LABS - DATA, TOOLS AND METHODS FOR EARTH SCIENCES – PRACTICALS

Anno accademico
2024/2025 Programmi anni precedenti
Titolo corso in inglese
LABS - DATA, TOOLS AND METHODS FOR EARTH SCIENCES – PRACTICALS
Codice insegnamento
PHD166 (AF:537745 AR:311560)
Lingua di insegnamento
Inglese
Modalità
In presenza
Crediti formativi universitari
3
Livello laurea
Master di Secondo Livello (DM270)
Settore scientifico disciplinare
GEO/12
Periodo
II Semestre
Anno corso
1
Sede
VENEZIA
Spazio Moodle
Link allo spazio del corso
Big data and cloud computing are rapidly evolving topics in Earth Sciences. Understanding the data types and limitations, in addition to the methods and tools, are basic fundamental building blocks for analysis and applications of earth observations data. The aim of this LABS is to make students familiar with state-of-the-art tools and data repositories that can prepare them to address various challenges when handling big data in earth sciences.
The course will introduce students to recent tools, methodologies, data repositories and advancements in computing infrastructures applicable in Earth Sciences, with special emphasis on climate impacts and risk assessment. Students will develop an understanding of various observational/model simulated data sources, scope and limitations of usage, and tools to access and process Earth Sciences' data on cloud computing infrastructures.
Basic knowledge of R and Python, IPCC/climate change scenarios and impacts assessments.
Overview of climate data variables, repositories, cloud computing and earth system grid infrastructures, such as: Earth System Grid Framework -ESGF, Copernicus Climate Data Store, Microsoft Planetary Computer, Google Earth Engine and Google Colab, commonly used data types and software environments used in earth science (e.g. Vector and Raster file types, NetCDF fIle format, NetCDF command line operators, R, Python).
Understanding limitations of observations, reanalysis and model simulated climate data products.
In addition to the material provided in each lecture (which includes slides, data and scripts), additional information on below weblinks will be useful:
https://open-meteo.com/
https://earthengine.google.com/
https://planetarycomputer.microsoft.com/
climate.copernicus.eu
copernicus.eu
ecmwf.int
https://colab.research.google.com
https://jupyter.org/
During the course, the students will be asked to participate in interactive sessions (coding skills) and graded on their active engagement and a general understanding of programming concepts. These will count towards 100% for the final grade.
orale
Each lecture will combine a frontal lecture and in-class activities (hands-on sessions using sample data and analysis/scripts prepared in R, Python and cloud computing). Activities will allow students to advance their knowledge of the commonly used methods and tools for analysing earth observations data. Students are expected to bring their laptops in each session.
Further details about readings, required data and software installation including practical exercises will be communicated at the beginning of the course and published on Moodle.

Questo insegnamento tratta argomenti connessi alla macroarea "Cambiamento climatico e energia" e concorre alla realizzazione dei relativi obiettivi ONU dell'Agenda 2030 per lo Sviluppo Sostenibile

Obiettivo 7: energia pulita e accessibile
Obiettivo 13: agire per il clima
Programma definitivo.
Data ultima modifica programma: 09/10/2024