scholarly journals Characteristics of Clouds and Raindrop Size Distribution in Xinjiang, Using Cloud Radar Datasets and a Disdrometer

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1382
Author(s):  
Yong Zeng ◽  
Lianmei Yang ◽  
Zuyi Zhang ◽  
Zepeng Tong ◽  
Jiangang Li ◽  
...  
Keyword(s):  
Diurnal Variation ◽  
Size Distribution ◽  
Cloud Base ◽  
Physical Parameters ◽  
Observation Data ◽  
Diurnal Changes ◽  
Cloud Radar ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
R Relation

Observation data from March to May 2020 of the Ka-band millimeter-wave cloud radar and disdrometer, located in Xinjiang, a typical arid region of China, were used to study the diurnal variation of clouds and precipitation, raindrop size distribution (DSD), and the physical parameters of raindrops. The results showed that there are conspicuous diurnal changes in clouds and precipitation. There is a decreasing trend of the cloud base height (CBH) from 05:00 to 19:00 CST (China Standard Time, UTC +8) and a rising trend of CBHs from 20:00 to 04:00 CST. The cloud top height (CTH) and the cloud thickness show a rising trend from 03:00 to 05:00 CST, 12:00 to 14:00 CST, and 20:00 to 01:00 CST. The diurnal variation of clouds is mainly driven by wind and temperature closely related to the topography of the study area. There are three apparent precipitation periods during the day, namely, 02:00–09:00 CST, 12:00 CST, and 17:00–21:00 CST. The changes in the physical parameters of raindrops are more drastic and evident with a lower CBH, lower CTH, and higher number of cloud layers from 12:00 to 21:00 CST than other times, which are closely related to day-to-day variations of systems moving through, and incoming solar radiation and the mountain–valley wind circulation caused by the trumpet-shaped topography that opens to the west played a secondary role. The DSD is in agreement with a normalized gamma distribution, and the value of the shape factor μ is significantly different from the fixed μ value in the Weather Research and Forecasting (WRF) Model. The rain in arid Xinjiang had a higher concentration of raindrops and a smaller average raindrop diameter than the rain in other humid regions of the Central and Southeast Asian continent. In the Z−R (radar reflectivity–rain rate) relationship, Z=249R1.20 is derived for stratiform rain, and it is significantly different from humid regions. Using Z/Dm (mass–weighted mean diameter) and R, a new empirical relationship Z/Dm=214R1.20 is established, and improvement is obtained in rain retrieval by using the Z/Dm−R relation relative to the conventional Z−R relation. Additionally, the Nt−R, Dm−R, Nw−R, and Nt−Nw relationships with larger differences from humid regions are established by fitting the power-law equations. These results are useful for improving the data parameters of microphysical processes of WRF and the accuracy of quantitative precipitation estimation in arid regions.

scholarly journals Analysis of the Vertical Air Motions and Raindrop Size Distribution Retrievals of a Squall Line Based on Cloud Radar Doppler Spectral Density Data

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 348
Author(s):  
Ningkun Ma ◽  
Liping Liu ◽  
Yichen Chen ◽  
Yang Zhang
Keyword(s):  
Spectral Density ◽  
Size Distribution ◽  
Squall Line ◽  
Vertical Profiles ◽  
Air Velocity ◽  
Density Data ◽  
Cloud Radar ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Reflectivity Factor

