Kennedy Omondi Obong o. Grad. Eng. ERB/IEK Kenya Meteorological Department ICT Division P.O. Box G.P.O NAIROBI, KENYA Tel No:

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Modernisation of Surface Observations Network in KENYA 7/15/2010 1

Presenter Kennedy Omondi Obong o. Grad. Eng. ERB/IEK Kenya Meteorological Department ICT Division P.O. Box 30259-00100 G.P.O NAIROBI, KENYA Tel No: 254-20-3867880-5 Ext 2071-2 Cell Phone No: 254-722857807 E-mail: kobongo@meteo.go.ke kobongo33@yahoo.com 7/15/2010 2

ABSTRACT In order to modernise surface observation technologies and systems, the Kenya Government has undertaken a milestone of stride in the installations ti of Meteorological, hydro-meteorological and oceanic observation technologies & systems. This paper focuses on modern automatic observational systems that are state of the art technology that provide realtime data. The systems have improved the temporal resolution of observed weather data but, hitherto, provide spatial resolution meteorological data. A cluster of 45 automatic surface observing systems have been installed but, the target is to install over 200 stations country wide by 2015. 7/15/2010 3

ABSTRACT Continues The triumphant entry of these systems has notably resulted in improved data accuracy, quality, availability, and efficiency in transmission to the collecting centre/nairobi RTH. From statistical comparisons, we deduced that more than 98%, of the observations are consistent and do correlate well with human manned observation stations. Embracing these technologies convincingly demonstrates that staffs IT skill levels have improved considerably by more than 20%. However, some teething challenges are also implicitly appreciated and will come out clearly in the paper. 7/15/2010 4

Keywords Sustainability, GSM/GPRS, Automatic Observational technologies (AWS, AWOS, Hydro-met, Tidal gauges, RG ), Technology transfer, ICT, Special and Temporal Resolutions 7/15/2010 5

Historically; BACKGROUNG -First KMD Automatic Surface Observational Systems installed mid 1990s. -Biggest challenge, g, Telemetry-System y time could not synchronise so has to lock to the satellite allocated slot for transmission and thus upload data to necessitate further communication and distributions. -Otherwise, monthly data would be retrieved by directly hooking a laptop computer to the system and down load data manually. Data then, had to undergo various cumbersome processes before stored. 7/15/2010 6

BACKGROUNG - cont The introduction of GSM/GPRS communications technology in Kenya at the beginning of this millennium was an eye opener for the implementations of several technologies including Automatic Observational Systems. 7/15/2010 7

Introduction The Automatic observational System -highly modular in design and architecture What are the advantages? Troubleshooting, Repair and Maintenance easier. Saves on system down time. Minimises/reduces on data lost during maintenance/repair. ep Scalability another characteristic of this system. Sensors can be added to the system without compromising ii on quality of the data acquisition. iii Self calibrating and operate in automatic mode. 7/15/2010 8

AWS BLOCK DIAGRAM TELEMETRY DATA LOGGER Functions 1. Acquire, Process, POWER UNIT 2. Archival SENSORS Figure 1 7/15/2010 9

REMOTE AUTOMATIC GSM/GPRS SYSTEM NETWORK AWS CENTRAL BASE SYSTEM SOLAR PANEL APPLICATION SOFTWARE COMMUNICATES TO UPDATE THE SYNOPTIC USER INTERFACE WITH NEWEST DATA DATA Fig 13: Observer Window LOGGER GSM Modem GSM Network (900/1800MHz) GSM Modem AT/RH RG/TB WS/WD PYRO BARO Figure 2 BASE STATION COMPUTER 7/15/2010 10

SOME AWS SENSORS SO S RGAUGE AT/RH EVAPORATION PAN BAROMETRIC PRESSURE WIND ANEMOMETERS SOLAR RADIATION NET RADIATION SUNSHINE HOURS 7/15/2010 11

Data logger The data acquisition system, heart of the remote monitoring and control system. Samples, processes, measures and logs the sensors as per the Setup configuration. Based on a microprocessor controlled system environment. 7/15/2010 12

Collecting raw data. Sensors In engineering terms, coverts the process variables in different energy forms to electrical energy then signal conditioned Measured elements -Air temperature, Relative humidity, Baro pressure, Rain, Wind speed and direction, Solar radiation, Soil moisture, Evaporation etc. 7/15/2010 13

Telemetry Communication ability of the system to relay data in real time through available communication media. Supported; satellite, radio, fixed line telephony, wireless through GSM/GPRS 7/15/2010 14

Power The life line of almost all blocks. AC power is used were available, but since most of the stations are installed in remote areas solar panels are used to charge battery and thus supply the systems. Areas with AC power still have solar panel connected as a redundant alternative. 7/15/2010 15

AWS distribution in Kenya Moyale Lodwar Wajir Marsabit Kitale Eldoret Meru Kakamega Nyahururu Kisumu Embu Garissa Nyanyuki Kericho Nakuru Nyeri Kisii Narok Nairobi Thika Makindu Lamu Figure 3 Voi Msabaha 7/15/2010 16

Where KMD Automatic System? Meteorological Network distributed nationally 37 Synoptic stations ( 24 AWS - Automated) 17 Automatic Hydro-met Systems 3 River Gauging-Automated Radar based Water Level 7/15/2010 17

Conts 10 Airports ( 3 AWOS + 2 up c- Automated ) 4 Automatic Tidal Gauges in India ocean 7/15/2010 18

