Available data and products for Agricultural purpose at the National Meteorological Agency of Ethiopia NSF-PIRE KICKOFF CONFERENCE, JULY 11-12 DELANO HOTEL, BAHIR DAR By Melesse Lemma National Meteorological Agency of Ethiopia, email:- mellemma2001@gmail.com, cell phone:- 0921-238812
Content • Introduction – Historical perspectives • Meteorological data observation systems in Ethiopia – Surface Observations, Automatic Observation System, Upper air Observation System, Air port weather monitoring systems, Remote sensing and Air pollution • Data Acquisition system (real and delayed data) • Data management system • Method of dissemination • Challenges
Historical perspectives The first meteorological stations were established in the 19 th century by • missionaries and explores • In 1890 and 1896 weather stations were established at Adamitulu and Gambella by the Italians. • During the five years (1936-1941) Italian invasion – 192 stations were established in Ethiopia • Since 1951 for the purpose of flight operations 495 aeronautical and climate stations were established. • After the establishment of NMSA (1980), the total number of stations have substantially increased to 1200; but later the number of stations dropped to 548. • The total number of stations has now rebounded and is more than 1200 • In the world and in our country as well people use different technologies and instruments to make meteorological observations
Meteorological data observation in Ethiopia For the purpose of collecting meteorological data NMA has deployed surface (manned and automatic), upper air, satellite, air port (manned and automatic stations) – Manned Surface Observing Stations – Synoptic, Indicative, Ordinary and Precipitation station – Automatic Weather Stations – Upper Air Stations • Radio sonde and Pilot Balloon – Satellite Data Receiving Stations – Air port stations – mainly for air navigation • Sadis and AWOS – Meteorological Radar – Air pollution station – Lightning detection network - yet to come
UOS Manned stns AWOS Satellite AWS Radar Air pollution
Manned SOS distribution in Ethiopia – as of 2012 Indicative Synoptic Ordinary Precipitation Station No. Type Synoptic/GTS 18 Indicative 172 Ordinary 546 Precipitation 418 • Manual observation • Mostly installed in places accessible at car • Sparse over low land and rural areas • Maintaining them need high cost
Meteorological elements recorded at manned meteorological stations No. Meteorological Elements Unit of Time /freq. of Observing measurements observation (LST) station 1 Rainfall millimeters 09 All 2 Maximum Temperature o C 18 Except pre. o C 3 Minimum Temperature 09 Except pre. o C 4 Dry Bulb Temperature 5 observation ( 06, Syn. and Ind. 09,12,15,18) o C 5 Wet bulb Temperature Syn. and Ind. per day at 6 Relative Humidity % Syn. and Ind. indicative station 7 Sun shine duration Hours and some Syn. and Ind. synoptic stations 8 Wind run at 2 meters M/s or knots Syn. and Ind. 8 observation 9 Wind spd and Dir. at 10 meters M/s and degree Syn. and Ind. ( 00,03,06,09,12,1 5,18,21) 10 Cloud Amount Oktas Syn. and Ind. at some synoptic o C 11 Soil temp. at 10, 20, 30, 50 and Syn. and Ind. stations 100 centimeters depth 12 Pan Evaporation millimeters Syn. and Ind. 13 Pitche Evaporation millimeters Syn. and Ind.
