Short, extreme rainfall events will increase in a warming climate, according to observations and climate models. Australian observations suggest these storms become smaller in size, with increased rainfall concentrating even more around the centre of the storm cell.

However, there has been recent contradictory climate model research that suggests storm areas may become larger.

To understand this contradiction the researchers compared two different model types to real world observations of storm cell changes that occurred with rising temperatures. An area centred on the Sydney Basin with 53 rain gauges, was the focus of their investigation.

The researchers used a convective resolving model with 2km grid spaces and a convective parameterization model with 10km grid spaces. The models outputs were compared to observations around Sydney for the period 1990-2009.

They focused on five broad statistics to interpret how storms changed with temperature – peak precipitation, total precipitation, the storm’s effective radius, rainfall variation and the number of areas with no precipitation.



Both models successfully simulated peak precipitation and total precipitation when compared to observations. They also showed contraction in storms cell radius for one-hour events.

However, the convective resolving model underestimated peak precipitation for three-hour storm events. Other parameterisations, such as cloud microphysics and planetary boundary layers, appeared to influence this result. This was an unexpected outcome, which suggests that on some occasions a convective parameterisation model can outperform a convective resolving model for regional studies.

The downscaling approach used for this research offers another way to compare and evaluate the performance of regional climate models.

  • Paper: Li J, Wasko C, Johnson F, et al (2018) Can Regional Climate Modeling Capture the Observed Changes in Spatial Organization of Extreme Storms at Higher Temperatures? Geophysical Research Letters 45:4475–4484. doi: 10.1029/2018GL077716