scholarly journals SIMULATION OF A THUNDERSTORM EVENT OVER BANGLADESH USING WRF-ARW MODEL

2015 ◽  
Vol 44 (2) ◽  
pp. 124-131 ◽  
Author(s):  
M. N. Ahasan ◽  
D. A. Quadir ◽  
K.A. Khan ◽  
M. S. Haque
Keyword(s):  
Numerical Simulation ◽  
Model Performance ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Arw Model ◽  
Advance Research ◽  
Weather Research

Numerical simulation of the thunderstorm event occurred over Srimangal, Bangladesh at 1200 UTCon 21 May 2011 have been carried out using Advance Research dynamic core of Weather Research andForecasting Model (WRF-ARW). The WRF model was run in a domain at 9 km horizontal resolution using sixhourly NCEP-FNL datasets from 0000UTC of 21 May to 0000UTC of 22 May 2011 as initial and boundaryconditions. Hourly outputs have been analyzed to asses and/or compare the model performance. The WRFmodel captured the studied thunderstorm event on 21 May 2011 in reasonably well with some spatial andtemporal biases in the results. But the model simulated 24-h rainfall over the country as a whole overestimatedthe rainfall by 46.72% compared to that of Bangladesh Meteorological Department (BMD) observation.

scholarly journals Verification of Forecast Weather Surface Variables over Vietnam Using the National Numerical Weather Prediction System

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Tien Du Duc ◽  
Lars Robert Hole ◽  
Duc Tran Anh ◽  
Cuong Hoang Duc ◽  
Thuy Nguyen Ba
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Model Performance ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Prediction System ◽  
Regional Models ◽  
Global Spectral Model ◽  
Numerical Weather ◽  
The Us

The national numerical weather prediction system of Vietnam is presented and evaluated. The system is based on three main models, namely, the Japanese Global Spectral Model, the US Global Forecast System, and the US Weather Research and Forecasting (WRF) model. The global forecast products have been received at 0.25- and 0.5-degree horizontal resolution, respectively, and the WRF model has been run locally with 16 km horizontal resolution at the National Center for Hydro-Meteorological Forecasting using lateral conditions from GSM and GFS. The model performance is evaluated by comparing model output against observations of precipitation, wind speed, and temperature at 168 weather stations, with daily data from 2010 to 2014. In general, the global models provide more accurate forecasts than the regional models, probably due to the low horizontal resolution in the regional model. Also, the model performance is poorer for stations with altitudes greater than 500 meters above sea level (masl). For tropical cyclone performance validations, the maximum wind surface forecast from global and regional models is also verified against the best track of Joint Typhoon Warning Center. Finally, the model forecast skill during a recent extreme rain event in northeast Vietnam is evaluated.

scholarly journals The Efficacy of the WRF-ARW Model in the Genesis and Intensity Forecast of Tropical Cyclone Fani over the Bay of Bengal

2022 ◽  
Vol 12 (3) ◽  
pp. 85-100
Author(s):  
Md Shakil Hossain ◽  
Md Abdus Samad ◽  
SM Arif Hossen ◽  
SM Quamrul Hassan ◽  
MAK Malliak
Keyword(s):  
Tropical Cyclone ◽  
Bay Of Bengal ◽  
Lead Time ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Outcome Analysis ◽  
Time Model ◽  
Cyclonic Storm ◽  
Arw Model ◽  
Global Data Assimilation System

An attempt has been carried out to assess the efficacy of the Weather Research and Forecasting (WRF) model in predicting the genesis and intensification events of Very Severe Cyclonic Storm (VSCS) Fani (26 April – 04 May 2019) over the Bay of Bengal (BoB). WRF model has been conducted on a single domain of 10 km horizontal resolution using the Global Data Assimilation System (GDAS) FNL (final) data (0.250 × 0.250). According to the model simulated outcome analysis, the model is capable of predicting the Minimum Sea Level Pressure (MSLP) and Maximum Sustainable Wind Speed (MSWS) pattern reasonably well, despite some deviations. The model has forecasted the Lowest Central Pressure (LCP) of 919 hPa and the MSWS of 70 ms-1 based on 0000 UTC of 26 April. Except for the model run based on 0000 UTC of 26 April, the simulated values of LCP are relatively higher than the observations. According to the statistical analysis, MSLP and MSWS at 850 hPa level demonstrate a significantly greater influence on Tropical Cyclone (TC) formation and intensification process than any other parameters. The model can predict the intensity features well enough, despite some uncertainty regarding the proper lead time of the model run. Reduced lead time model run, particularly 24 to 48 hr, can be chosen to forecast the genesis and intensification events of TC with minimum uncertainty. Journal of Engineering Science 12(3), 2021, 85-100

