agung saifulloh majid1 2 , untung merdijanto abstract · station in accordance with the...
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ICAWS-2017 (Initiating automation and supporting migration from manual to automated measurements)
AUTOMATION OF SURFACE OBSERVING NETWORK IN BMKG
Agung Saifulloh Majid1, G.S. Budhi Dharmawan2, Damianus Tri Heryanto3, Untung Merdijanto4
Agency for Meteorology, Climatology, and Geophysics of the Republic of
Indonesia(BMKG)1234 Phone : (6221) 4246321, Facs : (6221) 4246703
[email protected], [email protected],
[email protected], [email protected]
ABSTRACT
Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG) is an Indonesian government agency responsible for providing a comprehensive meteorological information service regarding weather forecast information, early warning of severe weather, aviation and maritime weather information, and climate monitoring as well. In order to achieve those goals, BMKG maintains a network of surface observing stations (manual and automatic), radiosondes, wind profiler radars and weather radars installed across Indonesia.
In terms of surface observation, BMKG currently operates 141 surface observing stations, with 59 stations are registered to the Regional Basic Synoptic Networks (RBSN) and 19 stations are registered to Regional Basic Climatological Network (RBCN).The majority of the observation equipment used at those stations is still conventional-manual type, including mercury or chart-based instruments, which are difficult to be integrated automatically.
This paper describes BMKG’s efforts to modernize its observations
equipment and to integrate its surface observing stations network as had been set
out in the BMKG’s roadmap of surface observation network automation 2015 –
2019. It is expected that BMKG able to support the WMO policy in eliminating the
use of mercury-containing instruments gradually before 2020, and able to increase
its ability in supporting the implementation of the WMO Integrated Global Observing
System (WIGOS) objectives in the Regional Association (RA) V and other regional
and international activities.
Keywords: automation, surface observing network, integration
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1. Introduction
BMKG, as an Indonesian government institution that responsible for providing
any public weather-related information, currently operates weather and climate
observation network consisting of 120 meteorological stations, 21 climatological
stations/posts, 3 Global Atmosphere Watch (GAW), 409 Automatic Weather Station
(AWS), 44 Automated Weather Observing System (AWOS), 402 Automatic Rain
Gauges (ARG), 44 Radiosonde stations, 40 weather radar, and 3 Wind Profiler
Radar (WPR) installed throughout Indonesian region.
Among 141 BMKG’s surface observation, 59 stations are registered the
Regional Basic Synoptic Networks (RBSN), an agreed selection of surface
meteorological observing stations of the World Weather Watch (WWW)/Global
Observing System (GOS). Most of the observation equipment used in those stations
are still rely on manual-conventional instruments including mercury or chart based
instruments.
The use of manual-conventional instruments brings some limitations, those
are:
a. Operator/observer dependency, the need of observer attendance
while measuring weather parameter.
b. Observer subjectivity may affect the quality of measurement results.
c. Observing duration in a manned station depends on the number of
observer. The longer observation hours, the more staff needed.
d. The weather observation results cannot be directly/automatically
processed by a computer.
2. Automation Roadmap
The UNEP Minamata Convention on Mercury will enter into force
internationally in 2020, and all activities involving production and trading of mercury-
based instruments will be banned. Following the convention, WMO recommends
National Meteorological and Hydrological Services (NMHSs) to reduce or eliminate
the use of mercury-containing instruments.
In addition, International Civil Aviation Organization (ICAO) and International
Air Transport Association (IATA) regulation on dangerous goods also cause the
transportation for mercury-based instrument become more difficult. BMKG has
established an Observing Station Network Automation Roadmap until 2019, which is
implemented gradually in accordance with the available budget, in order to maintain
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a reliable and sustainable observation data by the use of non-mercury or automatic
instruments.
