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Scientists' role in outreach and advocacy has been debated extensively, but empirical evidence on its perceived legitimacy is scarce. We contacted scientists researching climate change to investigate scientists' engagement levels, as well as expectations regarding political and public engagement. We then compared how scientists (N = 1107) and German and US citizens (N = 884) view scientists' engagement and how scientists' advocacy affects their credibility. We find that perceptions differ across countries, with scientists perceiving more strongly than the public that scientists should politically and publicly engage. However, the public agrees that scientists should engage, and that they should increase these efforts. The majority of citizens agrees that scientists should advocate for climate-related policies and work closely with policymakers but refrain from endorsing climate protests. Further, openly supporting climate policies does not adversely affect scientists' perceived trustworthiness or honesty, while it negatively affects perceptions of scientists' objectivity. Our study provides empirical evidence that can help climate change researchers to better understand the public's demand for, and perceived legitimacy of, different engagement activities. ; ISSN:1748-9326 ; ISSN:1748-9318

Understanding the patterns of urban temperature a high spatial and temporal resolution is of large importance for urban heat adaptation and mitigation. Machine learning offers promising tools for high-resolution modeling of urban heat, but it requires large amounts of data. Measurements from official weather stations are too sparse but could be complemented by crowd-sensed measurements from citizen weather stations (CWS). Here we present an approach to model urban temperature using the quantile regression forest algorithm and CWS, open government and remote sensing data. The analysis is based on data from 691 sensors in the city of Zurich (Switzerland) during a heat wave using data from for 25-30th June 2019. We trained the model using hourly data from for 25-29th June (n = 71,837) and evaluate the model using data from June 30th (n = 14,105). Based on the model, spatiotemporal temperature maps of 10 × 10 m resolution were produced. We demonstrate that our approach can accurately map urban heat at high spatial and temporal resolution without additional measurement infrastructure. We furthermore critically discuss and spatially map estimated prediction and extrapolation uncertainty. Our approach is able to inform highly localized urban policy and decision-making. ; ISSN:2212-0955

A Bayesian uncertainty analysis of 12 parameters of the Bern2.5D climate model is presented. This includes an extensive sensitivity study with respect to the major statistical assumptions. Special attention is given to the parameter representing climate sensitivity. Using the framework of robust Bayesian analysis, the authors first define a nonparametric set of prior distributions for climate sensitivity S and then update the entire set according to Bayes' theorem. The upper and lower probability that S lies above 4.5°C is calculated over the resulting set of posterior distributions. Furthermore, posterior distributions under different assumptions on the likelihood function are computed. The main characteristics of the marginal posterior distributions of climate sensitivity are quite robust with regard to statistical models of climate variability and observational error. However, the influence of prior assumptions on the tails of distributions is substantial considering the important political implications. Moreover, the authors find that ocean heat change data have a considerable potential to constrain climate sensitivity.

Uncertainties of climate projections are routinely assessed by considering simulations from different models. Observations are used to evaluate models, yet there is a debate about whether and how to explicitly weight model projections by agreement with observations. Here we present a straightforward weighting scheme that accounts both for the large differences in model performance and for model interdependencies, and we test reliability in a perfect model setup. We provide weighted multimodel projections of Arctic sea ice and temperature as a case study to demonstrate that, for some questions at least, it is meaningless to treat all models equally. The constrained ensemble shows reduced spread and a more rapid sea ice decline than the unweighted ensemble. We argue that the growing number of models with different characteristics and considerable interdependence finally justifies abandoning strict model democracy, and we provide guidance on when and how this can be achieved robustly. ; ISSN:0094-8276 ; ISSN:1944-8007

Uncertainties of climate projections are routinely assessed by considering simulations from different models. Observations are used to evaluate models, yet there is a debate about whether and how to explicitly weight model projections by agreement with observations. Here we present a straightforward weighting scheme that accounts both for the large differences in model performance and for model interdependencies, and we test reliability in a perfect model setup. We provide weighted multimodel projections of Arctic sea ice and temperature as a case study to demonstrate that, for some questions at least, it is meaningless to treat all models equally. The constrained ensemble shows reduced spread and a more rapid sea ice decline than the unweighted ensemble. We argue that the growing number of models with different characteristics and considerable interdependence finally justifies abandoning strict model democracy, and we provide guidance on when and how this can be achieved robustly.

In March 2019, German-speaking scientists and scholars calling themselves Scientists for Future, published a statement in support of the youth protesters in Germany, Austria, and Switzerland (Fridays for Future, Klimastreik/Climate Strike), verifying the scientific evidence that the youth protestors refer to. In this article, they provide the full text of the statement, including the list of supporting facts (in both English and German) as well as an analysis of the results and impacts of the statement. Furthermore, they reflect on the challenges for scientists and scholars who feel a dual responsibility: on the one hand, to remain independent and politically neutral, and, on the other hand, to inform and warn societies of the dangers that lie ahead.

