Impact of Atmospheric Infrared Sounder Data on the Numerical Simulation of a Historical Mumbai Rain Event

Abstract In this paper, the three-dimensional variational data assimilation scheme (3DVAR) in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (Penn State–NCAR) Mesoscale Model (MM5) is used to study the impact of assimilating Atmospheric Infrared Sounder (AIRS) retrieved temperature and moisture profiles on board Aqua, a satellite that is part of NASA’s Earth Observing System. A record-breaking heavy rain event that occurred over Mumbai, India, on 26 July 2005 with 24-h rainfall exceeding 94 cm was used for the simulation. By analyzing the data from the NCEP–NCAR reanalysis, possible causes of this heavy rainfall event were investigated. The temporal evolution of meteorological fields clearly indicates the formation of midtropospheric mesoscale vortices over Mumbai that exactly coincides with the duration of the intense rainfall. Analysis also indicated the midlevel dryness with higher temperature and moisture in the lower levels. This midlevel dryness with high temperature and moisture in the lower levels increases the conditional instability, which was conducive for the development of very severe local thunderstorms. The midtropospheric mesoscale vortices existed over Mumbai together with lower-level instability and the active monsoon conditions over the west coast resulted in intense rainfall, on the order of 94 cm in 24 h. Numerical experiments were conducted, with two nested domains (45- and 15-km grid spacing). The assimilation of the AIRS-retrieved temperature and moisture profiles produced significant impacts on the location and intensity of the simulated rainfall. It is seen from the numerical experiments that the assimilation of AIRS data could produce the structure of mesoscale vortices, and lower-level thermodynamics and convergence much more realistically compared with the control simulation. The spatial distribution of the rainfall from the simulation using AIRS data was more realistic than that without AIRS data. To make the quantitative comparison of the predicted rainfall with the observed one, the equitable threat score and bias were calculated for different threshold values of rainfall. Inclusion of AIRS data significantly improved the precipitation as indicated by the equitable threat scores and biases for almost all of the threshold rainfall categories.

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The impact of heavy rain event on groundwater microbial communities in Xikuangshan, Hunan Province, P.R. China

Journal of Hydrology ◽

10.1016/j.jhydrol.2020.125674 ◽

2020 ◽

pp. 125674

Author(s):

Mengxiaojun Wu ◽

Hongmei Wang ◽

Weiqi Wang ◽

Yuyang Song ◽

Liyuan Ma ◽

...

Keyword(s):

Microbial Communities ◽

Heavy Rain ◽

Hunan Province ◽

Rain Event ◽

Heavy Rain Event ◽

The Impact

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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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A Detention Reservoir Reduced Combined Sewer Overflows and Bathing Water Contamination Due to Intense Rainfall

Water ◽

10.3390/w13233425 ◽

2021 ◽

Vol 13 (23) ◽

pp. 3425

Author(s):

Marco Romei ◽

Matteo Lucertini ◽

Enrico Esposito Renzoni ◽

Elisa Baldrighi ◽

Federica Grilli ◽

...

Keyword(s):

Environmental Concern ◽

Treatment Options ◽

Heavy Rain ◽

Rain Event ◽

Storm Events ◽

Combined Sewer Overflows ◽

Bathing Water ◽

Combined Sewer ◽

Sewer Overflows ◽

The Impact

Combined sewer overflows (CSOs) close to water bodies are a cause of grave environmental concern. In the past few decades, major storm events have become increasingly common in some regions, and the meteorological scenarios predict a further increase in their frequency. Consequently, CSO control and treatment according to best practices, the adoption of innovative treatment solutions and careful sewer system management are urgently needed. A growing number of publications has been addressing the quality, quantity and types of available water management and treatment options. In this study, we describe the construction of an innovative detention reservoir along the Arzilla River (Fano, Italy) whose function is to store diluted CSO wastewater exceeding the capacity of a combined drain system. River water sampling and testing for microbial contamination downstream of the tank after a heavy rain event found a considerable reduction of fecal coliform concentrations, which would have compounded the impact of stormwater on the bathing site. These preliminary results suggest that the detention tank exerted beneficial environmental effects on bathing water by lowering the microbial load.

