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

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)

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Role of land state in a high resolution mesoscale model for simulating the Uttarakhand heavy rainfall event over India

Journal of Earth System Science ◽

10.1007/s12040-016-0678-x ◽

2016 ◽

Vol 125 (3) ◽

pp. 475-498 ◽

Cited By ~ 11

Author(s):

P V Rajesh ◽

S Pattnaik ◽

D Rai ◽

K K Osuri ◽

U C Mohanty ◽

...

Keyword(s):

High Resolution ◽

Heavy Rainfall ◽

Mesoscale Model ◽

Rainfall Event ◽

Heavy Rainfall Event

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Quantitative forecast experiment of a heavy rainfall event over Korea in a global model: horizontal resolution versus lead time issues

Meteorology and Atmospheric Physics ◽

10.1007/s00703-014-0312-x ◽

2014 ◽

Vol 124 (3-4) ◽

pp. 113-127 ◽

Cited By ~ 19

Author(s):

Jihyeon Jang ◽

Song-You Hong

Keyword(s):

Lead Time ◽

Heavy Rainfall ◽

Horizontal Resolution ◽

Rainfall Event ◽

Global Model ◽

Heavy Rainfall Event

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

International Journal of Atmospheric Sciences ◽

10.1155/2013/825395 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 5

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.

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

Atmosphere ◽

10.3390/atmos9090330 ◽

2018 ◽

Vol 9 (9) ◽

pp. 330 ◽

Cited By ~ 7

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.

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