WEATHER FORECASTING (CLIMATE SCIENCE II)

Reasons to study this course:
• More sustainable resource management – farming, horticulture, infrastructure
• Managing operations – daily work in all industries needs to be planned around weather
• Broaden and deepen an understanding of climate

Learn to understand how weather can be predicted. Observing patterns and understanding factors that affect weather, it is possible to predict what weather conditions are more likely. 

By understanding the likelihood of weather patterns:
• 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
• Tourism industry

Weather prediction is an application of science that impacts the lives of many people. Weather forecasting is simply an attempt to predict the atmospheric conditions at some point of time in the future. How we do this is fascinating.  

Learn how to use modelling to predict near-term and long-range weather patterns. 

There are eight 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

 

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 
 
Scroll to the top of the page to review your enrolment options. We have daily intakes!