sequential drop freezing using Marshall–Palmer DSDs along with the observations suggest that preferential freezing of small drops may be responsible for the refreezing polarimetric signature, as suggested in previous studies.
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Derin, Yagmur, Emmanouil Anagnostou, Marios Anagnostou, and John Kalogiros. "Evaluation of X-Band Dual-Polarization Radar-Rainfall Estimates from OLYMPEX." Journal of Hydrometeorology 20, no. 9 (September 1, 2019): 1941–59. http://dx.doi.org/10.1175/jhm-d-19-0097.1.
Full textAbstract:
Abstract The difficulty of representing high rainfall variability over mountainous areas using ground-based sensors is an open problem in hydrometeorology. Observations from locally deployed dual-polarization X-band radar have the advantage of providing multiparameter measurements near ground that carry significant information useful for estimating drop size distribution (DSD) and surface rainfall rate. Although these measurements are at fine spatiotemporal scale and are less inhibited by complex topography than operational radar network observations, uncertainties in their estimates necessitate error characterization based upon in situ measurements. During November 2015–February 2016, a dual-polarized Doppler on Wheels (DOW) X-band radar was deployed on the Olympic Peninsula of Washington State as part of NASA’s Olympic Mountain Experiment (OLYMPEX). In this study, rain gauges and disdrometers from a dense network positioned within 40 km of DOW are used to evaluate the self-consistency and accuracy of the attenuation and brightband/vertical profile corrections, and rain microphysics estimation by SCOP-ME, an algorithm that uses optimal parameterization and best-fitted functions of specific attenuation coefficients and DSD parameters with radar polarimetric measurements. In addition, the SCOP-ME precipitation microphysical retrievals of median volume diameter D0 and normalized intercept parameter NW are evaluated against corresponding parameters derived from the in situ disdrometer spectra observations.
36
Morris, M. P., P. B. Chilson, T. J. Schuur, and A. Ryzhkov. "Microphysical retrievals from simultaneous polarimetric and profiling radar observations." Annales Geophysicae 27, no. 12 (December 7, 2009): 4435–48. http://dx.doi.org/10.5194/angeo-27-4435-2009.
Full textAbstract:
Abstract. The character of precipitation detected at the surface is the final product of many microphysical interactions in the cloud above, the combined effects of which may be characterized by the observed drop size distribution (DSD). This necessitates accurate retrieval of the DSD from remote sensing data, especially radar as it offers large areal coverage, high spatial resolution, and rigorous quality control and testing. Combined instrument observations with a UHF wind profiler, an S-band polarimetric weather radar, and a video disdrometer are analyzed for two squall line events occuring during the calendar year 2007. UHF profiler Doppler velocity spectra are used to estimate the DSD aloft, and are complemented by DSDs retrieved from an exponential model applied to polarimetric data. Ground truth is provided by the disdrometer. A complicating factor in the retrieval from UHF profiler spectra is the presence of ambient air motion, which can be corrected using the method proposed by Teshiba et al. (2009), in which a comparison between idealized Doppler spectra calculated from the DSDs retrieved from KOUN and those retrieved from contaminated wind profiler spectra is performed. It is found that DSDs measured using the distrometer at the surface and estimated using the wind profiler and polarimetric weather radar generally showed good agreement. The DSD retrievals using the wind profiler were improved when the estimates of the vertical wind were included into the analysis, thus supporting the method of Teshiba et al. (2009). Furthermore, the the study presents a method of investigating the time and height structure of DSDs.
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Zhang, Guifu, Ming Xue, Qing Cao, and Daniel Dawson. "Diagnosing the Intercept Parameter for Exponential Raindrop Size Distribution Based on Video Disdrometer Observations: Model Development." Journal of Applied Meteorology and Climatology 47, no. 11 (November 1, 2008): 2983–92. http://dx.doi.org/10.1175/2008jamc1876.1.
Full textAbstract:
Abstract The exponential distribution N(D) = N0 exp(−ΛD) with a fixed intercept parameter N0 is most commonly used to represent raindrop size distribution (DSD) in rainfall estimation and in single-moment bulk microphysics parameterization schemes. Disdrometer observations show that the intercept parameter is far from constant and systematically depends on the rain type and intensity. In this study, a diagnostic relation of N0 as a function of rainwater content W is derived based on two-dimensional video disdrometer (2DVD) measurements. The data reveal a clear correlation between N0 and W in which N0 increases as W increases. To minimize the effects of sampling error, a relation between two middle moments is used to derive the N0–W relation. This diagnostic relation has the potential to improve rainfall estimation and bulk microphysics parameterizations. A parameterization scheme for warm rain processes based on the diagnostic N0 DSD model is formulated and presented. The diagnostic N0-based parameterization scheme yields less evaporation and accretion for stratiform rain than that using fixed N0.