Table 1. The stages of the automation project
FUNDING STATION YEAR GRAND
TOTAL 2015 2016 2017 2018 2019
APBN*
BASIC 5 25 5 35
NON-BASIC 7 45 52
CLIMATOLOGY 21 21
STR-1** BASIC 25 25
NON-BASIC 8 8
Total 38 25 26 7 45 141 * State Budget
** Strengthening project in collaboration with Meteo France International (MFI)
Activities involved in the automation project are:
1. Provision of integrated grounding system and surge protector devises to
prevent equipment damages because of lightning strikes and voltage surges.
2. Rearrangement of met garden, e.g: ground leveling; cable ducting setup,
sensors siting and exposure;
3. Equipment replacement from manual/conventional to electronic/digital.
4. Provision of supporting facilities such as UPS, solar panels, and generator
sets, to ensure continuous observation and to prevent observation data
losses due to the lack of quality and quantity main power supply.
5. Communication network reconfiguration.
6. Adjustment of data format and metadata.
7. Designing client interface and monitoring application.
8. Parallel observation.
9. Standard Operating Procedure for system maintenance
10. Data Repository upgrade.
3. Implementation
The overall implementation of automation project for every year stage started
from document preparation, procurement phase, project execution, until system
maintenance, has a similarity with those are explained in F. Kuik, et.al (2016).
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2015 2016 2017
Figure 1. Automated station from 2015 to 2017
a. Year 2015
- Automation is carried out in 5 stations: Kualanamu, Palembang,
Surabaya, Manado, dan Sentani.
b. Year 2016
- Automation was conducted in 25 stations, those are:
1. Banda Aceh 14. Denpasar
2. Tanjung Pinang 15. Bima
3. Pekanbaru 16. Majene
4. Padang 17. Makassar
5. Jambi 18. Baubau
6. Pangkal Pinang 19. Labuha
7. Lampung 20. Ambon
8. Pontianak 21. Sorong
9. Cengkareng 22. Biak
10. Semarang 23. Wamena
11. Balikpapan 24. Timika
12. Palangkaraya 25. Merauke
13. Banjarmasin
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c. Year 2017
In this year, there are 22 stations will be automated:
1. Batam
2. Banyuwangi
3. Ruteng
4. Naha
5. Wamena
6. Tanjung Balai Karimun
7. Aek Godang
8. Cengkareng
9. Cilacap
10. Kerinci
11. Paloh
12. Serang
13. Tanjung Selor
14. Tanjung Redep
15. Kotabaru
16. Tuban
17. Kalianget
18. Larantuka
19. Nabire
20. Sintang
21. Putusibau
22. Ketapang
4. Meteorological Garden Rearrangement
This activity is established by rearranging the existing meteorological park at the
station in accordance with the requirements specified in the system design.
The rearrangement includes the following activities:
1. Re-siting of observation equipment. After a site survey, it was found that
there are several equipment that need to be relocated in order to get a better
exposure as recommended in WMO-8 document.
2. Improving ground leveling, since there are several sites that the ground
needs to be leveled first.
3. Installing concrete cable ducts to give an easy access for cabling
maintenance. The cable duct is made from U-Ditch concrete that needs to be
fabricated on the site because it's easier than transporting them from the
manufacturer to the site that sometimes is not possible due to the long
transportation time and the more complicated bureaucracy.
4. Replacement/reparation of the meteorological garden fences.
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An example of meteorological garden layout redesign can be viewed in Figure 2.
(a)
(b)
Gambar 2. Example of meteorological garden layout rearrangement:
(a) Before, (b) After
The new layout is made to accommodate the additional structures, like cable
duct, new mast, etc., and the need for parallel observation.
Figure 3 below, shows the transformation of the meteorological garden in
Kualanamu station from 2015 to 2016 condition.
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a. Kualanamu station, 2015 b. Kualanamu station, 2016
Figure 3. Example of meteorological garden transformation
5. Detail Specifications
5.1 Sensors
All the automated stations are equipped with sensors for sensing
parameters like wind speed, wind direction, temperature, relative humidity,
atmospheric pressure, rainfall, solar radiation, and evaporation. The sensor
specifications are shown in Table 2.
