Confidence levels and likelihood terms in IPCC reports: a survey of experts from different scientific disciplines

Kause, Astrid; Bruin, Wändi Bruine de; Persson, Johannes; Thorén, H.; Olsson, Lennart; Wallin, Annika; Dessai, Suraje; Vareman, Niklas

doi:10.1007/s10584-022-03382-3

Cited by 12 publications

(4 citation statements)

References 48 publications

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“…In addition, the likelihood term associated with the projection of carbon dioxide uptake presented in this study is "very likely", referring to the 90-100% probability according to the IPCC guidance note which translates each likelihood term into a probability interval [49]. To sum up, the uncertainty is presented in a manner that relates to decision-makers' concerns [52].…”

Section: Resultsmentioning

confidence: 99%

Carbon Dioxide Uptake Estimation for Spanish Cement-Based Materials

Sanjuán,

Mora,

Sanjuán

et al. 2024

Materials

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The Intergovernmental Panel on Climate Change (IPCC), which is the United Nations body for assessing the science related to climate change, has recently recognized the natural carbonation process as a way of carbon offsetting with mortar and concrete. Accordingly, this activity could be recognized as a carbon removal process for which certification should be granted. The aim of the certification of carbon removal is to promote the development of adequate and efficient new carbon removal processes. Therefore, the main objective of this study is to provide reliable results on carbon dioxide uptake by cement-based materials in Spain. Yearly, greenhouse gas emissions are reported to the United Nations Framework Convention on Climate Change (UNFCCC) by each country, and the natural carbonation should be added up to the carbon accounting. Therefore, natural carbonation should be included in the IPCC Guidelines for National Greenhouse Gas Inventories, and such accounting information should be made available promptly to the national regulatory authorities. This paper provides the results of carbon dioxide uptake by Spanish cement-based materials from 1990 to 2020 by using an easy method of estimating the net carbon dioxide emissions (simplified method) considering the carbon dioxide released by the calcination during clinker production (process emissions). The outcome of this study reveals that there was 93,556,000 tons of carbon dioxide uptake by the mortar and concrete manufactured in Spain from 1990 to 2020.

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Section: Resultsmentioning

confidence: 99%

Carbon Dioxide Uptake Estimation for Spanish Cement-Based Materials

Sanjuán,

Mora,

Sanjuán

et al. 2024

Materials

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“…Considering potential inconsistency of CV trends across four long-term satellite remote sensing products (i.e., VIP15 NDVI, GIMMS NDVI3g, GLASS LAI and GLOBMAP LAI), we classified the levels of consistency of CV trends for each vegetated pixel using the following criterion (Kause et al, 2022;Xu et al, 2022): (a) "virtually certain" (CER) means the signs of CV trends derived from all four long-term satellite products are the same and significant (Mann-Kendall test, p ≤ 0.1); (b) "likely" (LIK) if the signs of the CV trends are the same and significant in any three satellite products; (c) "about likely as not" (ALN) if the signs of the CV trends are the same and significant in any two satellite products; (d) "possibly" (POS) if only one satellite product yields significant CV trend, and others are insignificant; (e) "no change" (NOC) if no significant CV changes were detected in all Earth's Future 10.1029/2023EF004119 four satellite products; and (f) "conflicting" (CON) if the observed CV trends are conflicting with each other (i.e., significant positive and negative CV trends were detected simultaneously across the four products). We further assigned "+" and " " signs to the consistency levels that refer to the direction of CV trends (i.e., positive and negative trends, respectively).…”

Section: Classifying the Levels Of Consistency Of Remote Sensing-base...mentioning

confidence: 99%

Conflicting Changes of Vegetation Greenness Interannual Variability on Half of the Global Vegetated Surface

Tian,

Luo

2024

Earth's Future

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Changes in the interannual variability (IAV) of vegetation greenness and carbon sequestration are key indicators of the stability and climate sensitivities of terrestrial ecosystems. Recent studies have examined the changes in the vegetation IAV using atmospheric CO2 observations and dynamic global vegetation models (DGVMs), however, reported different and even contradictory IAV trends. Here, we investigate the changes in the IAV of vegetation greenness, quantified as coefficient of variability (CV), over the past few decades based on multiple satellite remote sensing products and DGVMs. Our results suggested that, on half of the global vegetated surface (mostly in the tropics), the CV trends detected by different satellite remote sensing products are conflicting. We found that 22.20% and 28.20% of the global vegetated surface (mostly in the non‐tropical land surface) show significant positive and negative CV trends (p ≤ 0.1), respectively. Regions with higher air temperature and greater aridity tend to have increasing CV trends, whereas greater vegetation greening trend and higher nitrogen deposition lead to smaller CV trends. DGVMs generally cannot capture the CV trends obtained from satellite remote sensing products, while the inconsistency among satellite remote sensing products is likely caused by their process algorithms rather than the sensors utilized. Our study closely examines the changes in the IAV of global vegetation greenness, and highlights substantial uncertainty when using satellite remote sensing to study the response of terrestrial ecosystems to climate change.

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“…[ 9 , 10 ]), disciplinary differences in how uncertainties are conceptualized (e.g. [ 11 ]), what to do when we cannot muster quantitative reports on uncertainties (e.g. [ 12 ]), and so on.…”

Section: Models and Uncertainty Domesticationmentioning

confidence: 99%

Model uncertainty, the COVID-19 pandemic, and the science-policy interface

Thorén,

Gerlee

2024

R. Soc. Open Sci.

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The COVID-19 pandemic illustrated many of the challenges with using science to guide planning and policymaking. One such challenge has to do with how to manage, represent and communicate uncertainties in epidemiological models. This is considerably complicated, we argue, by the fact that the models themselves are often instrumental in structuring the involved uncertainties. In this paper we explore how models ‘domesticate’ uncertainties and what this implies for science-for-policy. We analyse three examples of uncertainty domestication in models of COVID-19 and argue that we need to pay more attention to how uncertainties are domesticated in models used for policy support, and the many ways in which uncertainties are domesticated within particular models can fail to fit with the needs and demands of policymakers and planners.

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Confidence levels and likelihood terms in IPCC reports: a survey of experts from different scientific disciplines

Cited by 12 publications

References 48 publications

Carbon Dioxide Uptake Estimation for Spanish Cement-Based Materials

Carbon Dioxide Uptake Estimation for Spanish Cement-Based Materials

Conflicting Changes of Vegetation Greenness Interannual Variability on Half of the Global Vegetated Surface

Model uncertainty, the COVID-19 pandemic, and the science-policy interface

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