International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 4, Issue 9  (September 2017), Pages:  26-34

Title: Simulation of high-resolution WRF model for an extreme rainfall event over the southern part of Thailand

Author(s):  Pramet Kaewmesri 1, Usa Humphries 1, *, Sirapong Sooktawee 2

Affiliation(s):

1Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi (KMUTT), 126 Pracha-Uthit Road, Bang mod, Thung khru, Bangkok 10140, Thailand
2Environmental Research and Training Center, Department of Environmental Quality Promotion, Ministry of Natural Resources and Environment, Bangkok 10400, Thailand

https://doi.org/10.21833/ijaas.2017.09.004

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Abstract:

The aim of research was to examine sensitivity to different microphysics parameterization schemes (Kessler, Lin, WSM3, WSM5 and WSM6) available in the Weather Research and Forecasting (WRF) model in the high-resolution heavy rainfall prediction. The Ensemble means technique was used to improve the results from the model in this case. The period was focused in November 2011. The different microphysics showed good agreements with observation from Tropical Rainfall Measure Mission (TRMM) and Thai Meteorological Department (TMD) station data. However, the Lin scheme performed that the good values of the Mean Absolute Error (MAE) and the Correlation Coefficient (CORR) were 1.16(0.39) and 0.88(0.61) to compare with TMD(TRMM) data. The Ensemble mean was an improved performance of heavy rainfall results that the good values of the (MAE) and the (CORR) were 1.03(0.16) and 0.92(0.67) to compare with TMD (TRMM) data. In summary, the WRF model demonstrated a good and reasonable rainfall simulation capability when to simulate were compared with the observations data over study areas. Detailed comparison indicates that Lin scheme and the Ensemble mean are highly recommended to simulate heavy rainfall. 

© 2017 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Microphysics parameterization schemes, Thai meteorological department, Tropical rainfall measure mission, Weather research and forecasting

Article History: Received 26 April 2017, Received in revised form 21 July 2017, Accepted 25 July 2017

Digital Object Identifier: 

https://doi.org/10.21833/ijaas.2017.09.004

Citation:

Kaewmesri P, Humphries U, and Sooktawee S (2017). Simulation of high-resolution WRF model for an extreme rainfall event over the southern part of Thailand. International Journal of Advanced and Applied Sciences, 4(9): 26-34

http://www.science-gate.com/IJAAS/V4I9/Kaewmesri.html

References:

  1. Chotamonsak C, Salate Jr PE, Kreasuwan J, and Chantara S (2012). Evaluation of Precipitation Simulations over Thailand using a WRF regional climate model. Chiang Mai Journal of Science, 39(4): 623–638. 
  2. Dudhia J (1989). Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. Journal of the Atmospheric Sciences, 46(20): 3077-3107. https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2 
  3. Efstathiou GA, Zoumakis NM, Melas D, and Kassomenos P (2012). Impact of precipitation ice on the simulation of a heavy rainfall event with advanced research WRF using two bulk microphysical schemes. Asia-Pacific Journal Atmospheric Science, 48(4): 357-368. https://doi.org/10.1007/s13143-012-0034-2 
  4. El Afandi G, Morsy, M, and El Hussieny F (2013). Heavy rainfall simulation over Sinai Peninsula using the weather research and forecasting model. International Journal of Atmospheric Sciences, 2013: Article ID 241050, 11 pages. https://doi.org/10.1155/2013/241050 
  5. Hong SY and Lim JOJ (2006). The WRF single-moment 6-class microphysics scheme (WSM6). Journal of the Korean Meteorological Society, 42(2): 129-151. 
  6. Hong SY, Dudhia J, and Chen SH (2004). A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Monthly Weather Review, 132(1): 103–120. https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2 
  7. Hong SY, Noh Y, and Dudhia J (2005). A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly Weather Review, 134(9): 2318-2341. https://doi.org/10.1175/MWR3199.1 
  8. Huffman GJ, Adler RF, Bolvin DT, Gu G, Enelkin EJ, Bowman KP, Stocker EF, and Wolff DB (2007). The TRMM multi-satellite precipitation analysis: quasi-global, multi-year, combined-sensor precipitation estimates at fine scale. Journal of Hydrometeorol, 8(1): 38-55. https://doi.org/10.1175/JHM560.1 
  9. Janjic ZI (1994). The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Monthly Weather Review, 122(5): 927-945. https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2 
  10. Kaewmesri P, Humphries U, Wangwongchai A, Wongwies P, Arche Varapuprok B, and Sooktawee S (2017). The simulation of heavy rainfall events over Thailand using microphysics schemes in weather research and forecasting (WRF) model. World Applied Sciences Journal, 35(2): 310-315.  
  11. Kessler E (1995). On the continuity and distribution of water substance in atmospheric circulations. Atmospheric Research, 38(1-4): 109-145. https://doi.org/10.1016/0169-8095(94)00090-Z 
  12. Kirtsaeng S, Chantar S, and Kreasuwan J (2010). Mesoscale simulation of a very heavy rainfall event over mumbai, using the weather research and forecasting (WRF) model. Chiang Mai Journal Science, 37(3): 429-442.  
  13. Kirtsaeng S, Kreasueun J, Chantara S, Kirtsaeng S, Sukthawee P, and Masthawee F (2012). Weather research and forecasting (WRF) model performance for a simulation of the 5 November 2009 heavy rainfall over southeast of Thailand. Chiang Mai Journal Sciences, 39(3): 511-523. 
  14. Lim JOJ, and Hong SY (2005). Effects of bulk ice microphysics on the simulated monsoonal precipitation over East Asia. Journal of Geophysical Research: Atmospheres, 110(D24). https://doi.org/10.1029/2005JD006166 
  15. Lin YL, Ferley RD, and Orvillie HD (1983). Bulk parameterization of the snow field in a cloud model. Journal of Climate and Applied Meteorology, 22(6): 1065-1092. https://doi.org/10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2 
  16. Litta AJ, Chakrapani B, and Mohankumar K (2007). Mesoscale simulation of an extreme rainfall event over Mumbai, India, using a high¡¾resolution MM5 model. Meteorological Applications, 14(3): 291-295. https://doi.org/10.1002/met.31 
  17. Mlawer Eli J, Taubman SJ, Brown DP, Iacono MJ, and Clough SA (1997). Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated¡¾k model for the longwave. Journal of Geophysical Research: Atmospheres, 102(D14): 16663-16682. https://doi.org/10.1029/97JD00237 
  18. Pennelly C, Reuter G, and Flesch T (2014). Verification of the WRF model for simulating heavy precipitation in Alberta. Atmospheric Research, 135: 172-192. https://doi.org/10.1016/j.atmosres.2013.09.004 
  19. Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, Huang XY, Wang W, and Powers JG (2008). A description of the advance research WRF Version 3. National Center for Atmospheric Research, Boulder, Colorado, USA. 
  20. Tewari M, Chen F, Wang W, Dudhia J, LeMone MA, Mitchell K, Ek M, Gayno G, Wegiel J, and Cuenca RH (2004). Implementation and verification of the unified NOAH land surface model in the WRF model. In the 20th Conference on Weather Analysis and Forecasting/16th Conference on Numerical Weather Prediction, USA: 11-15. 
  21. Wangwongchai A, Sixiong Z, and Qingcun Z (2005). A case study on a strong tropical disturbance and record heavy rainfall in Hat Yai Thailand during the winter monsoon. Advance in Atmospheric Sciences, 22(3): 426-450. https://doi.org/10.1007/BF02918757 
  22. Wilkins D (1995). Statistical Methods in the atmospheric sciences. Academic Press, San Diego, USA.