A squall line is a type of strongly organized mesoscale convective system that can cause severe weather disasters. Thus, it is crucial to explore the dynamic structure and hydrometeor distributions in squall lines. This study analyzed a squall line over Guangdong Province on 6 May 2016 that was observed using a Ka-band millimeter-wave cloud radar (CR) and an S-band dual-polarization radar (PR). Doppler spectral density data obtained by the CR were used to retrieve the vertical air motions and raindrop size distribution (DSD). The results showed the following: First, the CR detected detailed vertical profiles and their evolution before and during the squall line passage. In the convection time segment (segment B), heavy rain existed with a reflectivity factor exceeding 35 dBZ and a velocity spectrum width exceeding 1.3 m s−1. In the PR detection, the differential reflectivity factor (Zdr) was 1–2 dB, and the large specific differential phase (Kdp) also represented large liquid water content. In the transition and stratiform cloud time segments (segments B and C), the rain stabilized gradually, with decreasing cloud tops, stable precipitation, and a 0 °C layer bright band. Smaller Kdp values (less than 0.9) were distributed around the 0 °C layer, which may have been caused by the melting of ice crystal particles. Second, from the CR-retrieved vertical air velocity, before squall line passage, downdrafts dominated in local convection and weak updrafts existed in higher-altitude altostratus clouds. In segment B, the updraft air velocity reached more than 8 m s−1 below the 0 °C layer. From segments C to D, the updrafts changed gradually into weak and wide-ranging downdrafts. Third, in the comparison of DSD values retrieved at 1.5 km and DSD values on the ground, the retrieved DSD line was lower than the disdrometer, the overall magnitude of the DSD retrieved was smaller, and the difference decreased from segments C to D. The standardized intercept parameter (Nw) and shape parameter (μ) of the DSD retrieved at 1.8 km showed good agreement with the disdrometer results, and the mass-weighted mean diameter (Dm) was smaller than that on the ground, but very close to the PR-retrieved Dm result at 2 km. Therefore, comparing with the DSD retrieved at around 2 km, the overall number concentration remained unchanged and Dm got larger on the ground, possibly reflecting the process of raindrop coalescence. Lastly, the average vertical profiles of several quantities in all segments showed that, first of all, the decrease of Nw and Dm with height in segments C and D was similar, reflecting the collision effect of falling raindrops. The trends were opposite in segment B, indicating that raindrops underwent intense mixing and rapid collision and growth in this segment. Then, PR-retrieved Dm profiles can verify the rationality of the CR-retrieved Dm. Finally, a vertical velocity profile peak generated a larger Dm especially in segments C and D.

scholarly journals A Synergy Approach to Estimate Properties of Raindrop Size Distributions Using a Doppler Lidar and Cloud Radar

2010 ◽  
Vol 27 (6) ◽  
pp. 1095-1100 ◽  
Author(s):  
Katja Träumner ◽  
Jan Handwerker ◽  
Andreas Wieser ◽  
Jens Grenzhäuser
Keyword(s):  
Size Distribution ◽  
Analytical Description ◽  
Doppler Lidar ◽  
Fall Velocity ◽  
Rayleigh Approximation ◽  
Size Dependent ◽  
Cloud Radar ◽  
Raindrop Size Distribution ◽  
Remote Sensing Systems ◽  
Raindrop Size

Abstract Remote sensing systems like radars and lidars are frequently used in atmospheric measurement campaigns. Because of their different wavelengths, they operate in different scattering regimes. Combined use may result in new measurement options. Here, an approach to estimate raindrop size distribution using vertical velocities measured by a lidar–radar combination is introduced and tested using a 2-μm Doppler lidar and a 35.5-GHz cloud radar. The lidar spectra are evaluated to deduce air motion from the aerosol peak and the fall velocity of the raindrops from the rain peak. The latter is weighted by the area (D2) of the scatters. The fall velocity derived from radar measurements is weighted by D6 (Rayleigh approximation). Assuming a size-dependent fall velocity and an analytical description of the drop size distribution, its parameters are calculated from these data. Comparison of the raindrop size distribution from the lidar–radar combination with in situ measurements on the ground yields satisfying results.

scholarly journals Characteristics of Warm Clouds and Precipitation in South China during the Pre-Flood Season Using Datasets from a Cloud Radar, a Ceilometer, and a Disdrometer

2019 ◽  
Vol 11 (24) ◽  
pp. 3045 ◽  
Author(s):  
Jiafeng Zheng ◽  
Liping Liu ◽  
Haonan Chen ◽  
Yabin Gou ◽  
Yuzhang Che ◽  
...  
Keyword(s):  
South China ◽  
Cloud Base ◽  
Vertical Orientation ◽  
Integrated Technology ◽  
Flood Season ◽  
Cloud Radar ◽  
Raindrop Size Distribution ◽  
Type Size ◽  
Raindrop Size ◽  
Rain Rates

