predictability of the moisture regime during the pre-onset period of sahelian rains
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Predictability of the Moisture Regime During the Pre-onset Period of Sahelian Rains. Robert J. Mera Marine, Earth and Atmospheric Sciences North Carolina State University Seminar, April 3rd 2009. Motivation. Why is the moisture regime important?. Prediction of Monsoon rainfall. - PowerPoint PPT PresentationTRANSCRIPT
Climate Modeling LaboratoryMEASNC State University
Predictability of the Moisture Regime During the Pre-onset Period of
Sahelian RainsRobert J. Mera
Marine, Earth and Atmospheric SciencesNorth Carolina State University
Seminar, April 3rd 2009
Climate Modeling LaboratoryMEASNC State University
Motivation• Why is the moisture regime
important?Prediction of Monsoon rainfall
Agriculture
African Easterly Waves
Public health: Meningitis Outbreaks
Climate Modeling LaboratoryMEASNC State University
Outline
• The Application– Background– Health-climate link
• Our Study– Importance of Downscaling– Predictability of Pre-onset Conditions– Ensemble Prediction and Evaluation of
Model Skill
Climate Modeling LaboratoryMEASNC State University
The Application• Meningitis is a serious
infectious disease affecting 21 countries
• 300 million people at risk across the Sahel
• 700,000 cases in the past 10 years
• 10-50 % fatality rate • 256,000 people lost to the
disease in 1996
SAHEL
Climate Modeling LaboratoryMEASNC State University
Meningitis-Climate link• Outbreaks coincide with dry, dusty conditions over the Sahel due to the
Harmattan winds flowing south from the Sahara (Jan-May)• Largest correlation occurs between low humidity and disease outbreaks
(Molesworth et al., 2006)• Disease occurrence drops dramatically with the onset of humidity
January July
SHSHL
Har
mat
tan
Moi
sture
ITCZ
ITCZ
Climate Modeling LaboratoryMEASNC State University
Meningitis-Climate link• The most actionable case involves the link
between humidity onset and cessation of disease
Pink: # of cases Orange: Relative Humidity (%)
1998 2004
Climate Modeling LaboratoryMEASNC State University
Current Efforts
• University Corporation for Atmospheric Research (UCAR) and the Google Foundation are funding efforts to explore climate-meningitis dynamics
• Global scale models will be employed for operational purposes
Climate Modeling LaboratoryMEASNC State University
Our study: Importance of Downscaling
WRF at 30km resolution NCEP/NCAR Reanalysis at 2.5°
65
60
55
45
50
40
3530
25
20
Ghana Ghana
Relative Humidity (%)
Climate Modeling LaboratoryMEASNC State University
The Scientific Question: Predictability of Moisture
• What are the dynamics governing the northward progression of the moisture regime?
• How well does the model represent the physical processes?
• What is the skill of the model in predicting the dynamics and statistics of the physical processes?
Climate Modeling LaboratoryMEASNC State University
In the literature• The West Africa summer monsoon is characterized by
two steps: preonset and onset (Sultan and Janicot, 2003)
• The preonset stage corresponds to the arrival of the Inter Tropical Front (ITF) at 15°N
From Sultan and Janicot (2003)
Rain (mm/day)
ITF
Climate Modeling LaboratoryMEASNC State University
Schematic Cross Section of the West African Monsoon
SaharaSahel10 N 20 NEquator
600 hPa
200 hPa
1000 hPa
ITCZ
Deep dry
convectionDe
ep
moi
st c
onve
ctio
n
AEJ
Slide from John Marsham, U. of Leeds
Climate Modeling LaboratoryMEASNC State University
Our Study• The northward progression of moisture is related
to the preonset stage of the monsoon and the position of the ITF
• Two important factors at work:– Interannual variability is dictated by fluxes in sea
surface temperatures (SST), interaction with mid-latitude systems (teleconnections)
– Intraseasonal variability is related to east-west transient disturbances, African Easterly Jet
Climate Modeling LaboratoryMEASNC State University
Data and Methods• NCEP/NCAR, ECMWF Reanalysis, In-situ
observations & satellite data: Statistics of Relative Humidity, etc
• We use the Advanced Research WRF (WRF-ARW) Model for downscaling of reanalysis and operational forecasts, sensitivity analyses
*NCEP: National Centers for Environmental Prediction*NCAR: National Center for Atmospheric Research*WRF: Weather Research and Forecasting Model*ECMWF: European Centre for Medium-Range Weather Forecasts