Climate change is clearly discernible in observed climate records in Switzerland. It impacts on natural systems, ecosystems, and economic sectors such as agriculture, tourism, and energy, and it affects Swiss livelihood in various ways. The observed and projected changes call for a response from the political system, which in Switzerland is characterized by federalism and direct democratic instruments. Swiss climate science embraces natural and social sciences and builds on institutionalized links between researchers, public, and private stakeholders. In this article, we review the physical, institutional, and political aspects of climate change in Switzerland. We show how the current state of Swiss climate science and policy developed over the past 20 years in the context of international developments and national responses. Specific to Switzerland is its topographic setting with mountain regions and lowlands on both sides of the Alpine ridge, which makes climate change clearly apparent and for some aspects (tourist sector, hydropower, and extreme events) highly relevant and better perceivable (e.g., retreating glaciers). Not surprisingly the Alpine region is of central interest in Swiss climate change studies.

Discussions on a long-term global goal to limit climate change, in the form of an upper limit to warming, were only partially resolved at the United Nations Framework Convention on Climate Change negotiations in Paris, 2015. Such a political agreement must be informed by scientific knowledge. One way to communicate the costs and benefits of policies is through a mapping that systematically explores the consequences of different choices. Such a multi-disciplinary effort based on the analysis of a set of scenarios helped structure the IPCC AR5 Synthesis Report. This Perspective summarizes this approach, reviews its strengths and limitations, and discusses how decision-makers can use its results in practice. It also identifies research needs that can facilitate integrated analysis of climate change and help better inform policy-makers and the public.

Discussions on a long-term global goal to limit climate change, in the form of an upper limit to warming, were only partially resolved at the United Nations Framework Convention on Climate Change negotiations in Paris, 2015. Such a political agreement must be informed by scientific knowledge. One way to communicate the costs and benefits of policies is through a mapping that systematically explores the consequences of different choices. Such a multi-disciplinary effort based on the analysis of a set of scenarios helped structure the IPCC AR5 Synthesis Report. This Perspective summarizes this approach, reviews its strengths and limitations, and discusses how decision-makers can use its results in practice. It also identifies research needs that can facilitate integrated analysis of climate change and help better inform policy-makers and the public.

Political decisions, adaptation planning, and impact assessments need reliable estimates of future climate change and related uncertainties. To provide these estimates, different approaches to constrain, filter, or weight climate model projections into probabilistic distributions have been proposed. However, an assessment of multiple such methods to, for example, expose cases of agreement or disagreement, is often hindered by a lack of coordination, with methods focusing on a variety of variables, time periods, regions, or model pools. Here, a consistent framework is developed to allow a quantitative comparison of eight different methods; focus is given to summer temperature and precipitation change in three spatial regimes in Europe in 2041–60 relative to 1995–2014. The analysis draws on projections from several large ensembles, the CMIP5 multimodel ensemble, and perturbed physics ensembles, all using the high-emission scenario RCP8.5. The methods' key features are summarized, assumptions are discussed, and resulting constrained distributions are presented. Method agreement is found to be dependent on the investigated region but is generally higher for median changes than for the uncertainty ranges. This study, therefore, highlights the importance of providing clear context about how different methods affect the assessed uncertainty—in particular, the upper and lower percentiles that are of interest to risk-averse stakeholders. The comparison also exposes cases in which diverse lines of evidence lead to diverging constraints; additional work is needed to understand how the underlying differences between methods lead to such disagreements and to provide clear guidance to users. ; ISSN:0894-8755 ; ISSN:1520-0442

Discussions on a long-term global goal to limit climate change, in the form of an upper limit to warming, were only partially resolved at the United Nations Framework Convention on Climate Change negotiations in Paris, 2015. Such a political agreement must be informed by scientific knowledge. One way to communicate the costs and benefits of policies is through a mapping that systematically explores the consequences of different choices. Such a multi-disciplinary effort based on the analysis of a set of scenarios helped structure the IPCC AR5 Synthesis Report. This Perspective summarizes this approach, reviews its strengths and limitations, and discusses how decision-makers can use its results in practice. It also identifies research needs that can facilitate integrated analysis of climate change and help better inform policy-makers and the public.

To make sound decisions in the face of climate change, government agencies, policymakers and private stakeholders require suitable climate information on local to regional scales. In Switzerland, the development of climate change scenarios is strongly linked to the climate adaptation strategy of the Confederation. The current climate scenarios for Switzerland CH2018 - released in form of six user-oriented products - were the result of an intensive collaboration between academia and administration under the umbrella of the National Centre for Climate Services (NCCS), accounting for user needs and stakeholder dialogues from the beginning. A rigorous scientific concept ensured consistency throughout the various analysis steps of the EURO-CORDEX projections and a common procedure on how to extract robust results and deal with associated uncertainties. The main results show that Switzerland's climate will face dry summers, heavy precipitation, more hot days and snow-scarce winters. Approximately half of these changes could be alleviated by mid-century through strong global mitigation efforts. A comprehensive communication concept ensured that the results were rolled out and distilled in specific user-oriented communication measures to increase their uptake and to make them actionable. A narrative approach with four fictitious persons was used to communicate the key messages to the general public. Three years after the release, the climate scenarios have proven to be an indispensable information basis for users in climate adaptation and for downstream applications. Potential for extensions and updates has been identified since then and will shape the concept and planning of the next scenario generation in Switzerland. ; Climate Scenarios for Switzerland CH2018 – Approach and Implications ; publishedVersion