climate4R is a bundle of R packages for transparent climate data access, post processing (including bias correction and downscaling) and visualization. Predictia has been involved in its development since an early stage, in collaboration with researchers from the Santander Meteorology Group (University of Cantabria-CSIC).
Our workmate Markel García-Díez is presenting the study "Added value of a Kalman Filter in urban-scale forecasts in the city of Madrid" in the next European Meteorological Society annual meeting, that will take place in Budapest between the 3th and 7th of September 2018.
As part of the adapteCCa.es project, Predictia has developed a new visualization tool for climate change scenarios over Spain. This viewer allows to visualize and download data of the last generation of regional climate change projections over Spain.
Predictia has participated in the elaboration of the study "An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment" published in the journal International Journal of Climatology.
We have participated in a study titled "Tackling uncertainties of future projections from species distribution models with package mopa" which has been published in The R Journal.
Our colleague Joaquín Bedia has participated in the elaboration of the study "Background sampling and transferability of species distribution model ensembles under climate change" recently published in the journal Global and Planetary Change.