CLIMATE SCIENCE II - Weather Forecasting

Learn to predict probable weather prediction. An online Science course exploring tools and techniques used by science to predict weather.

Course Code: BSC309
Fee Code: S3
Duration (approx) Duration (approx) 100 hours
Qualification Statement of Attainment
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Explore the Weather

  • scientific tools and techniques that can be used to predict weather
  • what weather conditions are more likely to prevail.

Weather Prediction might not be a perfect science; but by measuring, observing and analysing it is possible to predict what weather conditions are likely; in the short term and long term. This is so valuable in so many ways.

Appreciate the difference between climate and weather. Climate is the study of an environment or the pattern of seasonal change over long periods of time. Weather on the other hand is a short-term event. Weather predication or predicting what we expect to see over a period of weeks (for the most part)..

 

Lesson Structure

There are 8 lessons in this course:

  1. What to Measure
    • What is Weather Forecasting?
    • Weather Warnings
    • Weather forecasting
    • Impacts to people
    • Impacts for farming
    • Weather factors
    • Cloud cover
    • Minimum temperature
    • Maximum temperature
    • Dry bulb temperature
    • Wet bulb temperature
    • Wind speed
    • Wind direction
    • Precipitation
    • Absolute humidity
    • Relative humidity
    • Dew point
    • Mean sea level pressure
    • Station level pressure
    • Water vapour pressure
    • UV index
  2. Tools for forecasting
    • Equipment
    • Weather stations
    • Weather balloons and drones
    • Satellites
    • Recording, Storing and Processing Data
    • High Performance Computers
    • Numerical Weather Forecasting
    • What should be in a minimal weather station?
  3. Types of Forecasting
    • Persistence Forecasting
    • Climatological Forecasting
    • Use of a Barometer
    • Looking at the Sky
    • Nowcasting
    • Numerical Weather Prediction models
    • Statistical Forecasting
    • Analogue Forecasting
    • Ensemble Forecasting
  4. Weather Models
    • Introduction
    • Weather models data sets and global weather models
    • ECMWF
    • GFS
    • How Weather Models are Built
    • Grid size
    • Problems with the Grid
    • How do parameterisations work?
    • Model Uncertainty
    • Data Assimilation
    • Mesoscale/Regional models
    • The Human Element of Weather Modelling
  5. Predicting Temperature
    • Diurnal temperature variation
    • Forecasting maximum temperature
    • Forecasting minimum temperature
    • Effect of snow cover
    • Severity of frost
    • Forecasting grass minimum temperature
    • Minimum temperature on road surfaces
    • Heat Stress Determination
    • Urban Heat Island
  6. Predicting Rain
    • Introduction
    • Convection and Showers
    • Forecasting convective cloud
    • Forecasting showers
    • Forecasting cumulonimbus and thunderstorms
    • Layer clouds and precipitation
    • Layer cloud formation
    • Condensation trails
    • Orographic rainfall
    • Formation of stratocumulus
    • Precipitation associated with layered clouds
    • Snow
  7. Air Conditions
    • Introduction
    • Air Quality
    • Air Pollution and Its Effect on Climate
    • Carbon Dioxide
    • Methane
    • Airborne Chemicals
    • Air Particles
    • Pollen and Allergies
    • Radon
    • Wind and Turbulence
    • Mechanical Turbulence
    • Thermal Turbulence
    • Frontal Turbulence
    • Wind shear
    • Humidity
    • Visibility
  8. Practical Applications
    • Introduction
    • Severe Weather Alerts
    • Aviation
    • Marine
    • Agriculture
    • Forestry
    • Utility Companies
    • Private Sector
    • Military
    • Medicine and Human Health
    • Waves and surges

Each lesson culminates in an assignment which is submitted to the school, marked by the school's tutors and returned to you with any relevant suggestions, comments, and if necessary, extra reading.

Aims

  • Determine where and when to measure factors affecting weather in order to predict weather conditions with relative and economically viable probability in any designated place.
  • Describe the use of different tools and equipment used to measure and analyse weather conditions.
  • Compare different types of forecasting to select the most appropriate type for situations encountered.
  • Explain how weather models are constructed and what they mean.
  • Explain how temperature ranges might be predicted.
  • Describe how rainfall is predicted in the short, medium, and long term.
  • Predict air conditions including humidity, turbulence, visibility, pollutants,
  • Apply an understanding of weather forecasting in practical ways to different industries.

Your opportunity to learn about weather forecasting.

Understanding the likelihood of weather patterns can benefit many different industry sectors. When you know what conditions are likely, the risk of disruption to work can be reduced, and that can over time translate to significant cost savings. Land and other resources can be managed for improvements to productivity and sustainability.

Studying this course will strengthen and broaden your understanding of climate change, helping you to observe, appreciate and respond to the environment around you, as the years roll by.

 

Who might benefit from doing this course?:

  • Gardeners, landscapers, land managers can manage short & long term work better
  • Farmers can plan better
  • Urban managers can plan better
  • Water and land resources can be better managed
  • Planning and managing events & activities
  • Managing severe conditions
  • Navigation – flying, sailing
  • Tourism industry
  • Students of horticulture, agriculture, ecology, environmental management and other relevant subjects.
 

 

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Course Contributors

The following academics were involved in the development and/or updating of this course.

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