Probabilistic climate projections in the age of CMIP6
4.2 هزار بار بازدید -
4 سال پیش
-
A/Prof Malte Meinshausen, Zebedee Nicholls
A/Prof Malte Meinshausen, Zebedee Nicholls and Jared Lewis, 11 November 2020.
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.
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.
4 سال پیش
در تاریخ 1399/08/22 منتشر شده
است.
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