INTERNATIONAL JOURNAL OF EARTH AND ATMOSPHERIC SCIENCE Journal homepage: www.jakraya.com/journal/ ijeas

ORIGINAL ARTICLE Intensity Estimation Associated with ‘Megh’ by the Spatial Distribution of Wind Shear and CAPE

Sushil Kumar 1*, Ashish Routray 2, P.V.S. Raju 3 and Bhanumati Panda 4

1*Department of Applied Mathematics, School of Vocational Studies and Applied Sciences, Gautam Buddha University, Greater Noida-201312, India. 2National Centre for Medium Range Weather Forecasting (NCMRWF), A-50, Sector 62, Noida 201309, India. 3Centre for Ocean Atmospheric Science and Technology, Amity University Rajasthan, NH-11C, Kant Kalwar, Jaipur, India. 4Department of Applied Science and Humanities, I.T.S Engineering College, Greater Noida, U.P-201308, India.

Abstract Vertical wind shear and Convective Available Potential Energy (CAPE) are of those mainly significant parameters which affect the

intensity of a tropical cyclone (TC). The TCs are categorized as having large or small ambient vertical wind shear. Highly sheared tropical storms produce larger area-averaged CAPE versus relatively un-sheared storms. The vortex-scale increase in the quantities lessens the negative impact of *Corresponding Author: large vertical wind shear. The effects of wind shear on TC genesis is explored from climatological perspective. The physical process of TC Sushil Kumar genesis in wind shear is reconnoitered for Extremely Severe Tropical Cyclone Megh (2015) over the with high-resolution numerical Email: [email protected] simulation using a mesoscale model in an idealized framework. The simulation study results that in terms of the formation of a closed, low-level Submitted: 20/01/2018 circulation, moderate wind shear is indeed more conducive to genesis, but Accepted: 15/06/2018 is also very prohibitive to further development of the cyclone. The reasons for the greater favorableness of vertical wind shear versus no wind shear, and of westerly shear versus easterly shear, are discussed briefly in the context in a reasonable sense. Based on the spatial plots of CAPE, zonal wind shear and vertical wind shear, it is clearly seen that the TC Megh is most intense on 08 November but due to a gradual increase in the wind

shear it lost the intensity and started to be dissipated towards the land-fall.

Keywords: Tropical cyclone, CAPE, Wind shear, Arabian Sea.

1. Introduction density along the coast, apart from comparatively Bay of Bengal (BoB) and Arabian Sea (AS) are higher track prediction errors for damaging the life and contributing about 7% of total tropical cyclones (TCs) property due to TCs nearby the regions. Hence, for over the world (WMO technical report 2008). planning and implementation of the mitigation However, BoB is facing more frequently TCs both in measures effectively, it is desirable to reasonably general and land-falling and hence causes more correct prediction of track, intensity, and associated disasters than the AS TCs (IMD, 2008). Arabian Sea is post cyclone effects of these devastating storms at least also facing all types of TCs time to time and land- in 48 h advance to save the loss of life and property falling TCs over the AS has shown a steady increase significantly. Though, there has been substantial due to the growing population and development near progress in the forecast of related fields of TCs using the coastal area. Various researchers (Mohanty and various global and mesoscale models, still there is lot Gupta, 1997; Gupta, 2006) have found that predicting of scope for the improvement of the performance of track and intensity beyond 24h over the NIO (including these numerical weather prediction models. Many Bay of Bengal (BoB) and Arabian Sea (AS)) have lot attempts have been done to improve the efficiency of of limitations using synoptic and statistical methods. the models by improving grid resolution, physical There are various factors like poor socio-economic parameterizations, different combinations of the conditions, shallow bathymetry, and huge population schemes and data assimilation, etc. For the

