university of nairobi, nairobi, kenya department of meteorology, august 15-19, 201111th...
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August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
1
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Predictability of Weather on Extended NWP Timescales over Kenya Using the GFS
Model
Franklin J. OpijahUniversity of Nairobi, Kenya
www.uonbi.ac.ke
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
2
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Early-Warning Systems may reduce vulnerabilityto floods, disease, pestilence, strong winds, hazardous air
Dust Storms/Hazardous AirDust Storms/Hazardous AirMalaria EpidemicsMalaria Epidemics
Communication ImpairmentCommunication ImpairmentStrong WindsStrong Winds
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
3
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
EWS can reduce vulnerability to pests, drought and famine
Food InsecurityFood Insecurity
Livestock ManagementLivestock ManagementPest InvasionsPest Invasions
Food AvailabilityFood Availability
Water Resource ManagementWater Resource Management
Heat WavesHeat Waves
Hydropower GenerationHydropower Generation
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
4
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Strong Linkage between Weather Conditions and Disease
• Malaria is rife in humid, high temperature areas
• Meningitis is rife in dusty, low-humidity areas
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
5
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Traditional Forecasting Techniques in Kenya
(UNDP Report)
• Is it possible to forecast impending weather using indigenous knowledge (IK)?
• Modelling Challenge: Is NWP Superior to IK?
Indicator Coming rains
Dry spell
Croaking frogs
Pronounced Reduced
Migrant birds Appearance Disappearance
Indigenous trees
Leaving, flowering
Shedding
Cattle Stampedes
Bird nests (weaver birds )
More nests Fewer nests
Red ants Appearance
Human body Discomfort (hot)
Discomfort (cold)
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
6
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Outline of Presentation
• Introduction• The Global Forecast System• Prevailing Weather Conditions over Kenya (OND
2008)• Error and Skill Analysis (Formulation and
Techniques)• Is RFE Data useful over Kenya? • Predictability of Daily Rainfall and Temperature• Predictability of Seven-Day Weather Outlooks• Summary and Conclusions
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
7
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Outline
• Introduction• The Global Forecast System• Prevailing Weather Conditions over Kenya (OND
2008)• Error and Skill Analysis (Formulation and
Techniques)• Is RFE Data useful over Kenya? • Predictability of Daily Rainfall and Temperature• Predictability of Seven-Day Weather Outlooks• Summary and Conclusions
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
8
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Global Forecast SystemHorizontal Resolution 35 km (T382)
Solution technique Spectral triangular; Nonlinear advection: Leapfrog Gravity waves: Semi-implicit
Vertical grid Hybrid p-sigma; 64 levels
PBL Bulk-Richardson approach + Monin-Obukhov similarity
Radiation scheme (LWR/3hr; SWR/1hr)
GHGs (O3, H2O, CO2, CH4, N2O, O2, CFCs ), atmospheric aerosols, Cloud-radiative properties
Convection Deep: Arakawa and Schubert (1974):
Shallow: bulk mass-flux parameterization
Gravity-wave drag: Nonlinear function of the surface wind speed and the local Froude number
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
9
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Outline
• Introduction• The Global Forecast System• Prevailing Weather Conditions over Kenya (OND
2008)• Error and Skill Analysis (Formulation and
Techniques)• Is RFE Data useful over Kenya? • Predictability of Daily Rainfall and Temperature• Predictability of Seven-Day Weather Outlooks• Summary and Conclusions
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
10
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Weather/Climate Controls over Kenya
• Quasi-permanent systems– ITCZ– Anticyclones
• Unusual systems – El Niño/La Nina– IOD– QBO
