Quantifying the effect of interannual ocean variability on the attribution of extreme climate events to human influence

In recent years, the climate change research community has become highly interested in describing the anthropogenic influence on extreme weather events, commonly termed "event attribution." Limitations in the observational record and in computational resources motivate the use of uncoupled, atmosphere/land-only climate models with prescribed ocean conditions run over a short period, leading up to and including an event of interest. In this approach, large ensembles of high-resolution simulations can be generated under factual observed conditions and counterfactual conditions that might have been observed in the absence of human interference; these can be used to estimate the change in probability of the given event due to anthropogenic influence. However, using a prescribed ocean state ignores the possibility that estimates of attributable risk might be a function of the ocean state. Thus, the uncertainty in attributable risk is likely underestimated, implying an over-confidence in anthropogenic influence. In this work, we estimate the year-to-year variability in calculations of the anthropogenic contribution to extreme weather based on large ensembles of atmospheric model simulations. Our results both quantify the magnitude of year-to-year variability and categorize the degree to which conclusions of attributable risk are qualitatively affected. The methodology is illustrated by exploring extreme temperature and precipitation events for the northwest coast of South America and northern-central Siberia; we also provides results for regions around the globe. While it remains preferable to perform a full multi-year analysis, the results presented here can serve as an indication of where and when attribution researchers should be concerned about the use of atmosphere-only simulations

Resolution Dependence of Future Tropical Cyclone Projections of CAM5.1 in the US CLIVAR Hurricane Working Group Idealized Configurations

The four idealized configurations of the U.S. CLIVAR Hurricane Working Group are integrated using the global Community Atmospheric Model version 5.1 at two different horizontal resolutions, approximately 100 and 25 km. The publicly released 0.9° × 1.3° configuration is a poor predictor of the sign of the 0.23° × 0.31° model configuration’s change in the total number of tropical storms in a warmer climate. However, it does predict the sign of the higher-resolution configuration’s change in the number of intense tropical cyclones in a warmer climate. In the 0.23° × 0.31° model configuration, both increased CO2 concentrations and elevated sea surface temperature (SST) independently lower the number of weak tropical storms and shorten their average duration. Conversely, increased SST causes more intense tropical cyclones and lengthens their average duration, resulting in a greater number of intense tropical cyclone days globally. Increased SST also increased maximum tropical storm instantaneous precipitation rates across all storm intensities. It was found that while a measure of maximum potential intensity based on climatological mean quantities adequately predicts the 0.23° × 0.31° model’s forced response in its most intense simulated tropical cyclones, a related measure of cyclogenesis potential fails to predict the model’s actual cyclogenesis response to warmer SSTs. These analyses lead to two broader conclusions: 1) Projections of future tropical storm activity obtained by a direct tracking of tropical storms simulated by coarse-resolution climate models must be interpreted with caution. 2) Projections of future tropical cyclogenesis obtained from metrics of model behavior that are based solely on changes in long-term climatological fields and tuned to historical records must also be interpreted with caution

Resolution Dependence of Future Tropical Cyclone Projections of CAM5.1 in the US CLIVAR Hurricane Working Group Idealized Configurations

The four idealized configurations of the U.S. CLIVAR Hurricane Working Group are integrated using the global Community Atmospheric Model version 5.1 at two different horizontal resolutions, approximately 100 and 25 km. The publicly released 0.9° × 1.3° configuration is a poor predictor of the sign of the 0.23° × 0.31° model configuration’s change in the total number of tropical storms in a warmer climate. However, it does predict the sign of the higher-resolution configuration’s change in the number of intense tropical cyclones in a warmer climate. In the 0.23° × 0.31° model configuration, both increased CO2 concentrations and elevated sea surface temperature (SST) independently lower the number of weak tropical storms and shorten their average duration. Conversely, increased SST causes more intense tropical cyclones and lengthens their average duration, resulting in a greater number of intense tropical cyclone days globally. Increased SST also increased maximum tropical storm instantaneous precipitation rates across all storm intensities. It was found that while a measure of maximum potential intensity based on climatological mean quantities adequately predicts the 0.23° × 0.31° model’s forced response in its most intense simulated tropical cyclones, a related measure of cyclogenesis potential fails to predict the model’s actual cyclogenesis response to warmer SSTs. These analyses lead to two broader conclusions: 1) Projections of future tropical storm activity obtained by a direct tracking of tropical storms simulated by coarse-resolution climate models must be interpreted with caution. 2) Projections of future tropical cyclogenesis obtained from metrics of model behavior that are based solely on changes in long-term climatological fields and tuned to historical records must also be interpreted with caution

Transient and Quasi-Equilibrium Climate States at 1.5 degrees C and 2 degrees C Global Warming

Recent climate change is characterized by rapid global warming, but the goal of the Paris Agreement is to achieve a stable climate where global temperatures remain well below 2 degrees C above pre-industrial levels. Inferences about conditions at or below 2 degrees C are usually made based on transient climate projections. To better understand climate change impacts on natural and human systems under the Paris Agreement, we must understand how a stable climate may differ from transient conditions at the same warming level. Here we examine differences between transient and quasi-equilibrium climates using a statistical framework applied to greenhouse gas-only model simulations. This allows us to infer climate change patterns at 1.5 degrees C and 2 degrees C global warming in both transient and quasi-equilibrium climate states. We find substantial local differences between seasonal-average temperatures dependent on the rate of global warming, with mid-latitude land regions in boreal summer considerably warmer in a transient climate than a quasi-equilibrium state at both 1.5 degrees C and 2 degrees C global warming. In a rapidly warming world, such locations may experience a temporary emergence of a local climate change signal that weakens if the global climate stabilizes and the Paris Agreement goals are met. Our research demonstrates that the rate of global warming must be considered in regional projections.11Nsciescopu

Detection and attribution of observed impacts

Introduction This chapter synthesizes the scientific literature on the detection and attribution of observed changes in natural and human systems in response to observed recent climate change. For policy makers and the public, detection and attribution of observed impacts will be a key element to determine the necessity and degree of mitigation and adaptation efforts. For most natural and essentially all human systems, climate is only one of many drivers that cause change-other factors such as technological innovation, social and demographic changes, and environmental degradation frequently play an important role as well. Careful accounting of the importance of these and other confounding factors is therefore an important part of the analysis. At any given location, observed recent climate change has happened as a result of a combination of natural, longer term fluctuations and anthropogenic alteration of forcings. To inform about the sensitivity of natural and human systems to ongoing climate change, the chapter assesses the degree to which detected changes in such systems can be attributed to all aspects of recent climate change. For the development of adaptation policies, it is less important whether the observed changes have been caused by anthropogenic climate change or by natural climate fluctuations. Where possible, the relative importance of anthropogenic drivers of climate change is assessed as well. 18.1.1. Scope and Goals of the Chapter Previous assessments, notably in the IPCC Fourth Assessment Report (AR4; Rosenzweig et al., 2007), indicated that numerous physical and biological systems are affected by recent climate change. Owing to a limited number of published studies, human systems received comparatively little attention in these assessments, with the exception of the food system, which is a coupled human-natural system. This knowledge base is growing rapidly, for all types of impacted systems, but the disequilibrium remains (see also Section 1.1.1, Figure 1-1). The great majority of published studies attribute local to regional changes in affected systems to local to regional climate change