Climate Science II - Weather Forecasting


Study the application of weather forecasting to different practical and commercial situations.

Course CodeBSC309
Fee CodeS3
Duration (approx)100 hours
QualificationStatement of Attainment


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Learn how to predict the weather

 

Weather forecasting is never 100% accurate, but by observing patterns and understanding the factors that influence weather it is possible to predict what weather conditions are more or less likely.

If you have any self or professional interest in the environment, science and climate, you don't need to look any further. 

This course leads you through key elements of weather forecasting. You need to study this if you:

  • have any personal interest in understanding weather patterns
  • work in any industry which is impacted by weather
  • need specialist knowledge which supports your business practices 

We can't escape or control weather, therefore it is vital that we learn how to work with it for the best possible outcomes. 

 

 

 

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.

This course can find practical application in a wide variety of situations, including:

  • Farmers can plan better
  • Urban managers can plan better
  • Gardeners, landscapers, land managers can manage short & long term work better
  • Water and land resources can be better managed
  • Planning and managing events & activities
  • Managing severe conditions
  • Navigation – flying, sailing
  • Anyone enjoying outdoor pursuits and activities 

 

This course will lead to: 

  • your appreciation of the significance of weather forecasting 

  • your understanding of how much value and risk is placed on weather forecasts 

  • your understanding of the implications of probabilities on every day life 

  • your insight into decisions which benefit business or performance 

  • your increased awareness of data modelling 
 

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Dr Robert Browne

Zoologist, Environmental Scientist and Sustainability, science based consultancy with biotechnology corporations. Work focused on conservation and sustainability. Robert has published work in the fields of nutrition, pathology, larval growth and develop