The impact of reflectivity correction and accounting for raindrop size distribution variability to improve precipitation estimation by weather radar for an extreme low-land mesoscale convective system

2014 ◽  
Vol 519 ◽  
pp. 3410-3425 ◽  
Author(s):  
Pieter Hazenberg ◽  
Hidde Leijnse ◽  
Remko Uijlenhoet
Keyword(s):  
Size Distribution ◽  
Mesoscale Convective System ◽  
Weather Radar ◽  
Convective System ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Mesoscale Convective ◽  
Raindrop Size ◽  
The Impact

scholarly journals Multipeak Raindrop Size Distribution Observed by UHF/VHF Wind Profilers during the Passage of a Mesoscale Convective System

2009 ◽  
Vol 137 (3) ◽  
pp. 976-990 ◽  
Author(s):  
B. Radhakrishna ◽  
T. Narayana Rao
Keyword(s):  
Size Distribution ◽  
Transition Period ◽  
Mesoscale Convective System ◽  
Bimodal Distribution ◽  
Convective System ◽  
Convective Storms ◽  
Freezing Level ◽  
Raindrop Size Distribution ◽  
Mesoscale Convective ◽  
Raindrop Size

Abstract The Indian Mesosphere–Stratosphere–Troposphere radar (IMSTR), Lower Atmospheric Wind Profiler (LAWP), and Joss–Waldvogel (JW) disdrometer measurements during the passage of two distinctly different (in terms of total rain and rainfall rate) convective storms are utilized to understand the nature and origin of the multipeak raindrop size distribution (MRDSD). Important issues, such as the preferential stage and height at which bi- or multimodal rain distribution occurs in a mesoscale convective system (MCS) are addressed. For both of the storms, the MRDSD is observed during the transition period from convection to stratiform rain. The pattern and variation of the MRDSD during this period is strikingly similar in both of the storms. The MRDSD is first observed above the freezing level in the presence of heavy riming. The subsequent spectra have shown bimodal distribution below the freezing level, and the bimodality is attributed to the coexistence of ice and supercooled droplets. Interestingly, the bimodal distribution has not varied much with altitude when it is produced because of the coexistence of ice and supercooled droplets. The MRDSD is also observed at few range gates and for a short duration. Such a type of MRDSD is seen during the transition period between decaying and intensifying rain.

scholarly journals Regional variability of raindrop size distribution over Indonesia

2013 ◽  
Vol 31 (11) ◽  
pp. 1941-1948 ◽  
Author(s):  
M. Marzuki ◽  
H. Hashiguchi ◽  
M. K. Yamamoto ◽  
S. Mori ◽  
M. D. Yamanaka
Keyword(s):  
Size Distribution ◽  
Mesoscale Convective System ◽  
Radar Reflectivity ◽  
The Other ◽  
Convective System ◽  
Horizontal Scale ◽  
Regional Variability ◽  
Raindrop Size Distribution ◽  
Mesoscale Convective ◽  
Raindrop Size

Abstract. Regional variability of raindrop size distribution (DSD) along the Equator was investigated through a network of Parsivel disdrometers in Indonesia. The disdrometers were installed at Kototabang (KT; 100.32° E, 0.20° S), Pontianak (PT; 109.37° E, 0.00° S), Manado (MN; 124.92° E, 1.55° N) and Biak (BK; 136.10° E, 1.18° S). It was found that the DSD at PT has more large drops than at the other three sites. The DSDs at the four sites are influenced by both oceanic and continental systems, and majority of the data matched the maritime-like DSD that was reported in a previous study. Continental-like DSDs were somewhat dominant at PT and KT. Regional variability of DSD is closely related to the variability of topography, mesoscale convective system propagation and horizontal scale of landmass. Different DSDs at different sites led to different Z–R relationships in which the radar reflectivity at PT was much larger than at other sites, at the same rainfall rate.

scholarly journals Observed Response of the Raindrop Size Distribution to Changes in the Melting Layer

