The Intergovernmental Panel on Climate Change (IPCC) assesses the sensitivity of the climate syst... more The Intergovernmental Panel on Climate Change (IPCC) assesses the sensitivity of the climate system to increases in greenhouse gas concentrations using multiple lines of evidence, covering paleoclimate data, historical observations, and numerical Earth system model (ESM) simulations. Within IPCC’s latest Assessment Report (AR6), there is, for the first time, a non-negligible difference between the most likely rate of warming estimated in the report and the average warming rate simulated by the ESMs that participated in the Coupled Model Intercomparison Project (CMIP6). This discrepancy occurs because a large number of CMIP6 models have projected future warming rates that are higher than previously reported but quite unlikely according to historical observations. The consequence is that using a random selection of CMIP6 simulations is likely to overestimate historical and future warming (compared to what is assessed in the IPCC report), potentially leading to avoidable inconsistencies when compared to observations or greater projected changes compared to what could be inferred from CMIP5.As this constitutes a wide-spread obstacle and limitation to using CMIP6 simulations ‘out of the box’, we propose here a simple model weighting method with the objective to address this problem. Our approach can be used to 1) evaluate the extent to which any given set of CMIP6 simulations is consistent with IPCC-assessed warming rates and 2) calculate the appropriate model weights so that potential inconsistencies are reduced as much as possible. The calculation of the weights is solely based on the user’s selection of a CMIP6 subset and does not require any data manipulation. The weights can then be easily implemented in existing analyses to calculate weighted (i.e. instead of just arithmetic) multi-model means, weighted quantiles, etc. We demonstrate the interest and flexibility of the method with some examples, including global to regional assessments of historical and projected changes in temperature and precipitation. We illustrate the extent to which applying model weights can reconcile otherwise divergent scientific results and provide assessments that are more robust across CMIP generations.
Global mean surface air temperature (GSAT) is a key diagnostic for understanding and constraining... more Global mean surface air temperature (GSAT) is a key diagnostic for understanding and constraining historical climate variability and change, and for climate policy. Yet, global temperature estimates (1) are usually based on blending sea surface temperatures (SST) with near-surface air temperature over land (LSAT), and (2) contain many missing values due to incomplete coverage in the historical record. While these issues are usually accounted for in model-observation comparisons, elucidating the consistency of LSAT and SST records, and their contribution to GSAT variability and change, remains difficult.Here, we present a set of new GSAT reconstructions based separately on either the historical LSAT or SST record. The method is based on regularized linear regression models trained on climate model simulations to optimally predict GSAT from the climate model’s LSAT or SST patterns, respectively. We then predict GSAT from the HadSST4 and CRUTEM5 observational data, respectively, for each month from January 1850 up to December 2020.We demonstrate that the land- or ocean based GSAT estimates show very similar variability and long-term changes, both in the early (1850-1900) as well as in the late record (post-1950). For example, GSAT of the past decade (2011-2020) increased by 1.15°C (LSAT-based) and 1.17°C (SST-based) relative to an early reference period (1850-1900), which is both well within IPCC AR6 estimates.However, the GSAT estimates show pronounced disagreement in the early 20th century (1900 up to around 1930), when the SST-based GSAT estimates appear on average around 0.3°C colder than the LSAT-based estimates. Decadal changes in the LSAT-based estimates are well explained by the multi-model mean of CMIP6 simulations driven with historical forcings, thus implying only a small role of unforced decadal global variability. In contrast, the SST-based estimate highlights pronounced variability during the early 20th century cold anomaly, which may be related to concerns about instrumental cold biases in SST measurements, but overall reasons for the disagreement remain unclear. Further analysis based on physical reasoning, climate models, and proxy reconstructions, indicates that the ocean data may indeed be implausibly cold.In conclusion, our methodology and results may help to constrain the magnitude of early 20th century warming, and thus to better understand and attribute decadal climate variability.
These datasets contain survey results from the German public, the US public and the surveyed scie... more These datasets contain survey results from the German public, the US public and the surveyed scientists. The file containing survey data of scientists has been modified (discipline, country of residence and comments have been taken out) in order to guarantee anonymity
Philosophical perspectives on numerical models help us to understand concepts, but will not predi... more Philosophical perspectives on numerical models help us to understand concepts, but will not predict the climate in the future. Studying climate model results in isolation on the other hand may seduce us to believe what we simulate will actually happen. A model is neither correct nor wrong as such; it is simply more or less useful as a representational tool for a certain purpose. I argue that process understanding is the key to make judgments about when this tool is adequate for insight relevant to certain aspects of the real world. It is only through understanding the relationships in components and variables of the climate and their representation in models, combined with understanding what our models are supposed to do, that we can make better use of them.
Scientists’ role in outreach and advocacy has been debated extensively, but empirical evidence on... more 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.
