scholarly journals Evaluation of the Polarimetric-Radar Quantitative Precipitation Estimates of an Extremely Heavy Rainfall Event and Nine Common Rainfall Events in Guangzhou

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 330 ◽  
Author(s):  
Yang Zhang ◽  
Liping Liu ◽  
Hao Wen ◽  
Chong Wu ◽  
Yonghua Zhang
Keyword(s):  
Heavy Rainfall ◽  
Doppler Radar ◽  
Heavy Rain ◽  
Rainfall Event ◽  
Retrieval Algorithm ◽  
Heavy Rainfall Event ◽  
Polarimetric Radar ◽  
Rainfall Events ◽  
Factors Affecting ◽  
Hourly Rainfall

The development and application of operational polarimetric radar (PR) in China is still in its infancy. In this study, an operational PR quantitative precipitation estimation (QPE) algorithm is suggested based on data for PR hydrometeor classification and local drop size distribution (DSD). Even though this algorithm performs well for conventional rainfall events, in which hourly rainfall accumulations are less than 50 mm, the capability of a PR to estimate extremely heavy rainfall remains unclear. The proposed algorithm is used for nine different types of rainfall events that occurred in Guangzhou, China, in 2016 and for an extremely heavy rainfall event that occurred in Guangzhou on 6 May 2017. It performs well for all data of these nine rainfall events and for light-to-moderate rain (hourly accumulation <50 mm) in this extremely heavy rainfall event. However, it severely underestimated heavy rain (>50 mm) and the extremely heavy rain at stations where total rainfall exceeded 300 mm within 5 h in this extremely heavy rainfall event. To analyze the reasons for underestimation, a rain microphysics retrieval algorithm is presented to retrieve Dm and Nw from the PR measurements. The DSD characteristics and the factors affecting QPE are analyzed based on Dm and Nw. The results indicate that compared with statistical DSD data in Yangjiang (estimators are derived from these data), the average raindrop diameter during this rainfall event occurred on 6 May 2017 was much smaller and the number concentration was higher. The algorithm underestimated the precipitation with small and midsize particles, but overestimated the precipitation with midsize and large particles. Underestimations occurred when Dm and Nw are both very large, and the severe underestimations for heavy rain are mainly due to these particles. It is verified that some of these particles are associated with melting hail. Owing to the big differences in DSD characteristics, R(KDP, ZDR) underestimates most heavy rain. Therefore, R(AH), which is least sensitive to DSD variations, replaces R(KDP, ZDR) to estimate precipitation. This improved algorithm performs well even for extremely heavy rain. These results are important for evaluating S-band Doppler radar polarization updates in China.

scholarly journals Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Basile Pauthier ◽  
Benjamin Bois ◽  
Thierry Castel ◽  
D. Thévenin ◽  
Carmela Chateau Smith ◽  
...  
Keyword(s):  
High Resolution ◽  
Heavy Rainfall ◽  
Rain Gauge ◽  
Local Scale ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
Preliminary Evaluation ◽  
Rainfall Variation ◽  
Hourly Rainfall ◽  
Rain Gauge Network

A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE) by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1) PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2) both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3) PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE). This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

scholarly journals Evolution of physicochemical species concentration in streams based on heavy rainfall event data obtained for high-frequency monitoring

RBRH ◽  
2016 ◽  
Vol 21 (4) ◽  
pp. 653-665
Author(s):  
Rubia Girardi ◽  
Adilson Pinheiro ◽  
Edson Torres ◽  
Vander Kaufmann ◽  
Luis Hamilton Pospissil Garbossa
Keyword(s):  
Water Quality ◽  
Water Level ◽  
Atlantic Forest ◽  
High Frequency ◽  
Heavy Rainfall ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
Rainfall Events ◽  
Frequency Monitoring ◽  
Heavy Rainfall Events

ABSTRACT Studies carried out over short time intervals assist in understanding the biogeochemical processes occurring relatively fast in natural waters. High frequency monitoring shows a greater variability in the water quality during and immediately after heavy rainfall events. This paper presents an assessment of the surface water quality parameters in the Atlantic Forest biome, caused by heavy rainfall events. The work was developed in two fluviometric sections of the Concordia River watershed, located in the state of Santa Catarina, southern Brazil. The spatial distribution of land use shows the predominance of Atlantic Forest in fluviometric section 1 (FS1) and pasture, forestry, agriculture, and Atlantic Forest in fluviometric section 2 (FS2). In each selected heavy rainfall event, the evolution rainfall height, the water level, and physicochemical parameters of water were analyzed. In all events, the water quality changed due to the heavy rainfall. After the events, an increase in water level and turbidity in both fluviometric sections were detected. In addition, the ammonium ion concentration increased in the river, and the pH value and nitrate concentration decreased. The electrical conductivity presented different behavior in each section. The dissolved oxygen concentration increased in 19 of 27 events. The principal component (PC1) correlated with the turbidity in FS1, and it correlated with level, turbidity, and pH in FS2.

