scholarly journals Simulation of Structure, Track and Landfall of Tropical Cyclone Bijli Using WRF-ARW Model

2015 ◽  
Vol 39 (2) ◽  
pp. 157-167 ◽  
Author(s):  
KM Zahir Rayhun ◽  
DA Quadir ◽  
MA Mannan Chowdhury ◽  
MN Ahasan ◽  
MS Haque
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Convective Available Potential Energy ◽  
Wrf Model ◽  
Relative Vorticity ◽  
Cumulus Parameterization ◽  
Arw Model ◽  
Boundary Layer Scheme ◽  
Cumulus Parameterization Schemes ◽  
Academy Of Sciences

An attempt was made to simulate the structure, track, landfall and a few dynamical aspects of the tropical cyclone Bijli that formed over the Bay of Bengal using WRF-ARW model. WRF model was run in a single domain using KF cumulus parameterization schemes with WSM 3 micro physics and YSU planetary boundary layer scheme. The ARW model was run for 24, 48, 72 and 96 hrs to simulate structure, track and landfall of tropical cyclones Bijli. The different simulated parameters viz. minimum sea level pressure, maximum wind speed, convective available potential energy and relative vorticity have been studied. The results showed that the model is capable to forecast the formation of the first depression 60 - 78 hrs in advance. This indicates the high and unique predictive power of ARW model for predicting the tropical cyclone formation. The model generates a realistic structure of the tropical cyclones with high spatial details. This was possible due to the higher spatial resolution of the regional model. One of the outstanding findings of the study is that the model was successfully predicted the tracks, recurvature and probable areas and time of landfall of the selected tropical cyclone Bijli with high accuracy even in the 96 hrs predictions.Journal of Bangladesh Academy of Sciences, Vol. 39, No. 2, 157-167, 2015

scholarly journals The Impact of Cumulus Parameterization Schemes on the Simulation of Tropical Cyclone “Roanu” Over the Bay of Bengal Using WRF Model

2020 ◽  
Vol 68 (1) ◽  
pp. 87-94
Author(s):  
Saifullah ◽  
Md Idris Ali ◽  
Ashik Imran
Keyword(s):  
Tropical Cyclone ◽  
Bay Of Bengal ◽  
Wrf Model ◽  
Absolute Error ◽  
Sensitivity Study ◽  
Cumulus Parameterization ◽  
Weather Research And Forecasting ◽  
Sea Level Pressure ◽  
Cumulus Parameterization Schemes ◽  
The Impact

A sensitivity study has been made on cumulus parameterization (CP) schemes of Weather Research and Forecasting (WRF) model for the simulation of tropical cyclone Roanu which formed over Bay of Bengal during May 2016. The model was run for 72 hours with different CP schemes such as Kain–Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell–Freit as Ensemble (GFE), Grell 3D Ensemble (G3E) and Grell–Devenyi (GD) Ensemble schemes to study the variation in track, intensity. The landfall position error is minimum for BMJ scheme but the time delayed only 1.5-5 hours for all schemes except GD scheme. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of minimum sea level pressure and maximum wind speed is smaller for BMJ, GFE, GD schemes. The RMSE-MAE of rainfall is minimum for BMJ and G3E schemes. Except GD scheme all the other schemes give the better result. Dhaka Univ. J. Sci. 68(1): 87-94, 2020 (January)

scholarly journals The Impact of Convective Momentum Transport on Tropical Cyclone Track Forecasts Using the Emanuel Cumulus Parameterization

2007 ◽  
Vol 135 (4) ◽  
pp. 1195-1207 ◽  
Author(s):  
Timothy F. Hogan ◽  
Randal L. Pauley
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Tropical Cyclones ◽  
Momentum Transport ◽  
Cumulus Parameterization ◽  
Transport Parameter ◽  
Medium Range Forecast ◽  
Medium Range ◽  
Convective Momentum Transport ◽  
The Impact

Abstract The influence of convective momentum transport (CMT) on tropical cyclone (TC) track forecasts is examined in the Navy Operational Global Atmospheric Prediction System (NOGAPS) with the Emanuel cumulus parameterization. Data assimilation and medium-range forecast experiments show that for 35 tropical cyclones during August and September 2004 the inclusion of CMT in the cumulus parameterization significantly improves the TC track forecasts. The tests show that the track forecasts are very sensitive to the magnitude of the Emanuel parameterization’s convective momentum transport parameter, which controls the CMT tendency returned by the parameterization. While the overall effect of this formulation of CMT in NOGAPS data assimilation/medium-range forecasts results in the surface pressure of tropical cyclones being less intense (and more consistent with the analysis), the parameterization is not equivalent to a simple diffusion of winds in the presence of convection. This is demonstrated by two data assimilation/medium-range forecast tests in which a vertical diffusion algorithm replaces the CMT. Two additional data assimilation/medium-range forecast experiments were conducted to test whether the skill increase primarily comes from the CMT in the immediate vicinity of the tropical cyclones. The results show that the inclusion of the CMT calculation in the vicinity of the TC makes the largest contribution to the increase in forecast skill, but the general contribution of CMT away from the TC also plays an important role.

