Climate Science II - Forecasting Weather

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

Learn How Weather Conditions are able to be Predicted

Weather forecasting can predict on a fine scale such as hourly, or as far into the future as required.

It is important however to remember that with weather forecasts, the more data available and the closer time frame, the greater probability of prediction accuracy. A two-day forecast will have a greater accuracy than a 2-week forecast.

Learn how modelling can be used to predict near term and long term weather patterns.

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

Why Study this course?

People could choose to study this course for many different reasons.

  • Some seek more knowledge and skills to better manage their properties - farmers, horticulturists, land managers
  • Some want a better understanding of climate change
  • Others may seek to better manage how they operate at work - planning and managing what they do where and when, according to likely weather conditions.

What can be gained from better Weather Prediction?

By understanding weather patterns, and likely conditions at different times:

  • Farmers can plan better
  • Construction workers, urban planners and infrastructure managers can organise operations better.
  • Logistics can be planned and supply of goods and services can become more efficient
  • Air, sea and land transport can be navigated better
  • Water resources may be managed more sustainably
  • Extreme events can be better prepared for

Whatever your reason for being able to better understand the weather; this course can potentially be a significant answer to your need.