A Sensitivity Research of Numerical Simulation about Winter Sea-Land Breeze

2013 ◽  
Vol 380-384 ◽  
pp. 1800-1803
Author(s):  
Xiao Lan Tang ◽  
Shui Yuan Cheng
Keyword(s):  
Numerical Simulation ◽  
Wind Field ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Land Breeze ◽  
Threshold Values ◽  
Tropical Island ◽  
Wind Field Simulation ◽  
Field Simulation ◽  
The Impact

Using the WRF model and NCEP data, a typical winter sea-land breeze progress in China tropical island was simulated, analyzing the impact of wind field simulation with the horizontal resolution, analog range, nesting level, and analog time. The results showed: the simulate effects of the WRF model could not always keep step with the increase of horizontal resolution. Obviously there was a threshold for the model horizontal resolution. By the same token, analog range, nesting level, and analog time have its threshold. The accuracy of the simulation reduced when the threshold values were exceeded.

scholarly journals Analysis of WRF Simulation Skill for Seasonal Rainfall: A Case Study of 2015 September–November Season

2019 ◽  
Author(s):  
Ronald Ingula Odongo ◽  
Isaac Mugume
Keyword(s):  
Wrf Model ◽  
Final Analysis ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Entire Study ◽  
Seasonal Characteristics ◽  
Rain Season ◽  
Environmental Prediction ◽  
Wet Spells ◽  
Weather Research

Rainfall is a major climate parameter whose variation in space and time influences activities in different weather sensitive sectors such as agriculture, transport, and energy among others. Therefore, accurately forecasting rainfall is of paramount importance to the development of these sectors. In this regard, this study sought to contribute to quantitative forecasting of rainfall over Eastern Uganda through assessing the Weather Research and Forecasting model’s ability to simulate the intra–seasonal characteristics of the September to December rain season. These were: onset and cessation dates; wet days and lengths of the wet spells. The data used in the study included daily ground rainfall observations and lateral and boundary conditions data from the National Centers for Environmental Prediction (NCEP) final analysis at 1 0 horizontal resolution and at a temporal resolution of 6 hours for the entire study period were used to initialize the Weather Research and Forecasting (WRF) model. The study considered four weather synoptic weather stations namely; Jinja, Serere, Soroti and Tororo. The results show that the WRF model generally simulated fewer wet days at each station except for Tororo. Also, the WRF model simulated earlier onset and cessation dates of the rainfall season and overestimated the length of the wet spells.

scholarly journals Moisture Recycling over the Iberian Peninsula: The Impact of 3DVAR Data Assimilation

Atmosphere ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 19
Author(s):  
Santos J. González-Rojí ◽  
Jon Sáenz ◽  
Javier Díaz de Argandoña ◽  
Gabriel Ibarra-Berastegi
Keyword(s):  
Data Assimilation ◽  
Iberian Peninsula ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Spatiotemporal Distribution ◽  
Weather Research And Forecasting ◽  
Atmospheric Moisture ◽  
Moisture Recycling ◽  
The Impact ◽  
Weather Research

In this paper, we have estimated the spatiotemporal distribution of moisture recycling over the Iberian Peninsula (IP). The recycling ratio was computed from two simulations over the IP using the Weather Research and Forecasting (WRF) model with a horizontal resolution of 15 km spanning the period 2010–2014. The first simulation (WRF N) was nested inside the ERA-Interim with information passed to the domain through the boundaries. The second run (WRF D) is similar to WRF N, but it also includes 3DVAR data assimilation every six hours (12:00 a.m., 6:00 a.m., 12:00 p.m. and 6:00 p.m. UTC). It was also extended until 2018. The lowest values of moisture recycling (3%) are obtained from November to February, while the highest ones (16%) are observed in spring in both simulations. Moisture recycling is confined to the southeastern corner during winter. During spring and summer, a gradient towards the northeastern corner of the IP is observed in both simulations. The differences between both simulations are associated with the dryness of the soil in the model and are higher during summer and autumn. WRF D presents a lower bias and produces more reliable results because of a better representation of the atmospheric moisture.

scholarly journals Numerical Simulation of Extreme Temperature (Heat Wave) in Bangladesh Using WRF-ARW Model

