Prediction Scheme Project
The aim of this project was to produce statistical-based daily weather predictions from on our ongoing Daily Analysis of Rainfall & Temperature (DART) Study. The project was conceived during the strict COVID-19 restrictions in 2020, and was intended for personal interest.
The resulting development is a statistical prediction scheme that produces daily predictions of temperature and rain in XML format for the following calendar year.
The scheme has desired outcomes that will evaluate its potential application and guide any further development. The experimental predictions are verified against the observations to assess the performance of the prediction scheme.
Predictions
Temperature predictions are expressed in whole degrees and represent the mean maximum and minimum temperatures in the DART Study on the given date.
The maximum temperature prediction applies to the 24 hours beginning at 9.00 am on the given date, which conforms to our standard observing practice.
The minimum temperature prediction applies to the 24 hours ending at 9.00 am on the given date, which conforms to our standard observing practice.
Rain predictions are given as a chance and possible rainfall. The prediction applies to the 24 hours ending at 9.00 am on the given date, which conforms to our standard observing practice.
Chance is expressed as a percentage. It compares the number of times that daily rainfall of 0.1 mm or more occurs in the DART Study on the given date, with the total number of daily rainfall observations in the DART Study on the given date.
Possible rainfall is expressed as a range: ≥ 0.1 mm, ≥ 1.0 mm, ≥ 10.0 mm and ≥ 25.0 mm, and represents the most common rainfall range in the DART Study on the given date. In the event that two or more ranges tie for the rank of most common, the higher rainfall range shall be represented.
Warning » These predictions are strictly experimental. They are based solely on the statistical analysis of past weather data and are devoid of any meteorological rationale.
Desired Outcomes
The future of the scheme, including any further development, depends on how it performs in the context of these ambitious outcomes.
- A high percentage of rain predictions (rain or dry) proven to be correct, conversely a low percentage of rain predictions proven to be incorrect.
- A high percentage of predicted rainfall is in the same range or overestimate the observed rainfall.
- A low percentage of predicted rainfall that underestimate the observed rainfall.
- A high percentage of predicted maximum temperatures from April to September within +/- 2° C of the observed temperatures.
- A high percentage of predicted maximum temperatures from October to March within +/- 5° C of the observed temperatures (preferably +/- 2° C).
- A high percentage of predicted minimum temperatures from April to September within +/- 2° C of the observed temperatures.
- A high percentage of predicted minimum temperatures from October to March within +/- 5° C of the observed temperatures (preferably +/- 2° C).
- Increased reliability over time as the volume of daily weather data expands further.
Verification
Verification is an automated four stage process using the scheme's inbuilt verification algorithms. Stage one deals with temperature, the remaining stages deal with rain.
Stage one rounds the predicted and observed maximum and minimum temperatures to the nearest whole degree, and then calculates the difference by subtracting the predicted value from the observed value.
Stage two classifies each rain prediction as either correct or incorrect.
Stage three selects the correct predictions of rain and then further classifies each case according to whether the predicted rainfall range: (1) matches the observed, (2) overestimates the observed, or (3) underestimates the observed.
Stage four selects the occasions when rain was predicted and did not eventuate. The predictions are based on chance and it is therefore reasonable to expect that not all will eventuate, particularly if the chance is low. The verification estimates the number of cases that could reasonably be expected to be dry, and recommends an adjustment to the assessment in stage two.
Project Status
This 2020 project was run in experimental mode from mid 2020 to December 2025. It successfully achieved its aims but is now closed.