This course is devoted to prediction, which has two components; simulating scenarios (prediction sensu stricto) and forecasting (calculating future trends from past observations). For this, the course will review both numerical simulation methods and statistical time and space series analysis methods.
Cohort: 2017, 2018
Semester 1
Semester 2
Semester 3
Semester 4
ECTS
6
FUTURE SEAS
Numerical methods for marine science
Sorbonne University
Synopsis
Content
Numerical Simulation
Data assimilation
Time Series Analysis
Time Series Forecasting
Spatial Statistics
Pre-requisites
Basic Statistics and Basic Modelling
Aims
Understanding the concepts and the methods to predict trends in biological oceanography.
Objectives
Learning numerical and statistical methods allowing to predict future trends in biological oceanography. Understanding methods of data assimilation and optimal control used in biological oceanography and resources management.
Key skills acquired
Numerical and Statistical Methods
Programming (R and Scilab)
Bibliography
None
Assessment
30% Written Exam
70% Personal Project Reporting
Involved teachers
Jean-Marc Guarini
Contact hours
lectures
25
practicals
35
seminars
0
computerclass
35
fieldwork
0
other
0