caio a. s. coelho centro de previsão de tempo e estudos climáticos (cptec) instituto nacional de...
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Caio A. S. CoelhoCentro de Previsão de Tempo e Estudos Climáticos (CPTEC)
Instituto Nacional de Pesquisas Espaciais (INPE)caio@cptec.inpe.br
1st EUROBRISA workshop, Paraty, 17-19 March 2008
Deriving South America seasonal rainfall from upper level circulation predictions
Conceptual framework
)y(p
)x(p)x|y(p)y|x(p
i
iiiii
Data Assimilation “Forecast Assimilation”
)x(p
)y(p)y|x(p)x|y(p
f
fffff
Stephenson et al. (2005)
Calibration and combination experiment
Common hindcast period: 1987-2005 (19 years)
y: observed rainfall (GPCP, Adler et al. 2003)x: predicted upper level (200 hPa) circulation
Use two EUROSIP model predictions: • ECMWF System 3• UK Met Office
Target season: DJFStart date: November (i.e. 1-month lead predictions for DJF)
NCEP/NCAR Reanalysis (Kalnay et al. 1996) is used to verify predicted upper level circulation
dy
du
dx
dv
Upper level circulation
u: zonal windv: meridional wind: stream function
': zonal mean of
: perturbed (eddy) stream function
'
uv
)v,u(V
Observed perturbed stream function
ECMWF perturbed stream function
UKMO perturbed stream function
Perturbed stream function verification
El Niño
Observed perturbed stream function anomaly
La Niña
Observed perturbed stream function anomaly
La Niña
El Niño
Observed perturbed stream function anomaly
El Niño
ECMWF perturbed stream function anomaly
La Niña
ECMWF perturbed stream function anomaly
El Niño
La Niña
ECMWF perturbed stream function anomaly
El Niño
UKMO perturbed stream function anomaly
La Niña
UKMO perturbed stream function anomaly
El Niño
La Niña
UKMO perturbed stream function anomaly
Perturbed stream function anomaly verification
)C,Y(N~Y b
)S),YY(G(N~Y|X o
Prior:
Likelihood:
Posterior:
),(~| DYNXY a
Calibration and combination procedure: Forecast Assimilation
qq:D
qn:Y
pn:X
qq:C q1:Yb
pp:S qn:Ya
Matrices
Stephenson et al. (2005)
Forecast assimilation uses first three leading MCA modes of the matrix YT X.
X: circulation predictions (ECMWF + UKMO)Y: DJF rainfall
)(
)()|()|(
Xp
YpYXpXYp
Forecast Assimilation: First MCA mode
Forecast Assimilation: Second MCA mode
Forecast Assimilation: Third MCA mode
Correlation between predicted and observed anomalies
Forecast AssimilationECMWF UKMO
Issued: November, Valid for DJF, Hindcast period: 1987-2005
Upper level circulation derived predictions obtained with forecast assimilation have comparable level of skill to indiv. model predictions
ECMWF UKMO Forecast Assimilation
Ranked Probability Skill Score (tercile categories)
Issued: November, Valid for DJF, Hindcast period: 1987-2005
Gerrity Score (tercile categories)
ECMWF UKMO Forecast Assimilation
Issued: November, Valid for DJF, Hindcast period: 1987-2005
Issued: November, Valid for DJF, Hindcast period: 1987-2005
ROC Skill Score (positive or negative anomaly)
ECMWF UKMO Forecast Assimilation
Issued: November, Valid for DJF, Hindcast period: 1987-2005
Reliability diagram (positive or negative anomaly)
ECMWF UKMO Forecast Assimilation
Forecast assimilation improves prediction reliability
ROC plot (positive or negative anomaly)
Issued: November, Valid for DJF, Hindcast period: 1987-2005
ECMWF UKMO Forecast Assimilation
Summary
• Forecast assimilation is a useful framework for exploring atmospheric teleconnections in seasonal forecasts
• ENSO atmospheric teleconnections is the main source of skill for South America rainfall predictions
• Combined and calibrated circulation derived predictions obtained with forecast assimilation have comparable level of skill to single model rainfall prediction
• Additional skill improvements can be investigated by including humidity predictions in the forecast assimilation procedure
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