Skip to main content
SpringerLink
Log in

Impact of assimilation of conventional and satellite meteorological observations on the numerical simulation of a Bay of Bengal Tropical Cyclone of November 2008 near Tamilnadu using WRF model

  • Original Paper
  • Published:
Meteorology and Atmospheric Physics Aims and scope Submit manuscript

Abstract

The objective of this study is to examine the impact of assimilation of conventional and satellite data on the prediction of a severe cyclonic storm that formed in the Bay of Bengal during November 2008 with the four-dimensional data assimilation (FDDA) technique. The Weather Research and Forecasting (WRF ARW) model was used to study the structure, evolution, and intensification of the storm. Five sets of numerical simulations were performed using the WRF. In the first one, called Control run, the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) was used for the initial and boundary conditions. In the remaining experiments available observations were used to obtain an improved analysis and FDDA grid nudging was performed for a pre-forecast period of 24 h. The second simulation (FDDAALL) was performed with all the data of the Quick Scatterometer (QSCAT), Special Sensor Microwave Imager (SSM/I) winds, conventional surface, and upper air meteorological observations. QSCAT wind alone was used in the third simulation (FDDAQSCAT), the SSM/I wind alone in the fourth (FDDASSMI) and the conventional observations alone in the fifth (FDDAAWS). The FDDAALL with assimilation of all observations, produced sea level pressure pattern closely agreeing with the analysis. Examination of various parameters indicated that the Control run over predicted the intensity of the storm with large error in its track and landfall position. The assimilation experiment with QSCAT winds performed marginally better than the one with SSM/I winds due to better representation of surface wind vectors. The FDDAALL outperformed all the simulations for the intensity, movement, and rainfall associated with the storm. Results suggest that the combination of land-based surface, upper air observations along with satellite winds for assimilation produced better prediction than the assimilation with individual data sets.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  • Aberson SD (2001) The ensemble of tropical cyclone track forecasting models in the north 986 Atlantic basin (1976–2000). Bull Amer Meteor Soc 82:1895–1904

    Article  Google Scholar 

  • Anthes RA (1977) Hurricane model experiments with a new cumulus parameterization scheme. Mon Weather Rev 105:287–300

    Article  Google Scholar 

  • Asnani GC (1993) Tropical Meteorology, vol 1, 2. Published by Prof. G.C. Asnani, c/o Indian Institute of Tropical Meteorology, Dr. Homi Bhabha Road, Pashan, Pune-411008, India

  • Bhaskar Rao DV, Hari Prasad D (2006) Numerical prediction of the Orissa super-cyclone (2006): sensitivity to the parameterization of convection, boundary layer and explicit moisture processes. Mausam 57(1):61–78

    Google Scholar 

  • Bhaskar Rao DV, Hari Prasad D (2007) Sensitivity of tropical cyclone intensification to boundary layer and convective processes. Nat Hazards 41(3):429–445

    Article  Google Scholar 

  • Bhaskar Rao DV, Hari Prasad D, Srinivas D (2009) Impact of horizontal resolution and the advantages of the nested domains approach in the prediction of tropical cyclone intensification and movement. J Geophys Res 114:D11106. doi:10.1029/2008JD011623

    Article  Google Scholar 

  • Braun SA (2002) A cloud-resolving simulation of hurricane Bob (1991): storm structure 997 and eyewall buoyancy. Mon Weather Rev 130:1573–1592

    Article  Google Scholar 

  • Braun SA, Tao W-K (2000) Sensitivity of high resolution simulations of hurricane Bob (1991) to planetary boundary layer parameterizations. Mon Weather Rev 128:3941–3961

    Article  Google Scholar 

  • Chen DR, Yeh TC, Haung KN, Peng MS, Chang SW (1995) A new operational typhoon track prediction system at the central weather Bureau in Taiwan. Preprints 21st Conference on Hurricanes and Tropical Meteorology Society, Boston, MA 02108, pp 50–51

  • Davis CA, Bossart LF (2001) Numerical simulations of the genesis of hurricane Diana (1984). Part I. Control Simulation. Mon Weather Rev 129:1859–1881

    Article  Google Scholar 

  • Dudhia J (1989) Numerical study of convection observed during winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107