38
Larsen, Michael L., Alexander B. Kostinski, and Ali Tokay. "Observations and Analysis of Uncorrelated Rain." Journal of the Atmospheric Sciences 62, no. 11 (November 1, 2005): 4071–83. http://dx.doi.org/10.1175/jas3583.1.
Full textAbstract:
Abstract Most microphysical models in precipitation physics and radar meteorology assume (at least implicitly) that raindrops are completely uncorrelated in space and time. Yet, several recent studies have indicated that raindrop arrivals are often temporally and spatially correlated. Resolution of this conflict must begin with observations of perfectly uncorrelated rainfall, should such “perfectly steady rain” exist at all. Indeed, it does. Using data with high temporal precision from a two-dimensional video disdrometer and the pair-correlation function, a scale-localized statistical tool, several ∼10–20-min rain episodes have been uncovered where no clustering among droplet arrival times is found. This implies that (i) rain events exist where current microphysical models can be tested in an optimal manner and (ii) not all rain can be properly described using fractals.
39
Renggono, Findy. "PENGAMATAN KEJADIAN HUJAN DENGAN DISDROMETER DAN MICRO RAIN RADAR DI SERPONG." Jurnal Sains & Teknologi Modifikasi Cuaca 18, no. 1 (November 30, 2017): 1. http://dx.doi.org/10.29122/jstmc.v18i1.2199.
Full textAbstract:
IntisariPengamatan hujan dengan menggunakan beberapa peralatan yang mempunyai metode berbeda telah dilakukan di wilayah Serpong. Peralatan yang digunakan adalah Disdrometer dan Micro Rain Radar (MRR). Kedua peralatan tersebut dipasang pada satu lokasi yang sama agar dapat mengukur kejadian hujan yang sama. Pengamatan dilakukan pada akhir tahun 2016 selama 5 bulan, disesuaikan dengan kondisi dimana musim hujan sudah mulai masuk untuk wilayah ini. Perbandingan pengukuran yang telah dilakukan menunjukkan kesesuaian hasil antara kedua peralatan tersebut. Pengamatan distribusi ukuran butir air pada empat kejadian hujan antara bulan Agustus-Desember 2016 menunjukkan bahwa hujan konvektif mempunyai distribusi ukuran yang lebih besar dibandingkan hujan stratiform. AbstractRain observation by using several instruments having different method has been done in Serpong area. The instrument used is Disdrometer and Micro Rain Radar (MRR). Both instruments are installed in the same location in order to measure the same rain events. Observations were made at the end of 2016 for 5 months, adjusted to the conditions in which the rainy season has begun to enter for the region. Comparison of measurements that have been done indicate the suitability of the results between the two instrument. Drop size distribution of four rain event during August - December 2016 shows that the drop size distribution on convective rain broaden than on stratiform rain.
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Gatlin, Patrick N., Merhala Thurai, V. N. Bringi, Walter Petersen, David Wolff, Ali Tokay, Lawrence Carey, and Matthew Wingo. "Searching for Large Raindrops: A Global Summary of Two-Dimensional Video Disdrometer Observations." Journal of Applied Meteorology and Climatology 54, no. 5 (May 2015): 1069–89. http://dx.doi.org/10.1175/jamc-d-14-0089.1.
Full textAbstract:
AbstractA dataset containing 9637 h of two-dimensional video disdrometer observations consisting of more than 240 million raindrops measured at diverse climatological locations was compiled to help characterize underlying drop size distribution (DSD) assumptions that are essential to make precise retrievals of rainfall using remote sensing platforms. This study concentrates on the tail of the DSD, which largely impacts rainfall retrieval algorithms that utilize radar reflectivity. The maximum raindrop diameter was a median factor of 1.8 larger than the mass-weighted mean diameter and increased with rainfall rate. Only 0.4% of the 1-min DSD spectra were found to contain large raindrops exceeding 5 mm in diameter. Large raindrops were most abundant at the tropical locations, especially in Puerto Rico, and were largely concentrated during the spring, especially at subtropical locations. Giant raindrops exceeding 8 mm in diameter occurred at tropical, subtropical, and high-latitude continental locations. The greatest numbers of giant raindrops were found in the subtropical locations, with the largest being a 9.7-mm raindrop that occurred in northern Oklahoma during the passage of a hail-producing thunderstorm. These results suggest large raindrops are more likely to fall from clouds that contain hail, especially those raindrops exceeding 8 mm in diameter.