2020 ◽  
pp. 44-54
Author(s):  
Md. Abdul Aziz ◽  
M. A. Samad ◽  
M. R. Hasan ◽  
M. N. U. Bhuiyan ◽  
M. A. K. Mallik
Keyword(s):  
Heat Wave ◽  
Mesoscale Model ◽  
Extreme Temperature ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Sea Level Pressure ◽  
Heat Wave Event ◽  
Arw Model ◽  
Wave Event

Every year Bangladesh experiences different types of natural hazards and heat wave is one of them. In the present study, an advanced high-resolution Weather Research and Forecasting (WRF-ARW) numerical mesoscale model is used to simulate a severe heat wave event occurred during April over Bangladesh and eastern part of India. The model is integrated for 6 days starting from UTC of 19 April to UTC of 24 April 2016, on a single domain of 10 km horizontal resolution. For validation of the model performance, the model simulated results of temperature at 2 m height, relative humidity (RH), mean sea level pressure (MSLP) at UTC of 6 days are compared with the BMD observed data. And the results indicate that the model is able to simulate the occurrence of the heat wave event with 6 days over Bangladesh.

scholarly journals Prediction of Thunderstorms based on Atmospheric Instability Indices over Bangladesh using WRF-ARW Model

Jalawaayu ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 21-37
Author(s):  
Jannatul Ferdaus ◽  
Dewan Abdul Quadir ◽  
Md. Shadekul Alam ◽  
Subrat Kumar Panda ◽  
Someshwar Das ◽  
...  
Keyword(s):  
Model Simulation ◽  
Model Performance ◽  
Wrf Model ◽  
Threshold Value ◽  
Microphysics Scheme ◽  
Arw Model ◽  
Double Moment ◽  
Global Data Assimilation System ◽  
Favorable Conditions ◽  
Instability Indices

In this study an attempt has been made to inspect the forecasting of thunderstorms based on two cases (1st case: 17th May, 2019 and 2nd case: 31st March, 2019) over Dhaka using WRF Model. The model is run for 72 hours with 03 nested domain of 09 km, 03 km and 01 km horizontal resolutions using 0.25º X 0.25º six hourly global data assimilation system. For model simulation, Milbrandt-Yau Double-Moment 7-class scheme (9) has been used as microphysics scheme in this study. The model performance is evaluated by calculating hourly instability indices (VTI, TTI, KI, CTI, MCAPE, MCIN, BRN, LI, SI, SWI) value and have been compared with the threshold value of indices. Different meteorological parameters such as MSLP, temperature, winds at upper (300 hPa) and lower (925 hPa) level, relative humidity along with vertical cross section are also studied by the model and compared with the favorable conditions for forming of thunderstorms. Area rage rainfall (hourly) value has been also calculated and compared with indices value to comprehend the nature of thunderstorms. Observing the indices value it is seen that all indices value increase sharply 5-6 hours before of thunderstorm occurring and MCAPE is giving more reliable result.  Moreover, this study shows that inner two domains (3 and 1 km resolution) are giving better results than outer one and which indices are more probable in forecasting of thunderstorm for our country as well as giving less Root Mean square Error. From the simulated and validated results, it can be concluded that the model performance of instability indices can be used as forecasting of thunderstorms over Bangladesh.

scholarly journals Evaluation of Weather Research and Forecasting (WRF) Microphysics single moment class-3 and class-6 in Precipitation Forecast

2018 ◽  
Vol 150 ◽  
pp. 03007 ◽  
Author(s):  
Syeda Maria Zaidi ◽  
Jacqueline Isabella Anak Gisen
Keyword(s):  
Model Performance ◽  
Wrf Model ◽  
Precipitation Forecast ◽  
Weather Research And Forecasting ◽  
Microphysics Scheme ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Single Moment ◽  
Minimum Medium ◽  
Weather Research

In this study, the performance of two different Microphysics Scheme options in Weather Research and Forecasting (WRF) model were evaluated for the estimating the precipitation forecast. The schemes WRF single moment class-3 (WSM-3) and single moment class-6 (WSM-6) were employed to produce the minimum, medium and maximum precipitation for the selected events over the Kuantan River Basin (KRB). The obtained simulated results were compared with the observed data from eight different rainfall gauging stations. The results comparison indicate that WRF model provides better forecasting at some rainfall stations for minimum and medium rainfall events but did not produce good result during maximum rainfall overall. The WSM-6 scheme is found to produce better result compared to WSM-3. The study also found that to acquire accurate precipitation results, it is also required to test some other physics scheme parameterization to enhance the model performance.