International Journal of Earth and Atmospheric Science | April-June, 2018 | Volume 05 | Issue 02 | Pages 94-100 © 2018 Jakraya Kumar et al… Intensity Estimation Associated with Tropical Cyclone ‘Megh’ by the Spatial Distribution of Wind Shear and CAPE development and intensification of TCs (Anthes, 1982), weakened rapidly to SCS to CS on next day and deep one of the important aspects is the procedure of depression (DD) at 0600 UTC of 10 th . Finally, it physical parameterizations in terms of surface fluxes crossed to coast near latitude 13.4°N and of heat, moisture, momentum, cumulus convection, and longitude 46.1°E around 0900 UTC 10 th as a DD after vertical mixing in the planetary boundary layer (PBL). recurving to northeastwards and on same day slow Due to generation of the huge fluxes of heat, moisture, down to depression. It continued to a well-marked low and momentum, PBL is a significant factor for study pressure area over Yemen and neighborhood at 1800 (Braun and Tao, 2000). Hence, many PBL UTC of 10 th and cyclone Megh occurred back to back parameterization schemes (PBLSs) is included in the just after a week of formation after Chapala. NWP models (Mellor and Yamada, 1982; Hong et al., 2006). Various cumulus parameterization schemes 3. WRF Modeling System (CPSs) is also developed to resolve the issue of very Present study is based on using Advanced small scale of convective clouds in the numerical Weather Research and Forecast model version 3.2.1 models and included into three-dimensional mesoscale which is developed at the National Center for models (Kuo, 1974; Arakawa and Schubert, 1974; Atmospheric Research (NCAR) with the collaboration Anthes, 1977; Betts and Miller, 1986; Kain and Fritsch, many other organizations namely National Oceanic and 1993; Grell, 1993) and mostly these schemes applied Atmospheric Administration (NOAA), the National for specific convective environment (Grell, 1993; Kuo Center for Environmental Prediction (NCEP), and et al., 1996). Raju et al. (2012) simulated the four various universities (Dudhi, 2004). Non-hydrostatic severe TCs over the BoB during the 2007-2010 using mesoscale WRF model is designed for fine-scale WRF (ARW) models and concluded that the model atmospheric phenomena of few kilometers or less well predicted the cyclone track, intensity in terms of horizontal grid lengths (Michalakes et al., 2005; central pressure, maximum sustained winds, and Skamarock et al., 2005). Eulerian mass dynamical core precipitation reasonably. is used with Arakawa C-grid staggering with terrain- In this study, extremely severe tropical cyclone following hybrid sigma-pressure vertical coordinates ‘Megh’ is considered formed over the Arabian Sea and for time integration Runge-Kutta 2 nd and 3 rd order during November 2015 to examine the performance of schemes are used. Advection schemes are used from WRF-ARW core model in terms of wind shear, 2nd to 6 th order in both the horizontal and vertical intensity and CAPE. Section 2 contains a brief directions with a time-split small step for acoustic and description of synoptic features of the ‘Megh’ cyclone, gravity-wave modes (Skamarock and Klemp, 2008). while in Section 3, details of the WRF modeling Raju et al. (2011) carried out sensitivity experiments system. The results of the model simulations are based on cumulus convection, PBL schemes, and presented for weather parameters such as wind shear, microphysics schemes and found that YSU PBL, Kain- strong winds, mean sea level pressure associated with Fritsch Convective schemes and Ferrier microphysics the ‘Megh’ cyclone and CAPE analysis. Section 4 and schemes are simulating Bay of Bengal cyclone Nargis. Section 5 provides a detailed discussion of the results Sateesh et al (2017) found that YSU schemes produced and concluding remarks respectively. a better simulation for the THANE cyclone in terms of winds, pressure distribution and cloud fractions against 2. Synoptic Features of Severe Cyclone MYJ scheme. In this study, convective ‘Megh’ Over Arabian Sea during Nov, parameterization of Kain-Fritsch new Eta scheme 2015 (Kain and Fritsch, 1993), the planetary Yonsei A Low level circulation is started over University (YSU) of boundary layer and microphysics Lakshadweep and nearby and formed into depression schemes of Ferrier (new Eta) and Dudhia shortwave over the east-central Arabian Sea (AS) at 0000 UTC of radiation scheme (Dudhia, 1989) is used in the simulation of ‘Megh’ TC. NCEP global operational 5th November 2015 and became cyclonic storm (CS) at 0 1200 UTC of 5 th November after moving analysis at 1X1 horizontal resolutions are used for westwards/west-southwestwards. On 0600 UTC of 7 th , initial inputs for the cyclone simulations and lateral boundary conditions are taken from the NCEP-GFS intensified into severe cyclonic storm (SCS) towards 0 west-southwestward and became a very severe cyclonic data for the time-varying at 6-h intervals. USGS at 10 storm (VSCS) at 1500 UTC of 7 th at 1500 UTC and resolutions data are used for model topography and within 10-12 hours, storm intensified into an extremely simulations are compared from the IMD observations. severe cyclonic storm (ESCS) at 0300 UTC of 8 th for Model configuration is given in Table 1 which is used next 06 hours. Then, it became down to VSCS at 0000 for simulation of ‘Megh’ TC. UTC of 9 th and moved towards west-northwestward. It

