Abstract
Forecasting skill of weather research and forecasting (WRF) model in simulating typhoons over the West Pacific and South China Sea with different trajectories has been studied in terms of track direction and intensity. Four distinct types of typhoons are chosen for this study in such a way that one of them turns toward left during its motion and had landfall, while the second took a right turn before landfall. The third typhoon followed almost a straight line path during its course of motion, while the fourth typhoon tracked toward the coast and just before landfall, ceased its motion and travelled in reverse direction. WRF model has been nested in one way with a coarse resolution of 9 km and a fine resolution of 3 km for this study, and the experiments are performed with National Center for Environmental Prediction-Global Forecasting System (NCEP-GFS) analyses and forecast fields. The model has been integrated up to 96 h and the simulation results are compared with observed and analyzed fields. The results show that the WRF model could satisfactorily simulate the typhoons in terms of time and location of landfall, mean sea-level pressure, maximum wind speed, etc. Results also show that the sensitivity of model resolution is less in predicting the track, while the fine-resolution model component predicted slightly better in terms of central pressure drop and maximum wind. In the case of typhoon motion speed, the coarse-resolution component of the model predicted the landfall time ahead of the actual, whereas the finer one produced either very close to the best track or lagging little behind the best track though the difference in forecast between the model components is minimal. The general tendency of track error forecast is that it increases almost linearly up to 48 h of model simulations and then it diverges quickly. The results also show that the salient features of typhoons such as warm central core, radial increase of wind speed, etc. are simulated well by both the coarse and fine domains of the WRF model.
Similar content being viewed by others
References
Asnani GC (1993) Tropical meteorology. Published by Prof. G.C. Asnani
Carr LE, Elsberry RL (1994) Systematic and integrated approach to tropical cyclone track forecasting Part 1. Approach overview and description of meteorological basis. NPS-MR-94-002, Naval Postgraduate School, Monterey, CA 93943, 273 pp
Carr LE III, Elseberry RL (1995) Monsoonal interactions leading to sudden tropical cyclone track changes. Mon Weather Rev 123:265–289
Carr LE, Elseberry RL (2000a) Dynamical tropical cyclone track forecast errors part I: tropical region error sources. Weather Forecast 15:641–661
Carr LE, Elseberry RL (2000b) Dynamical tropical cyclone track forecast errors part II: midlatitude circulation influences. Weather Forecast 15:662–681
Chan JCL (1984) An observational study of the physical processes responsible for tropical cyclone motion. J Atmos Sci 41:1036–1048
Chan JCL (2009) Thermodynamic control on the climate of intense tropical cyclones. Proc R Soc A 465:3011–3021
Chan CLC, Gray WM (1982) Tropical cyclone movement and surrounding flow relationships. Mon Weather Rev 110:1354–1374
Chan CLC, Gray WM, Kiddder SQ (1980) Forecasting tropical cyclone turning motion from surrounding wind and temperature fields. Mon Weather Rev 108:778–792
Cheng WYY, Steenbyrgh WJ (2005) Evaluation of surface sensible weather forecasts by WRF and ETA models over the Western United states. Weather Forecast 20:812–821
Davis C, Wang W, Chen SS, Chen Y, Corbosiero K, DeMaria M, Dudhia J, Holland G, Klemp J, Michalakes J, Reeves H, Rotunno R, Xiao Q (2008) Prediction of landfalling hurricanes with the advanced Hurricane WRF model. Mon Weather Rev 136:1990–2005
Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3177
Dudhia J (2004) The Weather Research and Forecasting Model (Version 2.0). In: 2nd International workshop on next generation NWP model. Seoul, Korea, Yonsei University, pp 19–23
Fiorino M, Elsberry RL (1989) Some aspects of vortex structure related to tropical cyclone motion. J Atmos Sci 46:975–990
Fujiwhara S (1921) The natural tendency towards symmetry of motion and its application as principle in meteorology. Q J R Meteorol Soc 47:287–293
Hong SY, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341
Kain JS, Fritsch JM (1993) Convective parameterization for mesoscale models: the Kain–Fritsch Scheme, the representation of cumulus convection in numerical models. In: Emanual, KA, Raymond, DJ (eds) American Meteorological Society
Krishnamurti TN, Bedi HS, Yap KS, Oosterhof D (1993) Hurricane Forecasts in the FSU models. Adv Atmos Sci 1:121–131
Litta AJ, Mohanty UC (2008) Simulation of a severe thunderstorm event during the field experiment of STORM programme 2006, using WRF-NMM model. Curr Sci 95:204–215
Mandal M, Mohanty UC, Raman S (2004) A study on the impact of parameterization of physical processes on prediction of tropical cyclones over the Bay of Bengal with NCAR/PSU mesoscale model. Nat Hazards 31:391–414
Neumann CJ (1981) Trends in forecasting the tracks of Atlantic tropical cyclones. Bull Am Meteorol Soc 62:1473–1485
Neumann CJ (1993) Global guide to tropical cyclone forecaster (Chapter 1) WMO technical document. WMO/TD-No. 560, Tropical Cyclone Programme, project no 16, report no TCP-31
Patra PK, Santhanam MS, Potty KVJ, Tewari M, Rao PLS (2000) Simulation of tropical cyclones using regional weather prediction models. Curr Sci 79(1):70–78
Pattanayak S, Mohanty UC (2008) A comparative study on performance of MM5 and WRF models in simulation of cyclones over Indian seas. Curr Sci 95:923–936
Raju PVS, Jayaraman Potty, Mohanty UC (2011) Sensitivity of Physical Parameterisation on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF Model. Meteorol Atmos Phys 113:125–137. doi:10.1007/s00703-011-0151-y
Riehl H (1979) Climate and weather in the tropics. Academic Press, New York, p 611
Routray A, Mohanty UC, Niyogi D, Rizvi SRH, Osuri KK (2010) Simulation of heavy rainfall events over Indian monsoon region using WRF-3DVAR data assimilation system. Meteorol Atmos Phys 106:107–125
Segami A, Kurihara K, Nakamura H, Ueno M, Takano I, Tatsumi Y (1989) Operational meso scale weather prediction with Japan spectral model. J Meteorol Soc Jpn 67:907–924
Sugi M, Noda A, Sato A (2002) Influence of global warming on tropical cyclone climatology: an experiment with the JMA global model. J Meteorol Soc Jpn 80:249–272
Vijaya Kumar TSV, Krishnamurti TN, Fiorino Michael, Nagata Masashi (2003) Multimodel superensemble forecasting of tropical cyclones in the Pacific. Mon Weather Rev 131:574–583
Acknowledgments
The initial and boundary conditions for this study are taken from the National Center for Environmental Prediction (NCEP), and the verification data for the experiments are drawn from the Joint Typhoon Warning Center (JTWC). The ARW core of the WRF model is downloaded from the NCAR web site. We also extend our acknowledgements to Mr. A. R. Subbiah for his encouragements and support for this study. The financial support for this study was provided by the Royal Norwegian Ministry of Foreign Affairs.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Potty, J., Oo, S.M., Raju, P.V.S. et al. Performance of nested WRF model in typhoon simulations over West Pacific and South China Sea. Nat Hazards 63, 1451–1470 (2012). https://doi.org/10.1007/s11069-011-0074-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11069-011-0074-4