Industry stakeholders have highlighted issues with widely used weather and climate datasets that they say can cause significant errors for building energy modellers.
Since August 2021, the CSIRO has distributed free weather and climate datasets for use by building energy modellers for estimating HVAC energy demand and consumption, as well as moisture management under typical climatic conditions. The datasets are widely used to demonstrate compliance with energy-efficiency provisions in the NCC, and also to help attain higher NABERS Energy ratings.
But the team at weather and climate data specialist Exemplary Energy has highlighted a number of what it says are issues with the datasets supplied through the CSIRO:
- A 60-minute timing offset in the instantaneous weather elements – dry-bulb temperature, humidity, wind speed and others.
- A 30-minute offset in solar elements
- A lack of precipitation data, despite the need for it in moisture modelling
- It is based on weather observations that ended in 2015
- Its indicative months are selected for simulation of solar systems including passive solar houses, when more weight should be given to temperature and humidity in selecting indicative months for non-residential buildings.
Exemplary Energy has quantified the impacts of the timing errors – points one and two in the list above – and says the resulting errors to be significant.
“We identified that the errors produced erroneous results in the order of 5–10 per cent during the cooling season and 25–30 per cent during the heating season, or about 7 per cent annual HVAC energy,” says Exemplary Energy’s Dave Ferrari, Affil.AIRAH.
“They also have significant impacts on the calculation of the timing and magnitude of simulated peak loads, but these are harder to quantify.”
Ferrari says his team has not yet quantified the difference from characterising the climate using up-to-date data rather than the period ending in 2015.
“But we do note that our ongoing changing climate means that older data is far less relevant to the climate that a building will experience during its operating lifetime,” he says.
Overall, Ferrari says practitioners should be concerned that their use of flawed data will provide misleading results, and will likely influence building design in ways that result in reduced efficiency.
Building modellers can purchase datasets that avoid these issues from commercial providers. Exemplary Energy provides such datasets, but it is also calling for the freely available files to be corrected.
“The issues need to be considered by policy-makers and modellers alike,” says Ferrari. “We have advised our colleagues at CSIRO of these findings, and will continue to work with them to avoid further propagation of the errors and offer our support to improve the data going forward.
“We urge policy-makers to be mindful of these issues, as modelling inaccuracies arising now are embedded in building operations for many years to come.”
Image by Pete Linforth from Pixabay