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 A Novel Approach for Solving CNOP and its Application in Identifying Sensitive Regions of Tropical Cyclone Adaptive Observations

2018 ◽  
Author(s):  
Linlin Zhang ◽  
Bin Mu ◽  
Shijin Yuan ◽  
Feifan Zhou
Keyword(s):  
Tropical Cyclone ◽  
Mesoscale Model ◽  
Search Algorithm ◽  
Principal Component ◽  
Conditional Nonlinear Optimal Perturbation ◽  
Optimal Perturbation ◽  
Fifth Generation ◽  
Novel Approach ◽  
Adaptive Observations ◽  
Parallel Particle Swarm Optimization

Abstract. In this paper, a novel approach is proposed for solving conditional nonlinear optimal perturbation (CNOP), named it adaptive cooperation co-evolution of parallel particle swarm optimization and wolf search algorithm (ACPW) based on principal component analysis. Taking Fitow (2013) and Matmo (2014) as two tropical cyclone (TC) cases, CNOP solved by ACPW is used to investigate the sensitive regions identification of TC adaptive observations with the fifth-generation mesoscale model (MM5). Meanwhile, the 60 km and 120 km resolutions are adopted. The adjoint-based method (short for the ADJ-method) is also applied to solve CNOP, and the result is used as a benchmark. To validate the validity of ACPW, the CNOPs obtained from the different methods are compared in terms of the patterns, energies, similarities and simulated TC tracks with perturbations. (1) The ACPW can capture similar CNOP patterns with the ADJ-method, and the patterns of TC Fitow are more similar than TC Matmo. (2) When using the 120 km resolution, similarities between CNOPs of the ADJ-method and ACPW are higher than those using the 60 km. (3) Compared to the ADJ-method, although the CNOPs of ACPW produce lower energies, they can obtain better benefits gained from the reduction of CNOPs, not only in the entire domain but also in the sensitive regions identified. (4) The sensitive regions identified by CNOPs-ACPW has the same influence on the improvements of the TC tracks forecast skills with those identified by CNOPs-ADJ-method. (5) The ACPW has a higher efficiency than the ADJ-method. All conclusions prove that ACPW is a meaningful and effective method for solving CNOP and can be used to identify sensitive regions of TC adaptive observations.

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

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 A novel approach for solving CNOPs and its application in identifying sensitive regions of tropical cyclone adaptive observations

2018 ◽  
Vol 25 (3) ◽  
pp. 693-712
Author(s):  
Linlin Zhang ◽  
Bin Mu ◽  
Shijin Yuan ◽  
Feifan Zhou
Keyword(s):  
Tropical Cyclone ◽  
Mesoscale Model ◽  
Search Algorithm ◽  
Principal Component ◽  
Cooperative Coevolution ◽  
Hybrid Strategy ◽  
Fifth Generation ◽  
Novel Approach ◽  
Adaptive Observations ◽  
Parallel Particle Swarm Optimization

Abstract. In this paper, a novel approach is proposed for solving conditional nonlinear optimal perturbations (CNOPs), called the adaptive cooperative coevolution of parallel particle swarm optimization (PSO) and the Wolf Search algorithm (WSA) based on principal component analysis (ACPW). Taking Fitow (2013) and Matmo (2014), two tropical cyclone (TC) cases, CNOPs solved by the ACPW algorithm are used to investigate the sensitive regions identified by TC adaptive observations with the fifth-generation Mesoscale Model (MM5). Meanwhile, the 60 and 120 km resolutions are adopted. The adjoint-based method (short for the ADJ method) is also applied to solve CNOPs, and the result is used as a benchmark. To evaluate the advantages of the ACPW algorithm, we run the PSO, WSA and ACPW programs 10 times and then compare the maximum, minimum and mean objective values as well as the RMSEs. The analysis results prove that the hybrid strategy and cooperative coevolution are useful and effective. To validate the ACPW algorithm, the CNOPs obtained from the different methods are compared in terms of the patterns, energies, similarities and simulated TC tracks with perturbations. The results of our study may be summarized as follows: The ACPW algorithm can capture similar CNOP patterns as the ADJ method, and the patterns of TC Fitow are more similar than TC Matmo. At the 120 km resolution, similarities between the CNOPs of the ADJ method and the ACPW algorithm are more than those at the 60 km resolution. Compared to the ADJ method, although the CNOPs of the ACPW method produce lower energies, they can have improved benefits gained from the reduction of the CNOPs not only across the entire domain but also in the identified sensitive regions. The sensitive regions identified by the CNOPs from the ACPW algorithm have the same influence on the improvements of the skill of TC-track forecasting as those identified by the CNOPs from the ADJ method. The ACPW method is more efficient than the ADJ method. All conclusions prove that the ACPW algorithm is a meaningful and effective method for solving CNOPs and can be used to identify sensitive regions of TC adaptive observations.

