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Published byCollin Robinson Modified over 8 years ago
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Presnted by suratno@bmkg.go.id R & D Research Center METEOROLOGY INDONESIA
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OULINE R & D ORGANIZATION AND RESPONSIBILITIES CURRENT WEATHER PREDICTION MODELLING ACTIVITIES SEA STATE ANLYSIS AND FORECASTING WRF-EMS VALIDATION CCAM APLICATION FOR MOS DEVELOPMENT
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R & D ORGANIZATION AND RESPONSIBILTIES BMKG DIRECTOR GENERAL R & D Director (Dr. Masturyono) Meterological Division Climatological Divison Geophisical Divison Administration R & D related seismisity, earthquake and Tsunami R & D related climate analysis and prediction, and air qualty R & D related wetaher and ocean analysis & forecastng
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CURRENT WEATHER PREDICTION Other Center’s NWP Products TLAPS, Arpege and etc CCAM 27 km outputs run in BMKG (GFS forcing)
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MODELLING ACTIVITIES SEA STATE ANALYSIS AND FORECASTING Existing : WINDWAVES-05 Type : LAM, Deep water, 2nd generation Boundaries : land =0, no energy trasnfer for open ocean Usage 1 : regular basis wave analisis & forecasting since 2005 & high wave warning since Jun, 2007 Input: GFS 10 wind 0.5 deg. in resolution Output : 6 hourly forecast up to 168 hour : weekly forecast Usage 2 : Climate Studies, forcing NCEP FNL 1 deg. Input : NCEP FNl 1. deg Output : monthly and seasonal - Average Hs - Average Highest Hs, and highest Hs - Hig waves (Hs > 2 m) frequency
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DECEMBER JANUARY FEBRUARY 0 5 10 20 30 40 50 60 70 80 90 > (percent)
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MARCH APRIL MAY 0 5 10 20 30 40 50 60 70 80 90 > (percent) CLIMATE STUDY
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JUNE JULY AUGUST 0 5 10 20 30 40 50 60 70 80 90 > (percent)
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SEPTEMBER OCTOBER NOVEMBER 0 5 10 20 30 40 50 60 70 80 90 > (percent) CLIMATE STUDY
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MODELLING ACTIVITIES SEA STATE ANALYSIS AND FORECASTING CURRENT DEVELOPMENT 2012 – 2014 WaveWatch III Global & Regional domain operate once a day using GFS 0.5 deg forcing MRI III under study WRF 10 m wind plan to be or regional after validation
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MODELLING ACTIVITIES WRF- EMS (2012 -20014) VALIDATION METODE Boudary and initial condition : GFS 0.5 Step 1 # : Various convection schemes test for higher resolusion regional Indonesian domain Step 1 # : Each schemes evaluated using rason/ rawind sonde, pibals and ground observation Step 3 # The best Scheme will be selected for operational testing Three schemes has been tested but eavaluation not yet finished
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MODELLING ACTIVITIES CCAM APLICATION FOR MOS DEVELOPMENT (2011 -2014) (Joint reseacrh BMKG & Surabaya Institude Tectonology WHY MOS ? TARGET AREA : Jabodetabek (Jakarta and serounding) MOS Post – Processing NWP Reduce NWP bias Aplicable for prediction of unpredicted vaiable by NWP such as visibilty, thunderstorm
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CCAM BIAS CCAM (TMAX, TMIN CCAM) Outputs VS observation CCAM (RH) VS observation
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= variable predictant at time t = variables predictor at time t t Model Output Statistics (MOS)
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NWP Output Curse of Dimentionality High dimensional BIAS Reduce the dimension of predictor variables Model Output Statistics (MOS) 15 NWP Dimension Reduction MOS Persuit ProjectionPersuit Projection regresion
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CCAM AREA Model Output Statistics (MOS) AREA OF INTERST
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Model Output Statistics (MOS) AREA OF INTEREST
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Determining NWP Domain Grid Figure 1. The Position of Observation Station on 3x3 Grid
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In Sample (01/01/2009 – 31/10/2010) Out Sample (01/10/2010 – 31/12/2010) Daily NWP Output Tmax-obs Tmin-obs Daily average RH-obs Respon Variables Tmax-NWP Tmin-NWP Daily average RH-NWP Predictor Variables Maritim Tanjung Priok Cengkareng Curug Dermaga Locations Model Output Statistics (MOS)
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Results of prediction using out of sample data Fig. 1 Tmax, Tmin and RH Mos prediction for Tanjung Priok versus Observation Fig. 2 Tmax, Tmin and RH Mos prediction for Curug versus Observation
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Results of prediction using out of sample data Fig. 3 Tmax, Tmin and RH Mos predictions for Cengkareng versus Observation Fig. 4 Tmax, Tmin and RH Mos prediction for Curug versus Observation
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Results of prediction using out of sample data Fig. 3 Tmax, Tmin and RH Mos predictions for Cengkareng versus Observation Fig. 4 Tmax, Tmin and RH Mos prediction for Curug versus Observation
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PERCENTAGE IMPROVAL
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THANK YOU
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