scholarly journals Numerical Simulations and Analysis of June 16, 2010 Heavy Rainfall Event over Singapore Using the WRFV3 Model

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
B. H. Vaid
Keyword(s):  
Numerical Simulations ◽  
Heavy Rainfall ◽  
Global Analysis ◽  
Heavy Rain ◽  
Rainfall Event ◽  
Cumulus Parameterization ◽  
Heavy Rainfall Event ◽  
Convective System ◽  
Rain Event ◽  
Simulated Precipitation

The Numerical Simulations of the June 16, 2010, Heavy Rainfall Event over Singapore are highlighted by an unprecedented precipitation which produced widespread, massive flooding in and around Singapore. The objective of this study is to check the ability of Weather Research Forecasting version 3 (WRFV3) model to predict the heavy rain event over Singapore. Results suggest that simulated precipitation amounts are sensitive to the choice of cumulus parameterization. Various model configurations with initial and boundary conditions from the NCEP Final Global Analysis (FNL), convective and microphysical process parameterizations, and nested-grid interactions have been tested with 48-hour (June 15–17, 2010) integrations of the WRFV3. The spatial distributions of large-scale circulation and dynamical and thermodynamical fields have been simulated reasonably well in the model. The model produced maximum precipitation of ~5 cm over Changi airport which is very near to observation (6.4 cm recorded at Changi airport). The model simulated dynamic and thermodynamic features at 00UTC of June 16, 2010, lead to understand the structure of the mesoscale convective system (MCS) that caused the extreme precipitation over Singapore. It is observed that Singapore heavy rain was the result of an interaction of synoptic-scale weather systems with the mesoscale features.

Numerical Experiments on Spatially Averaged Precipitation in Heavy Rainfall Event Using the WRF Model

2015 ◽  
Vol 10 (3) ◽  
pp. 436-447 ◽  
Author(s):  
Yuji Sugihara ◽  
◽  
Sho Imagama ◽  
Nobuhiro Matsunaga ◽  
Yukiko Hisada ◽  
...  
Keyword(s):  
Numerical Experiments ◽  
Heavy Rainfall ◽  
Wrf Model ◽  
Analysis Data ◽  
Rainfall Event ◽  
Weather Research And Forecasting ◽  
Heavy Rainfall Event ◽  
Spatial Averaging ◽  
Hourly Rainfall ◽  
Precipitation Analysis

It is difficult to forecast hourly rainfall locally even using the latest meteorological models, although hourly rainfall averaged spatially to some extent can be used for calculating practical rainfall. This study conducts numerical experiments with triple nesting on the 2012 heavy rainfall event in northern Kyushu using the weather research and forecasting (WRF) model and examines the features of hourly rainfall averaged spatially. The dependence of rainfall is averaged spatially on a spatial averaging scale and clarified by comparing rainfall calculated by simulation using the WRF model with radar/AMeDAS precipitation analysis data. This study’s findings indicate the effective spatial averaging scale making relative error of calculated values to the observed ones minimum.

scholarly journals The Role of Local Orography on the Development of a Severe Rainfall Event over Western Peninsular Malaysia: A Case Study

2020 ◽  
Vol 148 (5) ◽  
pp. 2191-2209
Author(s):  
Mohd Fadzil Firdzaus Mohd Nor ◽  
Christopher E. Holloway ◽  
Peter M. Inness
Keyword(s):  
Heavy Rainfall ◽  
Flash Floods ◽  
Peninsular Malaysia ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
Limited Area ◽  
Rainfall Events ◽  
Low Level ◽  
Sumatra Island ◽  
Strait Of Malacca