Climate Modeling LaboratoryMEASNC State University
Preliminary analysis and results
Climate Modeling LaboratoryMEASNC State University
0
20
40
60
80
1-Mar 15-Apr 30-May 14-Jul 28-Aug 12-Oct
Rel
ativ
e H
umid
ity (%
)Historical Data:
Reanalysis
• Mean 2000–2008 relative humidity time series (%) computed on the grid points located between 10°W and 10°E longitude, 14.5°N and 15.5°N latitude
Two distinct slopes
APR 15JUN 14
JUN 24
Climate Modeling LaboratoryMEASNC State University
April 1, 2006 relative humidity (%) at the surface, 925mb winds and u component at 0 to delineate ITF
Cross section along the prime meridian from 0° to 20 ° N: Relative humidity (shaded) and u component at 0 EQ 20N
700 mb
Model simulationsAEJ
Climate Modeling LaboratoryMEASNC State University
Ensemble Prediction
• We will use the ensemble prediction approach to generate probabilistic forecasts that will also allow us to analyze model skill
Climate Modeling LaboratoryMEASNC State University
An ensemble forecast run was tested against interpolated observations
Interpolated Observations Ensemble Simulation
Climate Modeling LaboratoryMEASNC State University
-10 -8 -6 -4 -2 2 4 6 8 10Relative Humidity Anomaly (%)
An ensemble forecast run was tested against interpolated observations
The error (anomaly) is much smaller than the signal
Climate Modeling LaboratoryMEASNC State University
Analyzing Model Skill
No Yes
No No cost ()
Miss()
Yes False Alarm()
Hit()
ObservationsE
PS
For
ecas
t
Climate Modeling LaboratoryMEASNC State University
The Relative Operating Characteristic (ROC)
0
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0.5
0.6
0.7
0.8
0.9
1
0 0.2 0.4 0.6 0.8 1False Alarm Rate
Hit
Rat
e
• The ROC method is widely used for estimating the skill of ensemble prediction systems (EPS) (Marzban, 2004)
• A perfect forecast system would have a ROC area (ROCA) of 1
Climate Modeling LaboratoryMEASNC State University
An Extended ROC Procedure• ROC plots model skill only for an optimum user
• We developed an extended (EROC) procedure that caters to a particular user’s needs:
0
0.1
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0.7
0.8
0.9
1
0 0.2 0.4 0.6 0.8 1False Alarm Rate
Hit
Rat
e
Base line for μ=ō(=0.33), Vmin=0
ROC
Base line for μ=0.25(<ō), Vmin=0
Base line for μ=0.40(>ō), Vmin=0
Shift in baselinesAccording to user
Semazzi & Mera, 2006
Climate Modeling LaboratoryMEASNC State University
Model Skill for End-user
• Additional analysis through EROC can help with current health efforts and the incurred costs:– Transportation of Supplies– Inoculation– Personnel
Climate Modeling LaboratoryMEASNC State University
Looking Forward
• Understanding the moisture regime statistics: variance of 40% RH date and changes in slope of humidity trends
• Sensitivity studies using SSTs, land cover, meridional transient distrubances, teleconnections with mid-latitude systems
• Application of EROC for surface conditions pertinent to health efforts
Climate Modeling LaboratoryMEASNC State University
Acknowledgements
• Dr Semazzi• CML crew• Google/UCAR group• NOAA ISET• Dr Arlene Laing, Dr Tom Hopson
Climate Modeling LaboratoryMEASNC State University
Questions?
Climate Modeling LaboratoryMEASNC State University
Auxiliary slides
Climate Modeling LaboratoryMEASNC State University
Historical Data: Reanalysis
• Mean 2000–2008 relative humidity time series (%) computed on the grid points located between 10°W and 10°E longitude, 14.5°N and 15.5°N latitude
Climate Modeling LaboratoryMEASNC State University
Large scale Climatology
Climate Modeling LaboratoryMEASNC State University
Large Scale Climatology
Climate Modeling LaboratoryMEASNC State University
Climate Modeling LaboratoryMEASNC State University
Criteria for Issuing a forecast
Decision to issue a forecast of an event (E) to occur is probabilistically based on the criteria:
p nN pt
Where:(N): size of the ensemble(n): number of the runs in the ensemble for which (E) actually occurs(p): probability given by the ratio (n/N)
This is the threshold fraction above which the event (E) is predicted to occur based on the model forecast
Climate Modeling LaboratoryMEASNC State University
Climate Modeling LaboratoryMEASNC State University
Climate Modeling LaboratoryMEASNC State University