STARDEX Deliverable D10

Objective

To recommend methodologies for identification of the best predictor variables for extreme events.

Responsible author

Clare Goodess, UEA

Outline

The STARDEX work described in the partner contributions to this deliverable indicates that the best predictor variables vary with region, season and predictand. Thus the D10 synthesis report focuses on methodologies for identification of the best predictor variables and makes recommendations as to how the process can be carried out as objectively as possible.

Reports

• Synthesis Report - coming soon
• ARPA-SMR: EOF, CCA and regression (Emilia Romagna)
• AUTH: Circulation/precipitation frequencies, ratios, trends and correlations (Greece)
• CNRS: Potential precipitation circulation index (French Alpes Maritimes)
• DMI: Stationarity of predictor-predictand relationships (Europe)
• FIC: Theoretical considerations
• KCL: Stepwise multiple linear regression, ranking procedure, genetic algorithm (UK)
• UEA: Linear correlation (UK)
• USTUTT-IWS: Fuzzy rule optimisation, circulation pattern/precipitation frequency, trends and correlations (German Rhine)

Presentations

Slides from these presentations may be used provided that STARDEX is duly acknowledged.
• D10 synthesis report outline Clare Goodess, October 2003