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Miriovsky, Benjamin J., A. Allen Bradley, William E. Eichinger, Witold F. Krajewski, Anton Kruger, Brian R. Nelson, Jean-Dominique Creutin, et al. "An Experimental Study of Small-Scale Variability of Radar Reflectivity Using Disdrometer Observations." Journal of Applied Meteorology 43, no. 1 (January 2004): 106–18. http://dx.doi.org/10.1175/1520-0450(2004)043<0106:aesosv>2.0.co;2.
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Bukovčić, Petar, Dušan Zrnić, and Guifu Zhang. "Convective–stratiform separation using video disdrometer observations in central Oklahoma – the Bayesian approach." Atmospheric Research 155 (March 2015): 176–91. http://dx.doi.org/10.1016/j.atmosres.2014.12.002.
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Lavanya, S., and N. V. P. Kirankumar. "Classification of tropical coastal precipitating cloud systems using disdrometer observations over Thumba, India." Atmospheric Research 253 (May 2021): 105477. http://dx.doi.org/10.1016/j.atmosres.2021.105477.
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Krajewski, W. F., A. Kruger, and V. Nespor. "Experimental and numerical studies of small-scale rainfall measurements and variability." Water Science and Technology 37, no. 11 (June 1, 1998): 131–38. http://dx.doi.org/10.2166/wst.1998.0452.
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A high-resolution rainfall observatory was established at the Iowa Institute of Hydraulic Research to support studies of small scale rainfall variability. It includes a vertically pointing X-band radar, a two-dimensional video disdrometer, an optical rain gauge, a standard tipping bucket raingauge, and high temporal resolution sensors for measurements of wind velocity and direction, temperature, humidity, and pressure. All the instruments are collocated. The observatory is being upgraded to include a Doppler processor for the radar, a mobile platform to enable participation in community-organized hydrometeorological experiments, and a network of about 15 high-resolution raingauges to be installed at a nearby airport. The airport network design includes innovative concepts of dual sensors constituting a single observational point, connected to the same data logger. The observational points are separated with distances ranging from 10-1000 metres. We present comparisons of data collected by the various sensors and discuss implications for radar-rainfall estimation. The capabilities of the experimental setup at IIHR will facilitate numerical studies of rainfall measurements. In particular, we present results of computational fluid dynamics calculations of the measurement error of the video disdrometer based on the high resolution observations of drop size distribution and wind velocity.
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Zhang, Yan, James A. Smith, Alexandros A. Ntelekos, Mary Lynn Baeck, Witold F. Krajewski, and Fred Moshary. "Structure and Evolution of Precipitation along a Cold Front in the Northeastern United States." Journal of Hydrometeorology 10, no. 5 (October 1, 2009): 1243–56. http://dx.doi.org/10.1175/2009jhm1046.1.
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Abstract Heavy precipitation in the northeastern United States is examined through observational and numerical modeling analyses for a weather system that produced extreme rainfall rates and urban flash flooding over the New York–New Jersey region on 4–5 October 2006. Hydrometeorological analyses combine observations from Weather Surveillance Radar-1988 Doppler (WSR-88D) weather radars, the National Lightning Detection Network, surface observing stations in the northeastern United States, a vertically pointing lidar system, and a Joss–Waldvogel disdrometer with simulations from the Weather Research and Forecasting Model (WRF). Rainfall analyses from the Hydro-Next Generation Weather Radar (NEXRAD) system, based on observations from WSR-88D radars in State College, Pennsylvania, and Fort Dix, New Jersey, and WRF model simulations show that heavy rainfall was organized into long-lived lines of convective precipitation, with associated regions of stratiform precipitation, that develop along a frontal zone. Structure and evolution of convective storm elements that produced extreme rainfall rates over the New York–New Jersey urban corridor were influenced by the complex terrain of the central Appalachians, the diurnal cycle of convection, and the history of convective evolution in the frontal zone. Extreme rainfall rates and flash flooding were produced by a “leading line–trailing stratiform” system that was rapidly dissipating as it passed over the New York–New Jersey region. Radar, disdrometer, and lidar observations are used in combination with model analyses to examine the dynamical and cloud microphysical processes that control the spatial and temporal structure of heavy rainfall. The study illustrates key elements of the spatial and temporal distribution of rainfall that can be used to characterize flash flood hazards in the urban corridor of the northeastern United States.
