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Validation of 3-day rainfall forecast at the regional scale

Melo, Raquel; Oliveira, Sandra ; Tomé, Ricardo; Ramos, Alexandre M. 1; Oliveira, Sérgio C.
1 Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO), Karlsruher Institut für Technologie (KIT)

Abstract:

Nearly half of the natural disasters in the world are due to hydro-geomorphological hazards. Therefore, rainfall forecast is a key parameter for the implementation of landslides and flash-floods early warning systems. In this work we developed a routine in R software that enables the validation of a 3-day rainfall forecast by comparison with the daily rainfall data recorded in 101 automatic meteorological stations available in mainland Portugal. The routine integrates the pre-processing of base data, the matching between the 3-day rainfall forecast and the daily rainfall registered in the automatic meteorological stations based on sequence of days, the estimation of the difference between the forecasted and the real rainfall values and the computation of error measures, such as the bias, the mean absolute error, the mean absolute percentage error and the root mean square error. The results from the error measures, estimated for the 101 automatic meteorological stations, are then exported to an excel file. The routine is implemented for mainland Portugal and tested using data from February 2015, however, the spatial and temporal data can be easily updated for other regions.
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Verlagsausgabe §
DOI: 10.5445/IR/1000156363
Veröffentlicht am 02.03.2023
Originalveröffentlichung
DOI: 10.1016/j.mex.2023.102071
Scopus
Zitationen: 1
Dimensions
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 2215-0161
KITopen-ID: 1000156363
HGF-Programm 12.11.33 (POF IV, LK 01) Regional Climate and Hydrological Cycle
Erschienen in MethodsX
Verlag Elsevier
Band 10
Seiten Art.-Nr.: 102071
Vorab online veröffentlicht am 11.02.2023
Schlagwörter Rainfall forecast, Automatic meteorological stations, Forecast validation, R software
Nachgewiesen in Dimensions
Scopus
Globale Ziele für nachhaltige Entwicklung Ziel 11 – Nachhaltige Städte und Gemeinden
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