• Migratory Systems– Tropical cyclones – Easterly waves– MJOs
• Mesoscale systems– Great lakes– High mountains– Urban areas
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
11
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Domain of Study Topography & Homogeneous Climate Zones
ARC
BAM
BAR
BAR COL
DAG
ELD
ELG
GAL
GARB
GAR
IS I
K ISU
KAJ
KAK
KAP
KAS
KAT
KER
K IBW
KINA
K IR I
K IS I
KAIS
LAIK
LAM
LOD
MAC
MAG
MAK I
MAL
MAN
MARL
MARS
MAT I
MBO
MOM
MON
MOY
MUT
NAIV
NAK
NAN NYK
NAR
NK IN
NYA
NYEOLEN
RUM
TAV
T IMAT IMB
ADU
VOI
WA
TOD
HOR
RHA
ELW
34.00 35.00 36.00 37.00 38.00 39.00 40.00 41.00
-4 .00
-3 .00
-2 .00
-1 .00
0.00
1.00
2.00
3.00
4.00
5.00
34.00 35.00 36.00 37.00 38.00 39.00 40.00 41.00
-4 .00
-3 .00
-2 .00
-1 .00
0.00
1.00
2.00
3.00
4.00
5.00
1
2
3
4 5
6
8
91 0
1 1
1 2
7
Rainfall climatic zones
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
12
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Observed Weather Patterns over Kenya in the 2008 OND SeasonObserved Rainfall and Maximum and
Minimum Temperature at Dagoretti, Kenya
0
10
20
30
40
50
60
70
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Date
Rai
nfa
ll (
mm
)
0
5
10
15
20
25
30
Tem
peratu
re (C)
Rainfall Tmax Tmin
Observed Rainfall and Maximum and Minimum Temperature at Eldoret, Kenya
05
1015202530354045
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Date
Rai
nfa
ll (
mm
)
0
5
10
15
20
25
30
Tem
peratu
re (C)
Rainfall Tmax Tmin
Observed Rainfall and Maximum and Minimum Temperature at Lodwar, Kenya
0
2
4
6
8
10
12
14
16
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Date
Rai
nfa
ll (
mm
)
0
5
10
15
20
25
30
35
40
Tem
peratu
re (C)
Rainfall Tmax Tmin
Observed Rainfall and Maximum and Minimum Temperature at Voi, Kenya
0
5
10
15
20
25
30
35
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Date
Rai
nfa
ll (
mm
)
0
5
10
15
20
25
30
35
40
Tem
peratu
re (C)
Rainfall Tmax Tmin
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
13
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Outline
• Introduction• The Global Forecast System• Prevailing Weather Conditions over Kenya (OND
2008)• Error and Skill Analysis (Formulation and
Techniques)• Is RFE Data useful over Kenya? • Predictability of Daily Rainfall and Temperature• Predictability of Seven-Day Weather Outlooks• Summary and Conclusions
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
14
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Verification Techniques• Signal/direction test
– Space-time graphical analysis – Correlation analysis
• Accuracy test– Root mean square error analysis
• Skill analysis: – Hit rate (HR)– Proportion Correct (PC)– Equitable Threat Score (ETC)– True Skill Statistic (TSS)– Heidke skill score (HSS)– Two-Alternative Forced Choice Test (2AFC)
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
15
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
OMOMr ),cov(
221
iii OM
NRMSE Forecast
‘Yes’Forecast
‘No’
Observed ‘Yes’
a b
Observed ‘No’
c d
ba
aHR
dcba
daPC
)(
)(
aRcba
aRaETS
dcba
cabaaR
))((
)(
))(( dbca
bcadTSS
)()(
)(
aR-dcba
aR-d)(a= HSS
)(
))(())(()(
dcba
dbdc+caba= aR
))(( dcba
bdacadP 2
1
AFC2
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
16
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Outline
• Introduction• The Global Forecast System• Prevailing Weather Conditions over Kenya (OND
2008)• Error and Skill Analysis (Formulation and
Techniques)• Is RFE Data useful over Kenya? • Predictability of Daily Rainfall and Temperature• Predictability of Seven-Day Weather Outlooks• Summary and Conclusions
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
17
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Station-Averaged Error Analysis: RFE and Observed Rainfall over Kenya
2004 2005 2006 2007 2008April Corr coef (%) -2.5 -12.6 -4.5 6.9 -7.4November Corr coef (%)
-6.5 -8.0 8.6 4.4 -6.3
April RMSE (mm) 12.8 8.9 15.4 9.6 9.6November RMSE (mm) 8.5 5.7 15.0 8.0 12.2
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
18
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Spatial Distribution of Correlation Coefficients and RMSE between Observed and RFE Rainfall over Kenya
April 2008 November 2008
Root mean square error
Correlation coefficients
34 35 36 37 38 39 40 41 42
