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Data Analysis in Meteorology and Oceanography

Language

English

Course format On-site
Date 2020-08-19 - 2020-12-07

Objectives and Content

Aim and Content

The course provides a basic introduction to statistical methods commonly applied in analysis of observed simulated quantities in oceanography and meteorology. This includes descriptive statistic, hypothesis testing, and probability distribution. The course will further contain frequency analysis and filtering of time series, and methods for identifying spatial coherences such as linear regressions, correlation analysis, and empirical orthogonal functions. The theory will be applied on geophysical problems.

Learning outcomes

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student:

  • knows hypothesis testing
  • can make inference based on a sample of data and quantify the uncertainty associated

Skills

The student:

  • can prepare and systemize observational and model data for statistical analysis
  • can present the results of the analysis
  • can compute correlations and regressions between time series
  • can determine the frequency spectrum of a time series
  • can deduce the spatial structure of data

General competence

The student:

  • is able to compute and assess basic statistical properties
  • is able to synthesize the result of analyzes in a scientific report

Prerequisites

GEOF105 or equivalent.

Recommended Previous Knowledge

Background in meteorology and/or oceanography; basic training in statistics.

Files/Documents

ISCED Categories

Physical and chemical oceanography
Statistics