Editing IPCC:AR6/SROCC/Chapter-1 (section)

=== 1.9.2 Communication of Confidence in Assessment Findings ===

<div id="section-1-9-2communication-of-confidence-in-assessment-findings-block-1"></div>

SROCC uses calibrated language for the communication of confidence in the assessment process (Mastrandrea et al., 2010 <sup>[[#fn:r539|539]]</sup> ; Mach et al., 2017 <sup>[[#fn:r540|540]]</sup> ). Calibrated language is designed to consistently evaluate and communicate uncertainties that arise from incomplete knowledge due to a lack of information, or from disagreement about what is known or even knowable. The IPCC calibrated language uses qualitative expressions of confidence based on the robustness of evidence for a finding, and (where possible) uses quantitative expressions to describe the likelihood of a finding (Figure 1.4).

''Qualitative expressions'' ( ''confidence scale'' ) describe the validity of a finding based on the type, amount, quality and consistency of evidence, and the degree of agreement between different lines of evidence (Figure 1.4, step 2). Evidence includes all knowledge sources, including IK and LK where available. ''Very high'' and ''high'' confidence findings are those that are supported by multiple lines of robust evidence with high agreement. ''Low'' or ''very low'' confidence describe findings for which there is limited evidence and/or low agreement among different lines of evidence, and are only presented in SROCC if they address a major topic of concern.

''Quantitative expressions (likelihood scale)'' are used when sufficient data and confidence exists for findings to be assigned a quantitative or probabilistic estimate (Figure 1.4, step 3). In the scientific literature, a finding is often said to be significant if it has a likelihood exceeding 95% confidence. Using calibrated IPCC language, this level of statistical confidence would be termed ''extremely likely'' . Lower levels of likelihood than those derived numerically can be assigned by expert judgement to take into account structural or measurement uncertainties within the products or data used to determine the probabilistic estimates (e.g., Table CB1.1). Likelihood statements may be used to describe how climate changes relate to the ends of distribution functions, such as in detection and attribution studies that assess the likelihood that an observed climate change or event is different to a reference climate state (Section 1.3). In other situations, likelihood statements refer to the central region across a distribution of possibilities. Examples are the estimates of future changes based on large ensembles of climate model simulations, where the central 66% of estimates across the ensemble (i.e., the 17–83% range) would be termed a ''likely'' range (Figure 1.4, step 3).

It is increasingly recognised that effective risk management requires assessments not just of ‘what is most likely’ but also of ‘how bad things could get’ (Mach et al., 2017 <sup>[[#fn:r541|541]]</sup> ; Weaver et al., 2017 <sup>[[#fn:r544|544]]</sup> ; Xu and Ramanathan, 2017 <sup>[[#fn:r545|545]]</sup> ; Spratt and Dunlop, 2018 <sup>[[#fn:r546|546]]</sup> ; Sutton, 2018 <sup>[[#fn:r547|547]]</sup> ). In response to the need to reframe policy relevant assessments according to risk (Section 1.5; Mach et al., 2016 <sup>[[#fn:r548|548]]</sup> ; Weaver et al., 2017 <sup>[[#fn:r549|549]]</sup> ; Sutton, 2018 <sup>[[#fn:r550|550]]</sup> ), an effort is made in SROCC to report on potential changes for which there is low scientific confidence or a low likelihood of occurrence, but that would have large impacts if realised (Mach et al., 2017 <sup>[[#fn:r551|551]]</sup> ). In some cases where evidence is limited or emerging, phenomena may instead be discussed according to physically plausible scenarios of impact (e.g., Table 6.1).

In some cases, ''deep uncertainty'' (Cross-Chapter Box 5 in Chapter 1) may exist in current scientific assessments of the processes, rate, timing, magnitude, and consequences of future ocean and cryosphere changes. This includes physically plausible high-impact changes, such as high-end sea level rise scenarios that would be costly if realised without effective adaptation planning and even then may exceed limits to adaptation. Means such as expert judgement, scenario building, and invoking multiple lines of evidence enable comprehensive risk assessments even in cases of uncertain future ocean and cryosphere changes.

<div id="section-1-9-2communication-of-confidence-in-assessment-findings-block-2"></div>

<span id="figure-1.4"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure 1.4'''

<span id="figure-1.4-schematic-of-the-ipcc-usage-of-calibrated-language-with-examples-of-confidence-and-likelihood-statements-from-this-report.-figure-developed-after-mastrandrea-et-al.-2010-mach-et-al.-2017-and-sutton-2018."></span>
<!-- IMG CAPTION -->
'''Figure 1.4 | Schematic of the IPCC usage of calibrated language, with examples of confidence and likelihood statements from this report. Figure developed after Mastrandrea et al. (2010), Mach et al. (2017) and Sutton (2018).'''
<!-- IMG FILE -->
[[File:7090735f464c1a2201aa2c855b3cf830 IPCC-SROCC-CH_1_4.jpg]]

Figure 1.4 | Schematic of the IPCC usage of calibrated language, with examples of confidence and likelihood statements from this report. Figure developed after Mastrandrea et al. (2010), Mach et al. (2017) and Sutton (2018).

<!-- END IMG -->
<div id="section-1-9-2communication-of-confidence-in-assessment-findings-block-3" class="box"></div>

<span id="ccb.5-confidence-and-deep-uncertainty"></span>