Longitude
R M SE Analysis of R FE vs O bserved R ainfa ll over Kenya for April 2008
-5
-4
-3
-2
-1
0
1
2
3
4
5
Latit
ude
3 m m
6 m m
9 m m
12 m m
15 m m
5 m m
8 m m
10 m m
13 m m
15 m m
18 m m
20 m m
34 35 36 37 38 39 40 41 42
Longitude
R M SE Analysis o f R FE vs O bserved R ainfa ll over Kenya in N ovem ber, 2008
-5
-4
-3
-2
-1
0
1
2
3
4
5
Latit
ude
34 35 36 37 38 39 40 41 42
Longitude
C orre lation Analysis Betw een O bserved andR FE R ainfa ll over Kenya for April 2008
-5
-4
-3
-2
-1
0
1
2
3
4
5
Latit
ude
-0 .25-0.20-0.15-0.10-0.050.000.050.100.150.200.25
34 35 36 37 38 39 40 41 42
Longitude
C orre lation Analysis Betw een O bserved andR FE R ainfa ll over Kenya in N ovem ber, 2008
-5
-4
-3
-2
-1
0
1
2
3
4
5
Latit
ude
-0 .2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
19
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Outline
• Introduction• The Global Forecast System• Prevailing Weather Conditions over Kenya (OND
2008)• Error and Skill Analysis (Formulation and
Techniques)• Is RFE Data useful over Kenya? • Predictability of Daily Rainfall and Temperature• Predictability of Seven-Day Weather Outlooks• Summary and Conclusions
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
20
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Comparison of Observed and GFS Rainfall : November 2008
GFS Model 7-Day Rainfall Forecast over Nyahururu, Kenya
0
5
10
15
20
25
30
05-Nov-08
06-Nov-08
07-Nov-08
08-Nov-08
09-Nov-08
10-Nov-08
11-Nov-08
Target Date
Rai
nfa
ll (
mm
)
Observed Forecast
GFS Model 7-Day Rainfall Forecast over Kisumu, Kenya
0
10
20
30
40
50
60
70
05-Nov-08
06-Nov-08
07-Nov-08
08-Nov-08
09-Nov-08
10-Nov-08
11-Nov-08
Target Date
Rai
nfa
ll (
mm
)
Observed ForecastGFS Model 7-Day Rainfall Forecast over Lodwar, Kenya
02468
1012141618
05-Nov-09
06-Nov-09
07-Nov-09
08-Nov-09
09-Nov-09
10-Nov-09
11-Nov-09
Target Date
Rai
nfa
ll (
mm
)
Observed Forecast
GFS Model 7-Day Rainfall Forecast over Mombasa, Kenya
05
1015202530354045
05-Nov-08
06-Nov-08
07-Nov-08
08-Nov-08
09-Nov-08
10-Nov-08
11-Nov-08
Target Date
Rai
nfa
ll (
mm
)
Observed Forecast
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
21
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Rainfall Spatial Distribution in Kenya: 1 November 2008 and 3 November 2008
GFS Observed Reanalysis RFE
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
22
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Observed and GFS Rainfall, Maximum and Minimum Temperature (7 November 2008)Observed 1-Day Lead Time 4-Day Lead Time 7-Day Lead Time
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
23
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
RMSE and Correlation Analysis: Rainfall, Maximum and Minimum Temperature
Averaged RMSE and Correlation Coefficients between GFS 7-Day Forecasts and Observed Rainfall over
Kenya at Various Lead Times
9.5
10.0
10.5
11.0
11.5
12.0
12.5
1 2 3 4 5 6 7
Lead Time (Days)
RM
SE
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Co
rrelation
C
oefficien
t
RMSE Corr Coef
Averaged RMSE and Correlation Coefficients between GFS 7-Day Forecasted and Observed Maximum Temperature over Kenya at Various Lead times
4.404.454.504.554.604.654.704.754.804.854.90
1 2 3 4 5 6 7
Lead Time (Days)R
MS
E
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
Co
rrelation
C
oefficien
t
RMSE Corr Coef
Averaged RMSE and Correlation Coefficients between GFS 7-Day Forecasted and Observed Minimum Temperature over Kenya at Various Lead Times
2.65
2.70
2.75
2.80
2.85
1 2 3 4 5 6 7
Lead Time (Days)
RM
SE
0.07
0.12
0.17
0.22 Co
rrelation
C
oefficien
t
RMSE Corr Coef
RMSE and Correlation Analyses between Averaged GFS 7-Day Forecasts and Observed Rainfall over
Kenya for Various Lead Times
1.5
2.5
3.5
4.5
5.5
6.5
7.5
1 2 3 4 5 6 7
Lead Time (Days)
RM
SE
-0.7
-0.5
-0.3
-0.1
0.1
0.3
0.5
0.7
0.9
Co
rrelation
C
oefficien
t
RMSE Corr Coef
RMSE and Correlation Coefficients Between Averaged GFS 7-Day Forecasts and Observed Maximum
Temperature over Kenya at Various Lead Times
4.1
4.2
4.3
4.4
4.5
4.6
4.7
1 2 3 4 5 6 7
Lead Time
RM
SE
0.400.450.500.550.600.650.700.750.800.850.90
Co
rrelation
C
oefficien
t
RMSE Corr Coef
RMSE and Correlation Coefficients Between Averaged GFS 7-Day Forecasts and Observed Minimum
