Tropical cyclone simulations over Bay of Bengal with ARW model: Sensitivity to cloud microphysics schemes

2019 ◽  
Vol 230 ◽  
pp. 104651 ◽  
Author(s):  
P. Reshmi Mohan ◽  
C. Venkata Srinivas ◽  
V. Yesubabu ◽  
R. Baskaran ◽  
B. Venkatraman
Keyword(s):  
Tropical Cyclone ◽  
Bay Of Bengal ◽  
Cloud Microphysics ◽  
Model Sensitivity ◽  
Arw Model

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 Impact of local data assimilation on tropical cyclone predictions over the Bay of Bengal using the ARW model

2015 ◽  
Vol 33 (7) ◽  
pp. 805-828 ◽  
Author(s):  
M. M. Greeshma ◽  
C. V. Srinivas ◽  
V. Yesubabu ◽  
C. V. Naidu ◽  
R. Baskaran ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Bay Of Bengal ◽  
Weather Research And Forecasting ◽  
Motion Vectors ◽  
Arw Model ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Radiance Data ◽  
Weather Research

Abstract. The tropical cyclone (TC) track and intensity predictions over Bay of Bengal (BOB) using the Advanced Research Weather Research and Forecasting (ARW) model are evaluated for a number of data assimilation experiments using various types of data. Eight cyclones that made landfall along the east coast of India during 2008–2013 were simulated. Numerical experiments included a control run (CTL) using the National Centers for Environmental Prediction (NCEP) 3-hourly 0.5 × 0.5° resolution Global Forecasting System (GFS) analysis as the initial condition, and a series of cycling mode variational assimilation experiments with Weather Research and Forecasting (WRF) data assimilation (WRFDA) system using NCEP global PrepBUFR observations (VARPREP), Atmospheric Motion Vectors (VARAMV), Advanced Microwave Sounding Unit (AMSU) A and B radiances (VARRAD) and a combination of PrepBUFR and RAD (VARPREP+RAD). The impact of different observations is investigated in detail in a case of the strongest TC, Phailin, for intensity, track and structure parameters, and finally also on a larger set of cyclones. The results show that the assimilation of AMSU radiances and Atmospheric Motion Vectors (AMV) improved the intensity and track predictions to a certain extent and the use of operationally available NCEP PrepBUFR data which contains both conventional and satellite observations produced larger impacts leading to improvements in track and intensity forecasts. The forecast improvements are found to be associated with changes in pressure, wind, temperature and humidity distributions in the initial conditions after data assimilation. The assimilation of mass (radiance) and wind (AMV) data showed different impacts. While the motion vectors mainly influenced the track predictions, the radiance data merely influenced forecast intensity. Of various experiments, the VARPREP produced the largest impact with mean errors (India Meteorological Department (IMD) observations less the model values) of 78, 129, 166, 210 km in the vector track position, 10.3, 5.8, 4.8, 9.0 hPa deeper than IMD data in central sea level pressure (CSLP) and 10.8, 3.9, −0.2, 2.3 m s−1 stronger than IMD data in maximum surface winds (MSW) for 24, 48, 72, 96 h forecasts respectively. An improvement of about 3–36 % in track, 6–63 % in CSLP, 26–103 % in MSW and 11–223 % in the radius of maximum winds in 24–96 h lead time forecasts are found with VARPREP over CTL, suggesting the advantages of assimilation of operationally available PrepBUFR data for cyclone predictions. The better predictions with PrepBUFR could be due to quality-controlled observations in addition to containing different types of data (conventional, satellite) covering an effectively larger area. The performance degradation of VARPREP+RAD with the assimilation of all available observations over the domain after 72 h could be due to poor area coverage and bias in the radiance data.

scholarly journals The Sensitivity of Microphysical Parameterization Schemes on the Prediction of Tropical Cyclone Mora Over the Bay of Bengal using WRF-ARW Model

2019 ◽  
Vol 67 (1) ◽  
pp. 33-40
Author(s):  
Md Jafrul Islam ◽  
Ashik Imran ◽  
Ishtiaque M Syed ◽  
SM Quamrul Hassan ◽  
Md Idris Ali
Keyword(s):  
Tropical Cyclone ◽  
Bay Of Bengal ◽  
Wrf Model ◽  
Mean Square ◽  
Latent Heat Release ◽  
Sea Level Pressure ◽  
Microphysical Process ◽  
Cloud Dynamics ◽  
Arw Model ◽  
Microphysical Parameterization

The sensitivity of Microphysics Parameterization (MP) schemes has been analyzed in the prediction of intensity and track of tropical cyclone (TC) Mora (28th May-31st May, 2017), over the Bay of Bengal (BoB) using WRF model. The study of MP schemes in numerical simulation is important because it includes microphysical process and cloud dynamics that controls the latent heat release in clouds. In this study seven MP schemes (Kessler, Lin, WSM3, Eta, WSM6, MYDM7, and WDM5) are used to study the variation in Mean Sea Level Pressure (MSLP), Maximum Wind Speed (MWS), rainfall distributions, and Tracks. The root mean square error (RMSE) of MSLP, MWS and 72-h simulated tracks are found minimum for WSM3 scheme while the RMSE of rainfall, 48 and 24-h simulated tracks are found minimum for WDM5 scheme. In conclusion, WSM3 and WDM5 schemes may give better results in the prediction of slowly intensifying TC like Mora. Dhaka Univ. J. Sci. 67(1): 33-40, 2019 (January)

Pathways to the Production of Precipitating Hydrometeors and Tropical Cyclone Development