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 319 ◽  
Author(s):  
Patrick Gatlin ◽  
Walter Petersen ◽  
Kevin Knupp ◽  
Lawrence Carey
Keyword(s):  
Size Distribution ◽  
Basic Assumption ◽  
Weighted Mean ◽  
Radar Rainfall ◽  
Melting Layer ◽  
Quantitative Precipitation Estimation ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Raindrop Size ◽  
Stratiform Rainfall

Vertical variability in the raindrop size distribution (RSD) can disrupt the basic assumption of a constant rain profile that is customarily parameterized in radar-based quantitative precipitation estimation (QPE) techniques. This study investigates the utility of melting layer (ML) characteristics to help prescribe the RSD, in particular the mass-weighted mean diameter (Dm), of stratiform rainfall. We utilize ground-based polarimetric radar to map the ML and compare it with Dm observations from the ground upwards to the bottom of the ML. The results show definitive proof that a thickening, and to a lesser extent a lowering, of the ML causes an increase in raindrop diameter below the ML that extends to the surface. The connection between rainfall at the ground and the overlying microphysics in the column provide a means for improving radar QPE at far distances from a ground-based radar or close to the ground where satellite-based radar rainfall retrievals can be ill-defined.

scholarly journals STUDY ON SUMMER RAINDROP SIZE DISTRIBUTION AND RETRIEVED POLARIMETRIC RADAR PARAMETER OVER LEIZHOU PENINSULA

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 245-250
Author(s):  
Z. B. Zhou ◽  
J. J. Lv ◽  
S. J. Niu
Keyword(s):  
Size Distribution ◽  
Gamma Distribution ◽  
Least Squares Method ◽  
Convective Precipitation ◽  
Polarimetric Radar ◽  
Leizhou Peninsula ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Raindrop Size ◽  
Subtropical Monsoon Climate

Abstract. Leizhou peninsula is located in the south of Guangdong Province, near South China Sea, and has a tropical and subtropical monsoon climate. Based on observed drop size distribution (DSD) data from July 2007 to August 2007 with PARSIVEL disdrometers deployed at Zhanjiang and Suixi, the characterists of DSDs are studied. Non-linear least squares method is used to fit Gamma distribution. Convective and stratiform averaged DSDs are in good agreement with Gamma distribution, especially in stratiform case. Convective average DSDs have a wider spectrum and higher peak. Microphysical parameter differences between convective and stratiform are discussed, convective precipitation has a higher mass-weighted mean diameter (Dm) and generalized intercepts (Nw) in both areas. The constrained relations between Gamma distribution parameter (μ, Λ, N0) is derived. The retrieved polarimetric radar parameter (KDP, ZDR, Zh) have a good self-consistency, which can be used to improve the accuracy of KDP calculation. R-KDP-ZDR is superior to the R-KDP, R-ZDR-Zh in quantitative precipitation estimation (QPE), with a correlation coefficient higher than 0.98.

scholarly journals Measurements and Modeling of the Full Rain Drop Size Distribution

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 39 ◽  
Author(s):  
Merhala Thurai ◽  
Viswanathan Bringi ◽  
Patrick Gatlin ◽  
Walter Petersen ◽  
Matthew Wingo
Keyword(s):  
Size Distribution ◽  
Small Drop ◽  
Dual Frequency ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Rain Drop ◽  
Double Moment ◽  
Raindrop Size ◽  
Microphysical Processes ◽  
Global Precipitation

The raindrop size distribution (DSD) is fundamental for quantitative precipitation estimation (QPE) and in numerical modeling of microphysical processes. Conventional disdrometers cannot capture the small drop end, in particular the drizzle mode which controls collisional processes as well as evaporation. To overcome this limitation, the DSD measurements were made using (i) a high-resolution (50 microns) meteorological particle spectrometer to capture the small drop end, and (ii) a 2D video disdrometer for larger drops. Measurements were made in two climatically different regions, namely Greeley, Colorado, and Huntsville, Alabama. To model the DSDs, a formulation based on (a) double-moment normalization and (b) the generalized gamma (GG) model to describe the generic shape with two shape parameters was used. A total of 4550 three-minute DSDs were used to assess the size-resolved fidelity of this model by direct comparison with the measurements demonstrating the suitability of the GG distribution. The shape stability of the normalized DSD was demonstrated across different rain types and intensities. Finally, for a tropical storm case, the co-variabilities of the two main DSD parameters (normalized intercept and mass-weighted mean diameter) were compared with those derived from the dual-frequency precipitation radar onboard the global precipitation mission satellite.