scholarly journals Observational Analysis of Tropical Cyclone Formation Associated with Monsoon Gyres

2013 ◽  
Vol 70 (4) ◽  
pp. 1023-1034 ◽  
Author(s):  
Liguang Wu ◽  
Huijun Zong ◽  
Jia Liang
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Western North Pacific ◽  
Large Scale ◽  
Vertical Wind Shear ◽  
Relative Vorticity ◽  
Monsoon Trough ◽  
Cyclonic Circulation ◽  
Tropical Cyclone Formation ◽  
Monsoon Gyre

Abstract Large-scale monsoon gyres and the involved tropical cyclone formation over the western North Pacific have been documented in previous studies. The aim of this study is to understand how monsoon gyres affect tropical cyclone formation. An observational study is conducted on monsoon gyres during the period 2000–10, with a focus on their structures and the associated tropical cyclone formation. A total of 37 monsoon gyres are identified in May–October during 2000–10, among which 31 monsoon gyres are accompanied with the formation of 42 tropical cyclones, accounting for 19.8% of the total tropical cyclone formation. Monsoon gyres are generally located on the poleward side of the composited monsoon trough with a peak occurrence in August–October. Extending about 1000 km outward from the center at lower levels, the cyclonic circulation of the composited monsoon gyre shrinks with height and is replaced with negative relative vorticity above 200 hPa. The maximum winds of the composited monsoon gyre appear 500–800 km away from the gyre center with a magnitude of 6–10 m s−1 at 850 hPa. In agreement with previous studies, the composited monsoon gyre shows enhanced southwesterly flow and convection on the south-southeastern side. Most of the tropical cyclones associated with monsoon gyres are found to form near the centers of monsoon gyres and the northeastern end of the enhanced southwesterly flows, accompanying relatively weak vertical wind shear.

scholarly journals Assessment of a Regional-Scale Weather Model for Hydrological Applications in South Korea

2016 ◽  
Vol 6 (2) ◽  
pp. 28
Author(s):  
Yong Jung ◽  
Yuh-Lang Lin
Keyword(s):  
Weather Prediction ◽  
Regional Scale ◽  
Wrf Model ◽  
Domain Size ◽  
Cumulus Parameterization ◽  
Precipitation Forecast ◽  
Mountainous Region ◽  
Parameterization Schemes ◽  
Plain Region ◽  
Cumulus Parameterization Schemes

<p class="1Body">In this study, a regional numerical weather prediction (NWP) model known as the Weather Research Forescasting (WRF) model was adopted to improve the quantitative precipitation forecasts (QPF) by optimizing combined microphysics and cumulus parameterization schemes. Four locations in two regions (plain region for Sangkeug and Imsil; mountainous region for Dongchun and Bunchun) in Korean Peninsula were examined for QPF for two heavy rainfall events 2006 and 2008. The maximum Index of Agreement (IOA) was 0.96 at Bunchun in 2006 using the combined Thompson microphysics and the Grell cumulus parameterization schemes. Sensitivity of QPF on domain size at Sangkeug indicated that the localized smaller domain had 55% (from 0.35 to 0.90) improved precipitation accuracy based on IOA of 2008. For the July 2006 Sangkeug event, the sensitivity to cumulus parameterization schemes for precipitation prediction cannot be ignored with finer resolutions. In mountainous region, the combined Thompson microphysics and Grell cumulus parameterization schemes make a better quantitative precipitation forecast, while in plain region, the combined Thompson microphysics and Kain-Frisch cumulus parameterization schemes are the best.</p>

scholarly journals Bayesian network model for flood forecasting based on atmospheric ensemble forecasts

2019 ◽  
Vol 19 (11) ◽  
pp. 2513-2524 ◽  
Author(s):  
Leila Goodarzi ◽  
Mohammad E. Banihabib ◽  
Abbas Roozbahani ◽  
Jörg Dietrich
Keyword(s):  
Bayesian Network ◽  
Relative Error ◽  
Wrf Model ◽  
Cumulus Parameterization ◽  
Small Data ◽  
Ensemble Forecasts ◽  
Validation Data ◽  
Flood Peak ◽  
Absolute Relative Error ◽  
Cumulus Parameterization Schemes

Abstract. The purpose of this study is to propose the Bayesian network (BN) model to estimate flood peaks from atmospheric ensemble forecasts (AEFs). The Weather Research and Forecasting (WRF) model was used to simulate historic storms using five cumulus parameterization schemes. The BN model was trained to compute flood peak forecasts from AEFs and hydrological pre-conditions. The mean absolute relative error was calculated as 0.076 for validation data. An artificial neural network (ANN) was applied for the same problem but showed inferior performance with a mean absolute relative error of 0.39. It seems that BN is less sensitive to small data sets, thus it is more suited for flood peak forecasting than ANN.

scholarly journals Why Are Tropical Cyclone Tracks over the Western North Pacific Sensitive to the Cumulus Parameterization Scheme in Regional Climate Modeling? A Case Study for Megi (2010)

