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EAE2011 · Environmental problem solving and visualisation

Official Handbook

2026 Handbook6 credit pointsLevel 2School of Earth, Atmosphere and Environment

Last checked: 23 Aug 2026 UTC

Overview

This unit will provide you with the ability to solve a wide-ranging set of common problems in environmental and climate science. Through practical problem solving it will introduce quantitative methods and techniques used in environmental and climate science to analyse data, to build scientific models and to visualise key results. Simple techniques and methods from the fields of mathematics, physics and information technology will be introduced in the context of real-world problems and will enable you to apply these necessary skills in the higher level units in the Earth science major streams of Earth's physical environment and Earth's climate. You will develop skills in computer coding and numerical simulations (with R-studio) to address environmental science problems. The methods learned in this unit are highly valued for academic research and in the professional workforce.

Areas of study: Climate and atmospheric science Earth science Environmental science Geographical science Human geography

Offerings

CampusTeaching periodMode
ClaytonFirst semesterTeaching activities are on-campus (ON-CAMPUS)

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

#AssessmentTypeWeightHurdle
1Problem solving activitiesDemonstration25%
2AssignmentsExercise25%
3Major projectProject50%

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

  1. Describe basic methods for data analysis and scientific modelling of earth, environmental and climate science.
  2. Perform statistical analyses of environmental and climate data sets with numerical methods and visualise results using common tools, such as the programming language R.
  3. Create simple quantitative models based on theoretical knowledge or statistical data analysis.
  4. Communicate clearly the interpretation of earth, environmental and climate data and models .

Workload

• One 2-hour practical class; • One 2-hour workshop; and • Seven hours of independent study per week.

ActivityDuration
Practical activities24 hours
Workshops24 hours

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