    Article  Google Scholar 

  • Elsberry RL, Carr LE (2000) Consensus over of dynamical tropical cyclone track forecasts errors versus spread. Mon Weather Rev 128:4131–4138

    Article  Google Scholar 

  • Gray WM (1968) Global view of the origin of tropical disturbances and storms. Mon Weather Rev 96:669–700

    Article  Google Scholar 

  • Hong SY, Dudhia J, Chen SH (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132:103–120

    Article  Google Scholar 

  • Hong SY, Noh Y, Dudhia J (2006) A new vertical diffusion package with explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341

    Article  Google Scholar 

  • IMD (2008) Report on Cyclonic Disturbances over North Indian Ocean During 2008. RSMC-Tropical Cyclones, India Meteorological Department, New Delhi, Jan 2009, p 108

  • Kain, JS, Fritsch. JM (1993) Convective parameterization for mesoscale models: the Kain-Fritcsh scheme. In: KA Emanuel, DJ Raymond (eds) The representation of cumulus convection in numerical models, American Meteorological Society, USA, p 246

  • Kalnay E (2003) Atmospheric modeling, data assimilation and predictability. Cambridge University Press, London, p 341

    Google Scholar 

  • Kim YH, Jeon E-H, Chang D-E, Lee H-S, Park J-I (2010) The impact of TPARC 2008 dropsonde observations on typhoon track forecasting. Asia-Pac J Atmos Sci 46:287–303

    Article  Google Scholar 

  • Krishnamurty TN, Pattnaik S, Stefenova L, Vijaykumar TSV, Mackey BP, O’shay AJ, Pasch RJ (2005) On the hurricane intensity issue. Mon Weather Rev 133:1886–1912

    Article  Google Scholar 

  • Kurihara Y, Bender MA (1980) Use of a movable nested-mesh model for tracking a small vortex. Mon Weather Rev 108:1792–1809

    Article  Google Scholar 

  • Kurihara Y, Tuleya RE, Bender MA (1998) The GFDL hurricane prediction system and its performance in the 1995 hurricane season. Mon Weather Rev 128:1306–1322

    Article  Google Scholar 

  • Langland RH, Velden C, Panley PM, Berger H (2009) Impact of satellite-derived rapid-scan wind observations on numerical model forecasts of hurricane Katrina. Mon Weather Rev 137:1615–1622

    Article  Google Scholar 

  • Leslie LM, Le Marshall JF, Morison RP, Spinoso C, Purser RJ, Pescod N, Seecamp R (1998) Improved hurricane track forecasting from the continuous assimilation of high quality satellite wind data. Mon Weather Rev 126:1248–1257

    Article  Google Scholar 

  • Ley GW, Elsberry RL (1976) Forecasts of typhoon Irma using a nested-grid model. Mon Weather Rev 104:1154–1161

    Article  Google Scholar 

  • Liu Y, Zhang DL, Yau MK (1977) A multi-scale numerical simulation of hurricane Andrew (1992). Part I. Explicit simulation and verification. Mon Weather Rev 125:3073–3093

    Article  Google Scholar 

  • Mandal M, Mohanty UC (2006) Numerical experiments for improvement in mesoscale simulation of Orissa super-cyclone. Mausam 57(1):79–96

    Google Scholar 

  • Marshall JL, Leslie L, Morrison R, Pescod N, Seecamp R, Spinoso C (2000) Recent developments in the continuous assimilation of satellite wind data for Tropical cyclone forecasting. Adv Space Res 25(25):1077–1080

    Article  Google Scholar 

  • Mlawer EJ, Taubman SJ, Brown PD, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J Geophys Res 102(D14):16663–16682

    Article  Google Scholar 

  • Mohanty UC, Mandal M, Raman S (2004) Simulation of Orissa super-cyclone (1999) using PSU/NCAR mesoscale model. Nat Hazards 31:373–390

    Article  Google Scholar 

  • Mukhopadhyay P, Sanjay J, Cotton WR, Singh SS (2004) Impact of surface meteorological observation on RAMS forecast of monsoon weather systems over the Indian region. Meteor Atmos Phys 90:77–108

    Article  Google Scholar 

  • Navon IM (2009) Data assimilation for numerical weather prediction: a review. In: Park SK, Xu L (eds) Data assimilation for atmospheric, oceanic and hydrologic applications. Springer, Berlin, pp 21–65