Meteorological elements … No. Meteorological Elements Unit of Time/freq. of Observing measureme observation (LST) station nts 14 Grass minimum temperature o C 5 observation ( 06, Synoptic 09,12,15,18) 15 Station level pressure mb (hPa) Synoptic per day at and 16 QNH (Sea level pressure) mb(hPa) Synoptic some synoptic stations 8 17 Weather ( Present weather, Past In symb ols Synoptic observation weather) ( 00,03,06,09,12,1 18 Cloud (Low cloud amount, Type of Oktas, type Synoptic 5,18,21) low cloud, Type of medium cloud, at some synoptic Type of high cloud) stations 19 Height of low cloud Kmts Synoptic 20 Horizontal visibility Kmts Synoptic
AWS distribution in Ethiopia Station Type We have two types of AWS Stations that measure only 6 parameter – about 100 in number Stations that measure more than 6 parameters about 47 Automatic observation Started in 2009 with the help of WFP Maintaining them incurs high cost
Data Flow Entry/Analysis/Storage/Exc Storage/Analysis/ Data Collection Transfer Transfer Usage hange/Usage Exchange/Usage Synoptic stn Users Branch Office MDCD Principal Stn Users Partner Headquarters Branch Office Ordinary Stns CLIDATA Partner Branch Office Nairobi Hard copy Precipitation stations Users AWS, UOS • Branch offices manage stations which come directly under their area of responsibility • The NMA head quarter gets hard copy data by post and softcopy data from MBD through emails, CD’s or flash disks. • Data delivery handled both at the NMA HQ and at the branch level. They use the data for operational activities. They manage, store and archive data. • The NMA HQ is responsible for managing all Ethiopia meteorological data.
The NMA Data Management system Data visualization software - adVantage pro of the ADCON web based system .
Gr Graphical phical view
Processed data and products • Raw data – Daily, hourly, 1 minutes data • Processed data – Pentad, dekadal, monthly, annual, seasonal and long term means – Merged data • Bulletins – Forecast (daily, three daily, ten daily, monthly, seasonal) and climate projections – Agromet advisories (ten daily, monthly, seasonal) – impact assessment, WRSI, moisture index, weather and livestoke insurance – Hydrometeorology • Monthly, seasonal and annual – Climate (monthly, seasonal and annual) – Health – monthly malaria suitability analysis
Satellite and raingauge merging • The problem – Both satellite and rain gauge measurements carry information about rainfall – How do you combine t hem to give the best possible Station Satellite estimate? measurements Estimate R w R w R merge g g s s Combined product Web access Visual presentation of the merged products can be accesses on NMA website (www.ethiomet.gov.et). The map room part of the website contains mean maps, dekadal climate monitoring and historical analysis of ENSO years. • The map room has – Climate analysis – Climate monitoring – 14 Climate forecast
Map room- The climate and society map room is a collection of maps and other figures that monitor climate and societal conditions at present and in the recent past. The maps and figures can be manipulated and are linked to the original data. Even if you are primarily interested in data rather than figures, this is a good place to see which datasets are particularly useful for monitoring current conditions.
Method of dissemination – Via website, radio, television, newspapers, by fax and post to registered users like ministerial offices and organizations – In some projects like (PAA, IRISH) sending data and forecast to local DA’s and project coordinators. – Farmers need area specific short range forecast, medium and long range climate outlooks for agricultural and climate adaptation and mitigation purpose – NMA can do but it needs lot’s of stations data, further researches and expertise in the area. It needs developing area specific models which takes into account the special features and climate controls of the area.
Challenges • All who participate in data acquisition, transmission, station establishment & inspection, play a role in the process of getting quality assured data. There are stations which are not maintained. Malfunctioning instruments are not replaced on time. Data quality is a big issue. • All stations which are supposed to send real time data via radio and telephone do not send data at all or regularly • All meteorological information are not well organized in the NMA Archive • All the historical data are not computerized. We are looking for upcoming projects. • Failure of Data Base Systems at times • All the charts are not processed for them to be ready for provision processing is a necessity. • Lack of trained manpower and fast advancement of technology • Network lines between head and branch offices are not functioning properly • No well organized and documented metadata of stations and instruments • Data Gaps and length – Most of the stations started recording in the 1970’s – Data gaps created due to many reasons • War outbreak, absence of observers and leaving the organization with our prior notice, instruments breakdown and slow maintenance services – Acquiring modern instruments needs high budget and using them requires trained manpower. – Data demand and supply do not agree
Recommend
More recommend