Science communication and public engagement with science have repeatedly been called for in recen... more Science communication and public engagement with science have repeatedly been called for in recent years, particularly during the COVID-19 pandemic. Therefore, die Swiss Academies of the Arts and Sciences have set up an expert group to assess the state of science communication in Switzerland, and to provide recommendations for how to improve it. The expert group report is based on a comprehensive review of the available interdisciplinary scholarship analyzing science communication and public engagement with science in Switzerland. Selectively, it also incorporates original data, international findings, and secondary analyses where little or no published scholarly work was available. The report covers a wide range of facets of science communication and public engagement in Switzerland, from public attitudes towards science over individuals and organizations engaging in science communication and engagement formats to news and social media representations of science. On this basis, it ...
Mesoscale eddies are ubiquitous features in the Southern Ocean, yet their phenomenology is not we... more Mesoscale eddies are ubiquitous features in the Southern Ocean, yet their phenomenology is not well quantified. To tackle this task, we use satellite observations of sea level anomalies and sea surface temperature (SST) as well as in situ temperature and salinity measurements from profiling floats. Over the period 1997–2010, we identified over a million mesoscale eddy instances and were able to track about 105 of them over 1 month or more. The Antarctic Circumpolar Current (ACC), the boundary current systems, and the regions where they interact are hot spots of eddy presence, representing also the birth places and graveyards of most eddies. These hot spots contrast strongly to areas shallower than about 2000 m, where mesoscale eddies are essentially absent, likely due to topographical steering. Anticyclones tend to dominate the southern subtropical gyres, and cyclones the northern flank of the ACC. Major causes of regional polarity dominance are larger formation numbers and lifespan...
State-of-the-art earth system models used for long-term climate projections are becoming ever mor... more State-of-the-art earth system models used for long-term climate projections are becoming ever more complex in terms of not only spatial resolution but also the number of processes. Biogeochemical processes are beginning to be incorporated into these models. The motivation of this study is to quantify how climate projections are influenced by biogeochemical feedbacks. In the climate modeling community, it is virtually accepted that climate-Carbon (C) cycle feedbacks accelerate the future warming (Cox et al. 2000; Friedlingstein et al. 2006). It has been demonstrated that the Nitrogen (N) cycle suppresses climate-C cycle feedbacks (Thornton et al. 2009). On the contrary, biogeochemical studies show that the coupled C-N-Phosphorus (P) cycles are intimately interlinked via biosphere and the N-P cycles amplify C cycle feedbacks (Ver et al. 1999). The question as to whether the N-P cycles enhance or attenuate C cycle feedbacks is debated and has a significant implication for projections o...
The Intergovernmental Panel on Climate Change (IPCC) assesses the sensitivity of the climate syst... more The Intergovernmental Panel on Climate Change (IPCC) assesses the sensitivity of the climate system to increases in greenhouse gas concentrations using multiple lines of evidence, covering paleoclimate data, historical observations, and numerical Earth system model (ESM) simulations. Within IPCC’s latest Assessment Report (AR6), there is, for the first time, a non-negligible difference between the most likely rate of warming estimated in the report and the average warming rate simulated by the ESMs that participated in the Coupled Model Intercomparison Project (CMIP6). This discrepancy occurs because a large number of CMIP6 models have projected future warming rates that are higher than previously reported but quite unlikely according to historical observations. The consequence is that using a random selection of CMIP6 simulations is likely to overestimate historical and future warming (compared to what is assessed in the IPCC report), potentially leading to avoidable inconsistencies when compared to observations or greater projected changes compared to what could be inferred from CMIP5.As this constitutes a wide-spread obstacle and limitation to using CMIP6 simulations ‘out of the box’, we propose here a simple model weighting method with the objective to address this problem. Our approach can be used to 1) evaluate the extent to which any given set of CMIP6 simulations is consistent with IPCC-assessed warming rates and 2) calculate the appropriate model weights so that potential inconsistencies are reduced as much as possible. The calculation of the weights is solely based on the user’s selection of a CMIP6 subset and does not require any data manipulation. The weights can then be easily implemented in existing analyses to calculate weighted (i.e. instead of just arithmetic) multi-model means, weighted quantiles, etc. We demonstrate the interest and flexibility of the method with some examples, including global to regional assessments of historical and projected changes in temperature and precipitation. We illustrate the extent to which applying model weights can reconcile otherwise divergent scientific results and provide assessments that are more robust across CMIP generations.
