scholarly journals Statistical Characteristics of Raindrop Size Distribution during Rainy Seasons in Northwest China

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yong Zeng ◽  
Lianmei Yang ◽  
Zepeng Tong ◽  
Yufei Jiang ◽  
Zuyi Zhang ◽  
...  
Keyword(s):  
Size Distribution ◽  
Arid Regions ◽  
Weighted Average ◽  
Northwest China ◽  
Rainfall Rate ◽  
Statistical Characteristics ◽  
Stratiform Rain ◽  
Convective Rain ◽  
Raindrop Size Distribution ◽  
Raindrop Size

Raindrop size distribution (DSD) is of great significance for understanding the microphysical process of rainfall and the quantitative precipitation estimation (QPE). However, in the past, there was a lack of relevant research on Xinjiang in the arid region of northwest China. In this study, the rainy season data collected by the disdrometer in the Yining area of Xinjiang were used for more than two years, and the characteristics of DSDs for all samples, for two rain types (convective and stratiform), and for six different rain rates were studied. The results showed that nearly 70% of the total samples had a rainfall rate of less than 1 mm·h−1, the convective rain was neither continental nor maritime, and there was a clear boundary between convective rain and stratiform rain in terms of the scattergram of the standardized intercept parameter ( log 10 N w ) versus the mass-weighted average diameter ( D m ). When the raindrop diameter was less than 0.7 mm, DSDs of the two rainfalls basically coincided, while when the raindrop diameter was greater than 0.7 mm, DSDs of convective rainfall were located above the stratiform rain. As the rainfall rate increased, D m increased, while log 10 N w first increased and then decreased. In addition, we deduced the Z − R (radar reflectivity-rain rate) relationship and μ − Λ relationship (shape parameter-slope parameter of the gamma DSDs) suitable for the Yining area. These conclusions are conducive to strengthening the understanding of rainfall microphysical processes in arid regions and improving the ability of QPE in arid regions.

scholarly journals Statistical characteristics of raindrop size distribution during rainy seasons in the Beijing urban area and implications for radar rainfall estimation

2019 ◽  
Vol 23 (10) ◽  
pp. 4153-4170 ◽  
Author(s):  
Yu Ma ◽  
Guangheng Ni ◽  
Chandrasekar V. Chandra ◽  
Fuqiang Tian ◽  
Haonan Chen
Keyword(s):  
Size Distribution ◽  
Urban Area ◽  
Rain Rate ◽  
Statistical Characteristics ◽  
Spatial And Temporal Variability ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Convective Rain ◽  
Raindrop Size Distribution ◽  
Raindrop Size

Abstract. Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation, especially in complex terrain or urban environments which are known for complicated rainfall mechanism and high spatial and temporal variability. In this study, the DSD characteristics of rainy seasons in the Beijing urban area are extensively investigated using 5-year DSD observations from a Parsivel2 disdrometer located at Tsinghua University. The results show that the DSD samples with rain rate < 1 mm h−1 account for more than half of total observations. The mean values of the normalized intercept parameter (log 10Nw) and the mass-weighted mean diameter (Dm) of convective rain are higher than that of stratiform rain, and there is a clear boundary between the two types of rain in terms of the scattergram of log 10Nw versus Dm. The convective rain in Beijing is neither continental nor maritime, owing to the particular location and local topography. As the rainfall intensity increases, the DSD spectra become higher and wider, but they still have peaks around diameter D∼0.5 mm. The midsize drops contribute most towards accumulated rainwater. The Dm and log 10Nw values exhibit a diurnal cycle and an annual cycle. In addition, at the stage characterized by an abrupt rise of urban heat island (UHI) intensity as well as the stage of strong UHI intensity during the day, DSD shows higher Dm values and lower log 10Nw values. The localized radar reflectivity (Z) and rain rate (R) relations (Z=aRb) show substantial differences compared to the commonly used NEXRAD relationships, and the polarimetric radar algorithms R(Kdp), R(Kdp, ZDR), and R(ZH, ZDR) show greater potential for rainfall estimation.

scholarly journals Statistical characteristics of raindrop size distribution during rainy seasons in Beijing urban area and implications for radar rainfall estimation

2019 ◽  
Author(s):  
Yu Ma ◽  
Guangheng Ni ◽  
V. Chandrasekar ◽  
Fuqiang Tian ◽  
Haonan Chen
Keyword(s):  
Size Distribution ◽  
Urban Area ◽  
Rain Rate ◽  
Statistical Characteristics ◽  
Spatial And Temporal Variability ◽  
Rainfall Estimation ◽  
Radar Rainfall ◽  
Convective Rain ◽  
Raindrop Size Distribution ◽  
Raindrop Size