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Assessing the Impact of Dropsonde Data on Rain Forecasts in Taiwan with Observing System Simulation Experiments

Atmosphere ◽

10.3390/atmos12121672 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1672

Author(s):

Fang-Ching Chien ◽

Yen-Chao Chiu

Keyword(s):

System Simulation ◽

Northern South China Sea ◽

Heavy Rain ◽

Separation Distance ◽

Rain Event ◽

Ensemble Forecasts ◽

Minimum Requirement ◽

Sensitivity Studies ◽

Observing System Simulation Experiment ◽

The Impact

This paper presents an observing system simulation experiment (OSSE) study to examine the impact of dropsonde data assimilation (DA) on rainfall forecasts for a heavy rain event in Taiwan. The rain event was associated with strong southwesterly flows over the northern South China Sea (SCS) after a weakening tropical cyclone (TC) made landfall over southeastern China. With DA of synthetic dropsonde data over the northern SCS, the model reproduces more realistic initial fields and a better simulated TC track that can help in producing improved low-level southwesterly flows and rainfall forecasts in Taiwan. Dropsonde DA can also aid the model in reducing the ensemble spread, thereby producing more converged ensemble forecasts. The sensitivity studies suggest that dropsonde DA with a 12-h cycling interval is the best strategy for deriving skillful rainfall forecasts in Taiwan. Increasing the DA interval to 6 h is not beneficial. However, if the flight time is limited, a 24-h interval of DA cycling is acceptable, because rainfall forecasts in Taiwan appear to be satisfactory. It is also suggested that 12 dropsondes with a 225-km separation distance over the northern SCS set a minimum requirement for enhancing the model regarding rainfall forecasts. Although more dropsonde data can help the model to obtain better initial fields over the northern SCS, they do not provide more assistance to the forecasts of the TC track and rainfall in Taiwan. These findings can be applied to the future field campaigns and model simulations in the nearby regions.

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Digital Filter Initialization for MM5

Monthly Weather Review ◽

10.1175/mwr3117.1 ◽

2006 ◽

Vol 134 (4) ◽

pp. 1222-1236 ◽

Cited By ~ 16

Author(s):

Min Chen ◽

Xiang-Yu Huang

Keyword(s):

Digital Filter ◽

Mesoscale Model ◽

Heavy Rain ◽

State University ◽

Initial Model ◽

Pennsylvania State University ◽

Fifth Generation ◽

Beijing Institute ◽

The Impact

Abstract In this paper several configurations of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), which is implemented at Beijing Institute of Urban Meteorology in China, are used to demonstrate the initial noise problem caused either by interpolating global model fields onto an MM5 grid or by using MM5 objective analysis schemes. An implementation of a digital filter initialization (DFI) package to MM5 is then documented. A heavy rain case study and intermittent data assimilation experiments are used to assess the impact of DFI on MM5 forecasts. It is shown that DFI effectively filters out the noise and produces a balanced initial model state. It is also shown that DFI improves the spinup aspects for precipitation, leading to better scores for short-range precipitation forecasts. The issues related to the initialization of variables that are not observed and/or analyzed, in particular those for nonhydrostatic quantities, are discussed.

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

Journal of Scientific Research ◽

10.3329/jsr.v3i2.6656 ◽

2011 ◽

Vol 3 (2) ◽

pp. 261-270 ◽

Cited By ~ 4

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)

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Investigating 3D and 4D variational rapid-update-cycling assimilation of weather radar reflectivity for a heavy rain event in central Italy

Natural Hazards and Earth System Science ◽

10.5194/nhess-21-2849-2021 ◽

2021 ◽

Vol 21 (9) ◽

pp. 2849-2865

Author(s):

Vincenzo Mazzarella ◽

Rossella Ferretti ◽

Errico Picciotti ◽

Frank Silvio Marzano

Keyword(s):

