Validation of 3-day rainfall forecast at the regional scale

Raquel Melo; Sandra Oliveira; Ricardo Tomé; Alexandre M Ramos; Sérgio C Oliveira

doi:10.1016/j.mex.2023.102071

Validation of 3-day rainfall forecast at the regional scale

MethodsX. 2023 Feb 11:10:102071. doi: 10.1016/j.mex.2023.102071. eCollection 2023.

Authors

Raquel Melo^{1

2}, Sandra Oliveira^{1

3}, Ricardo Tomé⁴, Alexandre M Ramos^{4

5}, Sérgio C Oliveira^{1

3}

Affiliations

¹ Centro de Estudos Geográficos, Instituto de Geografia e Ordenamento do Território, Universidade de Lisboa, Lisbon 1600-276, Portugal.
² Instituto de Ciências da Terra, Universidade de Évora, Evora 7000-671, Portugal.
³ Associate Laboratory, TERRA, Portugal.
⁴ Instituto Dom Luiz, Faculdade de Ciências da Universidade de Lisboa, Lisbon 1749-016, Portugal.
⁵ Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany.

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.•A routine to validate the rainfall forecast at the regional scale using R programming language is implemented.•The automated routine can be easily updated and adapted with different spatial and temporal scales.

Keywords: Automatic meteorological stations; Forecast validation; R software; Rainfall forecast; Validation of 3-day rainfall forecast at the regional scale.