Short course on use of R for analysing satelite-based rainfall estimates (SREs) in Germany
During the first week of May, I gave a short course to postgraduate students of the Institute for Technology and Resources Management in the Tropics and Subtropics (ITT) of TH Köln (University of Applied Sciences in Germany).
This course had two parts, the first one was given by the doctoral student Oscar Baez, who was at UFRO last April. The objective of this first part (April 23th to 27th) was to provide students with basic concepts about R, free software environment for statistical computing and graphics, (installation, types of variables, exploratory data analysis, and spatial data management). The second part (May 3rd and 4th) was to introduce participants to the management of time series in R, and the use of it for the analysis of spatio-temporal data, in particular for reading and analysing satelite-based rainfall estimates (SREs), expanding the work “Using R for analyzing spatio-temporal datasets: a satellite-based precipitation case study” presented at the EGUA 2017 during the last week of April (EGU2017-18343), which was an oral PICO presentation.
This short course is product of the international collaboration with Lars Ribbe and Alexandra Nauditt from the Institute for Technology and Resources Management in the Tropics and Subtropics (ITT) of TH Köln (University of Applied Sciences in Germany).
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I am an Associate Professor in the Department of Civil Engineering at the University of La Frontera. I hold a PhD in Environmental Engineering from the University of Trento (Italy) and completed postdoctoral training at the European Commission’s Joint Research Centre. I have more than 20 years of experience in water resources research and have previously served as an Associate Researcher at the Center for Climate and Resilience Research (CR)2 and as a member of the Earth Sciences Assessment Group of the Chilean National Research and Development Agency (ANID).
My research lies at the interface of hydrology, data science, and environmental sciences, with a particular focus on the use of gridded datasets and open-source tools to investigate droughts, extreme events, and water-related impacts of global change.
I work across spatial and temporal scales to improve the understanding of catchment-scale hydrological processes and to translate this knowledge into operational modelling, forecasting, and early-warning systems that support robust environmental decision-making.
Please reach out to collaborate 😃