Data Assimilation ◽

Roc Curve ◽

Initial Conditions ◽

Central Italy ◽

Heavy Rain ◽

Radar Reflectivity ◽

Precipitation Forecast ◽

Rain Event ◽

Heavy Rain Event ◽

The Impact

Abstract. Forecasting precipitation over the Mediterranean basin is still a challenge because of the complex orographic region that amplifies the need for local observation to correctly initialize the forecast. In this context, data assimilation techniques play a key role in improving the initial conditions and consequently the timing and position of the precipitation forecast. For the first time, the ability of a cycling 4D-Var to reproduce a heavy rain event in central Italy, as well as to provide a comparison with the largely used cycling 3D-Var, is evaluated in this study. The radar reflectivity measured by the Italian ground radar network is assimilated in the Weather Research and Forecasting (WRF) model to simulate an event that occurred on 3 May 2018 in central Italy. In order to evaluate the impact of data assimilation, several simulations are objectively compared by means of a fraction skill score (FSS), which is calculated for several threshold values, and a receiver operating characteristic (ROC) curve. The results suggest that both assimilation methods in the cycling mode improve the 1-, 3- and 6-hourly quantitative precipitation estimation. More specifically, the cycling 4D-Var with a warm start initialization shows the highest FSS values in the first hours of the simulation both with light and heavy precipitation. Finally, the ROC curve confirms the benefit of 4D-Var: the area under the curve is 0.91 compared to 0.88 for the control experiment without data assimilation.

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High-Resolution Climate Change Impact Analysis on Expected Future Water Availability in the Upper Jordan Catchment and the Middle East

Journal of Hydrometeorology ◽

10.1175/jhm-d-13-0153.1 ◽

2014 ◽

Vol 15 (4) ◽

pp. 1517-1531 ◽

Cited By ~ 15

Author(s):

Gerhard Smiatek ◽

Harald Kunstmann ◽

Andreas Heckl

Keyword(s):

Climate Change ◽

High Resolution ◽

Water Availability ◽

Impact Analysis ◽

River Flow ◽

Climate Model ◽

Mesoscale Model ◽

Global Climate Model ◽

Full Range ◽

The Impact

Abstract The impact of climate change on the future water availability of the upper Jordan River (UJR) and its tributaries Dan, Snir, and Hermon located in the eastern Mediterranean is evaluated by a highly resolved distributed approach with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) run at 18.6- and 6.2-km resolution offline coupled with the Water Flow and Balance Simulation Model (WaSiM). The MM5 was driven with NCEP reanalysis for 1971–2000 and with Hadley Centre Coupled Model, version 3 (HadCM3), GCM forcings for 1971–2099. Because only one regional–global climate model combination was applied, the results may not give the full range of possible future projections. To describe the Dan spring behavior, the hydrological model was extended by a bypass approach to allow the fast discharge components of the Snir to enter the Dan catchment. Simulation results for the period 1976–2000 reveal that the coupled system was able to reproduce the observed discharge rates in the partially karstic complex terrain to a reasonable extent with the high-resolution 6.2-km meteorological input only. The performed future climate simulations show steadily rising temperatures with 2.2 K above the 1976–2000 mean for the period 2031–60 and 3.5 K for the period 2070–99. Precipitation trends are insignificant until the middle of the century, although a decrease of approximately 12% is simulated. For the end of the century, a reduction in rainfall ranging between 10% and 35% can be expected. Discharge in the UJR is simulated to decrease by 12% until 2060 and by 26% until 2099, both related to the 1976–2000 mean. The discharge decrease is associated with a lower number of high river flow years.

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Comprehensive Analytical Modelling of an Absolute pH Sensor

Sensors ◽

10.3390/s21155190 ◽

2021 ◽

Vol 21 (15) ◽

pp. 5190

Author(s):

Cristina Medina-Bailon ◽

Naveen Kumar ◽

Rakshita Pritam Singh Dhar ◽

Ilina Todorova ◽

Damien Lenoble ◽

...

Keyword(s):

Silicon Dioxide ◽

Numerical Experiments ◽

Ph Sensor ◽

Hafnium Dioxide ◽

Matlab Code ◽

Oxide Degradation ◽

Depletion Width ◽

Ion Activity ◽

The Absolute ◽

The Impact

In this work, we present a comprehensive analytical model and results for an absolute pH sensor. Our work aims to address critical scientific issues such as: (1) the impact of the oxide degradation (sensing interface deterioration) on the sensor’s performance and (2) how to achieve a measurement of the absolute ion activity. The methods described here are based on analytical equations which we have derived and implemented in MATLAB code to execute the numerical experiments. The main results of our work show that the depletion width of the sensors is strongly influenced by the pH and the variations of the same depletion width as a function of the pH is significantly smaller for hafnium dioxide in comparison to silicon dioxide. We propose a method to determine the absolute pH using a dual capacitance system, which can be mapped to unequivocally determine the acidity. We compare the impact of degradation in two materials: SiO2 and HfO2, and we illustrate the acidity determination with the functioning of a dual device with SiO2.

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