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Zhang, Asi, Junjun Hu, Sheng Chen, Dongming Hu, Zhenqing Liang, Chaoying Huang, Liusi Xiao, Chao Min, and Haowen Li. "Statistical Characteristics of Raindrop Size Distribution in the Monsoon Season Observed in Southern China." Remote Sensing 11, no. 4 (February 19, 2019): 432. http://dx.doi.org/10.3390/rs11040432.
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This study investigates the statistical characteristics of raindrop size distributions (DSDs) in monsoon season with observations collected by the second-generation Particle Size and Velocity (Parsivel2) disdrometer located in Zhuhai, southern China. The characteristics are quantified based on convective and stratiform precipitation classified using the rainfall intensity and total number of drops. On average of the whole dataset, the DSD characteristic in southern China consists of a higher number concentration of relatively small-sized drops when compare with eastern China and northern China, respectively. In the meanwhile, the Dm and log10Nw scatter plots prove that the convective rain in monsoon season can be identified as maritime-like cluster. The DSD is in good agreement with a three-parameter gamma distribution, especially for the medium to large raindrop size. Using filtered data observed by Parsivel2 disdrometer, a new Z–R relationship, Z = 498R1.3, is derived for convective rain in monsoon season in southern China. These results offer insights of the microphysical nature of precipitation in Zhuhai during monsoon season, and provide essential information that may be useful for precipitation retrievals based on weather radar observations.
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Wu, Zuhang, Yun Zhang, Lifeng Zhang, Xiaolong Hao, Hengchi Lei, and Hepeng Zheng. "Validation of GPM Precipitation Products by Comparison with Ground-Based Parsivel Disdrometers over Jianghuai Region." Water 11, no. 6 (June 16, 2019): 1260. http://dx.doi.org/10.3390/w11061260.
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In this study, we evaluated the performance of rain-retrieval algorithms for the Version 6 Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR) products, against disdrometer observations and improved their retrieval algorithms by using a revised shape parameter µ derived from long-term Particle Size Velocity (Parsivel) disdrometer observations in Jianghuai region from 2014 to 2018. To obtain the optimized shape parameter, raindrop size distribution (DSD) characteristics of summer and winter seasons over Jianghuai region are analyzed, in terms of six rain rate classes and two rain categories (convective and stratiform). The results suggest that the GPM DPR may have better performance for winter rain than summer rain over Jianghuai region with biases of 40% (80%) in winter (summer). The retrieval errors of rain category-based µ (3–5%) were proved to be the smallest in comparison with rain rate-based µ (11–13%) or a constant µ (20–22%) in rain-retrieval algorithms, with a possible application to rainfall estimations over Jianghuai region. Empirical Dm–Ze and Nw–Dm relationships were also derived preliminarily to improve the GPM rainfall estimates over Jianghuai region.
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Scarchilli, Claudio, Virginia Ciardini, Paolo Grigioni, Antonio Iaccarino, Lorenzo De Silvestri, Marco Proposito, Stefano Dolci, et al. "Characterization of snowfall estimated by in situ and ground-based remote-sensing observations at Terra Nova Bay, Victoria Land, Antarctica." Journal of Glaciology 66, no. 260 (October 1, 2020): 1006–23. http://dx.doi.org/10.1017/jog.2020.70.
