Understanding Ice Cloud‐Precipitation Properties of Three Modes of Mesoscale Convective Systems During PECAN

Cui, Wenjun; Dong, Xiquan; Xi, Baike; Fan, Jiwen; Tian, Jingjing; Wang, Jingyu; McHardy, T. M.

doi:10.1029/2019jd030330

Cited by 11 publications

(9 citation statements)

References 39 publications

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“…For SP (Figures 12a and 12c), the log 10 N w values of the three stages were identical except for higher values above 8 km in the mature stage. The higher log 10 N w values indicated that more ice particles in the mature stage might be advected from convective regions by divergent air motions (Cui et al, 2019;Herzegh & Hobbs, 1980). Their D m profiles were consistent with the order of the stratiform vertical precipitation profiles (Figure 11a), with the smallest being in the developing stage and the largest in the mature stage.…”

Section: Drop Size Distributionsupporting

confidence: 60%

Vertical Structures of Typical Meiyu Precipitation Events Retrieved From GPM‐DPR

et al. 2020

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This work for the first time analyzed the vertical structures of the different stages of Meiyu precipitation systems over the Yangtze-Huai River Valley in central China using measurements and retrievals from the Global Precipitation Measurement Mission Dual-Frequency Precipitation Radar (GPM-DPR) and Feng Yun satellites. GPM-DPR-retrieved near-surface rain and drop size distributions were first validated against the surface disdrometer measurements and showed good agreement. Then we analyzed three cases from the Integrative Monsoon Frontal Rainfall Experiment to demonstrate the different characteristics of convective precipitation and stratiform precipitation (SP) in the developing, mature, and dissipating stages of the Meiyu precipitation systems, respectively. For statistical analysis, all Meiyu cases during the period 2016-2018 detected by GPM-DPR were collected and classified into different types and stages.In the stratiform regions of Meiyu precipitation systems, coalescence slightly overwhelms breakup and/or evaporation processes, but it was dominant in the convective regions when raindrops fall. There were large numbers of large ice particles during the developing stage due to strong updrafts and abundant moisture, whereas there were both large ice and liquid particles in the mature stage. The vertical structures of the SP examined in this study were similar to those over the ocean regions due to high relative humidity but different to the mountainous west regions of the USA. The findings of the stage-dependent SP vertical structures provide better understanding of the evolution of monsoon frontal precipitation, as well as the associated microphysical properties, and provide insights to improve microphysical parameterization in future models.

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Section: Drop Size Distributionsupporting

confidence: 60%

Vertical Structures of Typical Meiyu Precipitation Events Retrieved From GPM‐DPR

et al. 2020

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“…Through the combination of the Next Generation Radar (NEXRAD) network and the Geostationary Operational Environmental Satellite system (GOES) observations, Feng et al 2011developed a hybrid cloud classification algorithm that objectively separates the convective systems into the components of convective core (CC), stratiform rain (SR), and anvil clouds (AC). The SR regions have the largest coverage of warm-season rainfall over the midlatitudes, while the CC regions (corresponding to the precipitation type of CR) account for the most intense precipitation (Cui et al 2019). Feng et al (2012) also found that the CR rain rate is almost an order of magnitude higher than SR, causing a surge in accumulated precipitation within a short time period and possibly resulting in flooding events.…”

Section: E Separation Of Convective Versus Stratiform Rainmentioning

confidence: 94%

A Regime-Based Evaluation of Southern and Northern Great Plains Warm-Season Precipitation Events in WRF

