scholarly journals Analysis of Raindrop Size Distribution Characteristics in Permafrost Regions of the Qinghai–Tibet Plateau Based on New Quality Control Scheme

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2265 ◽  
Author(s):  
Ma ◽  
Zhao ◽  
Yang ◽  
Xiao ◽  
Zhang ◽  
...  
Keyword(s):  
Particle Size ◽  
Quality Control ◽  
Rain Rate ◽  
Tibet Plateau ◽  
Frozen Ground ◽  
Fall Velocity ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Qinghai Tibet Plateau ◽  
Permafrost Regions

Raindrop size distribution (DSD) can reflect the fundamental microphysics of precipitation and provide an accurate estimation of its amount and characteristics; however, there are few observations and investigations of DSD in cold, mountainous regions. We used the second-generation particle size and velocity disdrometer Parsivel2 to establish a quality control scheme for raindrop spectral data obtained for the Qinghai–Tibet Plateau in 2015. This scheme included the elimination of particles in the lowest two size classes, particles >10 mm in diameter and rain rates <0.01 mm∙h−1. We analyzed the DSD characteristics for different types of precipitation and rain rates in both permafrost regions and regions with seasonally frozen ground. The precipitation in the permafrost regions during the summer were mainly solid with a large particle size and slow fall velocity, whereas the precipitation in the regions with seasonally frozen ground were mainly liquid. The DSD of snow had a broader drop spectrum, the largest particle size, the slowest fall velocity, and the largest number of particles, followed by hail. Rain and sleet shared similar DSD characteristics, with a smaller particle size, slower velocity, and smaller number of particles. The particle concentration for different classes of rain rate decreased with an increase in particle size and decreased gradually with an increase in rain rate. Precipitation with a rain rate >2 mm∙h−1 was the main contributor to the annual precipitation. The dewpoint thresholds for snow and rain in permafrost regions were 0 and 1.5 °C, respectively. The dewpoint range 0–1.5 °C was characterized by mixed precipitation with a large proportion of hail. This study provides valuable DSD information on the Qinghai–Tibet Plateau and can be used as an important reference for the quality control of raindrop spectral data in regions dominated by solid precipitation.

scholarly journals Drop-Size Distributions in Thunderstorms Measured by Optical Disdrometers during VORTEX2

2013 ◽  
Vol 141 (4) ◽  
pp. 1182-1203 ◽  
Author(s):  
Katja Friedrich ◽  
Evan A. Kalina ◽  
Forrest J. Masters ◽  
Carlos R. Lopez
Keyword(s):  
Particle Size ◽  
Wind Speed ◽  
Size Distributions ◽  
Fall Velocity ◽  
Near Surface ◽  
Weather Radars ◽  
Raindrop Size Distribution ◽  
Strong Winds ◽  
Raindrop Size ◽  
Surface Buoyancy

Abstract When studying the influence of microphysics on the near-surface buoyancy tendency in convective thunderstorms, in situ measurements of microphysics near the surface are essential and those are currently not provided by most weather radars. In this study, the deployment of mobile microphysical probes in convective thunderstorms during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2) is examined. Microphysical probes consist of an optical Ott Particle Size and Velocity (PARSIVEL) disdrometer that measures particle size and fall velocity distributions and a surface observation station that measures wind, temperature, and humidity. The mobile probe deployment allows for targeted observations within various areas of the storm and coordinated observations with ground-based mobile radars. Quality control schemes necessary for providing reliable observations in severe environments with strong winds and high rainfall rates and particle discrimination schemes for distinguishing between hail, rain, and graupel are discussed. It is demonstrated how raindrop-size distributions for selected cases can be applied to study size-sorting and microphysical processes. The study revealed that the raindrop-size distribution changes rapidly in time and space in convective thunderstorms. Graupel, hailstones, and large raindrops were primarily observed close to the updraft region of thunderstorms in the forward- and rear-flank downdrafts and in the reflectivity hook appendage. Close to the updraft, large raindrops were usually accompanied by an increase in small-sized raindrops, which mainly occurred when the wind speed and standard deviation of the wind speed increased. This increase in small drops could be an indicator of raindrop breakup.

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 Observed Microphysical Characteristics of Stratiform and Convective Precipitation over an Inland Arid Region of the Qinghai–Tibet Plateau

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2300
Author(s):  
Hongwei Xie ◽  
Peichong Pan ◽  
Haiyun Shi ◽  
Ji Chen ◽  
Jinzhao Wang
Keyword(s):  
Arid Region ◽  
Rainfall Intensity ◽  
Radar Reflectivity ◽  
Convective Precipitation ◽  
Tibet Plateau ◽  
Raindrop Size Distribution ◽  
Stratiform Precipitation ◽  
Raindrop Size ◽  
Qinghai Tibet Plateau ◽  
Reflectivity Factor

This study analyzed the microphysical characteristics of stratiform and convective precipitation over an inland arid region of Qinghai–Tibet Plateau in summer for the first time. The observed precipitation data were from the OTT Parsivel2 laser raindrop spectrometer and the raindrop size distribution can be described by a gamma distribution and a general exponential distribution. The results indicate that: (1) compared to the exponential distribution, the gamma distribution is the better function with which to describe the raindrop size distribution in this region; (2) the raindrop sizes are mainly below 1 mm, and the raindrop sizes which contribute most to the rainfall intensity are below 2 mm for stratiform precipitation and convective precipitation; (3) the mean values of microphysical parameters, e.g., rainfall intensity, radar reflectivity factor, and liquid water content, are higher for convective precipitation than stratiform precipitation; and (4) the standard Z–R relationship underestimates the radar reflectivity factor in this region. Overall, the obtained results will enhance our understanding and facilitate future studies regarding the microphysical characteristics of precipitation in such regions. For example, the obtained Z–R relationship can be a reference for estimating the radar reflectivity factor in this region with higher accuracy.

