Dealing with uncertainty in the IPCC process
The Intergovernmental Panel on Climate Change (IPCC, Intergovernmental Panel on Climate Change ) used in its "progress reports" after the publication of the Third Assessment Report (TAR) in 2001, a standardized and formalized classification of statistical uncertainty of the presented summarized research results. This assessment of the uncertainty of the results should enable a generally valid evaluation of results and thus ensure the comparability of current and future research results, but also the comparability between different scientific studies .
The Uncertainty Factor in Science
Every scientific research is fraught with more or less great uncertainties. This is especially true for interdisciplinary research into such a complex system as the earth's atmosphere . Every step towards gaining knowledge leads to new uncertainties that have to be described and, if possible, quantified. When collecting data, the measurement inaccuracies and possibly systematic measurement errors must be taken into account. Especially when developing a theory, there is initially uncertainty in the analysis methods and thus also in the results. The complexity of the planet earth system is at the upper end of the spectrum in terms of non-linearity and degrees of freedom . This complexity means that knowledge about the processes prevailing in the earth's atmosphere cannot always be described and explained with absolute reliability. There are often very specific problems, such as the question of how the emissions from air traffic can be determined, since on the one hand these have a global effect, on the other hand they should be assigned to a state (territorial principle) in order to determine the respective share of the individual countries in the CO 2 balance to calculate.
Depending on the time and space scales of various processes, uncertainties can be eliminated more quickly or more slowly. In this way, the uncertainty about high-frequency variability can be quickly eliminated through measurements over short periods of time. However, the uncertainty about variability on time scales of several thousand years can persist much longer.
Description of uncertainties in a non-scientific context
The quantification of uncertainties is particularly relevant in the context of the ongoing political debate on climate change and the often ostensibly staged controversy about global warming . A subjective description of uncertainties is often chosen in the political discussion. This means that the classifications “very likely”, “likely” or “unlikely” are used in statements, but their meaning differs from person to person and from interpretation to interpretation. This sometimes gives outsiders an unclear picture of the facts and the objective results. On the other hand, concrete results, on which agreement was reached in the IPCC process, serve as a template for the formation of political opinions. Criticism can arise, which in turn promotes the scientific knowledge process. A German study in 2007 said: "The emissions from maritime transport are not considered because they are not included in emissions from transport according to their current definition according to the IPCC principle."
One of the first to deal intensively with the communication of statistical uncertainty and the public perception of the topic of global warming was the physicist and climate scientist Stephen Schneider . As a long-time IPCC employee and lead author (Working Group I from 1994 to 1996, from 1997 coordinating lead author of Working Group II), he devoted himself in detail to the uncertainties in the modeling of the interactions between human and natural systems and published a large number of statements and scientific papers on them.
Formalization
As part of the creation of the fourth assessment report (AR4), the IPCC introduced a standardized and formalized classification of uncertainty. This classification was updated for the Fifth Assessment Report (AR5). In the introduction to the Fifth Assessment Report, the IPCC makes it clear that the current treatment of uncertainties should not be viewed as a final, but as a continuously changing approach. The current status is divided into two aspects that are assessed individually. The significance of a result ( validity of finding) and the probability of a result (measure of certainty of finding) are described. Only by combining these aspects can a statement about future developments (predictions and projection) be made and evaluated.
The significance of a result is currently (2017 March) about the type ( type ), quality ( quality ), quantity ( amount ), consistency ( consistency ) and agreement ( degree of agreement determines) the found scientific evidence. A distinction is made here between the quality of the results (type, quality, quantity and consistency) and the significance of the results across all studies (agreement). The quality is on a qualitative scale with limited ( limited) , medium ( middle) or robust ( robust rated). High quality is achieved, for example, by combining in-situ measurements, satellite measurements, simulation results and theoretical models. The agreement is also described qualitatively on a scale with low ( low ), medium ( middle ) or high ( high ). Taking this information into account, the significance of a result is expressed in a two-dimensional matrix. Along the lines of the matrix, the type, quality, quantity and consistency of the results show increasing significance. Along the columns, increasing informative value is shown through the correspondence of several results. The significance increases diagonally through the matrix and has its highest (lowest) value with robust (limited) evidence and high (low) agreement. It is important to mention that in this context we speak of expressiveness / confidence in the semantic sense and not of statistical confidence . Therefore, for a given quality and consistency of evidence, a variable significance could be given. However, higher quality and higher agreement correlate with higher significance.
The probability of an outcome evaluates how likely it is that this outcome will occur. It is given on a linguistically calibrated scale based on quantified probabilities. This scale consists of seven possible assessment levels ( qualifiers ):
| Valuation level | probability |
|---|---|
| virtually certain ( virtually certain ) | 99-100% |
| very likely ( very likely ) | 90-100% |
| probable ( likely ) | 66 - 100% |
| about as likely as not ( about as likely as not ) | 66-33 % |
| unlikely ( unlikely ) | 0 - 33% |
| very unlikely ( very unlikely ) | 0-10 % |
| exceptionally unlikely ( exceptionally unlikely ) | 0 - 1% |
This quantification can be based on calculations based on in-situ data, satellite data or simulations or the evaluation of expert interviews. At sufficiently large data base, it is preferable, however, the overall probability density function (PDF, probabilit density function ) to show.
Individual evidence
- ↑ see Fig. 1.3.1 in: Steven H. Strogatz: Nonlinear Dynamics and Chaos . Ed .: Perseus Books. Perseus Books, Reading, Massachusetts 1994, ISBN 978-0-7382-0453-6 , pp. 10 .
- ↑ Detailed information on this: Forecast of the Germany-wide transport links in 2025
- ↑ Forecast of Germany-wide transport links in 2025 , ITP and BVU 2007, page 259
- ^ RH Moore, SH Schneider: Recommendations to lead authors for more consistent assessment and reporting . (PDF) In: Guidance Papers on the Cross Cutting Issues of the Third Assessment Report of the IPCC (Ed.R. Pachauri, T. Taniguchi, K. Tanaka) . 2000, pp. 33-51.
- ↑ Intergovernmental Panel on Climate Chage: Guidance Notes for Lead Authors of the IPCC Fourth Assessment Report on Addressing Uncertainties . Ed .: Intergovernmental Panel on Climate Change. 2005.
- ↑ Michael D. Mastrandre, Christopher B. Field, Thomas F. Stocker , Ottmar Edenhofer, Kristie L. Ebi, David J. Frame, Hermann Held, Elmar Kriegler, Katharine J. Mach, Patrick R. Matschoss, Gian-Kasper Plattner, Gary W. Yohe, Francis W. Zwiers: Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties . (PDF) In: IPCC Cross-Working Group Meeting on Consistent Treatment of Uncertainties . July 2010.
- ↑ Climate Change 2013: The Physical Science Basis ( English ) Intergovernmental Panel on Climate Change. Retrieved January 17, 2019.
- ↑ a b Cubasch, U., D. Wuebbles, D. Chen, MC Facchini, D. Frame, Natalie Mahowald , and J.-G. Winther, 2013: Introduction. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, TF, D. Qin, G.-K. Plattner, M. Tignor, SK Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and PM Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.