Impact of data assimilation and air−sea flux parameterization schemes on the prediction of cyclone Phailin over the Bay of Bengal using the WRF‐ARW model

Singh, Kuvar Satya; Tyagi, Bhishma

doi:10.1002/met.1734

Cited by 16 publications

(4 citation statements)

References 47 publications

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“…Figure b shows the model domains with topography. The model set‐up uses 35 vertical sigma levels, with higher resolution in the lowest 1 km and the model top at 10 hPa (Singh and Bhaskaran, ; Singh and Tyagi, ). Six CPSs of the ARW‐WRF model are used, namely the Grell‐3 (G3) scheme (Grell and Devenyi, ), the new Kain–Fritsch (KF) scheme (Kain, ), the old simplified Arakawa–Schubert (SAS4) scheme (Pan, ), the new simplified Arakawa–Schubert (SAS14) scheme (Han and Pan, ), the new simplified Arakawa–Schubert Hurricane Weather Research and Forecasting version (SAS84) scheme (Han and Pan, ) and the Tiedtke (TDK) scheme (Tiedtke, ; Zhang et al , 2011); other model physics are kept unchanged and are described in Table .…”

Section: Description Of the Modelmentioning

confidence: 99%

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Assessing the performance evaluation of different convective parameterization schemes in simulating the intensity of severe cyclonic storms over the Bay of Bengal region

Singh¹,

Tyagi

Verma³

et al. 2019

Meteorological Applications

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In the present work, the performance of six convective parameterization schemes (CPSs) of the Weather Research and Forecasting model is tested for the intensity simulation of the cyclonic storms Mala, Sidr, Nargis, Aila, Laila, Jal and Thane which formed over the Bay of Bengal, with a special focus on Jal (formed in November 2010). It is found that the Grell‐3, new Kain–Fritsch and old simplified Arakawa–Schubert CPSs provide higher intensity and give higher divergence in the upper‐level convective precipitation rate, horizontal eddy viscosity, eddy viscosity of heat and total advective moisture tendency than other tested CPSs. It is noted that no single CPS can be assumed “best” for simulating all characteristics of a storm including intensity, track, rainfall amount, the spatial distribution of rainfall, and landfall (time and location). The study also incorporated some of the critically simulated parameters such as vorticity (shear, curvature and total), latent heating, relative humidity, equivalent potential temperature, cloud water content and cloud fraction in the intensity forecast and their importance in the cyclone forecast is discussed. The CPSs influence the forecasted convective precipitation rate of the storm and have a good correlation with the maximum surface wind, cloud fraction and upper‐level divergence.

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Section: Description Of the Modelmentioning

confidence: 99%

“…A tropical cyclone (TC) is one of the most destructive weather phenomena in coastal regions worldwide due to its association with strong winds, heavy rainfall and storm surges (Singh and Tyagi, ). The accurate prediction of strong wind and heavy rain due to these storms is challenging to atmospheric modellers.…”

Section: Introductionmentioning

confidence: 99%

Assessing the performance evaluation of different convective parameterization schemes in simulating the intensity of severe cyclonic storms over the Bay of Bengal region

Singh¹,

Tyagi

Verma³

et al. 2019

Meteorological Applications

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“…However, in the past few decades a significant improvement has been observed in the forecast of intense tropical cyclones over the North Indian Ocean. This improvement due to the high-resolution atmospheric modeling system [14][15][16] with improved physical processes [17][18][19][20], advanced data assimilation techniques including good quality of observations [21][22][23][24][25][26][27][28][29][30][31][32]. Therefore, a modeling study is very important in a high resolution to forecast the intensity of the ESCS over Bay of Bengal region in an increasing intensity and life-period.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Bay of Bengal Extremely Severe Cyclonic Storm "Fani” Using Moving Nested Domain

