Presnted by R & D Research Center METEOROLOGY INDONESIA

OULINE  R & D ORGANIZATION AND RESPONSIBILITIES  CURRENT WEATHER PREDICTION  MODELLING ACTIVITIES  SEA STATE ANLYSIS AND FORECASTING  WRF-EMS VALIDATION  CCAM APLICATION FOR MOS DEVELOPMENT

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

CURRENT WEATHER PREDICTION Other Center’s NWP Products TLAPS, Arpege and etc CCAM 27 km outputs run in BMKG (GFS forcing)

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

DECEMBER JANUARY FEBRUARY > (percent)

MARCH APRIL MAY > (percent) CLIMATE STUDY

JUNE JULY AUGUST > (percent)

SEPTEMBER OCTOBER NOVEMBER > (percent) CLIMATE STUDY

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

MODELLING ACTIVITIES  WRF- EMS ( ) 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

MODELLING ACTIVITIES  CCAM APLICATION FOR MOS DEVELOPMENT ( ) (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

CCAM BIAS CCAM (TMAX, TMIN CCAM) Outputs VS observation CCAM (RH) VS observation

= variable predictant at time t = variables predictor at time t t Model Output Statistics (MOS)

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

CCAM AREA Model Output Statistics (MOS) AREA OF INTERST

Model Output Statistics (MOS) AREA OF INTEREST

Determining NWP Domain Grid Figure 1. The Position of Observation Station on 3x3 Grid

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)

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

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

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

PERCENTAGE IMPROVAL

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