International Journal of Earth and Atmospheric Science | April-June, 2018 | Volume 05 | Issue 02 | Pages 94-100 © 2018 Jakraya 95 Kumar et al… Intensity Estimation Associated with Tropical Cyclone ‘Megh’ by the Spatial Distribution of Wind Shear and CAPE

Table 1: Summary of WRF model configuration

Domain of Integration 35 0 E-75 0E , Equator- 25 0N Number of domain(s) One Horizontal grid size 9 km Vertical coordinate Terrain-following hydrostatic-pressure coordinate Time step 50 s Interval Seconds 21600 Seconds Map projection Mercator Horizontal Grid System Arakawa C-grid Top boundary condition Gravity wave absorbing (diffusion) Bottom boundary condition Physical Time integration 3rd order Runge-Kutta Spatial differencing Initial/Lateral boundary conditions NCEP-NCAR Final Analysis (FNL) Cumulus scheme Kain Fritsch PBL scheme YSU Radiation scheme Dudhia’s shortwave radiation, RRTM longwave radiation

Table 2: Comparison between IMD Observations and Model simulated ‘Mean Sea level pressure and wind’ at different times for ‘Megh’

Surface Winds (m/s) MSLP (hPa) Surface Winds (m/s) MSLP (hPa) 06 UTC 07 November 25 992 20 998 06 UTC 08 November 48 964 40 976 06 UTC 09 November 41 978 40 988 06 UTC 10 November 15 1003 15 1006

Fig 1: Distribution of wind at 850 hPa at different times for ‘Megh’.

4. Results and Discussion ‘Megh’ formed over the Arabian Sea during November The performance of the WRF-ARW core is 2015. The model is integrated up to 120 h and evaluated in terms of wind speed, MSLP, wind shear compared with IMD observations. Wind vectors and and CAPE analysis of extremely severe cyclone magnitude at 850 hPa are simulated for the ‘Megh’ –

International Journal of Earth and Atmospheric Science | April-June, 2018 | Volume 05 | Issue 02 | Pages 94-100 © 2018 Jakraya 96 Kumar et al… Intensity Estimation Associated with Tropical Cyclone ‘Megh’ by the Spatial Distribution of Wind Shear and CAPE

Fig 2: Mean Sea level pressure at different times for ‘Megh’.

Fig 3: Convective available potential energy (CAPE) analysis at different times for Megh’.

International Journal of Earth and Atmospheric Science | April-June, 2018 | Volume 05 | Issue 02 | Pages 94-100 © 2018 Jakraya 97 Kumar et al… Intensity Estimation Associated with Tropical Cyclone ‘Megh’ by the Spatial Distribution of Wind Shear and CAPE

Fig 4: Vertical wind profile analysis at different times for ‘Megh’.

