Statistical Climatology, 7.5hp
The course covers basic statistical tools that are used to analyze weather and/or climate data, in time series or gridded fields.
Learning outcomes
After taking the course the student should be able to analyse weather/climate time series for trends, power spectra, probability distributions and relationships between times series vis, e.g. simple and multiple regression, and evaluate significance and hypothesis testing. For weather/climate fields, the student should be able to identify and interpret the modes of variability and/or propagating patterns and their associated explained variance.
Content
- Basic Concepts of probability and statistics in weather and climate,
- Stationary time series
- Statistical significance and hypothesis testing
- Spectral analysis
- Regression analysis
- Empirical orthogonal functions and extensions
- Analysis of variance – ANOVA
- Extreme value analysis and MCMC estimation
Compulsory elements
Computer lab
Examination
Assignment in the form of a written project
Teaching
Lectures and computer lab
Schedule
The course does not run every year. A detailed schedule is announced in connection with each course instance.
Literature
- Hannachi, A., 2021: Statistical Climatology, PhD course.
- Hannachi A., 2021: Pattern Identification and Data Mining in Weather and Climate. Springer
- Hannachi et al., 2007: EOFs and related techniques in atmospheric Science. Int. J. Climatol., 27, 1119-1152.
- V. Storch and F Zwiers, 1999: Statistical Analysis in Climate Research. Springer.
Responsible teacher - contact
Abdel Hannachi (a.hannachi@misu.su.se)
Last updated: September 20, 2024
Source: MISU