Singh¹,

Nayak²,

Maity³

et al. 2022

Preprint

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The prediction of an extremely severe cyclonic storm (ESCS) is one of the challenging issues due to increasing intensity and its life period. In this study, an ESCS Fani that developed over Bay of Bengal region during 27 April - 4May, 2019 and made landfall over Odisha coast of India is investigated to forecast the storm track, intensity and structure. Two numerical experiments (changing two air-sea flux parameterization schemes; namely FLUX-1 and FLUX-2) are conducted with the Advanced Research version of the Weather Research and Forecasting (ARW-WRF) model by using a moving nest with fine horizontal resolution about 3 km. The high resolution (25 km) NCEP operational Global Forecast System (GFS) analysis and forecast datasets are used to derive the initial and boundary conditions, the ARW model initialized at 00 UTC 29 April 2019 and forecasted for 108 hours. The forecasted track and intensity of Fani is validated with available India Meteorological Department (IMD) best-fit track datasets. Result shows that the track, landfall (position and time) and intensity in terms of minimum sea level pressure (MSLP) and maximum surface wind (MSW) of the storm is well predicted in the moving nested domain of the WRF model using FLUX-1 experiment. The track forecast errors on day-1 to day-4 are ~ 47 km, 123 km, 96 km, and 27 km in FLUX-1 and ~54 km, 142 km, 152 km and 166 km in Flux-2 respectively. The intensity is better predicted in FLUX-1 during the first 60 h followed by FLUX -2 for the remaining period. The structure in terms of relative humidity, water vapor, maximum reflectivity and temperature anomaly of the storm is also discussed and compared with available satellite and Doppler Weather Radar observations.

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“…Mandal et al (2016) reported that mean track errors (MTEs) for different ICs on days 1-4 were less than 100 km for the prediction of extremely severe cyclonic storm (ESCS) Phailin over the BoB region. A recent study by Singh and Tyagi (2019) suggested that the predicted storm track error and intensity were reduced using the 3DVar technique and with parameterization of the air-sea flux scheme in the WRF model. A study by Singh and Bhaskaran (2018) suggested that high resolution and more frequent lateral boundary conditions with assimilation of conventional and satellite radiances provide a better forecast of BoB TCs.…”

Section: Introductionmentioning

confidence: 99%

Prediction of landfalling Bay of Bengal cyclones during 2013 using the high resolution Weather Research and Forecasting model

Singh¹,

Bhaskaran

2019

Meteorological Applications

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The present study investigated the capability of the Weather Research and Forecasting (WRF) model in the forecast/simulation of five landfalling Bay of Bengal (BoB) cyclones during 2013. A 3D variational (3DVar) method of data assimilation of the WRF model was used to assimilate the Global Telecommunication System and satellite radiances to improve the initial conditions. The results demonstrated that the model has the ability to simulate the cyclone track, intensity and structure. The study also indicates that predicted storm track, landfall and intensity improved with the 3DVar technique compared to without it. This was due to better initial conditions in the 3DVar experiment. The predicted track errors of the five storms were compared to available global and regional forecasting systems and the results show that the model has the capability for prediction of cyclones over the BoB region. The forecasted mean track errors were about 70, 114, 182 and 184 km; minimum centre pressure was about 8, 10, 13, 13 hPa and maximum surface wind was about 6, 10, 9, 8 m·s−1 on day 1 to day 4 forecast respectively. The study also presents some of the important predicted diagnostic parameters such as temperature anomaly, divergence, heating rate, frozen hydrometeors, vorticity field, equivalent potential temperature, maximum reflectivity, accumulated rainfall and horizontal wind fields compared to available observations for the extremely severe cyclonic storm Phailin. The warm core structure of the Phailin cyclone was resolved in the model between 9 and 15 km compared to satellite observations. The statistical analysis, distribution and magnitude of forecasted accumulated rainfall are also compared to the rainfall of 174 automatic weather stations.

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Impact of data assimilation and air−sea flux parameterization schemes on the prediction of cyclone Phailin over the Bay of Bengal using the WRF‐ARW model

Cited by 16 publications

References 47 publications

Assessing the performance evaluation of different convective parameterization schemes in simulating the intensity of severe cyclonic storms over the Bay of Bengal region

Assessing the performance evaluation of different convective parameterization schemes in simulating the intensity of severe cyclonic storms over the Bay of Bengal region

Prediction of Bay of Bengal Extremely Severe Cyclonic Storm "Fani” Using Moving Nested Domain

Prediction of landfalling Bay of Bengal cyclones during 2013 using the high resolution Weather Research and Forecasting model

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