scholarly journals CNOP based on ACPW for Identifying Sensitive Regions of Typhoon Target Observations with WRF Model

2019 ◽  
Author(s):  
Bin Mu ◽  
Linlin Zhang ◽  
Shijin Yuan ◽  
Wansuo Duan
Keyword(s):  
Positive Impact ◽  
Search Algorithm ◽  
Wrf Model ◽  
Principal Component ◽  
Horizontal Resolution ◽  
Optimal Perturbation ◽  
Arw Model ◽  
Parallel Particle Swarm Optimization ◽  
Typhoon Tracks ◽  
Energy Similarity

Abstract. In this paper, we rewrite the ACPW (adaptive cooperation co-evolution of parallel particle swarm optimization and wolf search algorithm based on principal component analysis) and applied it to solve conditional nonlinear optimal perturbation (CNOP) in the WRF-ARW for identifying sensitive areas of typhoon target observations, which is proposed by us in the study of Zhang et al. (2018), to investigate its feasibility and effectiveness in the WRF-ARW model. Fitow (2013) and Matmo (2014) are taken as two typhoon cases, and simulated with the 60 km horizontal resolution. The total dry energy is adopted as the objective function. The CNOP is also calculated by the method based on the adjoint model (ADJ-method) as a benchmark. To evaluate the ACPW-CNOP, five aspects are analysed, such as the pattern, energy, similarity, benefits from the CNOPs reduced in the whole domain and the sensitive regions identified, and the simulated typhoon tracks. The experimental results show that the temperature and wind patterns of ACPW-CNOP is similar to those of the ADJ-CNOP in all typhoons. And the similarity values of ADJ-CNOP and ACPW-CNOP of two typhoon cases are more than 0.5. When reducing CNOPs in the sensitive regions, the forecast income of ACPW-CNOP is greater than that of ADJ-CNOP in all typhoons. Moreover, the sensitive regions identified by the ACPW-CNOP has the similar influence with the ADJ-CNOP on the simulation of typhoon tracks, sometimes the ACPW-CNOP has more positive impact on the simulation of typhoon tracks. The ACPW is more efficient than the ADJ-method in this paper.

scholarly journals Sensitivity of the WRF model to PBL parametrisations and nesting techniques: evaluation of wind storms over complex terrain

2015 ◽  
Vol 8 (10) ◽  
pp. 3349-3363 ◽  
Author(s):  
J. J. Gómez-Navarro ◽  
C. C. Raible ◽  
S. Dierer
Keyword(s):  
Wind Speed ◽  
Complex Terrain ◽  
Model Performance ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Data Set ◽  
Spectral Nudging ◽  
Pbl Scheme ◽  
Wind Storms ◽  
Set Up

Abstract. Simulating surface wind over complex terrain is a challenge in regional climate modelling. Therefore, this study aims at identifying a set-up of the Weather Research and Forecasting Model (WRF) model that minimises systematic errors of surface winds in hindcast simulations. Major factors of the model configuration are tested to find a suitable set-up: the horizontal resolution, the planetary boundary layer (PBL) parameterisation scheme and the way the WRF is nested to the driving data set. Hence, a number of sensitivity simulations at a spatial resolution of 2 km are carried out and compared to observations. Given the importance of wind storms, the analysis is based on case studies of 24 historical wind storms that caused great economic damage in Switzerland. Each of these events is downscaled using eight different model set-ups, but sharing the same driving data set. The results show that the lack of representation of the unresolved topography leads to a general overestimation of wind speed in WRF. However, this bias can be substantially reduced by using a PBL scheme that explicitly considers the effects of non-resolved topography, which also improves the spatial structure of wind speed over Switzerland. The wind direction, although generally well reproduced, is not very sensitive to the PBL scheme. Further sensitivity tests include four types of nesting methods: nesting only at the boundaries of the outermost domain, analysis nudging, spectral nudging, and the so-called re-forecast method, where the simulation is frequently restarted. These simulations show that restricting the freedom of the model to develop large-scale disturbances slightly increases the temporal agreement with the observations, at the same time that it further reduces the overestimation of wind speed, especially for maximum wind peaks. The model performance is also evaluated in the outermost domains, where the resolution is coarser. The results demonstrate the important role of horizontal resolution, where the step from 6 to 2 km significantly improves model performance. In summary, the combination of a grid size of 2 km, the non-local PBL scheme modified to explicitly account for non-resolved orography, as well as analysis or spectral nudging, is a superior combination when dynamical downscaling is aimed at reproducing real wind fields.

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