Temperature over Kenya at Various Lead Times
1.8
1.9
2.0
2.1
2.2
2.3
2.4
1 2 3 4 5 6 7
Lead Time (Days)
RM
SE
0.29
0.31
0.33
0.35
0.37
0.39
0.41
0.43
0.45
Co
rrelation
C
oefficien
t
RMSE Corr Coef
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
24
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Averaged Hit Rate and Proportion Correct for Rainfall and Temperature
• Rainfall
• Temperature 0
10
20
30
40
50
60
70
80
90
100
1 Day 2 Days 3 Days 4 Days 5 Days 6 Days 7 Days
Lead Time
Sc
ore
(%
)
HR PC
0
10
20
30
40
50
60
70
80
90
1 2 3 4 5 6 7
Lead Time
Sc
ore
(%
)
Tmax_HR Tmax_PC Tmin_HR Tmin_PC
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
25
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
GFS Skill Score Indices (%): Rainfall, Maximum and Minimum Temperature
Rainfall Maximum Temperature
Minimum Temperature
2AFCETSHSSTSS
Two-alternative forced choice test scoreEquitable threat scoreHeidke skill score True skill statistic
Averaged Skill Score Indices for the GFS Model Rainfall for Various Lead Times over Kenya
-30
-20
-10
0
10
20
30
40
50
1 2 3 4 5 6 7
Lead Time (Days)
Skill
Scor
e (%)
2AFC ETS HSS TSS
Averaged Skill Score Indices for the GFS Model Maximum Temperature for Various Lead Times over
Kenya
20
25
30
35
40
45
50
55
60
1 2 3 4 5 6 7
Lead Time (Days)
Skill
Score
(%)
2AFC_mean ETS_mean HSS_mean TSS_mean
Averaged Skill Score Indices for the GFS Model Minimum Temperature for Various Lead Times over
Kenya
3
5
7
9
11
13
15
1 2 3 4 5 6 7
Lead Time (Days)
Skill
Score
(%)
2AFC_mean ETS_mean HSS_mean TSS_mean
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
26
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Outline
• Introduction• The Global Forecast System• Prevailing Weather Conditions over Kenya (OND
2008)• Error and Skill Analysis (Formulation and
Techniques)• Is RFE Data useful over Kenya? • Predictability of Daily Rainfall and Temperature• Predictability of Seven-Day Weather Outlooks• Summary and Conclusions
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
27
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Spatial Distribution of 7-day cumulative Rainfall :
1-7 November 2008
GFS Model Observed Reanalysis RFE
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
28
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Spatial Distribution of 7-day Maximum and Minimum Temperature:
1-7 November 2008
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
29
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Rainfall Bias: GFS minus Observed Rainfall
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
30
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Temperature Difference: GFS minus Observed Maximum and Minimum Temperature
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
31
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
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7-day GFS and Observed Total Rainfall and Average Temperature
Rainfall Tmax Tmin
Eldoret
Mombasa
Narok
Temporal Variability of GFS and Observed 7-Day Total Rainfall at Eldoret, Kenya
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.51-
7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
Temporal Variability of GFS and Observed 7-Day Mean Maximum Temperature at Eldoret, Kenya
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
Temporal Variability of GFS and Observed 7-Day Mean Minimum Temperature at Eldoret, Kenya
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
Temporal Variability of GFS and Observed 7-Day Total Rainfall at Mombasa, Kenya
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
Temporal Variability of GFS and Observed 7-Day Mean Maximum Temperature at Mombasa, Kenya
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
Temporal Variability of GFS and Observed 7-Day Mean Minimum Temperature at Mombasa, Kenya
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
Temporal Variability of GFS and Observed 7-Day Total Rainfall at Narok, Kenya
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
Temporal Variability of GFS and Observed 7-Day Mean Maximum Temperature at Narok, Kenya
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
