1. SWFDP Eastern Africa- Cascading ForecastBy
Ruben K. Barakiza
Institut Geographique du Burundi( IGEBU)
Meteorological Department
P.O.BOX 331
BUJUMBURA
BURUNDI

2. 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

3. 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

4. Target users
Department of Disaster Management and Public Safety Authority
General 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; and
to 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, 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)  

7. 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

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 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

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. 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
J kg-1 Deep Convection
J kg-1 Maximum Values- (extreme atm. instability)

17. 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

18. 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

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

22. 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 .

23. 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

24. 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

25. Guidance Forecast for Tuesday 16th April, 2013

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 various
facilities such as:
National Radio broadcating
Telephone
Internet- s
Gaps:
Lack of television presentation,
Lack of MOU with Newspapers
Lack 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 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.

29. 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.

30. THE END
THANK YOU FOR LISTENNING !!!