From figure 3, the systems have improved the temporal and spatial resolution of observed weather data in particularly in the western part of the county along the Nzoia basin that is currently well cover and therefore e e predictions have been 90 percent accurate. In fact from these systems data, the disastrous floods that have caused numerous calamities over the years were averted thanks to prompt real time information for flood forecast, earlier warning and mitigations alert issuance. 7/15/2010 19

The country spatial resolution of observed weather data still remains a challenge thus calling for more efforts and resources to be mobile to alleviate this trend. From statistical comparisons, we deduced that more than 98%, of the observations are consistent and do correlate well with human manned observation stations. 7/15/2010 20

The system comes with WMO message formats of SYNOP, METER, SPECI, BUFR, CREX, reports, graphs, exporting, importing, printing, troubleshooting tools and many other capabilities. Thus Manual entries made easy. The system is also observer interactive, it allow an observer to enter weather phenomenon and information. This has made work easier at station levels and thus work that was previously being done by three people p is now comfortably being done by one person and more interesting just by a lick of a mouse. 7/15/2010 21

BOTTLENECKS Maintenance Sustainability Technology transfer and capacity building GSM/GPRS S service providers Large data Volumes Vandalisms 7/15/2010 22

Maintenance Sustainability The recommended routine and preventive maintenance/repair should be performed quarterly per year, but being a developing country with many financial constraints, sometimes, a year passes without maintenance/repair being carried out. However, should it be done, it is a curative maintenance or when the system has completely failed. 7/15/2010 23

Maintenance Sustainability Thus, sustainability is one of the greatest challenges. Stocking of recommended d spare pairs for maintenance/repair and computer virus are also notable challenges. 7/15/2010 24

Technology transfer and capacity building Technology transfer and capacity building task was first difficult and was meet with resistance. However, as days went by the staff started appreciating the technology suffice to say that some of them even took a bold step of registering g themselves to IT teaching institutions. To day, considerable numbers of staff in the out stations are computer literate. Embracing these technologies convincingly demonstrates that staffs IT skill levels have improved considerably by more than 20%. In all out stations officers were trained on the away to interact with the systems and more so the computer receiving stations. 7/15/2010 25

GSM/GPRS service providers GSM/GPRS service providers have also contributed negatively to data exchange. Circuit switched data (CSD) used Poor signal strength or no coverage in some parts of the country. Another difficulty is in remote login via GSM network. The communications often hangs while interrogating the remote station. Lastly, the cost of GSM/GPRS service is still exorbitant. 7/15/2010 26

Large data Volumes The Automatic Observational Systems provide real-time data at frequency that is determined by the user of the system. For Meteorological purposes, we have configured our system to log data every 10 minutes. This is definitely large volumes of Data. Currently, we are using access database with storage capacity of 2GB. 7/15/2010 27

Vandalisms Last but not least, 10 percent of all the installed Automatic Observational Systems have had solar panel vandalized so far. 7/15/2010 28

NZOIA RIVER Hydro-met network -figure 4 MT. ELGON CHERANGANY HILLS MAU WATER TOWER Figure 4 FLOOD PLAIN LAKE VICTORIA 7/15/2010 29

Figure 5 Automatic Telemetric Hydromet Stations WEBUYE (Automatic Telemetric) SEMOGERE Kaimosi FTC RWAMBWA 7/15/2010 30

AWS INSTALLATION AT LODWAR- Figure 6 7/15/2010 31

PRODUCT - Forecast chart - Figure 7 700 7.00 00 0.0 6.00 0.47 1.49 3.09 4.76 7.22 0 1.13 2.31 2.01 10.48 5.0 10.0 5.00 4.57 4.54 4.65 15.32 16.32 16.6 4.18 4.63 4.00 372 3.72 22.54 3.81 3.15 24.91 3.45 3.33 3.00 2.73 2.93 2.83 2.6 2.83 2.58 2.45 2.00 15.0 20.0 Water Level (m) Areal Rainfal ll (mm) 25.0 30.0 35.0 40.0 1.00 45.0 0.00 50.0 26-Oct-08 27-Oct-08 28-Oct-08 29-Oct-08 30-Oct-08 31-Oct-08 01-Nov-08 02-Nov-08 03-Nov-08 04-Nov-08 05-Nov-08 06-Nov-08 07-Nov-08 08-Nov-08 09-Nov-08 10-Nov-08 11-Nov-08 Rainfall Forecast Level Water Level Flood Alert Flood Warning 7/15/2010 32

Observed and Predicted River levels at Rwambwa RGS 6 Observed Predicted 5 4 3 2 River level (m) 1 0 1 Sep 08 6 Sep 08 11 Sep 08 16 Sep 08 21 Sep 08 26 Sep 08 1 Oct 08 6 Oct 08 11 Oct 08 16 Oct 08 21 Oct 08 26 Oct 08 31 Oct 08 5 Nov 08 10 Nov 08 15 Nov 08 20 Nov 08 7/15/2010 33

CONCLUSIONS In a nutshell, Automatic Observational system is the technology that envisages assuring availability of meteorological data for posterity development. The triumphant entry of these systems has notably resulted in improved data accuracy, quality, availability, and efficiency in transmission to the collecting centre/nairobi RTH. Installation of these systems in remote area will definitely improve on spatial data resolution and reduce manual observational constraints that are experienced in remote areas. 7/15/2010 34

God G d bless and inspire i this technology in developing countries and world over. 7/15/2010 35

THANK YOU FOR YOUR TIME 7/15/2010 36