Probabilistic climate projections in the age of CMIP6
Climate projections are a key part of societal, infrastructure and policy planning. These climate projections are made by climate models and come in a variety of forms. In this seminar, we focus on so-called probabilistic climate projections of global-mean temperatures, which provide not only a best-estimate of future climate but also its uncertainty. We begin by discussing the scenarios which are currently being run by the world’s most powerful climate models (Earth System Models, ESMs) and our role in creating the greenhouse gas concentration timeseries used in these scenarios. Then we examine available results from models participating in the Sixth Coupled Model Intercomparison Project (CMIP6), using the output from a new tool we have developed. We discuss how these CMIP6 results differ from probabilistic projections and explain how we make probabilistic projections for global- annual-mean quantities using our reduced complexity climate model, MAGICC7. Finally, we present a newly available tool which allows users to visualise these projections and examine how sensitive they are to our understanding of the climate system.
Malte’s research interests comprise probabilistic climate projections, carbon budgets and emulations of multiple climate system uncertainties. He is one of the Lead Authors for the IPCC Sixth Assessment Report on the physical climate science (WG1), and part of the Core Writing Team of the IPCC Synthesis Report. Malte has been the scientific advisor to the German Environmental Ministry, being part of the German negotiation team at international climate change negotiations for more than 10 years. In his scientific career, he received an Australian Research Council’s Future Fellowship Award to investigate Australia’s fair contribution towards a global mitigation effort. Malte is Associate Professor in Climate Science at the School of Geography, Earth and Atmospheric Sciences at the University of Melbourne.
Zebedee is a world-leading expert in reduced complexity climate model development. He is the only researcher to have contributed heavily to the development of both MAGICC and FaIR, the two reduced complexity climate models used for emissions scenario assessment in the IPCC’s Special Report on Global Warming of 1.5°C. Alongside Malte, he leads the Reduced Complexity Model Intercomparison Project (RCMIP), which performs standardised evaluation of reduced complexity climate models (see rcmip.org). He also led the development of a common resource for reduced complexity model calibration data based on ESM output (cmip6.science.unimelb.edu.au) and helped create the input greenhouse gas datasets for CMIP6’s future scenario experiments (greenhousegases.science.unimelb.edu.au). Before his PhD, Zebedee completed his undergraduate Masters course in Physics at St.John’s College, University of Oxford. Beyond his PhD and Climate Resource work, Zebedee is also a Contributing Author to Chapter 1 of Working Group 1 of the forthcoming IPCC Sixth Assessment Report.
Jared is an expert at developing solutions for processing and visualising large scientific datasets with more than 10 years of experience working with climate data. He was a member of the establishment team for Xerra (formerly the Centre for Space Science Technology) which was funded to develop Earth Observation products for the benefit of New Zealand and has worked with a number of start-up projects. Prior to that he completed his BE(Mechatronics) and Masters of Engineering Management at the University of Canterbury.