scholarly journals Mapping Surficial Soil Particle Size Fractions in Alpine Permafrost Regions of the Qinghai–Tibet Plateau

2021 ◽  
Vol 13 (7) ◽  
pp. 1392
Author(s):  
Chong Wang ◽  
Lin Zhao ◽  
Hongbing Fang ◽  
Lingxiao Wang ◽  
Zanpin Xing ◽  
...  
Keyword(s):  
Particle Size ◽  
Spatial Distribution ◽  
Spatial Information ◽  
Machine Learning Techniques ◽  
Tibet Plateau ◽  
Size Fractions ◽  
Particle Size Fractions ◽  
Log Ratio ◽  
Qinghai Tibet Plateau ◽  
Permafrost Regions

Spatial information of particle size fractions (PSFs) is primary for understanding the thermal state of permafrost in the Qinghai-Tibet Plateau (QTP) in response to climate change. However, the limitation of field observations and the tremendous spatial heterogeneity hamper the digital mapping of PSF. This study integrated log-ratio transformation approaches, variable searching methods, and machine learning techniques to map the surficial soil PSF distribution of two typical permafrost regions. Results showed that the Boruta technique identified different covariates but retained those covariates of vegetation and land surface temperature in both regions. Variable selection techniques effectively decreased the data redundancy and improved model performance. In addition, the spatial distribution of soil PSFs generated by four log-ratio models presented similar patterns. Isometric log-ratio random forest (ILR-RF) outperformed the other models in both regions (i.e., R2 ranged between 0.36 to 0.56, RMSE ranged between 0.02 and 0.10). Compared with three legacy datasets, our prediction better captured the spatial pattern of PSFs with higher accuracy. Although this study largely improved the accuracy of spatial distribution of soil PSFs, further endeavors should also be made to improve model accuracy and interpretability for a better understanding of the interaction and processes between environmental predictors and soil PSFs at permafrost regions.

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 Evaluation of Gamma Raindrop Size Distribution Assumption through Comparison of Rain Rates of Measured and Radar-Equivalent Gamma DSD

2014 ◽  
Vol 53 (6) ◽  
pp. 1618-1635 ◽  
Author(s):  
Elisa Adirosi ◽  
Eugenio Gorgucci ◽  
Luca Baldini ◽  
Ali Tokay
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Rain Rate ◽  
Hydrological Cycle ◽  
Drop Size Distribution ◽  
Dual Polarization ◽  
Raindrop Size Distribution ◽  
Radar Measurements ◽  
Raindrop Size ◽  
Rain Rates

AbstractTo date, one of the most widely used parametric forms for modeling raindrop size distribution (DSD) is the three-parameter gamma. The aim of this paper is to analyze the error of assuming such parametric form to model the natural DSDs. To achieve this goal, a methodology is set up to compare the rain rate obtained from a disdrometer-measured drop size distribution with the rain rate of a gamma drop size distribution that produces the same triplets of dual-polarization radar measurements, namely reflectivity factor, differential reflectivity, and specific differential phase shift. In such a way, any differences between the values of the two rain rates will provide information about how well the gamma distribution fits the measured precipitation. The difference between rain rates is analyzed in terms of normalized standard error and normalized bias using different radar frequencies, drop shape–size relations, and disdrometer integration time. The study is performed using four datasets of DSDs collected by two-dimensional video disdrometers deployed in Huntsville (Alabama) and in three different prelaunch campaigns of the NASA–Japan Aerospace Exploration Agency (JAXA) Global Precipitation Measurement (GPM) ground validation program including the Hydrological Cycle in Mediterranean Experiment (HyMeX) special observation period (SOP) 1 field campaign in Rome. The results show that differences in rain rates of the disdrometer DSD and the gamma DSD determining the same dual-polarization radar measurements exist and exceed those related to the methodology itself and to the disdrometer sampling error, supporting the finding that there is an error associated with the gamma DSD assumption.

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 Dataset on raindrop size distribution, raindrop fall velocity and precipitation data measured by disdrometers and rain gauges over Peruvian central Andes (12.0°S)

Data in Brief ◽  
2020 ◽  
Vol 29 ◽  
pp. 105215
Author(s):  
Jairo M. Valdivia ◽  
Kevin Contreras ◽  
Daniel Martinez-Castro ◽  
Elver Villalobos-Puma ◽  
Luis F. Suarez-Salas ◽  
...  
Keyword(s):  
Size Distribution ◽  
Central Andes ◽  
Precipitation Data ◽  
Fall Velocity ◽  
Rain Gauges ◽  
Raindrop Size Distribution ◽  
Raindrop Size

scholarly journals Validation of GPM Precipitation Products by Comparison with Ground-Based Parsivel Disdrometers over Jianghuai Region

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1260 ◽  
Author(s):  
Zuhang Wu ◽  
Yun Zhang ◽  
Lifeng Zhang ◽  
Xiaolong Hao ◽  
Hengchi Lei ◽  
...  
Keyword(s):  
Shape Parameter ◽  
Rain Rate ◽  
Dual Frequency ◽  
Raindrop Size Distribution ◽  
Precipitation Measurement ◽  
Retrieval Algorithms ◽  
Raindrop Size ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Rain Retrieval

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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