Fig 5: Zonal wind shear analysis at different times for ‘Megh’. cyclone at four different times in Fig 1. Cyclone landfall with high order accuracy. The model predicted intensity is measured in terms of mean sea level the MSLP closed to the observed MSLP up to 72 h, pressure and and it is (Fig 2) however, it slightly over predicted than the observed that the model simulated wind intensity is IMD observations and it is well matched at the time of well matched with IMD observations and model could land-fall. Table 2 shows the comparison between IMD maintained the maximum sustained wind till the observations and model simulated results of MSLP and

International Journal of Earth and Atmospheric Science | April-June, 2018 | Volume 05 | Issue 02 | Pages 94-100 © 2018 Jakraya 98 Kumar et al… Intensity Estimation Associated with Tropical Cyclone ‘Megh’ by the Spatial Distribution of Wind Shear and CAPE

Fig 6: Meridional wind shear analysis at different times for ‘Megh’. surface wind at four different times and it is observed is shown in Fig 6. From 06 UTC 07 November to 06 that the wind is slightly under predicted and MSLP is UTC 08 November there is a clear visible vertical wind slightly over predicted up to the 48 h and it is very profile which get disturbed continuously for next 48 closely matched with the observations from 06 UTC hours and intensity of TC ‘Megh’ weakened. November to the landfall of the cyclone. Model simulated Convective Available Potential 5. Conclusion Energy (CAPE) is analyzed to measure instability In this study the performance of the WRF-ARW through the depth of the atmosphere (Fig 3) and model mesoscale model with 9 km resolution is evaluated in predicted the strong instability on 06 UTC 08 terms of various parameters like wind speed, MSLP, November as compared to the 06 UTC 07 November as CAPE and wind shear in all directions for the it is moderate instability and it persists till 06 UTC 09 prediction of TC ‘Megh’ in the AS during 05-10 November and finally model predicted the weak November 2015 and compared with IMD observations. instability on 06 UTC 10 November. Fig 4 shows the Model could predict the intensity in terms of central vertical wind profile at four different times after every pressure, maximum sustained winds and CAPE 24 h interval from 06 UTC 07 November to 06 UTC 10 reasonably well for the ‘Megh’ simulations. Model November. Sometimes the ordinary disturbances in predicted the maximum sustained wind 40 m/s at 06 tropical regions can attain tropical characteristics, UTC 09 and maximum drop of sea central pressure 976 which are due to the existence of warm sea surface hPa at the same time and well predicted the intensity of temperatures and low values of wind shear. central pressure of ‘Megh’. Hence it is concluded that Therefore, shear of the atmosphere over the the system was steered towards the west- tropical cyclone plays an important role for southwestwards by the lower mid-tropospheric development of the tropical cyclones. It is seen from intensity of wind. Model is indicating the weakening of the figures 5 that the value of zonal wind shear is very the system over AS before landfall. Based on the low on 06 UTC 07 November to 06 UTC 09 November spatial plots of CAPE, zonal wind shear and vertical and slowly increasing to next 24 h which is almost wind shear, it is clearly seen that the TC Megh is most equal to 6-7 m/s at 06 UTC 10 November and it was intense on 08 November but due to a gradual increase enough amount of shear for a tropical cyclone to start in the wind shear it lost the intensity and started to be dissipate. Meridional wind shear related to TC ‘Megh’ dissipated towards the land-fall.

International Journal of Earth and Atmospheric Science | April-June, 2018 | Volume 05 | Issue 02 | Pages 94-100 © 2018 Jakraya 99 Kumar et al… Intensity Estimation Associated with Tropical Cyclone ‘Megh’ by the Spatial Distribution of Wind Shear and CAPE

Acknowledgement model community and NCEP-NCAR for availing the Authors are thankful to SOVSAS Lab at data in the study. We acknowledge the contribution Gautam Buddha University for providing the given by Mr. Gaurav Tiwari (from IISER Bhopal) who computing facilities. We are grateful to the WRF helped us to explain the results and discussion section.

