Presentation on theme: "SWFDP Eastern Africa- Cascading Forecast"— Presentation transcript:
1 SWFDP Eastern Africa- Cascading Forecast ByRuben K. BarakizaInstitut Geographique du Burundi( IGEBU)Meteorological DepartmentP.O.BOX 331BUJUMBURABURUNDI
2 The provision of timely and effective information ObjectiveThe provision of timely and effective informationthrough identified institutionsthat allows individuals exposed to a hazard to take adequate actions to avoid or reduce their risk and prepare for effective response
3 Extreme weather events Currently, the SWFD focuses on the following weather extreme events:Heavy rainsStrong winds associated with thunderstormsDry spellsOcean/lake waves
4 Target usersDepartment of Disaster Management and Public Safety AuthorityGeneral public,Various socio-economic institutions impacted by weather/climate
5 The Cascading Forecasting Process In the framework of the general organization of the Global Data-Processing and Forecasting System (GDPFS), the SWFDP implies a co-ordinated functioning among three types of GDPFS centres.These are:Global NWP Centres to provide available NWP products, including in the form of probabilities;Regional Centres to interpret information received from the global NWP centres,run limited-area models to refine products,liaise with the participating NMCs;The NMCs to issue alerts, advisories, severe weather warnings;to liaise and collaborate with Media, and Disaster Management and CivilPprotection Authorities; andto contribute to the evaluation of the project.
6 Cascading FCST ( cont’d) The first phase of this project commenced October 2011 and focused on:heavy rain,strong winds,sea/lake waves, andprolonged dry spells. The participating Services and Centres in the SWFDP Eastern Africa include:NMHSs: Kenya, Burundi, Ethiopia, Rwanda, Tanzania and UgandaRegional Centres: RSMC, KMD - Nairobi, RSMC, TMA - Dar es Salaam; andGlobal Products Centres:European Centre for Medium Range Weather Forecast( ECMWF)Exeter (Met Office UK),Washington (NOAA/NCEP ), andDWD (Germany)
7 NWP Product Analysis Analysis of national observational data Regional Productsfrom the RSMC-NairobiExtreme weather guidanceRisk tableCosmos model productsLake Victoria projectInternatinal CentresECMWF Determistic forecasts and EPSRainfall model productsNOAA NWP products, including:10-day precipitation forecasts,wind flow forecast,Atmospheric Instability indicesUk Metoffice productsEUMETSAT Products: satellite imagery, vertical atmosphere sounding
8 CURREWNT STATUS OF OBSERVATIONAL NETWORK IN BURUNDI The current status of meteorological observational network in Burundi is as follows:2 synoptic stations operating 24 hours per day.13 main climatological stations125 rainfall stations43 hydrometric stations at main rivers such as Ruvubu, Rusizi and Malagarazi rivers from where hydrological measurements are carried out and data collected.5 Automatic Weather Stations (AWS)EUMETSAT AMESD-PUMA satellite data station
9 National Meteorological Observational Network in Burundi
11 ECMWF Deterministic Forecast for Bujumbura, 01/04/2013
12 ECMWF 6-hour Rainfall Model Forecast over Burundi on 01/04/2013 ( 06UTC-12UTC)
13 NOAA 10-day Precipitation Forecast, 18-25 May 2013
14 NOAA/GFS 850hpa Temperature, Relative humidity and Streamlines
15 NOAA/GFSPrecipitable water, and Convective Available Potential Energy(CAPE) on 18/05/2013 00h
16 CAPEConvective available potential energy(CAPE),is the amount of energy a parcel of air would have if lifted a certain distance vertically through the atmosphere.CAPE is effectively the positive buoyancy of an air parcel and is an indicator of atmospheric instability,It is very valuable in predicting severe weather.CAPE Values Potential WeatherJ kg-1 Deep ConvectionJ kg-1 Maximum Values- (extreme atm. instability)
17 RSMC-NAIROBI RISK TABLE - Day 1: Monday 1st April, 2013 OUNTRYHEAVY RAINSTRONG WINDSLARGE WAVESRISKNoLowMedHighBURUNDIXKENYAC,S,W&NEERWANDATANZANIAN,E, C & SWOff SE CoastUGANDASETHIOPIA
18 RSMC-NAIROBI Risk Table-Day 2: Tuesday 2nd April, 2013 COUNTRYHEAVY RAINSTRONG WINDSLARGE WAVESRISKNoLowMedHighBURUNDIXKENYAC&WERWANDATANZANIAN&COff SE CoastUGANDAETHIOPIAS
22 Case study: Example of 16 April, 2013 Risk table: Low risk of Rainfall>50mm/24hGuidance forecast from RSMC-Nairobi showed that much of the country expected rainfall> 50mm/24hOn 15 April, 2013: A warning for heavy rains was issued.What happened on the groundIn the Eastern parts of Burundi, in Ruyigi Province, Muriza weather station recorded 108.6mm/24h on 16/04/2013 .
23 RISK TABLE Day 1: Monday 15th April, 2013 Issue Monday 15th April, 2013COUNTRYHEAVY RAINSTRONG WINDSLARGE WAVESRISKNoLowMediumHighM edi umH i g hBURUNDIWXKENYAW&CCoastERWANDATANZANIAOff E CoastOff SE CoastUGANDAETHIOPIASW
24 RISK TABLE DAY 2: Tuesday 16th April, 2013 COUNTRYHEAVY RAINSTRONG WINDSLARGE WAVESRISKNoLowMediumHighMe diu mH i g hBURUNDIXKENYASWCoastERWANDATANZANIAN&WOff E CoastOff SE CoastUGANDAETHIOPIA
26 2013 April 16th , 24h-Total rainfall over Burundi
27 Information Dissemination and communication The Burundi NMHS dissemites and weather information to the socio-economic sectors and to the general public through variousfacilities such as:National Radio broadcatingTelephoneInternet- sGaps:Lack of television presentation,Lack of MOU with NewspapersLack of allocated budget for providing weather information ( for instance, newspapers)
28 Relationship with disaster management and civil protection authorities and media A networking and viable communication links exist between Burundi NMHS and the Disaster Management and Civil Protection Office.The National Platform for disaster Management has a representative from the Burundi NMHSUNDP-funded workshops focusing on Disaster prevention and preparedness have been organized aimed at capacity building of DMCPA, Media, NMHS and other concerned institutions.Media have been important means for disseminating information on extreme weather events.
29 ChallengesMost extreme weather events such as hail, strong winds, etc. are associated with small scale thunderstorms, sometimes not materialized by global models.Inadequate feedback from user communityLow level of awareness and disaster preparedness in the general public leading to low coping capacity.
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