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AbstractKnowledge of the precipitation contribution to the Antarctic surface mass balance is essential for defining the ice-sheet contribution to sea-level rise. Observations of precipitation are sparse over Antarctica, due to harsh environmental conditions. Precipitation during the summer months (November–December–January) on four expeditions, 2015–16, 2016–17, 2017–18 and 2018–19, in the Terra Nova Bay area, were monitored using a vertically pointing radar, disdrometer, snow gauge, radiosounding and an automatic weather station installed at the Italian Mario Zucchelli Station. The relationship between radar reflectivity and precipitation rate at the site can be estimated using these instruments jointly. The error in calculated precipitation is up to 40%, mostly dependent on reflectivity variability and disdrometer inability to define the real particle fall velocity. Mean derived summer precipitation is ~55 mm water equivalent but with a large variability. During collocated measurements in 2018–19, corrected snow gauge amounts agree with those derived from the relationship, within the estimated errors. European Centre for the Medium-Range Weather Forecasts (ECMWF) and the Antarctic Mesoscale Prediction System (AMPS) analysis and operational outputs are able to forecast the precipitation timing but do not adequately reproduce quantities during the most intense events, with overestimation for ECMWF and underestimation for AMPS.
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Lim, S. "A Novel Electromagnetic Wave Rain Gauge and its Average Rainfall Estimation Method." Remote Sensing 12, no. 21 (October 28, 2020): 3528. http://dx.doi.org/10.3390/rs12213528.
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It is essential to accurately estimate rainfall to predict and prevent hydrological disasters such as floods. In this paper, an electromagnetic wave rain gauge system and a method to estimate average rainfall using the system’s multiple elevation observation data are presented. The compact electromagnetic wave rain gauge is a small-sized radar that performs very short-range observations using K-band dual-polarization technology. The method to estimate average rainfall is based on the concept of an average observation derived from multiple elevation scans with very short range and dual-polarization information. The proposed method was evaluated by comparing it with ground instruments, including a pit-gauge, tipping-bucket rain gauges, and a Parsivel disdrometer. The evaluation results demonstrated that the new methodology worked fairly well for various rainfall events.
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Guyot, Adrien, Jayaram Pudashine, Alain Protat, Remko Uijlenhoet, Valentijn R. N. Pauwels, Alan Seed, and Jeffrey P. Walker. "Effect of disdrometer type on rain drop size distribution characterisation: a new dataset for south-eastern Australia." Hydrology and Earth System Sciences 23, no. 11 (November 19, 2019): 4737–61. http://dx.doi.org/10.5194/hess-23-4737-2019.
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Abstract. Knowledge of the full rainfall drop size distribution (DSD) is critical for characterising liquid water precipitation for applications such as rainfall retrievals using electromagnetic signals and atmospheric model parameterisation. Southern Hemisphere temperate latitudes have a lack of DSD observations and their integrated variables. Laser-based disdrometers rely on the attenuation of a beam by falling particles and are currently the most commonly used type of instrument to observe the DSD. However, there remain questions on the accuracy and variability in the DSDs measured by co-located instruments, whether identical models, different models or from different manufacturers. In this study, raw and processed DSD observations obtained from two of the most commonly deployed laser disdrometers, namely the Parsivel1 from OTT and the Laser Precipitation Monitor (LPM) from Thies Clima, are analysed and compared. Four co-located instruments of each type were deployed over 3 years from 2014 to 2017 in the proximity of Melbourne, a region prone to coastal rainfall in south-eastern Australia. This dataset includes a total of approximately 1.5 million recorded minutes, including over 40 000 min of quality rainfall data common to all instruments, equivalent to a cumulative amount of rainfall ranging from 1093 to 1244 mm (depending on the instrument records) for a total of 318 rainfall events. Most of the events lasted between 20 and 40 min for rainfall amounts of 0.12 to 26.0 mm. The co-located LPM sensors show very similar observations, while the co-located Parsivel1 systems show significantly different results. The LPM recorded 1 to 2 orders of magnitude more smaller droplets for drop diameters below 0.6 mm compared to the Parsivel1, with differences increasing at higher rainfall rates. The LPM integrated variables showed systematically lower values compared to the Parsivel1. Radar reflectivity–rainfall rate (ZH–R) relationships and resulting potential errors are also presented. Specific ZH–R relations for drizzle and convective rainfall are also derived based on DSD collected for each instrument type. Variability of the DSD as observed by co-located instruments of the same manufacturer had little impact on the estimated ZH–R relationships for stratiform rainfall, but differs when considering convective rainfall relations or ZH–R relations fitted to all available data. Conversely, disdrometer-derived ZH–R relations as compared to the Marshall–Palmer relation ZH=200R1.6 led to a bias in rainfall rates for reflectivities of 50 dBZ of up to 21.6 mm h−1. This study provides an open-source high-resolution dataset of co-located DSD to further explore sampling effects at the micro scale, along with rainfall microstructure.