scholarly journals Fast Search Method Based on Vector Quantization for Raman Spectroscopy Identification

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1970
Author(s):  
Jun-Kyu Park ◽  
Suwoong Lee ◽  
Aaron Park ◽  
Sung-June Baek
Keyword(s):  
Search Algorithm ◽  
Principal Component ◽  
Search Method ◽  
Reference Spectrum ◽  
Search Range ◽  
Fast Search ◽  
Input Spectrum ◽  
Computationally Intensive ◽  
Multiple Clusters ◽  
Full Search

In spectroscopy, matching a measured spectrum to a reference spectrum in a large database is often computationally intensive. To solve this problem, we propose a novel fast search algorithm that finds the most similar spectrum in the database. The proposed method is based on principal component transformation and provides results equivalent to the traditional full search method. To reduce the search range, hierarchical clustering is employed, which divides the spectral data into multiple clusters according to the similarity of the spectrum, allowing the search to start at the cluster closest to the input spectrum. Furthermore, a pilot search was applied in advance to further accelerate the search. Experimental results show that the proposed method requires only a small fraction of the computational complexity required by the full search, and it outperforms the previous methods.

scholarly journals A Case Study of Observed and Modeled Barrier Flow in the Denmark Strait in May 2015

2017 ◽  
Vol 145 (6) ◽  
pp. 2385-2404 ◽  
Author(s):  
Alice K. DuVivier ◽  
John J. Cassano ◽  
Steven Greco ◽  
G. David Emmitt
Keyword(s):  
Wrf Model ◽  
Horizontal Resolution ◽  
Surface Energy Budget ◽  
Vertical Resolution ◽  
Structure Comparison ◽  
Denmark Strait ◽  
Pbl Scheme ◽  
Barrier Jets ◽  
The Impact ◽  
Jet Structure

Abstract Mesoscale barrier jets in the Denmark Strait are common in winter months and have the capability to influence open ocean convection. This paper presents the first detailed observational study of a summertime (21 May 2015) barrier wind event in the Denmark Strait using dropsondes and observations from an airborne Doppler wind lidar (DWL). The DWL profiles agree well with dropsonde observations and show a vertically narrow (~250–400 m) barrier jet of 23–28 m s−1 near the Greenland coast that broadens (~300–1000 m) and strengthens farther off coast. In addition, otherwise identical regional high-resolution Weather Research and Forecasting (WRF) Model simulations of the event are analyzed at four horizontal grid spacings (5, 10, 25, and 50 km), two vertical resolutions (40 and 60 levels), and two planetary boundary layer (PBL) parameterizations [Mellor–Yamada–Nakanishi–Niino, version 2.5 (MYNN2.5) and University of Washington (UW)] to determine what model configurations best simulate the observed jet structure. Comparison of the WRF simulations with wind observations from satellites, dropsondes, and the airborne DWL scans indicate that the combination of both high horizontal resolution (5 km) and vertical resolution (60 levels) best captures observed barrier jet structure and speeds as well as the observed cloud field, including some convective clouds. Both WRF PBL schemes produced reasonable barrier jets with the UW scheme slightly outperforming the MYNN2.5 scheme. However, further investigation at high horizontal and vertical resolution is needed to determine the impact of the WRF PBL scheme on surface energy budget terms, particularly in the high-latitude maritime environment around Greenland.

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 Simulation of Severe Thunderstorms in Conjugation of Westerly and Easterly on 31 March 2019 in Bangladesh

2022 ◽  
Vol 12 (3) ◽  
pp. 29-43
Author(s):  
Samarendra Karmakar ◽  
Mohan Kumar Das ◽  
Md Quamrul Hassam ◽  
Md Abdul Mannan
Keyword(s):  
South Asian ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Atmospheric Conditions ◽  
Microphysics Scheme ◽  
Severe Thunderstorms ◽  
Synoptic Conditions ◽  
Pbl Scheme ◽  
Single Moment