Table 2. Sensors specifications
No Parameter Sensor Accuracy Range Resolution
1 Wind Speed Ultrasonic ± 0.2 m/s 0 – 75 m/s 0.1 m/s
2 Wind Direction Ultrasonic < 2 ° 0 - 359.9 ° 0.1 °
3 Temperature Pt100 RTD Class F0
-40 s/d +85 °C ± 0.1 °C
4 Relative Humidity Capacitive
thin film
1,5%RH for 0 -
90%RH
0 – 100%
5 Atmospheric Pressure
Silicone Capacitive
+ 0.15 hPa 500 - 1100 hpa 0.1 hPa
6 Rainfall Tipping bucket
2%
0.2 mm
7 Solar Radiation Silicon
photodiode 100m
V/W/m2 0 - 2.000W/m2
0.4 – 1.1 µm
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No Parameter Sensor Accuracy Range Resolution
8 Evaporation Open pan
a. Water level
Pressure difference
0.4 mm 0 - 200 mm
b. Water temperature
Thermistor ± 0.03˚C -50 - +70 ˚C
c. Wind speed Cup + 0.5 m/s 0.4 - 55 m/s ≤ 0.1 m/s
The system specification was made to facilitate the use of different sensors
from different manufacturers, to keep the interchangeability and minimize the
conflict of interest during the procurement process.
5.2 Datalogger
Datalogger used in this project needs a supply voltage 10 – 24 V with power
consumption 0.5 - 0.7 W depending on the used mode. The Datalogger equipped
with an LCD display, 13 input, 6 output, and configurable virtual channel with an
easily adjustable measuring interval for single values per channel. The Compact
Flash Card ( CF Card) data memory provide a data storage buffer for 1 year. The
Datalogger also provides mobile and wireless data transfer via CF card, with cable
via interface RS232 or optional via GSM modem, telephone modem, radio modem,
or RS485.
5.3 Data Collection System (DCS)
Datalogger Application Software. It has ability as explained below:
- Store raw data of observed weather parameters in the database. - Display the results of processed data - instantly, hourly and daily
interval - in a graphical display or in a statistical tabulation format on each observed/measured weather parameter.
- Able to display and store data parameters 5 minutes, 10 minutes, 15 minutes, 30 minutes, 60 minutes, and 24 hours each day.
- Send data through communication channels (BMKG GTS) as needed automatically.
- Able to display the sensor condition. - Provide alert if wind speed exceeds 20 knots, rain intensity is larger
than 40 mm in 2 hours, air humidity is smaller than 65% and air
temperature is greater than 32˚ or can be set as needed.
Observation Application Software, has the following functions:
- Process data, display, and create reports of routine observations in
SYNOP (ME 48 and ME 45), WXRev, METAR, and SPECI code as
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per WMO standards (weather parameters which are not generated by
the tool can be inputted manually by operator/observer).
- Output code should be sent to Computerized Message Switching
System (CMSS) or BMKGSoft server.
- Observation data is sent to AWS Center server
(http://172.19.1.120/awscenter) according to the format of database
structure automatically.
- Send raw data files compressed (zip, rar, or tar) and processed data
automatically through communication channels (BMKG GTS)
available as needed.
- Display reports SYNOP (ME48 and ME45), WXRev, monthly in .xls
and .pdf format.
- Download raw data (weather parameter) from datalogger and save it
in CSV format and database.
- Connection with datalogger can be through Serial, TCP, or UDP.
- Numerical and graphical views (such as curves and histograms).
- User-friendly software running stand-alone or via a web browser.
- The software can synchronize the internal clock (RTC) Datalogger
with NTP server (ntp.bmkg.go.id) automatically.
- Run on open source platform (Linux).
Screenshots sample of the local display application is shown in Figure 4.
Figure 4. Local Display Screenshot
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Figure 5. Detail display screenshot in observation room
The application interface enabling the observer to enter the data of
unautomated parameters, such as visibility and cloudiness, and check the data of
the weather parameters whether within tolerable limits or not.
