FYS340 Environmental and climate measurements and models

Credits (ECTS):5

Course responsible:Mareile Astrid Wolff

Campus / Online:Taught campus Ås

Teaching language:Engelsk, norsk

Limits of class size:25

Course frequency:yearly

Nominal workload:

The standard workload is 25 hours per credit (including structured learning activities and independent study/self-study).

The course will include lectures, independent work, and joint seminars.

Teaching and exam period:Teaching and exam in the January block

About this course

climate models
meteorological in-situ measurements
remote sensing as a tool for monitoring the environment

Learning outcome

general introduction in climate modelling, data collection from ground-based stations and remote sensing methods.
Overview of strengths and weaknesses of those methods

You'll learn

to run a simple climate model
to find data sources from surface stations and learn to evaluate the data quality of different measurements
basics methods for analysing images taken from drones, planes and satellites
about the importance of metadata

Learning activities
lectures, case studies and presentations
Teaching support
Web page with course information and resources. Students will be able to meet the lecturers, with appointment.
Syllabus
Available at course start.
Prerequisites
- FYS241 Environmental physics
- FYS140 Climate change, sustainability and adaptation
- FYS141 Meteorology for sustainable development
Recommended prerequisites
- INF250 Image Analysis
- FYS103 Experimental Methods and Data Analysis
Assessment method
Assessment Method
Oral presentation with A-F grading
Mandatory Activity
Each participant must actively engage in individual and group tasks across all three weekly themes. Active participation is required for permission to take the exam.
About use of AI
K2 - Specified use of AI
In student activities and exam preparation, AI can be used for brainstorming, language editing, and programming support. The use of AI must be accompanied by a brief explanation of which programs were used and how they were applied. Students are responsible for the final content of the text and must be able to explain how their analysis programs work
All use of AI must comply with the guidelines for the use of artificial intelligence (AI) at NMBU.
Descriptions of AI-category codes.
Examiner scheme
The external examinator is present at the final seminar/oral exam.
Mandatory activity
Attendence is manditory for the first lecture, the weekly seminars and the final seminar. Also the students have to actively participated in the case study work and preparation of presentations.
Teaching hours
ca. 15 hours lectures, 6 hours seminar and whole day final seminar
Preferential right
M-MF, M-IØ, M-LUN