Minh, Pham Thi, Bui Thi Tuyet, Tran Thi Thu Thao et Le Thi Thu Hang. « Application of ensemble Kalman filter in WRF model to forecast rainfall on monsoon onset period in South Vietnam ». VIETNAM JOURNAL OF EARTH SCIENCES 40, no 4 (18 septembre 2018) : 367–94. http://dx.doi.org/10.15625/0866-7187/40/4/13134.
Résumé :
This paper presents some results of rainfall forecast in the monsoon onset period in South Vietnam, with the use of ensemble Kalman filter to assimilate observation data into the initial field of the model. The study of rainfall forecasts are experimented at the time of Southern monsoon outbreaks for 3 years (2005, 2008 and 2009), corresponding to 18 cases. In each case, there are five trials, including satellite wind data assimilation, upper-air sounding data assimilation, mixed data (satellite wind+upper-air sounding data) assimilation and two controlled trials (one single predictive test and one multi-physical ensemble prediction), which is equivalent to 85 forecasts for one trial. Based on the statistical evaluation of 36 samples (18 meteorological stations and 18 trials), the results show that Kalman filter assimilates satellite wind data to forecast well rainfall at 48 hours and 72 hours ranges. With 24 hour forecasting period, upper-air sounding data assimilation and mixed data assimilation experiments predicted better rainfall than non-assimilation tests. The results of the assessment based on the phase prediction indicators also show that the ensemble Kalman filter assimilating satellite wind data and mixed data sets improve the rain forecasting capability of the model at 48 hours and 72 hour ranges, while the upper-air sounding data assimilation test produces satisfactory results at the 72 hour forecast range, and the multi-physical ensemble test predicted good rainfall at 24 hour and 48 hour forecasts. The results of this research initially lead to a new research approach, Kalman Filter Application that assimilates the existing observation data into input data of the model that can improve the quality of rainfall forecast in Southern Vietnam and overall country in general.References Bui Minh Tuan, Nguyen Minh Truong, 2013. Determining the onset indexes for the summer monsoon over southern Vietnam using numerical model with reanalysis data. VNU Journal of Science, 29(1S), 187-195.Charney J.G., 1955. The use of the primitive equations of motion in numerical prediction, Tellus, 7, 22.Cong Thanh, Tran Tan Tien, Nguyen Tien Toan, 2015. Assessing prediction of rainfall over Quang Ngai area of Vietnam from 1 to 2 day terms. VNU Journal of Science, 31(3S), 231-237.Courtier P., Talagrand O., 1987. Variational assimilation of meteorological observations with the adjoint vorticity equations, Part II, Numerical results. Quart. J. Roy. Meteor. Soc., 113, 1329.Daley R., 1991. Atmospheric data analysis. Cambridge University Press, Cambridge.Elementi M., Marsigli C., Paccagnella T., 2005. High resolution forecast of heavy precipitation with Lokal Modell: analysis of two case studies in the Alpine area. Natural Hazards and Earth System Sciences, 5, 593-602.Fasullo J. and Webster P.J., 2003. A hydrological definition of India monsoon onset and withdrawal. J. Climate, 16, 3200-3211.Haltiner G.J., Williams R.T., 1982. Numerical prediction and dynamic meteorology, John Wiley and Sons, New York.Hamill T.M., Whitaker J.S., Snyder C., 2001. Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Wea. Rev., 129, 2776.He J., Yu J., Shen X., and Gao H., 2004. Research on mechanism and variability of East Asia monsoon. J. Trop. Meteo, 20(5), 449-459.Hoang Duc Cuong, 2008. Experimental study on heavy rain forecast in Vietnam using MM5 model. A report on the Ministerial-level research projects on science and technology, 105p.Houtekamer P.L., Mitchell H.L., Pellerin G., Buehner M., Charron M., Spacek L., Hansen B., 2005. Atmospheric data assimilation with an ensemble Kalman filter: Results with real observations. Mon. Wea. Rev., 133, 604.Houtekamer P.L., Mitchell H.L., 2005. Ensemble Kalman filtering, Quart. J. Roy. Meteor. Soc., 131C, 3269-3289.Hunt B.R., Kostelich E., Szunyogh I., 2007. Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter. Physica D., 230, 112-126.Kalnay E., 2003. Atmospheric modeling, data assimilation and predictability. Cambridge University Press, 181.Kalnay et al., 2008. A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus A, 60(1), 113-130.Kato T., Aranami K., 2009. Formation Factors of 2004 Niigata-Fukushima and Fukui Heavy Rainfalls and Problems in the Predictions using a Cloud-Resolving Model. SOLA. 10, doi:10.2151/sola.Kieu C.Q., 2010. Estimation of Model Error in the Kalman Filter by Perturbed Forcing. VNU Journal of Science, Natural Sciences and Technology, 26(3S), 310-316.Kieu C.Q., 2011. Overview of the Ensemble Kalman Filter and Its Application to the Weather Research and Forecasting (WRF) model. VNU Journal of Science, Natural Sciences and Technology, 27(1S), 17-28.Kieu C.Q., Truong N.M., Mai H.T., and Ngo Duc T., 2012. Sensitivity of the Track and Intensity Forecasts of Typhoon Megi (2010) to Satellite-Derived Atmosphere Motion Vectors with the Ensenble Kalman filter. J. Atmos. Oceanic Technol., 29, 1794-1810.Kieu Thi Xin, 2005. Study on large-scale rainfall forecast by modern technology for flood prevention in Vietnam. State-level independent scientific and technological briefing report, 121-151.Kieu Thi Xin, Vu Thanh Hang, Le Duc, Nguyen Manh Linh, 2013. Climate simulation in Vietnam using regional climate nonhydrostatic NHRCM and hydrostatic RegCM models. Vietnam National University, Hanoi. Journal of Natural sciences and technology, 29(2S), 243-25.Krishnamurti T.N., Bounoa L., 1996. An introduction to numerical weather prediction techniques. CRC Press, Boca Raton, FA.Lau K.M., Yang S., 1997. Climatology and interannual variability of the Southeast Asian summer monsoon. Adv. Atmos. Sci., 14,141-162.Li C., Qu X., 1999. Characteristics of Atmospheric Circulation Associated with Summer monsoon onset in the South China Sea. Onset and Evolution of the South China Sea Monsoon and Its Interaction with the Ocean. Ding Yihui, and Li Chongyin, Eds, Chinese Meteorological Press, Beijing, 200-209.Lin N., Smith J.A., Villarini G., Marchok T.P., Baeck M.L., 2010. Modeling Extreme Rainfall, Winds,and Surge from Hurricane Isabel, 25. Doi: 10.1175/2010WAF2222349.Lu J., Zhang Q., Tao S., and Ju J., 2006. The onset and advance of the Asian summer monsoon. Chinese Science Bulletin, 51(1), 80-88.Matsumoto J., 1997. Seasonal transition of summer rainy season over Indochina and adjacent monsoon region. Adv. Atmos. Sci., 14, 231-245.Miyoshi T., and Kunii M., 2012. The Local Ensenble Transform Kalman Filter with the Weather Rearch and Forecasting Model: Experiments with Real Observation. Pure Appl. Geophysic, 169(3), 321-333. Miyoshi T., Yamane S., 2007. Local ensemble transform Kalman filtering with an AGCM at a T159/L48 resolution. Mon. Wea. Rev., 135, 3841-3861.Nguyen Khanh Van, Tong Phuc Tuan, Vuong Van Vu, Nguyen Manh Ha, 2013. The heavy rain differences based on topo-geographical analyse at Coastal Central Region, from Thanh Hoa to Khanh Hoa. J. Sciences of the Earth, 35, 301-309.Nguyen Minh Truong, Bui Minh Tuan, 2013. A case study on summer monsoon onset prediction for southern Vietnam in 2012 using the RAMS model. VNU Journal of Science, 29(1S), 179-186.Phillips N.A., 1960b. Numerical weather prediction. Adv. Computers, 1, 43-91, Kalnay 2004.Phillips N., 1960a. On the problem of the initial data for the