Geographical characteristics of raindrop size distribution in the southern parts of Korea

2020 ◽  
Author(s):  
Sung–Ho Suh ◽  
Hyeon–Joon Kim ◽  
Dong–In Lee ◽  
Tae–Hoon Kim
Keyword(s):  
Size Distribution ◽  
Coastal Area ◽  
Sea Breeze ◽  
Convective Precipitation ◽  
Drop Diameter ◽  
Local Maxima ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Raindrop Size ◽  
Stratiform Rainfall

AbstractThis study analyzed the regional characteristics of raindrop size distribution (DSD) in the southern coastal area of South Korea. Data from March 2016 to February 2017 were recorded by four PARSIVEL disdrometers installed at intervals of ~20 km from the coastline to inland. Within 20 km from the coastline, multiple local maxima in the probability density function (PDF) were observed at Dm (mass-weighted drop diameter) = 0.6 mm and logNw (normalized intercept parameter) = 5.2 for stratiform rainfall, but these features were not observed more than 20 km from the coastline. Based on mean Dm–logNw values, stratiform rainfall clearly differed between coastal and inland areas. For convective precipitation, there was a linear relationship between Dm and Nw with the distance from the coastline. PDF analyses of diurnal variation in DSD confirmed that in spring and autumn the multiple local maxima appear in the daytime. The multiple local maxima in Dm (logNw) values were lower (higher) at nighttime (NT) than DT in the spring and summer season. These features were highly dependent on the prevailing wind. There was a pattern of increasing A and decreasing b in the radar reflectivity–rainfall rate (Z–R) relationship (Z = ARb) with distance from the coastline, and these features were more pronounced in convective precipitation. These diurnal variabilities were regular in stratiform rainfall, and there were large differences in quantitative precipitation estimation depending on the land–sea breeze in the coastal area.

Multiscale Characteristics and Evolution of Perturbations for Warm Season Convection-Allowing Precipitation Forecasts: Dependence on Background Flow and Method of Perturbation

2014 ◽  
Vol 142 (3) ◽  
pp. 1053-1073 ◽  
Author(s):  
Aaron Johnson ◽  
Xuguang Wang ◽  
Ming Xue ◽  
Fanyou Kong ◽  
Gang Zhao ◽  
...  
Keyword(s):  
Warm Season ◽  
Mesoscale Convective System ◽  
Haar Wavelet ◽  
Precipitation Forecast ◽  
Initial Time ◽  
Small Scale ◽  
Convective System ◽  
Mesoscale Convective ◽  
Perturbation Energy ◽  
The Impact

Abstract Multiscale convection-allowing precipitation forecast perturbations are examined for two forecasts and systematically over 34 forecasts out to 30-h lead time using Haar Wavelet decomposition. Two small-scale initial condition (IC) perturbation methods are compared to the larger-scale IC and physics perturbations in an experimental convection-allowing ensemble. For a precipitation forecast driven primarily by a synoptic-scale baroclinic disturbance, small-scale IC perturbations resulted in little precipitation forecast perturbation energy on medium and large scales, compared to larger-scale IC and physics (LGPH) perturbations after the first few forecast hours. However, for a case where forecast convection at the initial time grew upscale into a mesoscale convective system (MCS), small-scale IC and LGPH perturbations resulted in similar forecast perturbation energy on all scales after about 12 h. Small-scale IC perturbations added to LGPH increased total forecast perturbation energy for this case. Averaged over 34 forecasts, the small-scale IC perturbations had little impact on large forecast scales while LGPH accounted for about half of the error energy on such scales. The impact of small-scale IC perturbations was also less than, but comparable to, the impact of LGPH perturbations on medium scales. On small scales, the impact of small-scale IC perturbations was at least as large as the LGPH perturbations. The spatial structure of small-scale IC perturbations affected the evolution of forecast perturbations, especially at medium scales. There was little systematic impact of the small-scale IC perturbations when added to LGPH. These results motivate further studies on properly sampling multiscale IC errors.