The millimeter-wave cloud radar, ceilometer, and disdrometer have been widely used to observe clouds and precipitation. However, there are some drawbacks when those three instruments are solely employed due to their own limitations, such as the fact that radars usually suffer from signal attenuation and ceilometers/disdrometers cannot provide measurements of the hydrometeors of aloft clouds and precipitation. Thus, in this paper, we developed an integrated technology by combining and utilizing the advantages of three instruments together to investigate the vertical structure and diurnal variation of warm clouds and precipitation, and the raindrop size distribution. Specifically, the technology consists of appropriate data processing, quality control, and retrieval methods. It was implemented to study the warm clouds and precipitation in South China during the pre-flood season of 2016. The results showed that the hydrometeors of warm clouds and precipitation were mainly distributed below 2.5 km and most of the rainfall events were very light with a rain rate less than 1 mm h−1, however, the stronger precipitation primarily contributed the accumulated rain amount. Furthermore, a rising trend of cloud base height from 1000 to 1900 BJT was found. The cloud top height and cloud thickness gradually increased from 1200 BJT to reach a maximum at 1600 BJT (Beijing Standard Time, UTC+8), and then decreased until 2000 BJT. Also, three periods of the apparent rainfall on the ground of the day, namely, 0400–0700 BJT, 1400–1800 BJT, and 2300–2400 BJT were observed. During three periods, the raindrops had wider size spectra, higher number concentrations, larger rain rates, and higher water contents than at other times. The hydrometeor type, size, and concentration were gradually changed in the vertical orientation. The raindrop size distributions of warm precipitation in the air and on the ground were different, which can be expressed by γ distributions N(D) = 1.49 × 104D−0.9484exp(−6.79D) in the air and N(D) = 1.875 × 103D0.862exp(−2.444D) on the ground, where D and N(D) denote the diameter and number concentration of the raindrops, respectively.

Diurnal Variation of Rain Attenuation Obtained From Measurement of Raindrop Size Distribution in Equatorial Indonesia

2009 ◽  
Vol 57 (4) ◽  
pp. 1191-1196 ◽  
Author(s):  
M. Marzuki ◽  
T. Kozu ◽  
T. Shimomai ◽  
W. L. Randeu ◽  
H. Hashiguchi ◽  
...  
Keyword(s):  
Diurnal Variation ◽  
Size Distribution ◽  
Rain Attenuation ◽  
Raindrop Size Distribution ◽  
Raindrop Size

scholarly journals Improving the rainfall rate estimation in the midstream of the Heihe River Basin using raindrop size distribution

2011 ◽  
Vol 15 (3) ◽  
pp. 943-951 ◽  
Author(s):  
G. Zhao ◽  
R. Chu ◽  
T. Zhang ◽  
J. Li ◽  
J. Shen ◽  
...  
Keyword(s):  
Size Distribution ◽  
Rain Rate ◽  
Tibet Plateau ◽  
Heihe River ◽  
Drop Diameter ◽  
Observation Data ◽  
Polarimetric Radar ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Raindrop Size

Abstract. During the intensive observation period of the Watershed Allied Telemetry Experimental Research (WATER), a total of 1074 raindrop size distribution were measured by the Parsivel disdrometer, the latest state-of-the-art optical laser instrument. Because of the limited observation data in Qinghai-Tibet Plateau, the modelling behaviour was not well done. We used raindrop size distributions to improve the rain rate estimator of meteorological radar in order to obtain many accurate rain rate data in this area. We got the relationship between the terminal velocity of the raindrop and the diameter (mm) of a raindrop: v(D) = 4.67D0.53. Then four types of estimators for X-band polarimetric radar are examined. The simulation results show that the classical estimator R (ZH) is most sensitive to variations in DSD and the estimator R (KDP, ZH, ZDR) is the best estimator for estimating the rain rate. An X-band polarimetric radar (714XDP) is used for verifying these estimators. The lowest sensitivity of the rain rate estimator R (KDP, ZH, ZDR) to variations in DSD can be explained by the following facts. The difference in the forward-scattering amplitudes at horizontal and vertical polarizations, which contributes KDP, is proportional to the 3rd power of the drop diameter. On the other hand, the exponent of the backscatter cross-section, which contributes to ZH, is proportional to the 6th power of the drop diameter. Because the rain rate R is proportional to the 3.57th power of the drop diameter, KDP is less sensitive to DSD variations than ZH.