Temporal Variability of GFS and Observed 7-Day Mean Minimum Temperature at Narok, Kenya
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
32
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Station-averaged Temporal Variability Rainfall, Maximum and Minimum Temperature
Temporal Variability of GFS and Observed 7-Day Total Rainfall Averaged over Kenya
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed ModelTemporal Variability of GFS and Observed 7-Day Mean Maximum Temperature Averaged over Kenya
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
Temporal Variability of GFS and Observed 7-Day Mean Minimum Temperature Averaged over Kenya
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
1-7
3-9
5-11
7-13
9-15
11-1
7
13-1
9
15-2
1
17-2
3
19-2
5
21-2
7
23-2
9
Dates
Sta
ndar
dize
d A
nom
aly
Observed Model
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
33
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.keError Analysis of 7-Day Total Rainfall (mm) and 7-Day Average Maximum
and Minimum Temperature (C)
Correlation Coefficient (%) Root Mean Square Error
Rain-fall
Max Temp
Min Temp
Rain-fall
Max Temp
Min Temp
12-Station Mean
57 76 21 26.6 4.6 2.5
Area Average 82 -12 38 14.8 7.1 1.3
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
34
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Skill Score Indices (%) : Rainfall, Maximum and Minimum Temperature
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
35
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Outline
• Introduction• The Global Forecast System• Prevailing Weather Conditions over Kenya (OND
2008)• Error and Skill Analysis (Formulation and
Techniques)• Is RFE Data useful over Kenya? • Predictability of Daily Rainfall and Temperature• Predictability of Seven-Day Weather Outlooks• Summary and Conclusions
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
36
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Summary of Results
• RFE rainfall estimates may not be representative indicators of the rainfall distribution over Kenya & should only be used with caution
• GFS displaces the location of the observed rainfall over the region and underestimates the observed rainfall (but also gives false alarms for some ASALs areas)
• The accuracy of the model-generated rainfall and maximum and minimum temperature decreases with increasing prediction lead time
• The skill for rainfall beyond 5 days is unreliable
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
37
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Summary of Results• GFS generally captures the locations of
highest and lowest maximum and minimum temperatures but exaggerates their areal extent
• GFS underestimates maximum temperature but overestimates minimum temperature
• GFS has better skill in predicting daily maximum temperature than it does with rainfall, and worst for minimum temperature
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
38
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Conclusions• GFS is a useful tool for predicting the cycle of 7-
day rainfall and maximum temperature, but not minimum temperature over the domain
• GFS has better skill in predicting rainfall, maximum and minimum temperature for seven day averaged forecasts than for daily forecasts over a seven-day period
• Seven-day averaged quantities are not superior to daily forecasts within the first two to four days of the forecasts, but may be useful for predicting mean quantities on extended NWP range
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
39
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
Recommendation
• The model needs some fine tuning to improve its ability to predict the maximum temperature and rainfall. The model, in its current form, is not suitable for predicting minimum temperatures over the domain
• There is need to recalibrate RFE and improve the quality of reanalysis data
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
40
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke
• Thank you for your attention
• Merci boucoup
• Ahsante sana
August 15-19, 2011 11th Inter'l RSM Workshop-National Central University, Jhongli, ROC
41
University of N
airobi, Nairobi, K
enya
Departm
ent of Meteorology, w
ww
.uonbi.ac.ke