Probabilities of causation of climate changes

Probabilities of causation of climate changes AbstractMultiple changes in Earth’s climate system have been observed over the past decades. Determining how likely each of these changes are to have been caused by human inuence, is important for decision making on mitigation and adaptation policy. Here we describe an approach for deriving the probability that anthropogenic forcings have caused a given observed change. The proposed approach is anchored into causal counterfactual theory (Pearl 2009) which has been introduced recently, and was in fact partly used already, in the context of extreme weather event attribution (EA). We argue that these concepts are also relevant, and can be straightforwardly extended to, the context of detection and attribution of long term trends associated to climate change (D&A). For this purpose, and in agreement with the principle of fingerprinting applied in the conventional D&A framework, a trajectory of change is converted into an event occurrence defined by maximizing the causal evidence associated to the forcing under scrutiny. Other key assumptions used in the conventional D&A framework, in particular those related to numerical models error, can also be adapted conveniently to this approach. Our proposal thus allows to bridge the conventional framework with the standard causal theory, in an attempt to improve the quantification of causal probabilities. An illustration suggests that our approach is prone to yield a significantly higher estimate of the probability that anthropogenic forcings have caused the observed temperature change, thus supporting more assertive causal claims. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Climate American Meteorological Society

Probabilities of causation of climate changes

Loading next page...
 
/lp/ams/probabilities-of-causation-of-climate-changes-7v2pdCj8L4
Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0442
D.O.I.
10.1175/JCLI-D-17-0304.1
Publisher site
See Article on Publisher Site

Abstract

AbstractMultiple changes in Earth’s climate system have been observed over the past decades. Determining how likely each of these changes are to have been caused by human inuence, is important for decision making on mitigation and adaptation policy. Here we describe an approach for deriving the probability that anthropogenic forcings have caused a given observed change. The proposed approach is anchored into causal counterfactual theory (Pearl 2009) which has been introduced recently, and was in fact partly used already, in the context of extreme weather event attribution (EA). We argue that these concepts are also relevant, and can be straightforwardly extended to, the context of detection and attribution of long term trends associated to climate change (D&A). For this purpose, and in agreement with the principle of fingerprinting applied in the conventional D&A framework, a trajectory of change is converted into an event occurrence defined by maximizing the causal evidence associated to the forcing under scrutiny. Other key assumptions used in the conventional D&A framework, in particular those related to numerical models error, can also be adapted conveniently to this approach. Our proposal thus allows to bridge the conventional framework with the standard causal theory, in an attempt to improve the quantification of causal probabilities. An illustration suggests that our approach is prone to yield a significantly higher estimate of the probability that anthropogenic forcings have caused the observed temperature change, thus supporting more assertive causal claims.

Journal

Journal of ClimateAmerican Meteorological Society

Published: Jan 18, 2018

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from
Google Scholar,
PubMed
Create lists to
organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off