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

Academic year

2024/2025 Syllabus of previous years

Official course title

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

Course code

PHD166 (AF:545178 AR:311560)

Modality

On campus classes

ECTS credits

3

Degree level

Corso di Dottorato (D.M.226/2021)

Educational sector code

GEO/12

Period

2nd Semester

Course year

1

Where

VENEZIA

Contribution of the course to the overall degree programme goals

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.

Expected learning outcomes

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.

Pre-requirements

Basic knowledge of R and Python, IPCC/climate change scenarios and impacts assessments.

Contents

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.

Referral texts

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/

Assessment methods

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.

Teaching methods

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.

Teaching language

English

Further information

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.

Type of exam

oral

2030 Agenda for Sustainable Development Goals

This subject deals with topics related to the macro-area "Climate change and energy" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development

Definitive programme.

Last update of the programme: 09/10/2024