2016 ◽  
Vol 144 (6) ◽  
pp. 2395-2420 ◽  
Author(s):  
J.-W. Bao ◽  
S. A. Michelson ◽  
E. D. Grell
Keyword(s):  
Tropical Cyclone ◽  
Wrf Model ◽  
Cloud Microphysics ◽  
Weather Research And Forecasting ◽  
Rapid Intensification ◽  
Latent Heating ◽  
Vertical Distributions ◽  
Double Moment ◽  
Microphysical Processes ◽  
Definition Of

Abstract Pathways to the production of precipitation in two cloud microphysics schemes available in the Weather Research and Forecasting (WRF) Model are investigated in a scenario of tropical cyclone intensification. Comparisons of the results from the WRF Model simulations indicate that the variation in the simulated initial rapid intensification of an idealized tropical cyclone is due to the differences between the two cloud microphysics schemes in their representations of pathways to the formation and growth of precipitating hydrometeors. Diagnoses of the source and sink terms of the hydrometeor budget equations indicate that the major differences in the production of hydrometeors between the schemes are in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes, such as accretion growth and sedimentation. These differences lead to different horizontally averaged vertical profiles of net latent heating rate associated with significantly different horizontally averaged vertical distributions and production rates of hydrometeors in the simulated clouds. Results from this study also highlight the possibility that the advantage of double-moment formulations can be overshadowed by the uncertainties in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes.

scholarly journals Effects of ocean eddies on the tropical storm Roanu intensity in the Bay of Bengal

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247521
Author(s):  
Yujun Liu ◽  
Haibin LÜ ◽  
Honghua Zhang ◽  
Yusheng Cui ◽  
Xueting Xing
Keyword(s):  
Tropical Cyclone ◽  
Bay Of Bengal ◽  
Tropical Storm ◽  
The West ◽  
Initial Development ◽  
Ocean Eddies ◽  
Tropical Cyclone Heat Potential ◽  
Warm Eddy ◽  
Heat Potential ◽  
Cold Eddy

A tropical storm (TS) Roanu occurred in northern Sri Lanka in 2016, which transported northwards along the west coast of the Bay of Bengal (BoB). During the development of the TS, ocean eddies on its track had an important effect on the intensity of Roanu. The dynamic mechanism was investigated with multisource reanalysis and Argo float data in this study. The results show that ocean eddies were the main reason why Roanu first enhanced, weakened, and then enhanced again. Warm eddy W1 supports the initial development of the TS, cold eddy C1 weakens Roanu, and warm eddy W2 continues to support Roanu. On May 19, 2016, the maximum average latent heat flux over W1 was 260.85 w/m2, while that of C1 was only 200.71 w/m2. After the passage of Roanu, the tropical cyclone heat potential (TCHP) of eddies significantly decreased. The TCHP of W1, W2, C1 and C2 decreased by 20.95 kJ/cm2, 11.07 kJ/cm2, 29.82 kJ/cm2, 9.31 kJ/cm2, respectively. The mixed layer of warm eddies deepened much more than that of cold eddies, supporting Roanu development. In addition, changes in potential vorticity (PV) values caused by the disturbance of eddies may also reflect changes in the TS intensity. This study offers new insights on the influence of ocean eddies in regulating the development of tropical cyclone (TC) in the BoB.

Analysis of Idealized Tropical Cyclone Simulations Using the Weather Research and Forecasting Model: Sensitivity to Turbulence Parameterization and Grid Spacing

2009 ◽  
Vol 137 (2) ◽  
pp. 745-765 ◽  
Author(s):  
Kevin A. Hill ◽  
Gary M. Lackmann
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Maximum Intensity ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Exchange Coefficient ◽  
Model Sensitivity ◽  
Wind Speeds ◽  
Horizontal Grid ◽  
Weather Research

Abstract The Weather Research and Forecasting Advanced Research Model (WRF-ARW) was used to perform idealized tropical cyclone (TC) simulations, with domains of 36-, 12-, and 4-km horizontal grid spacing. Tests were conducted to determine the sensitivity of TC intensity to the available surface layer (SL) and planetary boundary layer (PBL) parameterizations, including the Yonsei University (YSU) and Mellor–Yamada–Janjic (MYJ) schemes, and to horizontal grid spacing. Simulations were run until a quasi-steady TC intensity was attained. Differences in minimum central pressure (Pmin) of up to 35 hPa and maximum 10-m wind (V10max) differences of up to 30 m s−1 were present between a convection-resolving nested domain with 4-km grid spacing and a parent domain with cumulus parameterization and 36-km grid spacing. Simulations using 4-km grid spacing are the most intense, with the maximum intensity falling close to empirical estimates of maximum TC intensity. Sensitivity to SL and PBL parameterization also exists, most notably in simulations with 4-km grid spacing, where the maximum intensity varied by up to ∼10 m s−1 (V10max) or ∼13 hPa (Pmin). Values of surface latent heat flux (LHFLX) are larger in MYJ than in YSU at the same wind speeds, and the differences increase with wind speed, approaching 1000 W m−2 at wind speeds in excess of 55 m s−1. This difference was traced to a larger exchange coefficient for moisture, CQ, in the MYJ scheme. The exchange coefficients for sensible heat (Cθ) and momentum (CD) varied by <7% between the SL schemes at the same wind speeds. The ratio Cθ/CD varied by <5% between the schemes, whereas CQ/CD was up to 100% larger in MYJ, and the latter is theorized to contribute to the differences in simulated maximum intensity. Differences in PBL scheme mixing also likely played a role in the model sensitivity. Observations of the exchange coefficients, published elsewhere and limited to wind speeds <30 m s−1, suggest that CQ is too large in the MYJ SL scheme, whereas YSU incorporates values more consistent with observations. The exchange coefficient for momentum increases linearly with wind speed in both schemes, whereas observations suggest that the value of CD becomes quasi-steady beyond some critical wind speed (∼30 m s−1).

Sign in / Sign up

Export Citation Format

Share Document