6. System Data Flow
Figure 6 shows the data flow from observation equipment to database center
at BMKG headquarter. In this system there are still two parameters, visibility, and
cloudiness, which should be entered manually through the application on the local
server by the observers who also functions as data Quality Controller (QC) level I.
The data in the form of the SYNOP, WXREV, and METAR code is then sent
to the Center for Database via the VSAT communications network with 10 minutes
time interval. Then the data will be validated and standardized by the Center for
Database, which also functions as QC level II, and stored in the National Data
Repository.
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Figure 6. Data Flow
7. Parallel Observation
The WMO recommends the need for parallel observations, at least 2 years,
in case of system migrations from manual to automatic or the changes of the
observation location, to ensure the continuity and homogeneity of the climatological
data. For that reason, BMKG General Director also had issued an instruction for
conducting such parallel observations as a basis for evaluating the effect of changes
emerging from the implementation of this automation program.
b. Evaporation b. Temperature and Relative Humidity
Figure 7. Parallel Observation
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A sample of parallel observation results, depicted in Figure 8, shows the
difference value for several parameters between manual and automatic
measurement at Kualanamu station from April 2016 until April 2017.
There are still a lot of methods and formulas that can be used to analyze the
parallel measurement results but will not be discussed further in this paper.
(a)
(b)
(c)
Figure 8. Example of measurement difference between automatic and manual parallel
observation; (a) Temperature difference, (b) RH difference, and (c) Pressure difference
-5
-3
-1
1
3
5
1 1001 2001 3001 4001 5001 6001 7001 8001 9001
T au
to -
Tm
an (o
C)
Data number
Temperature Difference, Kualanamu Station
Average = 0.2242
-15
-10
-5
0
5
10
15
1 1001 2001 3001 4001 5001 6001 7001 8001 9001
RH
auto
- R
Hm
an (%
)
Data number
RH Difference, Kualanamu Station
Average = -3.6084
-5
-3
-1
1
3
5
1 1001 2001 3001 4001 5001 6001 7001 8001 9001
P au
to -
Pm
an (m
b)
Data number
Pressure Difference, Kualanamu Station
Average = 0.08133
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8. Consequences of automation
The automation project brings some consequences that some of them should
be addressed carefully, some of them are:
a. The role change from observers become quality controllers.
b. Field calibration should be taken intensively since the electronic
equipment is more fragile than the manual/conventional one. Therefore,
BMKG has decentralized the calibration authority of the station
observation’s equipment to the BMKG Regional Office.
c. The use of paper for charting or reporting can be reduced significantly,
contributes to keeping our world clean and green.
9. Challenges
- Indonesia is an archipelagic country with its unique geographical condition
needs a special attention mainly in mobilizing the required materials in this
automation program to ensure that all plans will run on schedule.
- The need for capacity building capabilities on maintenance human resources.
The increasing use of electronic equipment requires more skilled technicians,
both quality and quantity, that are currently still limited.
- The amount of allocated funds provided by the State Budget that directly
affects the project implementation.
- The availability of adequate electricity is still a problem, especially for eastern
Indonesia, because of its significant influence on the durability of electronic
equipment.
- The capacity and quality of communication network also need to be
addressed seriously, especially between stations to the headquarter, to
minimize the potential lost of observation data.
10. Conclusion
a. Automation of 63 observing station had been carried out until the end of
2016.
b. Automation of 22 observing station is being carried out in 2017.
c. Parallel observation is established for all stations involved in this project.
11. Reference
- F. Kuik, et.al, Requirement Specifications for SYNOPTIC Observation
Networks, 2016
- WMO-No. 8-16, Guide to Meteorological Instruments and Methods of
Observation: (CIMO guide), WMO, provisional 2014 ed., approved by
CIMO-16.
- Instruction of General Director of BMKG on parallel observation, 2014