    Chapter  Google Scholar 

  • Park SK, Zupanski D (2003) Four-dimensional variational data assimilation for mesoscale and storm-scale applications. Meteor Atmos Phys 82:173–208

    Article  Google Scholar 

  • Park SK, Zhang D-L, Kim HH (2008) Impact of dropwindsonde data on the track forecasts of a tropical cyclone: an observing-systems simulation experiment study. Asia-Pac J Atmos Sci 44:85–92

    Google Scholar 

  • Prasad K, Rama Rao YV (2003) Cyclone track prediction by a quasi-Lagrangian model. Meteorol and Atmos Phys 83:173–185

    Google Scholar 

  • Pu Z et al (2009) Assimilation of satellite data in improving numerical simulation of tropical cyclones: progress, challenge and development. In: Park SK, Xu L (eds) Data assimilation for atmospheric, oceanic and hydrologic applications. Springer, Berlin, pp 163–176

    Chapter  Google Scholar 

  • Kusuma G Rao (2008) PRWONAM for mesoscale monsoon research in India and predictions over SHAR-Kalpakkam—Bangalore region. Technology Development for Atmospheric Research and Applications. 193–230

  • Rosenthal SL (1971) The response of a tropical cyclone model to variations in boundary layer parameters, initial conditions, lateral boundary conditions, and domain size. Mon Weather Rev 99:767–777

    Article  Google Scholar 

  • Roy Bhowmik SK (2003) Prediction of monsoon rainfall with a nested grid mesoscale limited area model. Proc Indian Acad Sci Earth Planet Sci 112:499–519

    Google Scholar 

  • Sandeep S, Chandrasekar A, Singh D (2006) The impact of assimilation of AMSU data for the prediction of a tropical cyclone over India using a mesoscale model. Int J Remote Sens 27:4621–4653

    Article  Google Scholar 

  • Sathi Devi V, Hari Prasad D, Bhaskar Rao DV (2006) The evaluation of Kain-Fritisch Scheme in tropical cyclone simulation. Mausam 57(3):395–410

    Google Scholar 

  • Singh R, Pal PK, Kishtawal CM, Joshi PC (2008) The impact of variational assimilation of SSM/I and QSCAT satellite observations on the numerical simulation of Indian ocean tropical cyclones. Weather forecast 23:460–476

    Article  Google Scholar 

  • Skamarock, WC, Klemp, JB., Dudhia, J, Gill, DO, Barker, DM, Dudha, MG, Huang, X, Wang, W, Powers, Y (2008) A description of the Advanced Research WRF Ver.30. NCAR Technical Note. NCAR/TN-475 + STR. Mesocale and Microscale Meteorology Davison, National Centre for Atmospheric Research, Boulder Colorado, USA, p 113

  • Soden BJ, Velden CS, Tuleya RE (2001) The impact of satellite winds on experimental GFDL Hurricane model forecasts. Mon Weather Rev 129:835–852

    Article  Google Scholar 

  • Srinivas CV, Venkatesan R, Bhaskar Rao DV, Hariprasad D (2007) Numerical simulation of Andhra severe cyclone (2003): model sensitivity to boundary layer and convection parameterization. Pure Appl Geophys 164:1–23

    Article  Google Scholar 

  • Stauffer DR, Seaman N (1990) Use of four-dimensional data assimilation in a limited-area mesoscale model. Part I. Experiments with Synoptic-Scale Data. Mon Weather Rev 118:1252–1277

    Article  Google Scholar 

  • Stauffer DR, Seaman N (1994) Multiscale four-dimensional data assimilation. J Appl Meteorol 33:416–434

    Article  Google Scholar 

  • Stauffer DR, Seaman N, Binkowski FS (1991) Use of four-dimensional data assimilation in a limited-area mesoscale model. Part II. Effects of data assimilation within the planetary boundary layer. Mon Weather Rev 119:734–754

    Article  Google Scholar 

  • Sundqvist H (1970) Numerical simulation of the development of tropical cyclones with a ten-level model. Part I. Tellus 22:359–390

    Article  Google Scholar 

  • Trivedi DK, Sanjay J, Singh SS (2002) Numerical simulation of a super cyclonic storm, 1081 Orissa (1999): impact of initial conditions. Meteorol Appl 9:367–376

