Description: Though primarily driven by insolation changes associated with well-known variations in Earth's astronomical parameters, the response of the climate system during interglacials includes a diversity of feedbacks involving the atmosphere, ocean, sea ice, vegetation and land ice. A thorough multi-model-data comparison is essential to assess the ability of climate models to resolve interglacial temperature trends and to help in understanding the recorded climatic signal and the underlying climate dynamics. We present the first multi-model-data comparison of transient millennial-scale temperature changes through two intervals of the Present Interglacial (PIG; 8–1.2 ka) and the Last Interglacial (LIG; 123–116.2 ka) periods. We include temperature trends simulated by 9 different climate models, alkenone-based temperature reconstructions from 117 globally distributed locations (about 45% of them within the LIG) and 12 ice-core-based temperature trends from Greenland and Antarctica (50% of them within the LIG). The definitions of these specific interglacial intervals enable a consistent inter-comparison of the two intervals because both are characterised by minor changes in atmospheric greenhouse gas concentrations and more importantly by insolation trends that show clear similarities. Our analysis shows that in general the reconstructed PIG and LIG Northern Hemisphere mid-to-high latitude cooling compares well with multi-model, mean-temperature trends for the warmest months and that these cooling trends reflect a linear response to the warmest-month insolation decrease over the interglacial intervals. The most notable exception is the strong LIG cooling trend reconstructed from Greenland ice cores that is not simulated by any of the models. A striking model-data mismatch is found for both the PIG and the LIG over large parts of the mid-to-high latitudes of the Southern Hemisphere where the data depicts negative temperature trends that are not in agreement with near zero trends in the simulations. In this area, the positive local summer insolation trend is counteracted in climate models by an enhancement of the Southern Ocean summer sea-ice cover and/or an increase in Southern Ocean upwelling. If the general picture emerging from reconstructions is realistic, then the model-data mismatch in mid and high Southern Hemisphere latitudes implies that none of the models is able to resolve the correct balance of these feedbacks, or, alternatively, that interglacial Southern Hemisphere temperature trends are driven by mechanisms which are not included in the transient simulations, such as changes in the Antarctic ice sheet or meltwater-induced changes in the overturning circulation.

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.