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 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 Articulating and Stationary PARSIVEL Disdrometer Measurements in Conditions with Strong Winds and Heavy Rainfall

2013 ◽  
Vol 30 (9) ◽  
pp. 2063-2080 ◽  
Author(s):  
Katja Friedrich ◽  
Stephanie Higgins ◽  
Forrest J. Masters ◽  
Carlos R. Lopez
Keyword(s):  
Particle Size ◽  
Quality Control ◽  
Wind Speed ◽  
Number Concentration ◽  
High Wind ◽  
Sampling Area ◽  
Fall Velocity ◽  
Wind Speeds ◽  
Strong Winds

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 (&gt;5 mm) and unrealistic fall velocities (&lt;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.

scholarly journals On the Shape–Slope Relation of Drop Size Distributions in Convective Rain

2005 ◽  
Vol 44 (7) ◽  
pp. 1146-1151 ◽  
Author(s):  
Axel Seifert
Keyword(s):  
Size Distribution ◽  
Gamma Distribution ◽  
Drop Size ◽  
Empirical Relation ◽  
Size Distributions ◽  
Shape Parameters ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Drop Size Distributions ◽  
Good Agreement

Abstract The relation between the slope and shape parameters of the raindrop size distribution parameterized by a gamma distribution is examined. The comparison of results of a simple rain shaft model with an empirical relation based on disdrometer measurements at the surface shows very good agreement, but a more detailed discussion reveals some difficulties—for example, deviations from the gamma shape and the overestimation of collisional breakup.

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

Seasonal size distributions of suspended solids in a stormwater management pond

1999 ◽  
Vol 39 (2) ◽  
pp. 127-134 ◽  
Author(s):  
B. G. Krishnappan ◽  
J. Marsalek ◽  
W. E. Watt ◽  
B. C. Anderson
Keyword(s):  
Particle Size ◽  
Water Samples ◽  
Stormwater Management ◽  
Suspended Solids ◽  
Size Range ◽  
Empirical Relationship ◽  
Size Distributions ◽  
Fall Velocity ◽  
Floc Size ◽  
Primary Particles

Three seasonal surveys of suspended solids were carried out in an on-stream stormwater management pond, by means of a submersible laser particle size analyser. Size distributions were measured at up to 17 points in the pond, and water samples collected at the same locations were analysed for primary particles aggregated in flocs. Observed suspended solids were mostly composed of flocs, with maximum sizes ranging from 30 to 212 μm for winter and summer surveys, respectively. Using a relationship defining the floc density as a function of floc size and Stokes' equation for settling, an empirical relationship expressing the floc fall velocity as a function of floc size was produced. This relationship indicates that naturally formed flocs in the size range from 5 to 15 μm would settle faster than both smaller primary particles of higher density, and somewhat larger flocs of lower density, which are however susceptible to break up by turbulence.

scholarly journals Dust Particle Size Distributions during Spring in Yinchuan, China

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Jiangfeng Shao ◽  
Jiandong Mao
Keyword(s):  
Particle Size ◽  
Wind Speed ◽  
Dust Particle ◽  
Dust Storm ◽  
Fine Particles ◽  
Dust Particles ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Mass Distributions ◽  
Mass Size

Dust particle size distributions in Yinchuan, China, were measured during March and April 2014, using APS-3321 sampler. The distributions were measured under different dust conditions (background, floating dust, blowing dust, and dust storm) and statistical analyses were performed. The results showed that, under different dust conditions, the instantaneous number concentrations of dust particles differed widely. For example, during blowing sand and dust storm conditions, instantaneous dust particles concentrations varied substantially, while, under floating dust conditions, concentration differences were relatively small. The average dust particles size distributions were unimodal under all dust conditions, but the average surface area and mass size distributions were all bimodal. These distributions had peaks in different locations under different dust conditions. Under different dust conditions, wind speed and humidity were very important factors for particles size distributions. With increasing wind speed and decreasing humidity, fine particles were dominant in the atmosphere and the number and mass distributions of the coarse particles were indicative of long-range transport from surrounding deserts. Different dust conditions had different influences on PM1, PM2.5, and PM10concentrations.

scholarly journals Wind Effects on the Shape of Raindrop Size Distribution

2017 ◽  
Vol 18 (5) ◽  
pp. 1285-1303 ◽  
Author(s):  
Firat Y. Testik ◽  
Bin Pei
Keyword(s):  
Wind Speed ◽  
Size Distribution ◽  
Liquid Water Content ◽  
Shape Evolution ◽  
Wind Effects ◽  
Breakup Process ◽  
Radar Rainfall ◽  
Wind Speeds ◽  
Raindrop Size Distribution ◽  
Raindrop Size

Abstract The wind effects on the shape of drop size distribution (DSD) and the driving microphysical processes for the DSD shape evolution were investigated using the dataset from the Midlatitude Continental Convective Clouds Experiment (MC3E). The quality-controlled DSD spectra from MC3E were grouped for each of the rainfall events by considering the precipitation type (stratiform vs convective) and liquid water content for the analysis. The DSD parameters (e.g., mass-weighted mean diameter) and the fitted DSD slopes for these grouped spectra showed statistically significant trends with varying wind speed. Increasing wind speeds were observed to modify the DSD shapes by increasing the number of small drops and decreasing the number of large drops, indicating that the raindrop breakup process governs the DSD shape evolution. Both spontaneous and collisional raindrop breakup modes were analyzed to elucidate the process responsible for the DSD shape evolution with varying wind speed. The analysis revealed that the collisional breakup process controls the wind-induced DSD shape. The findings of this study are of importance in DSD parameterizations that are essential to a wide variety of applications such as radar rainfall retrievals and hydrologic models.