Wang

Dong

Kennedy

et al. 2019

Weather and Forecasting

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A competitive neural network known as the self-organizing map (SOM) is used to objectively identify synoptic patterns in the North American Regional Reanalysis (NARR) for warm-season (April–September) precipitation events over the Southern and Northern Great Plains (SGP/NGP) from 2007 to 2014. Classifications for both regions demonstrate contrast in dominant synoptic patterns ranging from extratropical cyclones to subtropical ridges, all of which have preferred months of occurrence. Precipitation from deterministic Weather Research and Forecasting (WRF) Model simulations run by the National Severe Storms Laboratory (NSSL) are evaluated against National Centers for Environmental Prediction (NCEP) Stage IV observations. The SGP features larger observed precipitation amount, intensity, and coverage, as well as better model performance than the NGP. Both regions’ simulated convective rain intensity and coverage have good agreement with observations, whereas the stratiform rain (SR) is more problematic with weaker intensity and larger coverage. Further evaluation based on SOM regimes shows that WRF bias varies with the type of meteorological forcing, which can be traced to differences in the diurnal cycle and properties of stratiform and convective rain. The higher performance scores are generally associated with the extratropical cyclone condition than the subtropical ridge. Of the six SOM classes over both regions, the largest precipitation oversimulation is found for SR dominated classes, whereas a nocturnal negative precipitation bias exists for classes featuring upscale growth of convection.

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“…The major NEXRAD products used in this study include: reflectivity data, and the dual‐pol products of specific differential phase ( k dp ), differential reflectivity ( Z dr ), and cross‐correlation ( ρ hv ). The k dp , Z dr , and ρ hv products illustrate the vertical and horizontal interaction of the radar beam with hydrometeors (Brauer et al., 2020; Cifelli et al., 2010; Cui et al., 2019; Fridlind et al., 2019; Kumjian, 2013; Li & Mecikalski, 2012; Tian et al., 2020). For example, a falling raindrop is considered to have a larger horizontal than vertical semi‐axis (“hamburger shape”) with positive k dp and Z dr values.…”

Section: Methodsmentioning

confidence: 99%

An Analysis of the Performance of the Houston Lightning Mapping Array During an Intense Period of Convection During Tropical Storm Harvey

Logan

2021

JGR Atmospheres

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Extreme lightning activity (∼300,000 flashes) was observed by the Houston Lightning Mapping Array (HLMA) network during Tropical Storm Harvey on August 26, 2017–August 27, 2017. There was an overall weak correlation between the lightning flash and precipitation rates (R = 0.14; p ∼ 0.17) likely due to feeder bands transitioning between deep and shallow convection. The peak precipitation rate (14.2 mm hr−1) lagged the peak lightning flash rate (∼18,000 flashes [30 min]−1) by 7 h. Adjusting for the lag, the correlation increased to 0.71 (p < 0.01) indicating a relationship between the uptick in lightning activity in the convective feeder bands and the resulting heavy precipitation during episodes of shallow convection. Peak lightning flash extent densities of 12.4 km−2 min−1 were spatially collocated with precipitation rates exceeding 9 mm hr−1. NEXRAD reflectivity data featured 30 dBZ echo heights in excess of 10 km that were collocated with peak lightning flash extent densities exceeding 3 km−2 min−1. The NEXRAD specific phase (kdp) and differential phase (Zdr) dual‐polarization products were highest (≥2° km−1 and dB) below the melting layer (4.6 km) indicating heavy precipitation and strong updrafts. Negative kdp and Zdr values (≤−0.15° km−1 and dB) collocated with the peak lightning flash extent density altitudes indicated ice particle generation which likely augmented the charge separation process. This is likely the first time a major tropical cyclone has occurred within the confines of a lightning mapping array. The lightning data, when used synergistically with radar and precipitation data, can adequately quantify tropical convection exhibiting an elevated mixed‐phase depth.

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Understanding Ice Cloud‐Precipitation Properties of Three Modes of Mesoscale Convective Systems During PECAN

Cited by 11 publications

References 39 publications

Vertical Structures of Typical Meiyu Precipitation Events Retrieved From GPM‐DPR

Vertical Structures of Typical Meiyu Precipitation Events Retrieved From GPM‐DPR

A Regime-Based Evaluation of Southern and Northern Great Plains Warm-Season Precipitation Events in WRF

An Analysis of the Performance of the Houston Lightning Mapping Array During an Intense Period of Convection During Tropical Storm Harvey

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