SWFDP Eastern Africa- Cascading Forecast By Ruben K. Barakiza Institut Geographique du Burundi( IGEBU) Meteorological Department P.O.BOX 331 BUJUMBURA BURUNDI Email: barakiza_r@yahoo.co.uk

The provision of timely and effective information Objective The provision of timely and effective information through identified institutions that allows individuals exposed to a hazard to take adequate actions to avoid or reduce their risk and prepare for effective response

Extreme weather events Currently, the SWFD focuses on the following weather extreme events: Heavy rains Strong winds associated with thunderstorms Dry spells Ocean/lake waves

Target users Department of Disaster Management and Public Safety Authority General public, Various socio-economic institutions impacted by weather/climate

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; and to contribute to the evaluation of the project.

Cascading FCST ( cont’d) The first phase of this project commenced October 2011 and focused on: heavy rain, strong winds, sea/lake waves, and prolonged dry spells.  The participating Services and Centres in the SWFDP Eastern Africa include: NMHSs: Kenya, Burundi, Ethiopia, Rwanda, Tanzania and Uganda Regional Centres: RSMC, KMD - Nairobi, RSMC, TMA - Dar es Salaam; and Global Products Centres: European Centre for Medium Range Weather Forecast( ECMWF) Exeter (Met Office UK), Washington (NOAA/NCEP ), and DWD (Germany)  

NWP Product Analysis Analysis of national observational data Regional Productsfrom the RSMC-Nairobi Extreme weather guidance Risk table Cosmos model products Lake Victoria project Internatinal Centres ECMWF Determistic forecasts and EPS Rainfall model products NOAA NWP products, including: 10-day precipitation forecasts, wind flow forecast, Atmospheric Instability indices Uk Metoffice products EUMETSAT Products: satellite imagery, vertical atmosphere sounding

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 stations 125 rainfall stations 43 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

National Meteorological Observational Network in Burundi

ECMWF Deterministic Forecast for Bujumbura, 01/04/2013

ECMWF 6-hour Rainfall Model Forecast over Burundi on 01/04/2013 ( 06UTC-12UTC)

NOAA 10-day Precipitation Forecast, 18-25 May 2013

NOAA/GFS 850hpa Temperature, Relative humidity and Streamlines

NOAA/GFSPrecipitable water, and Convective Available Potential Energy(CAPE) on 18/05/2013 00h

CAPE Convective 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 Weather 1000 - 3000 J kg-1 Deep Convection 5000 - 7000 J kg-1 Maximum Values- (extreme atm. instability)

RSMC-NAIROBI RISK TABLE - Day 1: Monday 1st April, 2013 OUNTRY HEAVY RAIN STRONG WINDS LARGE WAVES RISK No Low Med High BURUNDI X KENYA C,S,W& NE E RWANDA TANZANIA N,E, C & SW Off SE Coast UGANDA S ETHIOPIA

RSMC-NAIROBI Risk Table-Day 2: Tuesday 2nd April, 2013 COUNTRY HEAVY RAIN STRONG WINDS LARGE WAVES RISK No Low Med High BURUNDI X KENYA C&W E RWANDA TANZANIA N&C Off SE Coast UGANDA ETHIOPIA S

EUMETSAT, 2013-04-01 IR image at 1200UTC

Case study: Example of 16 April, 2013 Risk table: Low risk of Rainfall>50mm/24h Guidance forecast from RSMC-Nairobi showed that much of the country expected rainfall> 50mm/24h On 15 April, 2013: A warning for heavy rains was issued. What happened on the ground In the Eastern parts of Burundi, in Ruyigi Province, Muriza weather station recorded 108.6mm/24h on 16/04/2013 .

RISK TABLE Day 1: Monday 15th April, 2013 Issue Monday 15th April, 2013 COUNTRY HEAVY RAIN STRONG WINDS LARGE WAVES RISK No Low Medium High M edi um H i g h BURUNDI W X KENYA W&C Coast E RWANDA TANZANIA Off E Coast Off SE Coast UGANDA ETHIOPIA SW

RISK TABLE DAY 2: Tuesday 16th April, 2013 COUNTRY HEAVY RAIN STRONG WINDS LARGE WAVES RISK No Low Medium High Me diu m H i g h BURUNDI X KENYA SW Coast E RWANDA TANZANIA N&W Off E Coast Off SE Coast UGANDA ETHIOPIA

Guidance Forecast for Tuesday 16th April, 2013

2013 April 16th , 24h-Total rainfall over Burundi

Information Dissemination and communication The Burundi NMHS dissemites and weather information to the socio-economic sectors and to the general public through various facilities such as: National Radio broadcating Telephone Internet-emails Gaps: Lack of television presentation, Lack of MOU with Newspapers Lack of allocated budget for providing weather information ( for instance, newspapers)

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 NMHS UNDP-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.

Challenges Most 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 community Low level of awareness and disaster preparedness in the general public leading to low coping capacity.

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