Dynamic rainfall mapping using multi-radar multi-gauge observations in changing synoptic environments

2021 ◽  
Author(s):  
Yabin Gou ◽  
Haonan Chen
Keyword(s):  
Real Time ◽  
Physical Model ◽  
Feedback Mechanism ◽  
Radar Rainfall ◽  
Weather Radars ◽  
Raindrop Size Distribution ◽  
Precipitation Estimates ◽  
Storm Cells ◽  
Raindrop Size ◽  
Quantitative Precipitation Estimates

&lt;p&gt;It is well known that the performance of radar-derived quantitative precipitation estimates greatly relies on the physical model of the raindrop size distribution (DSD) and the relation between the physical model and radar parameters. However, incorporating changing precipitation microphysics to dynamically adjust the radar reflectivity (Z) and rain rate (R) relations can be challenging for real-time applications. In this study, two adaptive radar rainfall approaches are developed based on the radar-gauge feedback mechanism using 16 S-band Doppler weather radars and 4579 surface rain gauges deployed over the Eastern JiangHuai River Basin (EJRB) in China. Although the Z&amp;#8211;R relations in both approaches are dynamically adjusted within a single precipitation system, one is using a single global optimal (SGO) Z&amp;#8211;R relation, whereas the other is using different Z&amp;#8211;R relations for different storm cells identified by a storm cell identification and tracking (SCIT) algorithm. Four precipitation events featured by different rainfall microphysical characteristics are investigated to demonstrate the performances of these two rainfall mapping methodologies. In addition, the short-term vertical profile of reflectivity (VPR) clusters are extensively analyzed to resolve the storm-scale characteristics of different storm cells. The verification results based on independent gauge observations show that both rainfall estimation approaches with dynamic Z&amp;#8211;R relations perform much better than fixed Z&amp;#8211;R relations. The adaptive approach incorporating the SCIT algorithm and real-time gauge measurements performs best since it can better capture the spatial variability and temporal evolution of precipitation.&lt;/p&gt;

Precipitation structure during the life cycle of cloud systems over Peru using satellite based observations

2020 ◽  
Author(s):  
Shailenda Kumar ◽  
Yamina Silva ◽  
Carlos Del Castillo ◽  
Jose Luis Flores Rojas ◽  
Aldo Moya S. Alveraz ◽  
...  
Keyword(s):  
Life Cycle ◽  
Rain Rate ◽  
Convective Precipitation ◽  
Mature Stage ◽  
Near Surface ◽  
Cloud Systems ◽  
Freezing Level ◽  
Microphysical Properties ◽  
Raindrop Size Distribution ◽  
Raindrop Size

&lt;p&gt;In the present study, a unique approach is applied to investigate the life cycle properties of the precipitation combining the satellite-based information. Data from Global Precipitation Measurement Dual Precipitation Radar (GPM-DPR) and brightness temperature (BT) form the GOES satellite. First, we used the GPM-DPR data to identify the precipitating cloud systems (PCSs) and then 9 (&amp;#177; 4 hours) hours of GOES BT data to identify the life phases for a particular PCSs e.g., a developing stage, a mature stage, or a dissipating stage. The case study of PCS related to different phases of the PCSs shows that PCSs consist of different systematic properties including the area of convective-stratiform precipitation, the convective rain rate and the storm-top height. The developing stage PCSs have the highest convective precipitation fraction (~26%) with highest near surface rain rate (RR, 4.97 mm h-1), whereas the dissipating stage PCSs have the largest precipitation area (11489 km2) with least near surface convective RR (~4.11 mm h-1). The vertical structure of precipitation and raindrop size distribution (DSD parameters) show the different characteristics above and below the freezing level and related with the different microphysical processes during different stages and related with the convective to stratiform area fraction and water vapour. The developing stage PCSs have the largest but sparse, droplets in convective precipitation, whereas the mature stage has the largest droplets below in the freezing level for all the vertical rainy profiles. The developing stage PCSs have the highest concentration of least sized of hydrometeors. Also, north-eastern continent of SA has higher near surface RR with higher sized of hydrometeors and even higher in developing stage PCSs. Our analysis indicates that the different microphysical properties for the PCSs in different phases are related to cloud and ice water path upward motion and related to the orographic influence.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document