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MT12CNU-Skills for Environmental Science
Module Provider: Meteorology
Number of credits: 20 [10 ECTS credits]
Level:4
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2019/0
Email: k.morrison@reading.ac.uk
Type of module:
Summary module description:
This module introduces instruments and techniques used to measure meteorological parameters, basic skills in observation, data collection, analyses and management, as well as developing skills in computer programming useful in environmental science.
The Module lead at NUIST is Yanwei Li.
Aims:
• To introduce the instruments and techniques used to measure meteorological parameters, and to appreciate their limitations;
• To observe meteorological parameters in the observing field.
• To develop skills in computer programming useful in environmental science, for data processing and analysis.
Assessable learning outcomes:
• Knowledge of meteorological instruments and their application;
• Ability to observe parameters, including an appreciation of experimental errors;
• Ability to use observation software to read, analyze, collect, manage meteorological data.
• Ability to communicate experimental results in a concise, accurate and comprehensible manner;
• Ability to understand basic computer programming principles;
• Ability to construct a simple computer program to perform logical and numerical operations;
• Ability to perform simple science data processing tasks using a computer program and spreadsheet tools.
Additional outcomes:
The student will develop enhanced team-working and basic experimental skills.
Outline content:
- First half: Generic characteristics of instruments for environmental measurement, as determined by response, sensitivity, lag, sampling and error analysis. The design, operation of instruments used to measure temperature, humidity, wind, pressure, broadband solar and
- terrestrial radiation, rainfall and upper air properties;
- Second half: Basic understanding of programming for environmental data analysis including: code readability and commenting, variables mathematical and logical operators, conditional branching, conditional loops, functions, reading data from files, plotting, module structure.
Brief description of teaching and learning methods:
The instrumentation and practical components are taught in the weeks 1-8 of the semester and involve 16 45-minute lectures plus approximately 16 hours of practical work. The IT component is taught in the weeks 9-16 of the semester and involve practical classes with a strong self-learning element supported by notes and demonstrations.
Ìý | Autumn | Spring | Summer |
Lectures | 56 | ||
Practicals classes and workshops | 40 | ||
Guided independent study: | 104 | ||
Ìý | Ìý | Ìý | Ìý |
Total hours by term | 0 | 200 | 0 |
Ìý | Ìý | Ìý | Ìý |
Total hours for module | 200 |
Method | Percentage |
Report | 66 |
Set exercise | 34 |
Summative assessment- Examinations:
Summative assessment- Coursework and in-class tests:
Formative assessment methods:
For the practical component, the student is required to submit one report for formative assessment
Penalties for late submission:
The Module Convener will apply the following penalties for work submitted late:
The University policy statement on penalties for late submission can be found at:
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
Assessment requirements for a pass:
40% overall
Reassessment arrangements:
September examination only.
Additional Costs (specified where applicable):
Last updated: 13 May 2019
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.