scholarly journals The Impact of Low-Level Moisture Errors on Model Forecasts of an MCS Observed during PECAN

2017 ◽  
Vol 145 (9) ◽  
pp. 3599-3624 ◽  
Author(s):  
John M. Peters ◽  
Erik R. Nielsen ◽  
Matthew D. Parker ◽  
Stacey M. Hitchcock ◽  
Russ S. Schumacher
Keyword(s):  
Convective Available Potential Energy ◽  
Mesoscale Convective System ◽  
Squall Line ◽  
Convective System ◽  
Low Level ◽  
Eastern Flank ◽  
Western Flank ◽  
Mesoscale Convective ◽  
Outflow Boundary ◽  
The Impact

This article investigates errors in forecasts of the environment near an elevated mesoscale convective system (MCS) in Iowa on 24–25 June 2015 during the Plains Elevated Convection at Night (PECAN) field campaign. The eastern flank of this MCS produced an outflow boundary (OFB) and moved southeastward along this OFB as a squall line. The western flank of the MCS remained quasi stationary approximately 100 km north of the system’s OFB and produced localized flooding. A total of 16 radiosondes were launched near the MCS’s eastern flank and 4 were launched near the MCS’s western flank. Convective available potential energy (CAPE) increased and convective inhibition (CIN) decreased substantially in observations during the 4 h prior to the arrival of the squall line. In contrast, the model analyses and forecasts substantially underpredicted CAPE and overpredicted CIN owing to their underrepresentation of moisture. Numerical simulations that placed the MCS at varying distances too far to the northeast were analyzed. MCS displacement error was strongly correlated with models’ underrepresentation of low-level moisture and their associated overrepresentation of the vertical distance between a parcel’s initial height and its level of free convection ([Formula: see text], which is correlated with CIN). The overpredicted [Formula: see text] in models resulted in air parcels requiring unrealistically far northeastward travel in a region of gradual meso- α-scale lift before these parcels initiated convection. These results suggest that erroneous MCS predictions by NWP models may sometimes result from poorly analyzed low-level moisture fields.

scholarly journals Characteristics of Raindrop Size Distribution in Typhoon Nida (2016) before and after Landfall in Southern China from 2D Video Disdrometer Data

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Lu Feng ◽  
Xiantong Liu ◽  
Hui Xiao ◽  
Liusi Xiao ◽  
Feng Xia ◽  
...  
Keyword(s):  
Size Distribution ◽  
Southern China ◽  
Spectral Width ◽  
Average Mass ◽  
Raindrop Size Distribution ◽  
The Pacific ◽  
Before And After ◽  
Precipitation Estimation ◽  
Distribution Parameters ◽  
Raindrop Size

During the passage of Typhoon Nida, the raindrop size distribution parameters, the raindrop spectra, the shape and slope (μ–Λ) relationship, the radar reflectivity factor, and rain rate (Z–R) relationship were investigated based on a two-dimensional (2D) video disdrometer in Guangdong, China, from August 1 to 2, 2016. Due to the underlying surface difference between the ocean and land, this process was divided into two distinct periods (before landfall and after landfall). The characteristics of raindrop size distribution between the period before landfall and the period after landfall were quite distinct. The period after landfall exhibited higher concentrations of each size bin (particularly small drops) and wider raindrop spectral width than the period before landfall. Compared with the period before landfall, the period after landfall had a higher average mass-weighted mean diameter Dm that was smaller than those of other TCs from the same ocean (the Pacific). The μ–Λ relationship and Z–R relationship in this study were also compared with other TCs from the same ocean (the Pacific). This investigation of the microphysical characteristics of Typhoon Nida before landfall and after landfall may improve radar quantitative precipitation estimation (QPE) products and microphysical schemes by providing useful information.

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