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Heavy Rainfall Warning Assessment Tool User Guide. Version 1.2

Jones, A. E.; Jones, D. A.; Moore, R. J.; Robson, A. J.. 2004 Heavy Rainfall Warning Assessment Tool User Guide. Version 1.2. Wallingford, NERC/Centre for Ecology & Hydrology, 65pp. (CEH Project Number: C02161)

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Abstract/Summary

This report is a User Guide to a PC tool for assessing Heavy Rainfall Warnings. Development of the PC tool formed an important operational output of the Environment Agency and Met Office funded project: "Development of Rainfall Forecast Performance Monitoring Criteria. Phase 1: Development of Methodology and Algorithms" (Jones et al., 2003). The Heavy Rainfall Warning (HRW) Assessment Tool is a toolkit for Microsoft Excel. The tool allows the user to configure an assessment framework for a particular format of Heavy Rainfall Warning, enter and save data for forecasts and ground-truths, and generate a range of performance measures and other statistics for new and previously saved data. Summary tables are presented using Excel's PivotTable feature, from which charts can also be generated. Performance measures are provided to assess forecasts of heavy rainfall in continuous variable, categorical and probability form: these include bias, rmse, R-squared Efficiency, skill scores and the Continuous Brier Score.

Item Type: Publication - Report (UNSPECIFIED)
Programmes: CEH Programmes pre-2009 publications > Water
CEH Sections: Boorman
Funders/Sponsors: Environment Agency, Met Office
Additional Information. Not used in RCUK Gateway to Research.: For Additional Information contact the CEH Project Leader R. J. Moore rm@ceh.ac.uk The standard citation for this publication is: Jones, A.E., Jones, D.A., Moore, R.J., Robson, A.J. (2004) Heavy Rainfall Warning Assessment Tool User Guide. Report to the Environment Agency and the Met Office, CEH Wallingford, 65pp.
Additional Keywords: Rainfall, forecast, performance, assessment, verification
NORA Subject Terms: Meteorology and Climatology
Hydrology
Date made live: 24 Mar 2009 10:15
URI: http://nora.nerc.ac.uk/id/eprint/6743

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