Description: The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community‐sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive‐specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom‐up and top‐down approaches.

Description: Knowledge of the characteristics of natural climate variability is vital when assessing the range of plausible future climate trajectories in the next decades to centuries. The reliable detection of climate fluctuations on multidecadal to centennial timescales depends on proxy reconstructions and model simulations, as the instrumental record extends back only a few decades in most parts of the world. Systematic comparisons between model-simulated and proxy-based inferences of natural variability, however, often seem contradictory. Locally, simulated temperature variability is consistently smaller on multidecadal and longer timescales than is indicated by proxy-based reconstructions, implying that climate models or proxy interpretations might have deficiencies. In contrast, at global scales, studies found agreement between simulated and proxy reconstructed temperature variations. Here we review the evidence regarding the scale of natural temperature variability during recent millennia. We identify systematic reconstruction deficiencies that may contribute to differing local and global model–proxy agreement but conclude that they are probably insufficient to resolve such discrepancies. Instead, we argue that regional climate variations persisted for longer timescales than climate models simulating past climate states are able to reproduce. This would imply an underestimation of the regional variability on multidecadal and longer timescales and would bias climate projections and attribution studies. Thus, efforts are needed to improve the simulation of natural variability in climate models accompanied by further refining proxy-based inferences of variability.

Description: The projected increases in Earth’s mean temperature entail substantial changes in the climate’s variability. Appropriate mitigation and adaptation measures require understanding of these changes since they impact for example the occurrence of extreme events. While projections of the global mean temperature are relatively well constrained based on the employed forcing scenario, they are highly uncertain with respect to the hydrological cycle and local temperature variability. Thus, examining how periods of past warming can help constrain these changes is of vital importance.To this end, we examine how the variability of surface temperature and precipitation changes in simulations of past and future warming from climate models of varying complexity and compare these with changes in proxy-based reconstructions. Based on the simulations, we analyze the moments of the distributions of temperature and precipitation (variance, skewness and kurtosis), as well as the power spectra with a focus on societally-relevant annual to centennial timescales. The analysis contrasts the projected changes under future warming scenarios with those found in transient simulations of the Last Deglaciation from models ranging from an energy balance model to Earth System Models. Changes observed in the simulations of the Last Deglaciation often highly depend on timescale and forcings, in particular changing volcanic activity, meltwater release and ice distributions alter patterns of variability. Based on this, we examine how the faster rate of future change impacts, and potentially limits, the conclusions to be drawn about future climatic changes based on past periods of warming.