The role of National Meteorological and Hydrological Services (NMHS) in DRR Julius N. Kabubi Kenya Meteorological Department
The role of National Meteorological and Hydrological Services (NMHS) in DRR
Julius N. Kabubi
Kenya Meteorological Department
Some recent observations on disasters
• There is a Global increasing trend in the number of disasters and their total economic impacts
• 90% of these natural disasters are caused by severe weather and extreme climate events
A number of severe weather and extreme climate‐related events in recent years have led to disasters of devastating consequences to many societies, thus arousing even keener interest of the general public and policy makers
The role of NMHS
• Weather Monitoring • Weather Forecasting• Climate prediction• Early warnings• Weather and climate Advisories • Food security• Climate Change Detection and attribution• Research and outreach programmes
Other duties and responsibly NMHS
1. Establishment and maintenance of a national meteorological observation network mandatory for weather and climate observations
2. Monitoring, detection and prediction of weather and climate phenomena and dissemination of relevant products and early warnings;
3. Monitoring environmental pollution and Greenhouse Gases, including ozone
4. Exchange and transmission of meteorological data nationally, regional and internationally;
5. Carrying out meteorological training and research to improve the quality of meteorological services
6. Archival of long‐term reliable national climatologically records
Regional and international• Fulfillment of the national, regional and international obligations of the
Government under the Convention of the World Meteorological Organization (WMO)
• Fulfillment of the national, regional and international obligations of the Government under the Convention of the International Civil Aviation Organization (ICAO) and others
• Carrying out a Scientific assessment on Climate Agenda under the IPCC which supports country positions on the resolutions, protocols and conventions of the United Nations Framework Convention on Climate Change (UNFCCC)
• Fulfillment of such other climate and weather related national, regional and international obligations as may be directed.
Other duties
Analysis of weather variables • Trends and patterns in wind regimes
• Trends and patterns in Pressure systems
• Intensities of rainfall and durations
• Trends in temperature regimes
• Local modification of weather systems
• Regional influences by meso‐scale weather systems
• Seasonality
Generate weather products
• Nowcasting (6 hrs ahead)• Weather Forecasts• 24 hrs,4 days,7 days,14 days,1 month & Seasonal• Specialized forecasts;
– Aviation – Marine– Agriculture– Food security – Water resources – Energy – Disaster management – Health and other sectors
Some products –Long‐term distribution of RF
201.20
1962.201071.40
1379.30
2101.70
782.20
919.30
760.10
959.60
1341.30
281.80
329.10
816.90
393.40
731.70
602.00
568.50 1074.20
1105.00
943.10
2005.50
33.00 34.00 35.00 36.00 37.00 38.00 39.00 40.00 41.00 42.00 43.00
-5.00
-4.00
-3.00
-2.00
-1.00
0.00
1.00
2.00
3.00
4.00
5.00
6.00
LODWAR
KAKAMELDORET
KISUMU
KISII
NAROK
NAKURU
DAGORETTI
NYERI
MERU
MANDERA
WAJIR
MARSABIT
GARISSA
MOYALE
MAKINDU
VOI MALINDI
MOMBASA
LAMU
KERICHO
201.20
1962.201071.40
1379.30
2101.70
782.20
919.30
760.10
959.60
1341.30
281.80
329.10
816.90
393.40
731.70
602.00
568.50 1074.20
1105.00
943.10
2005.50
200.00
300.00
400.00
500.00
600.00
700.00
800.00
900.00
1000.00
1100.00
1200.00
1300.00
1400.00
1500.00
1600.00
1700.00
1800.00
1900.00
2000.00
Trends in Temperature at Dagoretti (Nairobi)
MINIMUM MAXIMUM
TEMPERATURE RANGE AT DAGORETTI
OBSERVED CLIMATE CHANGE SIGNALS IN KENYA : Increases in temperature
Local maximum temperature trends for Lodwar(Left) and Dagoretti(Right)
Annual Max Temp: Lodwar
y = 0.0317x + 34.322
33.0
33.5
34.0
34.5
35.0
35.5
36.0
36.5
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
2002
Year
Tem
pera
ture
( C
)
Annual Max Temp: Dagoretti
y = 0.0186x + 23.244
22.0
22.5
23.0
23.5
24.0
24.5
25.0
25.5
26.0
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
2002
2005
Year
Tem
pera
ture
( C)
Observed Climate Change Signals in Kenya: Decreasing October – November –December (OND) Seasonal Rainfall Trends
Nyahururu OND rainfall trend
y = -1.393x + 221.61
0.0
100.0
200.0
300.0
400.0
500.0
600.0
700.0
800.0
900.0
1961
1964
1967
1970
1973
1976
1979
1982
1985
1988
1991
1994
1997
2000
2003
2006
Year
Rai
nfal
l (O
ND
)
y = -1.3197x + 336.22
0.0
200.0
400.0
600.0
800.0
1000.0
1200.0
1950
1953
1956
1959
1962
1965
1968
1971
1974
1977
1980
1983
1986
1989
1992
1995
1998
2001
2004
Narok OND rainfall trend
y = - 0.2835x + 187.34
0.0
100.0
200.0
300.0
400.0
500.0
600.0
700.0
800.0
1950
1953
1956
1959
1962
1965
1968
1971
1974
1977
1980
1983
1986
1989
1992
1995
1998
2001
2004
Year
Rai
nfal
l (m
m)
Narok
MarsabitNyahururu
Finally – Early warning Information for DRR
Weather warnings and alertsWeather advisories Climate forecasts and predictionsClimate advisories Stream flow ModelingExtreme Weather and severe climate events
Droughts Early warning (La‐nina conditions)Floods Early warning (El Nino conditions )Real time flood forecasting Extreme temperatures (heat waves) Fog and frost
NB/ Early warning is applied throughout the disaster cycle (Preparedness, response, relief and reconstruction)
Initiatives to improve on EWS for DRR
• A awareness campaign with partners (Nile IWRM‐Net, UNISDR, UNOCHA, MOSSP, NDOC and Universities)
• Real time monitoring of hazards
• Timely communication of information
• Research work for thresh‐holding of hazards
• Campaign to reach the politicians
Main bottlenecks in NMHS??
• Little funding from national governments
• Inadequate data observational networks and data gaps
• Old equipments in some countries
• Human capacity and succession management problems
• Lack of awareness and poor perception by communities
General Challenges of EWS
Climate change impacts 1. Immergence of disease like Rift Valley Fever (RVF) – floods2. Highland malaria cases ‐ extreme temperaturesLack of knowledge by public to interpret disaster indicators andthresholdsChanging societal demands and expectation of EWSs over timeCommunication problemsHazard characteristics that can change over timeDomestication of EW tools (Models that are home grown)Lack of deterministic EW models rather than probabilistic onesLow level of appreciation and response by community Numerical Weather prediction and use of Radar systems is still low
EWS will not work where there is;
• Lack of (poorly implemented) climate‐change policies (A national climate change master plan)
• Lack of awareness/preparedness • A well developed disaster management systems and policies• Unsustainable exploitation (over‐reliance) of natural resources• Lack of relocation opportunities and procedures • Unfavourable Topography and climate• Land subdivision and poor land policies • Adverse socio‐economic attributes of risk prone communities (Primary?)
– Poverty– Conflicts– High population densities– Poor traditions and customs– Unwillingness to live with risks (unwillingness to change with
changing environment)
Conclusions
• NMHS play major roles in DRR through provision of EW information throughout the disaster cycle
• There is need therefore to strength NMHS capacities in order to improve on their role in DRR activities
• National DRR platforms should incorporate NMHS in their planning and execution of their national agenda