LABS - DATA, TOOLS AND METHODS FOR EARTH SCIENCES - INTRODUCTION

Academic year
2022/2023 Syllabus of previous years
Official course title
LABS - DATA, TOOLS AND METHODS FOR EARTH SCIENCES - INTRODUCTION
Course code
PHD165 (AF:401924 AR:222254)
Modality
On campus classes
ECTS credits
3
Degree level
Corso di Dottorato (D.M.45)
Educational sector code
GEO/12
Period
2nd Semester
Course year
1
Where
VENEZIA
Moodle
Go to Moodle page
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.

Overview of 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 weblink are useful:

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.
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.
English
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.
oral

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

Goal 7: affordable and clean energy
Goal 13: climate action
Definitive programme.
Last update of the programme: 09/05/2023