Implementation of WIGOS related programs in Indonesia
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- Marcus Baldwin
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1 Preparatory Meeting for WMO Joint RA II/RA V Workshop on WIGOS for DRR Jakarta / April 2015 Implementation of WIGOS related programs in Indonesia By : Indonesia Agency for Meteorology Climatology and Geophysics (BMKG)
2 Surface based Observing system
3 BMKG Surface Observation Network
4 DISTRIBUTION OF AUTOMATIC WEATHER STATIONS / AWS (217 SITES) Weather parameters measured : wind, air pressure, relative humidity, temperature, rainfall, global solar radiation
5 Automatic Rain Gauge (ARG) Sites ARG ARG SMPK ARG.BMKG = 178 sites = 28 sites = 7 sites
6 Main Parts of ARG and AWS AWS &Rain Sensor Data Logger Modem Communication Power supply for every single parts
7 ARG and AWS Data Communications RS 232 Mobile Modem GPRS/SMS/FTP Web HandPhone Server (aws-center) RS 485 PC Monitor ARG s AWS s USB Notebook Internet Web-based Monitoring
8 (Marine Met. Stations, VOS, Offshore Oil Platform/Rig, Ports)
9 Voluntary Observing Ships (AWS on board commercial ships) 8
10 Existing BMKG Doppler Weather Radars ( ) Existing : C/X Band single pol ( ) Installed in 2015 (X Band dual pol) Optimum Obs. Range : C Band = 150 km X Band = 50 km 10/03/11
11 Radar Data Transmission to BMKG Head office
12 Centralized Radar Radar Data Data Server Server BMKG Centralized Radar Data Processing (HDSS System) WEB DISPLAY Radar Radar Data Data QC QC NetCDF Storm Storm Tracking Tracking Attributes Attributes NetCDF Formatting Formatting Clean Clean up up Polar Polar Processing Processing NetCDF 3 D 3 D Mosaic Mosaic VPR VPR MAPLE MAPLE QPF QPF FFPA FFPA Products Products & Server Server QPEA QPEA Data Data Coversion Coversion NWP, NWP, AWS, AWS, Rain Rain gauges, gauges, Satellite Satellite processing processing Satellite, Satellite, NWP, NWP, AWS, AWS, Rain Rain Gauges Gauges Planned for next improvement FFPA : Flash Flood Prediction Area QPEA : Quantitative Precipitation Estimate Accumulation
13 Radar Data QC Developed at NSSL Apply to each radar Fully automated in real time NN Textural feature Horizontal/vertical gradients All moments Mitigates non precip echo Removes artifacts KAMA KTLX
14 Nowcasting product 1 hour up to 4 hours ahead (MAPLE forecast) MAPLE (McGill Algorithm for Precipitation Nowcasting Using Lagrangian Extrapolation) : An algorithm for prediction of the movement of radar echoes and rainfall accumulation. MAPLE examines a time sequence of up to the past 2-hours of radar mosaic data to determine the movement and evolution of storms and their radar echoes. The algorithm was developed by McGill University Canada.
15 Nowcasting products from BMKG Doppler weather radars
16 Satellite based Products
17 Hotspot / Firespot Detection for Forest fire monitoring : Cumulative detected hotspot for October 2014 (as of 23 Oct. 2014)
18 Daily Hotspot / Firespot Detection : 23 Oct. 2014
19 MTSAT Satellite Imagery : Eruption of G. Kelud Feb (10 minutes interval/rapid scan)
20 Surabaya Radar Imagery : Eruption of G. Kelud Feb (10 minutes interval/rapid scan)
21 Data Rescue and Database Management
22 DiDaH DiDaH (Digitisasi Data Historis) was a cooperation project of BMKG KNMI ( ) DiDaH was aiming at the digitization of historical Indonesian climate data that was recorded in the period and more recent BMKG climate data from the period 1970 present. All climate data time series that are newly digitized or obtained from observation have to be checked for validity and possibly corrected for known defects. For the historical data, that was digitized in the DiDaH framework, this QC, validation and correction was done at KNMI. For the BMKG non digitized data from will be digitized and entered in the future into the operational SACA&D system at BMKG (QC, validation and correction will be done by BMKG).
23 List of Scanning daily data of Batavia List of Scanning daily data of Batavia Daily Data Batavia some parameters from and magnetic data
24 Scanning of Monthly Data of Indonesia from
25 Scanning of Secondary stations about 73 stations
26 RESULT OF DATA DIGITIZATION A. Batavia Data Hourly for some parameters : PPP, TAV, BB, BK, HAV, Tension of the atmosferic vapour, precipitation, WD/WS: ; ; ; ; ; ; B. Precipitation Data : ( data daily rainfall ); digitized by KNMI and BMKG ( data daily rainfall ) digitized by Metropolitan Tokyo University ~ 1958 ( data monthly rainfall ) digitized by BMKG (Database center and Climatology Center staff and Taruna AMG)
27 Data Digitization in Digitized by Database center staff and Climatology Center staff. ( 2 years finished ). Data Batavia : Year 1883 ( 368 pages ) Secondary Stations digitized by Taruna AMG. : 4 Books was Finished. Number station : 3400 ~ 3700 Observation Stations Batavia Daily data ( All Parameters ) Rainfall Monthly Data : Magnetic Data ( )
28 The Indonesia data position in 2014
29 BMKG Data Acquisition (past) WEAKNESS : Poor data access Un validated Un standardized format No data integration
30 BMKG Data Acquisition (near future) ADVANTAGES : Faster data access Validated database Standardized format Data integration
31 SACA & D (Southeast Asia Climate Assessment & Dataset)
32 SACA&D Overview 1 Goal : SACA&D offers science based climate services for assessing observed changes in climate extremes in the Southeast Asian region and aims to serve stakeholders from e.g. the food security sector. These services rely on high quality observational data sets provided by the participants. Participants : 23 National Meteorological and Hydrological Services, observatories and universities mainly from Southeast Asia. Coordination : Jointly coordinated by the Badan Meteorologi, Klimatologi, dan Geofisika (BMKG, Indonesia) and the Royal Netherlands Meteorological Institute (KNMI, The Netherlands).