2014 ◽  
Vol 142 (3) ◽  
pp. 1240-1249 ◽  
Author(s):  
Yuan Sun ◽  
Zhong Zhong ◽  
Wei Lu ◽  
Yijia Hu
Keyword(s):  
Tropical Cyclone ◽  
Climate Modeling ◽  
Deep Convection ◽  
Regional Climate ◽  
Lower Troposphere ◽  
Western Pacific Subtropical High ◽  
Regional Climate Modeling ◽  
Cumulus Parameterization ◽  
Parameterization Schemes ◽  
Cumulus Parameterization Schemes

Abstract The Weather Research and Forecasting Model is employed to simulate Tropical Cyclone (TC) Megi (2010) using the Grell–Devenyi (GD) and Betts–Miller–Janjić (BMJ) cumulus parameterization schemes, respectively. The TC track can be well reproduced with the GD scheme, whereas it turns earlier than observations with the BMJ scheme. The physical mechanism behind different performances of the two cumulus parameterization schemes in the TC simulation is revealed. The failure in the simulation of the TC track with the BMJ scheme is attributed to the overestimation of anvil clouds, which extend far away from the TC center and reach the area of the western Pacific subtropical high (WPSH). Such extensive anvil clouds, which result from the excessively deep convection in the eyewall, eventually lead to a large bias in microphysics latent heating. The warming of the upper troposphere due to the condensation in anvil clouds coupled with the cooling of the lower troposphere due to precipitation evaporation cause a weakening of the WPSH, which in turn is favorable for the early recurvature of Megi.

A Parameter for Forecasting Tornadoes Associated with Landfalling Tropical Cyclones

2014 ◽  
Vol 29 (5) ◽  
pp. 1238-1255 ◽  
Author(s):  
Matthew J. Onderlinde ◽  
Henry E. Fuelberg
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Stepwise Regression ◽  
Atlantic Coast ◽  
Convective Available Potential Energy ◽  
Environmental Parameters ◽  
Time Of Day ◽  
Skill Scores ◽  
Landfalling Tropical Cyclones ◽  
Center Time

Abstract The authors develop a statistical guidance product, the tropical cyclone tornado parameter (TCTP), for forecasting the probability of one or more tornadoes during a 6-h period that are associated with landfalling tropical cyclones affecting the coastal Gulf of Mexico and the southern Atlantic coast. TCTP is designed to aid forecasters in a time-limited environment. TCTP provides a “quick look” at regions where forecasters can then conduct detailed analyses. The pool of potential predictors included tornado reports and tropical cyclone data between 2000 and 2008, as well as storm environmental parameters. The original pool of 28 potential predictors is reduced to six using stepwise regression and logistic regression. These six predictors are 0–3-km wind shear, 0–3-km storm relative helicity, azimuth angle of the tornado report from the tropical cyclone, distance from the cyclone’s center, time of day, and 950–1000-hPa convective available potential energy. Mean Brier scores and Brier skill scores are computed for the entire TCTP-dependent dataset and for corresponding forecasts produced by the Storm Prediction Center (SPC). TCTP then is applied to four individual cyclone cases to qualitatively and quantitatively assess the parameter and compare its performance with SPC forecasts. Results show that TCTP has skill at identifying regions of tornado potential. However, tornadoes in some tropical systems are overpredicted, but underpredicted in others. TCTP 6-h forecast periods provide slightly poorer statistical performance than the 1-day tornado probability forecasts from SPC, probably because the SPC product includes forecaster guidance and because their forecasts are valid for longer periods (24 h).

scholarly journals An Extended Model for the Potential Intensity of Tropical Cyclones

2012 ◽  
Vol 69 (2) ◽  
pp. 641-661 ◽  
Author(s):  
Thomas Frisius ◽  
Daria Schönemann
Keyword(s):  
Steady State ◽  
Wind Speed ◽  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Convective Instability ◽  
Cloud Model ◽  
Convective Available Potential Energy ◽  
Extended Model ◽  
Flow Imbalance ◽  
Conditional Instability

Abstract Emanuel’s theory of hurricane potential intensity (E-PI) makes use of the assumption that slantwise convective instability vanishes in a steady-state vortex of a tropical cyclone. In the framework of an extended mathematical potential intensity model it is shown that relaxing this assumption and including an eye results in a larger maximum wind speed compared to that of the predictions made by E-PI. Previous studies by Bryan and Rotunno demonstrate that the effect of unbalanced flow considerably contributes to maximum winds in excess of E-PI (“superintensity”). The authors argue that the proposed mechanism induced by convective instability provides another possible explanation for simulated and observed tropical cyclones exceeding E-PI in addition to flow imbalance. Further evidence for the relevance of conditional instability in mature tropical cyclones to superintensity is given by the fact that convective available potential energy arises in numerical simulations of tropical cyclones. This is demonstrated by means of an axisymmetric cloud model that is in qualitative agreement with the analytical model. These simulations reveal a dependence of superintensity on the amount of CAPE outside the eyewall and also reproduce the decrease in superintensity with increased horizontal diffusion as found in previous studies.

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