Abstract. Raindrop size distribution (DSD) information is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation, especially in complex terrain or urban environment which is known for its complicated rainfall mechanism and high spatial and temporal variability. In this study, the DSD characteristics of rainy seasons in Beijing urban area are extensively investigated using 5-year DSD observations from a Parsivel2 disdrometer located at Tsinghua University. The results show that the DSD samples with rain rate < 1 mm h−1 account for more than half of total observations. The mean values of log10 Nw and Dm of convective rain are higher than that of stratiform rain, and there is a clear boundary between the two types of rain in terms of the scattergram of log10Nw versus Dm. The convective rain in Beijing is neither continental nor maritime owing to the particular location and local topography. As the rainfall intensity increases, the DSD spectra become higher and wider, but they still have peaks around diameter D ~ 0.5 mm. The midsize drops contribute most towards accumulated rainwater. The Dm and log10Nw values show a diurnal cycle and an annual cycle. In addition, DSD shows higher Dm values and lower log10Nw values during the periods of strong urban heat island (UHI) effect and UHI up stage of a day, and the same in July and August. The localized radar reflectivity (Z) and rain rate (R) relations (Z = aRb) show substantial differences compared to the commonly used NEXRAD relationships. And the polarimetric radar algorithms R(Kdp), R(Kdp, ZDR), and R(ZH, ZDR) show greater potential for rainfall estimation.

scholarly journals Invariance of the Double-Moment Normalized Raindrop Size Distribution through 3D Spatial Displacement in Stratiform Rain

2017 ◽  
Vol 56 (6) ◽  
pp. 1663-1680 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne
Keyword(s):  
Size Distribution ◽  
Vertical Displacement ◽  
Statistical Moments ◽  
Stratiform Rain ◽  
Vertical Range ◽  
Raindrop Size Distribution ◽  
Double Moment ◽  
Raindrop Size ◽  
Polarimetric Weather Radar ◽  
Using Data

AbstractDouble-moment normalization of the drop size distribution (DSD) summarizes the DSD in a compact way, using two of its statistical moments and a “generic” double-moment normalized DSD function. Results are presented of an investigation into the invariance of the double-moment normalized DSD through horizontal and vertical displacement in space, using data from disdrometers, vertically pointing K-band Micro Rain Radars, and an X-band polarimetric weather radar. The invariance of the double-moment normalized DSD is tested over a vertical range of up to 1.8 km and a horizontal range of up to approximately 100 km. The results suggest that for practical use, with well-chosen input moments, the double-moment normalized DSD can be assumed invariant in space in stratiform rain. The choice of moments used to characterize the DSD affects the amount of DSD variability captured by the normalization. It is shown that in stratiform rain, it is possible to capture more than 85% of the variability in DSD moments zero to seven using the technique. Most DSD variability in stratiform rain can thus be explained through the variability of two of its statistical moments. The results suggest similar behavior exists in transition and convective rain, but the limited data samples available do not allow for robust conclusions for these rain types. The results have implications for practical uses of double-moment DSD normalization, including the study of DSD variability and microphysics, DSD-retrieval algorithms, and DSD models used in rainfall retrieval.

scholarly journals Measurements of Rainfall Velocity and Raindrop Size Distribution Using Coherent Doppler Lidar

2016 ◽  
Vol 33 (9) ◽  
pp. 1949-1966 ◽  
Author(s):  
Makoto Aoki ◽  
Hironori Iwai ◽  
Katsuhiro Nakagawa ◽  
Shoken Ishii ◽  
Kohei Mizutani
Keyword(s):  
Size Distribution ◽  
Wind Velocity ◽  
Vertical Wind ◽  
Doppler Spectrum ◽  
Doppler Lidar ◽  
Stratiform Rain ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Rain Events ◽  
Vertical Wind Velocity

AbstractRainfall velocity, raindrop size distribution (DSD), and vertical wind velocity were simultaneously observed with 2.05- and 1.54-μm coherent Doppler lidars during convective and stratiform rain events. A retrieval method is based on identifying two separate spectra from the convolution of the aerosol and precipitation Doppler lidar spectra. The vertical wind velocity was retrieved from the aerosol spectrum peak and then the terminal rainfall velocity corrected by the vertical air motion from the precipitation spectrum peak was obtained. The DSD was derived from the precipitation spectrum using the relationship between the raindrop size and the terminal rainfall velocity. A comparison of the 1-min-averaged rainfall velocity from Doppler lidar measurements at a minimum range and that from a collocated ground-based optical disdrometer revealed high correlation coefficients of over 0.89 for both convective and stratiform rain events. The 1-min-averaged DSDs retrieved from the Doppler lidar spectrum using parametric and nonparametric methods are also in good agreement with those measured with the optical disdrometer with a correlation coefficient of over 0.80 for all rain events. To retrieve the DSD, the parametric method assumes a mathematical function for the DSD and the nonparametric method computes the direct deconvolution of the measured Doppler lidar spectrum without assuming a DSD function. It is confirmed that the Doppler lidar can retrieve the rainfall velocity and DSD during relatively heavy rain, whereas the ratio of valid data significantly decreases in light rain events because it is extremely difficult to separate the overlapping rain and aerosol peaks in the Doppler spectrum.

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