Global mean surface air temperature (GSAT) is a key diagnostic for understanding and constraining... more Global mean surface air temperature (GSAT) is a key diagnostic for understanding and constraining historical climate variability and change, and for climate policy. Yet, global temperature estimates (1) are usually based on blending sea surface temperatures (SST) with near-surface air temperature over land (LSAT), and (2) contain many missing values due to incomplete coverage in the historical record. While these issues are usually accounted for in model-observation comparisons, elucidating the consistency of LSAT and SST records, and their contribution to GSAT variability and change, remains difficult.Here, we present a set of new GSAT reconstructions based separately on either the historical LSAT or SST record. The method is based on regularized linear regression models trained on climate model simulations to optimally predict GSAT from the climate model’s LSAT or SST patterns, respectively. We then predict GSAT from the HadSST4 and CRUTEM5 observational data, respectively, for each month from January 1850 up to December 2020.We demonstrate that the land- or ocean based GSAT estimates show very similar variability and long-term changes, both in the early (1850-1900) as well as in the late record (post-1950). For example, GSAT of the past decade (2011-2020) increased by 1.15°C (LSAT-based) and 1.17°C (SST-based) relative to an early reference period (1850-1900), which is both well within IPCC AR6 estimates.However, the GSAT estimates show pronounced disagreement in the early 20th century (1900 up to around 1930), when the SST-based GSAT estimates appear on average around 0.3°C colder than the LSAT-based estimates. Decadal changes in the LSAT-based estimates are well explained by the multi-model mean of CMIP6 simulations driven with historical forcings, thus implying only a small role of unforced decadal global variability. In contrast, the SST-based estimate highlights pronounced variability during the early 20th century cold anomaly, which may be related to concerns about instrumental cold biases in SST measurements, but overall reasons for the disagreement remain unclear. Further analysis based on physical reasoning, climate models, and proxy reconstructions, indicates that the ocean data may indeed be implausibly cold.In conclusion, our methodology and results may help to constrain the magnitude of early 20th century warming, and thus to better understand and attribute decadal climate variability.
These datasets contain survey results from the German public, the US public and the surveyed scie... more These datasets contain survey results from the German public, the US public and the surveyed scientists. The file containing survey data of scientists has been modified (discipline, country of residence and comments have been taken out) in order to guarantee anonymity
Philosophical perspectives on numerical models help us to understand concepts, but will not predi... more Philosophical perspectives on numerical models help us to understand concepts, but will not predict the climate in the future. Studying climate model results in isolation on the other hand may seduce us to believe what we simulate will actually happen. A model is neither correct nor wrong as such; it is simply more or less useful as a representational tool for a certain purpose. I argue that process understanding is the key to make judgments about when this tool is adequate for insight relevant to certain aspects of the real world. It is only through understanding the relationships in components and variables of the climate and their representation in models, combined with understanding what our models are supposed to do, that we can make better use of them.
Scientists’ role in outreach and advocacy has been debated extensively, but empirical evidence on... more 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.
Science communication and public engagement with science have repeatedly been called for in recen... more Science communication and public engagement with science have repeatedly been called for in recent years, particularly during the COVID-19 pandemic. Therefore, die Swiss Academies of the Arts and Sciences have set up an expert group to assess the state of science communication in Switzerland, and to provide recommendations for how to improve it. The expert group report is based on a comprehensive review of the available interdisciplinary scholarship analyzing science communication and public engagement with science in Switzerland. Selectively, it also incorporates original data, international findings, and secondary analyses where little or no published scholarly work was available. The report covers a wide range of facets of science communication and public engagement in Switzerland, from public attitudes towards science over individuals and organizations engaging in science communication and engagement formats to news and social media representations of science. On this basis, it ...
Mesoscale eddies are ubiquitous features in the Southern Ocean, yet their phenomenology is not we... more Mesoscale eddies are ubiquitous features in the Southern Ocean, yet their phenomenology is not well quantified. To tackle this task, we use satellite observations of sea level anomalies and sea surface temperature (SST) as well as in situ temperature and salinity measurements from profiling floats. Over the period 1997–2010, we identified over a million mesoscale eddy instances and were able to track about 105 of them over 1 month or more. The Antarctic Circumpolar Current (ACC), the boundary current systems, and the regions where they interact are hot spots of eddy presence, representing also the birth places and graveyards of most eddies. These hot spots contrast strongly to areas shallower than about 2000 m, where mesoscale eddies are essentially absent, likely due to topographical steering. Anticyclones tend to dominate the southern subtropical gyres, and cyclones the northern flank of the ACC. Major causes of regional polarity dominance are larger formation numbers and lifespan...
State-of-the-art earth system models used for long-term climate projections are becoming ever mor... more State-of-the-art earth system models used for long-term climate projections are becoming ever more complex in terms of not only spatial resolution but also the number of processes. Biogeochemical processes are beginning to be incorporated into these models. The motivation of this study is to quantify how climate projections are influenced by biogeochemical feedbacks. In the climate modeling community, it is virtually accepted that climate-Carbon (C) cycle feedbacks accelerate the future warming (Cox et al. 2000; Friedlingstein et al. 2006). It has been demonstrated that the Nitrogen (N) cycle suppresses climate-C cycle feedbacks (Thornton et al. 2009). On the contrary, biogeochemical studies show that the coupled C-N-Phosphorus (P) cycles are intimately interlinked via biosphere and the N-P cycles amplify C cycle feedbacks (Ver et al. 1999). The question as to whether the N-P cycles enhance or attenuate C cycle feedbacks is debated and has a significant implication for projections o...
Uploads