33 SACA&D Services and Products : SERVICES : Data gathering (long term daily observational series from met. stations) Archiving and storage in a centralized relational database QC and homogeneity checks Analysis (calculation of indices, particularly related to climate extremes) PRODUCTS : Daily data set built up from 5914 series of obs. for 10 essential climate variables (incl. T and RR) observed at 4065 meteorological stations in 15 countries (34% publicly available) Meta information on stations and time series homogeneity Maps and plots for changes in extremes in the form of trends, anomalies and climatologies for 44 indices
34 Reresentative of WMO (Dr. Peer Hechler) with DG of BMKG (President of RA V) International Workshop on Digitization of Historical Climate Data (Citeko Bogor, April 2012) Attended by some ASEAN countries and some International speakers, opened by Director Generalof BMKG and Representative of WMO, Dr. Omar Baddour. International ASEAN SACA&D Conference & Workshop ( IASCW 2014 ) Citeko,Bogor / May 2014.
35 Some Recomendations from IASCW 2014 : 1. A good sense for partnership on equal level is a prerequisite for successful collaboration. The RCC concept provides a platform for such partnership. (SACA&D as an RCC tool, plans to implement RCC Network for ASEAN ). 2. Exploit all channels including WMO and regional mechanisms to promote the sharing of as much data appropriate within SACA&D concept. 3. BMKG invites other countries in the South East Asia region to participate in SACA&D while respecting the data policies of the participating countries. 4. Agree on a time specified for maintenance and regular update cycle for the SACA&D system, for example once a month, and as a future step to post a log file with all the system updates required and done on the web.
36 Country visit Step I ( 2013 ) : Thailand Malaysia Singapore Philippines Brunei Darussalam 3. Countries Visit Country Visit Step II ( 2014 ) : Timor Leste ( October 2014 ) Cambodia ( November 2014 ) Viet Nam ( November 2014 ) Myanmar ( November 2014 ) Lao PDR ( November 2014 )
37 BMKG SUMMARY OF VISIT to 5 ASEAN COUNTRIES : The TMD has 72 stations and data from 24 stations already ingested in SACA&D The TMD support SACA&D existence and would add the number of the station if other ASEAN countries agreed Data Policy for SACA&D of other ASEAN Countries The MSS Singapore given a support to SACA&D and underline the importance of operational sustainability of SACA&D. The MMD Malaysia still needs to give approval and want to learn more about SACA&D. Brunei Darussalam is still waiting the decision from their DG. The PAGASA Philippines gives full support to SACA&D and will provide non downlodable high resolution data for SACA&D. The BMKG Indonesia has 173 Observation stations and data from 60 stations has been ingested in SACA&D and in progress to ingest 173 stations. BMKG would continue roadshow to the rest 5 other ASEAN countries (Myanmar, Vietnam, Lao PDR, Cambodia and Timor Leste) in 2014.
38 BMKG Modernization through Strengthening BMKG Climate and Weather Service Capacity Project
39
40 AWOS Modernization on Observation System Surface Observation Network Wind Profiler Voluntary Observing Ships Upper Air Observation Network Lightning Detection Networks Hydrogen Generator for Upper Air Balloon Inflation
41 Modernization on Integrated Dataflow...for the world class BMKG...
42 Modernization on IT Infrastructures Weather Analysis and Forecasting Tools Central Information and Processing System High Performance Computing System
43 Transformation of Manual Production System towards Digital Forecasting System & Automatic Production
44 I. Benefit of the Project : 1. Enhance the effectiveness of BMKG 2. Contribute to regional and WMO programme 3. Raise the institution s profile and develop its recognition by the public 4. Automate and boost production towards economic sectors 5. Increase BMKG s visibility and its relations with stakeholders...for the world class BMKG...
45 II. Implementation of Digital Forecast &Automatic Production Concepts Why Digital Forecast??? Automatic production system and dissemination All products in digital format Information products nationally integrated Mass production Comply with CAP WMO standard Major inputs for derived products for public and media (TV System, Visumet, Website)...for the world class BMKG...
46 III. Digital Forecast system : Meteo Factory...for the world class BMKG...
47 Main Modul Model guidance Access by Province Validasi Prakiraan per wilayah Input Data Prakiraan Forecast technical guidances:...for the world class BMKG...
48 IV. Improved Services through Digital Forecast (1) a. Enhance Graphical Elements: Weather symbols (extracts) Maps rendering...for the world class BMKG...
49 Improved Services through Digital Forecast (2) b. Web based based Products Dissemination ( meteo.bmkg.go.id):...for the world class BMKG...
50 Improved Services through Digital Forecast (3) c. Products Diversification :...for the world class BMKG...
51 Improved Services through Digital Forecast (4) d. Production of Specific Products for Specific Users Road operations Railway Operations...for the world class BMKG...
52 Port operations:...for the world class BMKG...
53 Marine Tourism: Fishing activities:...for the world class BMKG...
54 Tourism:...for the world class BMKG...
55 Agriculture:...for the world class BMKG...
56 V. Current Available Automated Products : A. Daily Precipitation Analysis B. Daily Maximum Temperature C. Daily Minimum Temperature D. Daily Mean Relative Humidity...for the world class BMKG...
57 E. Daily Forecast Products National:
58 F. Daily Forecast JABODETABEK
59 ...for the world class BMKG...
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