primitive equations, Tellus, 12, 121126.Phuong Nguyen Duc, 2013. Experiment on combinatorial Kalman filtering method for WRF model to forecast heavy rain in central region in Vietnam. The Third International MAHASRI/HyARC Workshop on Asian Monsoon and Water Cycle, 28-30 August 2013, Da Nang, Viet Nam, 217-224.Richardson L.F., 1922. Weather prediction by numerical process. Cambridge University Press, Cambridge. Reprinted by Dover (1965, New York).Routray, Mohanty U.C., Niyogi D., Rizvi S.R., Osuri K.K., 2008. First application of 3DVAR-WRF data assimilation for mesoscale simulation of heavy rainfall events over Indian Monsoon region. Journal of the Royal Meteorological Society, 1555.Schumacher, R. S., C. A. Davis, 2010. Ensemble-based Forecast Uncertainty Analysis of Diverse Heavy Rainfall Events, 25. Doi: 10.1175/2010WAF2222378.Snyder C., Zhang F., 2003. Assimilation of simulated Doppler radar observations with an Ensemble Kalman filter. Mon. Wea. Rev., 131, 1663.Szunyogh I., Kostelich E.J., Gyarmati G., Kalnay E., Hunt B.R., Ott E., Satterfield E., Yorke J.A., 2008. A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus A., 60, 113-130.Tanaka M., 1992. Intraseasonal oscillation and the onset and retreat dates of the summer monsoon east, southeast Asia and the western Pacific region using GMS high cloud amount data. J. Meteorol. Soc. Japan, 70, 613-628.Tan Tien Tran, Nguyen Thi Thanh, 2011. The MODIS satellite data assimilation in the WRF model to forecast rainfall in the central region. VNU Journal of Science, Natural Sciences and Technology, 27(3S), 90-95.Tao S., Chen L., 1987. A review of recent research on East summer monsoon in China, Monsoon Meteorology. C. P. Changand T. N. Krishramurti, Eds, Oxford University Press, Oxford, 60-92.Tippett M.K., Anderson J.L., Bishop C.H., Hamill T.M., Whitaker J.S., 2003. Ensemble square root filters. Mon. Wea. Rev., 131, 1485.Thuy Kieu Thi, Giam Nguyen Minh, Dung Dang Van, 2013. Using WRF model to forecast heavy rainfall events on September 2012 in Dong Nai River Basin. The Third International MAHASRI/HyARC Workshop on Asian Monsoon and Water Cycle, 28-30 August 2013, Da Nang, Viet Nam, 185-200.Xavier, Chandrasekar, Singh R. and Simon B., 2006. The impact of assimilation of MODIS data for the prediction of a tropical low-pressure system over India using a mesoscale model. International Journal of Remote Sensing 27(20), 4655-4676. https://doi.org/10.1080/01431160500207302. Wang B., 2003. Atmosphere-warm ocean interaction and its impacts on Asian-Australian monsoon variation. J. Climate, 16(8), 1195-1211.Wang B. and Wu R., 1997. Peculiar temporal structure of the South China Sea summer monsoon. J. Climate., 15, 386-396.Wang L., He J., and Guan Z., 2004. Characteristic of convective activities over Asian Australian ”landbridge” areas and its possible factors. Act a Meteorologic a Sinica, 18, 441-454.Wang, B., and Z. Fan, 1999. Choice of South Asian Summer Monsoon Indices. Bull. Amer. Meteor. Sci., 80, 629-638.Webster P.J., Magana V.O., Palmer T.N., Shukla J., Tomas R.A., Yanai M., Yasunari T., 1998. Monsoons: Processes, predictability, and teprospects for prediction, J. Geophys. Res., 103, 14451-14510.Wilks Daniel S., 1997. Statistical Methods in the Atmospheric Sciences. Ithaca New York., 59, 255.Whitaker J.S., Hamill T.M., 2002. Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913.Wu G., Zhang Y., 1998. Tibetan plateau forcing and the timing of the monsoon onset over South Asia and the South China Sea. Mon.Wea.Rev., 126, 913-927.Zhang Z., Chan J.C.L., and Ding Y., 2004. Characteristics, evolution and mechanisms of the summer monsoon onset over Southeast Asia. J.Climatology, 24, 1461-1482.http://weather.uwyo.edu/upperair/sounding.html and http://tropic.ssec.wisc.edu/archive/