An R package for daily precipitation climate series reconstruction

15 Pags. - 3 Figs. The definitive version, with Appendix and Supplementary Data, is available at: http://www.sciencedirect.com/science/journal/13648152Daily precipitation datasets are usually large, bulky and hard to handle, but they are of key importance in many environmental studies. We developed a tool to create custom datasets from observed daily precipitation records. Reference values (RV) are computed for each day and location using multivariate logistic regression with altitude, latitude and longitude as covariates. The operations were compiled in an Open Source R package called reddPrec. The reddPrec package consists of a set of functions used to: i) apply a comprehensive quality control over original daily precipitation datasets, flagging suspect data based on five predefined criteria; ii) fill missing values in original data series by estimating precipitation values using the 10 nearest observations for each day; and iii) create new series and gridded datasets in locations where no data were recorded.This study was supported by research projects CGL2012-31668, CGL2015-69985-R, CGL2011-24185 and CGL2014-52135-C3-1-R, financed by the Spanish Ministerio de Economía y Competitividad (MINECO) and FEDER-ERDF funds. We were financially supported by the Government of Aragón through the ‘Programme of research groups’ (groups ‘H38, Clima, Cambio Global y Sistemas Naturales’ and ‘E68, Geomorfología y Cambio Global’).Peer reviewe