    Article  Google Scholar 

  • Trivedi DK, Mukhopadhyay P, Vaidya SS (2006) Impact of physical parameterization schemes on the numerical simulation of Orissa super cyclone (1999). Mausam 57(1):97–110

    Google Scholar 

  • Vinodkumar, Chandrasekhar A, Alapaty K, Niyogi DS (2007) The effect of a surface data assimilation technique and the traditional four-dimensional data assimilation on the simulation of a monsoon depression over India using a mesoscale model. Nat Hazards 42:439–453

    Article  Google Scholar 

  • Wang Y (2001) An explicit simulation of tropical cyclones with a triply nested movable mesh primitive equation model: TCM3. Part I. description of the model and control experiment. Mon Weather Rev 130:3022–3036

    Article  Google Scholar 

  • Wang Y (2002) Vortex Rossby waves in a numerically simulated tropical cyclone. Part II: the role in tropical cyclone structure and intensity changes. J Atmos Sci 59:1239–1262

    Article  Google Scholar 

  • Wu C-C, Chou K-H, Lin P-H, Aberson SD, Peng MS, Nakazawa T (2007) The impact of dropwindsonde data on typhoon track forecast in DOTSTAR. Weather Forecast 22:1157–1176

    Article  Google Scholar 

  • Xavier VF, Chandrasekhar A, Rahman H, Niyogi D, Alapaty K (2008) The effect of satellite and conventional meteorological data assimilation on the mesoscale modeling of monsoon depressions over India. Meteor Atmos Phys. doi:10.1007/s00703-008-0314-7

  • Yang MJ, Ching L (2005) A modeling study of typhoon Toraji 2001: physical parameterisation sensitivity and topographic effect. Terr Atmospheric Ocean Sci 16:177–213

    Google Scholar 

  • Zhang X, Xiao Q, Fitzpatrick PJ (2007) The Impact of Multisatellite Data on the Initialization and Simulation of Hurricane Lili’s (2002) Rapid Weakening Phase. Adv Atmospheric Sci 22(4):534–544

    Google Scholar 

  • Zhihua Z, Yihong D, Xudong L, Leiming M, Chan JC (2005) The effect of three-dimensional variational data assimilation of QSCAT data on the numerical simulation of typhoon track and intensity. Adv Atmospheric Sci 22(4):534–544

    Article  Google Scholar 

Download references

Acknowledgments

Authors sincerely thank Dr.Baldevraj, Director, IGCAR, Dr.P.Chellapandi, Director, Safety Group, Dr.B.Venkatraman, Head RSD and Sri K.M.Somayaji for their encouragement in carrying out the study. The WRF ARW model was obtained from NCAR. The NCEP FNL analysis was available from NCEP. The QSCAT, SSM/I data were obtained from NASA. The upper air observations are taken from University of Wyoming. Thanks are due to Dr.B.Manikiam and Dr. Kusuma Rao, ISRO for providing AWS observations as part of PRWONAM mesoscale program from MOSDAC, SAC, Ahmadabad. One of the authors Mr.Yesubau is thankful to SAC, ISRO for the grant of junior research fellowship in the SAC MTUP project. The authors wish to record grateful thanks to the anonymous reviewers for suggesting many improvements in the manuscript.

Author information

Authors and Affiliations

  1. Safety Group, Indira Gandhi Centre for Atomic Research, Kalpakkam, 603102, Tamilnadu, India

    C. V. Srinivas, V. Yesubabu & R. Venkatesan

  2. Department of Meteorology and Oceanography, Andhra University, Vishakhapatnam, 530003, India

    S. S. V. S. Ramarkrishna

Authors
  1. C. V. Srinivas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. V. Yesubabu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. R. Venkatesan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. S. S. V. S. Ramarkrishna
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to C. V. Srinivas.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Srinivas, C.V., Yesubabu, V., Venkatesan, R. et al. Impact of assimilation of conventional and satellite meteorological observations on the numerical simulation of a Bay of Bengal Tropical Cyclone of November 2008 near Tamilnadu using WRF model. Meteorol Atmos Phys 110, 19–44 (2010). https://doi.org/10.1007/s00703-010-0102-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00703-010-0102-z

Keywords

Search

Navigation