Abstract Severe rainfall events are common in western Peninsular Malaysia. They are usually short and intense, and occasionally cause flash floods and landslides. Forecasting these local events is difficult and understanding the mechanisms of the rainfall events is vital for the advancement of tropical weather forecasting. This study investigates the mechanisms responsible for a local heavy rainfall event on 2 May 2012 that caused flash floods and landslides using both observations and simulations with the limited-area high-resolution Met Office Unified Model (MetUM). Results suggest that previous day rainfalls over Peninsular Malaysia and Sumatra Island influenced the development of overnight rainfall over the Strait of Malacca by low-level flow convergence. Afternoon convection over the Titiwangsa Mountains over Peninsular Malaysia then induced rainfall development and the combination of these two events influenced the development of severe convective storm over western Peninsular Malaysia. Additionally, anomalously strong low-level northwesterlies also contributed to this event. Sensitivity studies were carried out to investigate the influence of the local orography on this event. Flattened Peninsular Malaysia orography causes a lack of rainfall over the central part of Peninsular Malaysia and Sumatra Island and produces a weaker overnight rainfall over the Strait of Malacca. By removing Sumatra Island in the final experiment, the western and inland parts of Peninsular Malaysia would receive more rainfall, as this region is more influenced by the westerly wind from the Indian Ocean. These results suggest the importance of the interaction between landmasses, orography, low-level flow, and the diurnal cycle on the development of heavy rainfall events.

scholarly journals Simulation of a Heavy Rainfall Event on 14 September 2004 over Dhaka, Bangladesh Using MM5 Model

2011 ◽  
Vol 3 (2) ◽  
pp. 261-270 ◽  
Author(s):  
M. N. Ahasan ◽  
Dr. M. A. M. Chowdhury ◽  
D. A. Quadir
Keyword(s):  
Heavy Rainfall ◽  
Mesoscale Model ◽  
Model Performance ◽  
Heavy Rain ◽  
Horizontal Resolution ◽  
Rainfall Event ◽  
Heavy Rainfall Event ◽  
Cumulus Scheme ◽  
Mm5 Model ◽  
The Right

An attempt has been made to simulate a heavy rainfall event on 14 September 2004 over Dhaka, Bangladesh using the fifth-generation PSU/NCAR Mesoscale model (MM5). This was an extraordinary rainfall event and recorded 341 mm rainfall in 24-h which was the highest ever recorded. The MM5 model was run on triple-nested domains at 45, 15, 5 km horizontal resolutions using Anthes-Kuo cumulus  scheme. The model performance was evaluated by examining the different predicted parameters like mean sea level pressure, upper and lower level circulations, moisture, windshear, vorticity, convergence and rainfall. The model derived rainfall was compared with TRMM rainfall. The present results indicate that the MM5 model with the right combination of the nesting domain, horizontal resolution and cumulus scheme was able to simulate the heavy rainfall event, and associated dynamical and thermo-dynamical features reasonably well. The MM5 model suggested that the highly localized heavy rain over Dhaka was the result of an interaction of the monsoon land depression with southwest summer monsoon weather systems. The analysis shows that the depression almost remains stationary over southwest Bangladesh and zone of heavy rain was laid over Dhaka, and required moisture have been supplied from the Bay of Bengal.Keywords: Depression; Heavy rainfall; TRMM; MM5 model; High resolution.© 2011 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.doi:10.3329/jsr.v3i2.6656                 J. Sci. Res. 3 (2), 261-270 (2011)

scholarly journals Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy Meiyu Frontal Rainfall Event

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Hongli Li ◽  
Xiangde Xu ◽  
Yang Hu ◽  
Yanjiao Xiao ◽  
Zhibin Wang
Keyword(s):  
Heavy Rainfall ◽  
Doppler Radar ◽  
Radar Data ◽  
Correction Method ◽  
Rainfall Event ◽  
Radar Reflectivity ◽  
Local Analysis ◽  
Heavy Rainfall Event ◽  
Radar Observations ◽  
Reflectivity Data

Operational Doppler radar observations have potential advantages over other above-surface observations when it comes to assimilation for mesoscale model simulations with high spatial and temporal resolution. To improve the forecast of a heavy frontal rainfall event that occurred in the Yangtze-Huaihe River Basin from 4 July to 5 July 2014 in China, operational radar observations are assimilated by the Local Analysis and Prediction System (LAPS). Radar reflectivity data are used primarily in the LAPS cloud analysis procedure, which retrieves the number of hydrometeors and adjusts the moisture and cloud fields. Radial velocity data are analyzed through the LAPS wind analysis-based successive correction method. A new correction method is developed to correct three-dimensional radar reflectivity data based on hourly surface rain gauge observations. The performance of the correction method is demonstrated by assimilating radar reflectivity observations into LAPS. Experiments with different radar data assimilation are examined. Results show that the assimilation of radar data can effectively correct the background errors and improve the heavy rainfall forecast. The simulated intensity, pattern, and temporal evolution of the heavy rainfall event are better improved with radar reflectivity assimilation, especially when the correction method is implemented to correct radar observations.

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