The diagnostic and prognostic studies of thunderstorms/squalls are very important to save live and loss of properties. The present study aims at diagnose the different tropospheric parameters, instability and synoptic conditions associated the severe thunderstorms with squalls, which occurred at different places in Bangladesh on 31 March 2019. For prognostic purposes, the severe thunderstorms occurred on 31 March 2019 have been numerically simulated. In this regard, the Weather Research and Forecasting (WRF) model is used to predict different atmospheric conditions associated with the severe storms. The study domain is selected for 9 km horizontal resolution, which almost covers the south Asian region. Numerical experiments have been conducted with the combination of WRF single-moment 6 class (WSM6) microphysics scheme with Yonsei University (YSU) PBL scheme in simulation of the squall events. Model simulated results are compared with the available observations. The observed values of CAPE at Kolkata both at 0000 and 1200 UTC were 2680.4 and 3039.9 J kg-1 respectively on 31 March 2019 and are found to be comparable with the simulated values. The area averaged actual rainfall for 24 hrs is found is 22.4 mm, which complies with the simulated rainfall of 20-25 mm for 24 hrs. Journal of Engineering Science 12(3), 2021, 29-43

Fog forecasting for Schiphol airport at sub-kilometre scale.  

2021 ◽  
Author(s):  
Gert-Jan Steeneveld ◽  
Roosmarijn Knol
Keyword(s):  
Spatial Resolution ◽  
Numerical Models ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Physical Processes ◽  
Radiation Fog ◽  
Fog Forecasting ◽  
Elevation Data ◽  
The Individual ◽  
The Impact

<p>Fog is a critical weather phenomenon for safety and operations in aviation. Unfortunately, the forecasting of radiation fog remains challenging due to the numerous physical processes that play a role and their complex interactions, in addition to the vertical and horizontal resolution of the numerical models. In this study we evaluate the performance of the Weather Research and Forecasting (WRF) model for a radiation fog event at Schiphol Amsterdam Airport (The Netherlands) and further develop the model towards a 100 m grid spacing. Hence we introduce high resolution land use and land elevation data. In addition we study the role of gravitational droplet settling, advection of TKE, top-down diffusion caused by strong radiative cooling at the fog top. Finally the impact of heat released by the terminal areas on the fog formation is studied. The model outcomes are evaluated against 1-min weather observations near multiple runways at the airport.</p><p>Overall we find the WRF model shows an reasonable timing of the fog onset and is well able to reproduce the visibility and meteorological conditions as observed during the case study. The model appears to be relatively insensitive to the activation of the individual physical processes. An increased spatial resolution to 100 m generally results in a better timing of the fog onset differences up to three hours, though not for all runways. The effect of the refined landuse dominates over the effect of refined elevation data. The modelled fog dissipation systematically occurs 3-4 h hours too early, regardless of physical processes or spatial resolution. Finally, the introduction of heat from terminal buildings delays the fog onset with a maximum of two hours, an overestimated visibility of 100-200 m and a decrease of the LWC with 0.10-0.15 g/kg compared to the reference.</p>

scholarly journals Impact of Assimilated Precipitation-Sensitive Radiances on the NU-WRF Simulation of the West African Monsoon

2017 ◽  
Vol 145 (9) ◽  
pp. 3881-3900 ◽  
Author(s):  
Sara Q. Zhang ◽  
T. Matsui ◽  
S. Cheung ◽  
M. Zupanski ◽  
C. Peters-Lidard
Keyword(s):  
Positive Impact ◽  
Model Simulation ◽  
Forecast Error ◽  
Wrf Model ◽  
West African Monsoon ◽  
West African ◽  
Full Description ◽  
The West ◽  
African Monsoon ◽  
State Dependent

Abstract This work assimilates multisensor precipitation-sensitive microwave radiance observations into a storm-scale NASA Unified Weather Research and Forecasting (NU-WRF) Model simulation of the West African monsoon. The analysis consists of a full description of the atmospheric states and a realistic cloud and precipitation distribution that is consistent with the observed dynamic and physical features. The analysis shows an improved representation of monsoon precipitation and its interaction with dynamics over West Africa. Most significantly, assimilation of precipitation-affected microwave radiance has a positive impact on the distribution of precipitation intensity and also modulates the propagation of cloud precipitation systems associated with the African easterly jet. Using an ensemble-based assimilation technique that allows state-dependent forecast error covariance among dynamical and microphysical variables, this work shows that the assimilation of precipitation-sensitive microwave radiances over the West African monsoon rainband enables initialization of storms. These storms show the characteristics of continental tropical convection that enhance the connection between tropical waves and organized convection systems.

Sign in / Sign up

Export Citation Format

Share Document