PREVISIONI STAGIONALI

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Consiglio Nazionale delle Ricerche
Rainfall seasonal forecasting in the Sahel
region an analogue algorithm approach.
5th Annual Meeting of the European
Meteorological Society (EMS)7th European
Conference on Applications of Meteorology (ECAM)
12-16 September 2005
F. Piani, M. Pasqui, F. Meneguzzo, G.
Maracchi IBIMET-CNR
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Seasonal Forecasting Motivations

• Why a new seasonal forecasting method is
  needed?
• New insights on African Monsoon physical
  mechanism and SST role on precipitation
  (VizyCook2001, Giannini et al 2003).
• A monthly anomaly data is needed, at least, for
  any agrometeorological application seeding time
  and early warning systems.

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Motivations 2

• Giannini et al.
• Southern Sahel Precipitation is positive
  correlated with Guinea Gulf SST
• Northern Sahel Precipitation is negative
  correlated with Indian and Central Pacific SST

• Interannual variability due to Niño
• Long term trend due to slow Atlantic and Indian
  Ocean variability

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Analogues method an overview

• OUTPUT Precip. Anomaly vs. 1979-2003 Clim.
• ISSUED every month
• VALIDITY Quarterly and Monthly

• SST as Predictors over
• Niño-3 (5S-5N150W-90W)
• Guinea Gulf (10S-5N20W-10E)
• Indian Ocean (5S-15N60E-90E)

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Method

• Standardized Anomalies (SSTA) obtained by
• Subtraction of the 1979-2003 SST average
• Division by 1979-2003 SST standard deviation
• Standardized Change Rates to consider the trend
  of the predictors defined as difference between
  current and previous standardized SSTA
• Standardization is used to have the same order
  of magnitude of all the predictors

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Search for the Analogue
Each month in 1979-2003 is defined by a vector
in a 6 dimentional space

• Predictors Pi
• SST Nino-3 std anomalies
• SST Guinea std anomalies
• SST Indian std anomalies
• SST Nino-3 Change rate
• SST Guinea Change rate
• SST Indian Change rate

Analog criterion Minimization of the Euclidean
distance in the 6-dimensional space of predictors
Pi
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Seasonal Forecast Step by Step
CURRENT MONTH e.g. April 2005
ANALOGUE YEAR e.g. April 1989
MONTH1 e.g. May 2005 May 1989
MONTH2 e.g. June 2005 June 1989
MONTH3 e.g. July 2005 July 1989
CLIMATOLOGICAL AVERAGE e.g. May, June, July
1979-2003
ANOMALIES
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IBIMET Seasonal Products
http//www.ibimet.cnr.it/Case/sahel/
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Seasonal Rainfall Forecasts
http//www.ibimet.cnr.it/Case/sahel/
AMJ - Anomaly
May Percent Anomaly
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Qualitative Comparison
1998
Good Accordance
JAS issued on June
1999
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Qualitative Comparison
2001
Good Accordance
2003
JAS issued on June
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Qualitative Comparison
Good Accordance
2004
JAS issued on June
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Qualitative Comparison
2000
Bad Accordance
2002
JAS issued on June
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Qualitative Comparison
AMJ issued on March
Good Accordance
2005
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Ongoing Activities

• Quantitative Validation
• Definition of POD, FAR, ROC curve.
• Further method development
• Sensitivity study to the adopted metric.
• Possible displacements of active SST areas.
• Use of Forecast SST anomalies from ECMWF as
  Predictors.
• Possible inclusion of the SST of the
  Extra-Tropics North Atlantic (Mauritania) as
  predictor.
• Evaluation of a possible extension of the method
  to the temperature anomalies over Mediterranean
  Basin.

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Conclusion

• The improving of seasonal forecasts on Sahel
  region, especially for agrometeorological
  applications, should include a full comprehension
  of physical mechanism including Hadley Cell
  dynamics.
• The present spatial resolution should be
  improved in order to obtain an useful
  geographical information input for
  agrometeorological models ( 10km ).
• Dissemination of seasonal forecast information
  should take into account the new web-based tools
  such as Map Server.
• The method, due to its direct link with some
  physical mechanism, could be use as an
  independent tool for further analysis with other
  statistic approaches.