References World Meteorological Organization technical document models, Meteorological Monograph, No. 46, American (2008). Tropical cyclone operational plan for the Bay of Meteorological Society . pp. 165-170. Bengal and the Arabian Sea. Document No. WMO/TD Grell GA (1993). Prognostic evaluation of assumptions used No. 84 , 1. by cumulus parameterizations. Monthly Weather IMD Atlas (2008). Tracks of storms and depressions in the Review , 121: 764-787. Bay of Bengal and the Arabian Sea, India Kuo Y-H, Reed RJ and Liu Y-B (1996). The ERICA IOP 5 Meteorological Department, New Delhi, India. storm. Part III: Mesoscale cyclogenesis and Mohanty UC and Gupta A (1997). Deterministic methods for precipitation parameterization. Monthly Weather prediction of tropical cyclone tracks. Mausam , 48: 257- Review , 124: 1409-1434. 272. Raju PVS, Jayaraman P and Mohanty UC (2011). Sensitivity Gupta A (2006). Current status of tropical cyclone track of physical parameterizations on prediction of tropical prediction techniques and forecast errors. Mausam , 57: cyclone Nargis over the Bay of Bengal using WRF 151-158. model. Meteorological Atmosphere Physics , 113(3-4): Anthes RA (1982). Tropical cyclones-their evolution, 125-137. structure, and effects. Monograph No. 41, American Raju PVS, Jayaraman P and Mohanty UC (2012). Prediction Meteorological Society. of severe tropical cyclones over the Bay of Bengal Braun SA and Tao W-K (2000). Sensitivity of high- during 2007-2010 using high-resolution mesoscale resolution simulations of hurricane Bob (1991) to model. Natural Hazards , 63(3): 1361-1374. planetary boundary layer parameterizations. Monthly M Sateesh, Srinivas CV and Raju PVS (2017). Numerical Weather Review , 128: 3941-3961. simulation of tropical cyclone Thane: role of boundary Hong SY, Noh Y and Dudhia J (2006). A new vertical layer and surface drag parameterization schemes. diffusion package with an explicit treatment of Natural Hazards , 89(3): 1255-1271. entrainment processes. Monthly Weather Review , 134: Dudhia J (2004). The weather research and forecasting model 2318-2341. (version 2.0) 2 nd international workshop on next Mellor GL and Yamada T (1982). Development of a generation NWP model. Yonsei University Seoul, turbulence closure model for geophysical fluid Korea . pp. 19-23. problems. Reviews of Geophysics and Space Physics , Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, 20: 851-875. Wang W and Powers JG (2005). A description of the Kuo H-L (1974). Further studies of the parameterization of advanced research WRF version 2, NCAR Technical the influence of cumulus convection on largescale flow. Note NCAR/TN-468+STR . pp. 88. Journal of Atmosphere Science , 31: 1232-1240. Michalakes J, Dudhia J, Gill DO, Henderson T, Klemp J, Arakawa A and Schubert WH (1974). Interaction of a Skamarock W and Wand W (2005). The weather cumulus cloud ensemble with the large-scale research and forecast model: software architecture and environment. Part I. Journal of Atmosphere Science, performance. 11 th workshop on high performance 31: 674-701. computing in meteorology. World Scientific . pp. 156- Anthes RA (1977). Hurricane model experiments with a new 168. cumulus parameterization scheme. Monthly Weather Skamarock WC and Klemp JB (2008). A time-split non- Review , 105: 287-300. hydrostatic atmospheric model for weather research and Betts AK and Miller MJ (1986). A new convective forecasting applications. Journal of Computational adjustment scheme. Part II: single column tests using Physics , 227: 3465-3485. GATE wave, BOMEX, ATEX, and Arctic air-mass Kain JS and Fritsch JM (1993). Convective parameterization data sets. Quarterly Journal of the Royal for mesoscale models: the Kain-Fritsch scheme, the Meteorological Society , 112: 693-709. representation of cumulus convection in numerical Kain JS and Fritsch JM (1993). Convective parameterization models. In: Emanuel KA and Raymond DJ (eds). for mesoscale models: The Kain-Fritsch scheme. The American Meteorological Society . pp. 246. representation of cumulus convection in numerical

International Journal of Earth and Atmospheric Science | April-June, 2018 | Volume 05 | Issue 02 | Pages 94-100 © 2018 Jakraya 100