scholarly journals Improving the rainfall rate estimation in the midstream of the Heihe River Basin using rain drop size distribution

2009 ◽  
Vol 6 (5) ◽  
pp. 6107-6134 ◽  
Author(s):  
G. Zhao ◽  
R. Chu ◽  
X. Li ◽  
T. Zhang ◽  
J. Shen ◽  
...  
Keyword(s):  
Size Distribution ◽  
Rain Rate ◽  
Terminal Velocity ◽  
Tibet Plateau ◽  
Heihe River ◽  
Drop Diameter ◽  
Observation Data ◽  
Raindrop Size Distribution ◽  
Rain Drop ◽  
Raindrop Size

Abstract. During the intensive observation period of the Watershed Allied Telemetry Experimental Research (WATER), a total of 1074 raindrop size distribution were measured by the Parsivel disdrometer, a latest state of the art optical laser instrument. Because of the limited observation data in Qinghai-Tibet Plateau, the modeling behavior was not well-done. We used raindrop size distributions to improve the rain rate estimator of meteorological radar, in order to obtain many accurate rain rate data in this area. We got the relationship between the terminal velocity of the rain drop and the diameter (mm) of a rain drop: v(D)=4.67 D0.53. Then four types of estimators for X-band polarimetric radar are examined. The simulation results show that the classical estimator R(Z) is most sensitive to variations in DSD and the estimator R (KDP, Z, ZDR) is the best estimator for estimating the rain rate. The lowest sensitivity of the rain rate estimator R (KDP, Z, ZDP) to variations in DSD can be explained by the following facts. The difference in the forward-scattering amplitudes at horizontal and vertical polarizations, which contributes KDP, is proportional to the 3rd power of the drop diameter. On the other hand, the exponent of the backscatter cross section, which contributes to Z, is proportional to the 6th power of the drop diameter. Because the rain rate R is proportional to the 3.57th power of the drop diameter, KDP is less sensitive to DSD variations than Z.

scholarly journals A Field Study of Pixel-Scale Variability of Raindrop Size Distribution in the Mid-Atlantic Region

2016 ◽  
Vol 17 (6) ◽  
pp. 1855-1868 ◽  
Author(s):  
Ali Tokay ◽  
Leo Pio D’Adderio ◽  
David B. Wolff ◽  
Walter A. Petersen
Keyword(s):  
Spatial Variability ◽  
Field Study ◽  
Size Distribution ◽  
Exponential Function ◽  
Rain Rate ◽  
Rain Gauge ◽  
Separation Distance ◽  
Physical Parameters ◽  
Raindrop Size Distribution ◽  
Raindrop Size

Abstract The spatial variability of parameters of the raindrop size distribution and its derivatives is investigated through a field study where collocated Particle Size and Velocity (Parsivel2) and two-dimensional video disdrometers were operated at six sites at Wallops Flight Facility, Virginia, from December 2013 to March 2014. The three-parameter exponential function was employed to determine the spatial variability across the study domain where the maximum separation distance was 2.3 km. The nugget parameter of the exponential function was set to 0.99 and the correlation distance d0 and shape parameter s0 were retrieved by minimizing the root-mean-square error, after fitting it to the correlations of physical parameters. Fits were very good for almost all 15 physical parameters. The retrieved d0 and s0 were about 4.5 km and 1.1, respectively, for rain rate (RR) when all 12 disdrometers were reporting rainfall with a rain-rate threshold of 0.1 mm h−1 for 1-min averages. The d0 decreased noticeably when one or more disdrometers were required to report rain. The d0 was considerably different for a number of parameters (e.g., mass-weighted diameter) but was about the same for the other parameters (e.g., RR) when rainfall threshold was reset to 12 and 18 dBZ for Ka- and Ku-band reflectivity, respectively, following the expected Global Precipitation Measurement mission’s spaceborne radar minimum detectable signals. The reduction of the database through elimination of a site did not alter d0 as long as the fit was adequate. The correlations of 5-min rain accumulations were lower when disdrometer observations were simulated for a rain gauge at different bucket sizes.

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