Harnessing the data storage at RDSI to model extreme weather events in

Professor David Karoly ARC Centre of Excellence for Climate System Science and School of Earth Sciences, University of

TC Yasi, 2 Feb 2011 Source: Hannah Phillips, Labertouche From Bureau of Meteorology Outline • Background: Attribution of extreme climate events • Weather@home ANZ citizen science project • Some preliminary results and future plans

Project partners • ARC Centre of Excellence for Climate System Science: Mitchell Black, Sophie Lewis • University of Oxford Climateprediction.net (CPDN) and Oxford e-research Centre: Myles Allen, Andy Bowery, Fredi Otto • NIWA (NZ): Suzanne Rosier, Sam Dean • RDSI & TPAC at U. Tas.: Just Berkout, Tom Remenyi

From climatecommission.gov.au Are recent extreme weather events due to: • Natural climate variability, or • Greenhouse ?? This is a silly question.

Australian Prime Minister in 2014: “The CSIRO, amongst many other reputable scientific organisations, has cautioned against attributing any particularly weather event to man-made climate change’ NSW bushfires in Oct 2013: “Climate change is real …. but these bushfires are certainly not a function of climate change, they are just a function of life in Australia.”

In practice, we need to quantify the different factors affecting the likelihood of extreme weather and climate events. Weather and climate extremes

The effect of changes in temperature distribution on extremes.

From IPCC Special Report on Extremes (2011) From climatecommission.gov.au What is a climate model? • Physically-based tool for studying climate variability and change • Uses mathematical representations of physical laws, including Newton's second law of motion, the laws of conservation of mass and energy, laws of thermodynamics, and the ideal gas law • Represent important processes in atmosphere, ocean, land surface and ice, as well as coupling between them • More than thirty different models developed independently around the world • Typically represent the atmosphere as a series of boxes ~ 200km across, and simulate the average properties in each box

Weather@home project (http://www.climateprediction.net/weatherathome ) • Distributed computing project running on individual home computers, saving daily data, for analysis of weather variations • Uses HaDAM3P global climate model (130km resol) and nested HaDRM3P regional model (40km) driven with specified SST for Europe, southern Africa and western North America domains • Assess impacts of initial conditions and model parameters on weather extremes • More than 1 million model years already • W@H ANZ launched on on 26 March 2014 [email protected] Citizen Science project

Uni of Oxford Australia-New Zealand Regional Climate Model Weather@Home ANZ data at RDSI TPAC • Data files for daily regional model output, monthly global model output, and 1 restart file sent to TPAC, one month at a time, 0.36 GB per full year run, ~1 TB per week max return rate • 40km resolution, 145 x 216 grid over Australia and NZ • Only surface data returned for max and min temperature, rainfall, wind speed, surface pressure, and relative humidity Australia-New Zealand Regional Climate Model Probability distributions of daily data for Canberra in summer; nearest grid cell from ANZ W@H run Canberra airport weather station Preliminary results Compare results for natural vs all observed forcings for daily Australian average Tmax in Jan, record 7 Jan 2013 of 40.3°C Area-mean daily Tmax, All and Nat only forcings

FAR>0.73 Best estimate, 6x increase At least 4x increase in risk in risk

W@H ANZ CMIP5 selected models Next steps • Extend analysis of daily record temperatures in 2013 to assess their sensitivity to using different estimates of anthropogenic change in SST • Also consider extreme fire danger conditions in eastern NSW in Oct 2013 • Future simulations for 2014, 2009, 2010, 2011 and 2012 – Extreme rainfall in 2010-2012 – Heatwaves and bush fires in 2009