Sometimes, scenarios of possible future climate change are examined if they would represent a "statistically significant" change from present conditions. Usage of this terminology is misleading, and valid only in a very restricted sense - because of the sampling assumptions needed for employing the machinery of statistical hypothesis testing.
This issue is discussed in the paper "Testing ensembles of climate change scenarios for"statistical significance"by Hans von Storch and Francis W. Zwiers, which has been accepted for publication by "Climatic Change".
Abstract: Climate impacts and adaptation research increasingly uses ensembles of regional and local climate change scenarios. To do so, the ensembles are examined to evaluate whether they describe a systematic difference between present states (and impacts) and envisaged future states - and such differences are often characterized as being statistically significant. This term "significance" is well defined by statistical terminology as the result of a test of a null hypothesis that is applied to samples of observations that are obtained with a defined sampling strategy. However such a statistical null hypothesis may not be a well-posed problem in the context of the evaluation of climate change scenarios. Therefore, the usage of terms such "statistical significant scenario" may be misunderstood in the general discourse about the certainty of projected climate change. We propose to employ instead a simple descriptive approach for characterizing the information in an ensemble of scenarios. Physical plausibility in the light of theoretical reasoning often adds robustness to the interpretation of climate change scenarios.
In the conclusion, this disucssion is offered: "The question arises why the term "statistical signi cance" is used. Presumably, one reason is that such "signi ficance" is often confounded with importance. The lay and statistical usages of "signi ficance" are often mixed in the overall discourse on climate change. For many, this terminology may indicate a certainty when this may not, in fact, be the case. This shrouds the character of scenarios as scripts of possible future change, which should be used by stakeholders to examine possible consequences and possible countermeasures. Among lay-people, this may also contribute to the common blending of the term "projections" with the term "predictions", in spite of the careful distinctions made in IPCC reports. "
This issue is discussed in the paper "Testing ensembles of climate change scenarios for"statistical significance"by Hans von Storch and Francis W. Zwiers, which has been accepted for publication by "Climatic Change".
Abstract: Climate impacts and adaptation research increasingly uses ensembles of regional and local climate change scenarios. To do so, the ensembles are examined to evaluate whether they describe a systematic difference between present states (and impacts) and envisaged future states - and such differences are often characterized as being statistically significant. This term "significance" is well defined by statistical terminology as the result of a test of a null hypothesis that is applied to samples of observations that are obtained with a defined sampling strategy. However such a statistical null hypothesis may not be a well-posed problem in the context of the evaluation of climate change scenarios. Therefore, the usage of terms such "statistical significant scenario" may be misunderstood in the general discourse about the certainty of projected climate change. We propose to employ instead a simple descriptive approach for characterizing the information in an ensemble of scenarios. Physical plausibility in the light of theoretical reasoning often adds robustness to the interpretation of climate change scenarios.
In the conclusion, this disucssion is offered: "The question arises why the term "statistical signi cance" is used. Presumably, one reason is that such "signi ficance" is often confounded with importance. The lay and statistical usages of "signi ficance" are often mixed in the overall discourse on climate change. For many, this terminology may indicate a certainty when this may not, in fact, be the case. This shrouds the character of scenarios as scripts of possible future change, which should be used by stakeholders to examine possible consequences and possible countermeasures. Among lay-people, this may also contribute to the common blending of the term "projections" with the term "predictions", in spite of the careful distinctions made in IPCC reports. "
Mir ist dieser Begriff von Signifikanz in diesem Zusammenhang auch schon begegnet. Es ging um regionale Veränderungen der Niederschlagsmengen. Da die Modelle stark schwanken, waren dann diejenigen Regionen gepunktet, wo die übergroße Mehrzahl der Modelle dieselbe Entwicklung zeigt, die nannte man dann "signifikant".
ReplyDeleteIm Grunde aber meint es ja nur, dass eben die Mehrzahl der Modelle, von denen wir nicht wissen, wie gut oder schlecht sie regionale Vorhersagen bilden können, denselben Trend angeben.
Insofern schließe ich mich hvw an, das klingt aller sehr interessant, ich wüsste auch gerne mehr darüber.
Andreas
@Hans von Storch
ReplyDeleteThank you, I appreciate the offer. But if its just me in the know, it won't help for a lively blog-chat. Therefore the "publicly" in the question. If you put it on your website, Springer would be OK with that.
The article has now been published "open access" - at this time: online first - by Springer:
ReplyDeletehttp://www.springerlink.com/content/826307478128851l/fulltext.pdf