Description: Rapid monsoon changes since the last deglaciation remain poorly constrained due to the scarcity of geological archives. Here we present a high-resolution scanning X-ray fluorescence (XRF) analysis of a 13.5 m terrace succession on the western Chinese Loess Plateau (CLP) to infer rapid monsoon changes since the last deglaciation. Our results indicate that Rb∕Sr and Zr∕Rb are sensitive indicators of chemical weathering and wind sorting, respectively, which are further linked to the strength of the East Asian summer monsoon (EASM) and the East Asian winter monsoon (EAWM). During the last deglaciation, two cold intervals of the Heinrich event 1 and Younger Dryas were characterized by intensified winter monsoon and weakened summer monsoon. The EAWM gradually weakened at the beginning of the Holocene, while the EASM remained steady till 9.9 ka and then grew stronger. Both the EASM and EAWM intensities were relatively weak during the Middle Holocene, indicating a mid-Holocene climatic optimum. Rb∕Sr and Zr∕Rb exhibit an antiphase relationship between the summer and winter monsoon changes on a centennial timescale during 16–1 ka. Comparison of these monsoon changes with solar activity and North Atlantic cooling events reveals that both factors can lead to abrupt changes on a centennial timescale in the Early Holocene. During the Late Holocene, North Atlantic cooling became the major forcing of centennial monsoon events.

Description: The research area of climate field reconstructions has developed strongly during the past 20 years, motivated by the need to understand the complex dynamics of the earth system in a changing climate. Climate field reconstructions aim to build a consistent gridded climate reconstruction of different variables, often from a range of climate proxies, using either statistical tools or a climate model to fill the gaps between the locations of the proxy data. Commonly, large-scale climate field reconstructions covering more than 500 years are of annual resolution. In this method study, we investigate the potential of seasonally resolved climate field reconstructions based on oxygen isotope records from Greenland ice cores and an isotope-enabled climate model. Our analogue-type method matches modeled isotope patterns in Greenland precipitation to the patterns of ice core data from up to 14 ice core sites. In a second step, the climate variables of the best-matching model years are extracted, with the mean of the best-matching years comprising the reconstruction. We test a range of climate reconstructions, varying the definition of the seasons and the number of ice cores used. Our findings show that the optimal definition of the seasons depends on the variability in the target season. For winter, the vigorous variability is best captured when defining the season as December–February due to the dominance of large-scale patterns. For summer, which has weaker variability, albeit more persistent in time, the variability is better captured using a longer season of May–October. Motivated by the scarcity of seasonal data, we also test the use of annual data where the year is divided during summer, that is, not following the calendar year. This means that the winter variability is not split and that the annual data then can be used to reconstruct the winter variability. In particularly when reconstructing the sea level pressure and the corresponding main modes of variability, it is important to take seasonality into account, because of changes in the spatial patterns of the modes throughout the year. Targeting the annual mean sea level pressure for the reconstruction lowers the skill simply due to the seasonal geographical shift of the circulation modes. Our reconstructions based on ice core data also show skill for the North Atlantic sea surface temperatures, in particularly during winter for latitudes higher than 50◦ N. In addition, the main modes of the sea surface temperature variability are qualitatively captured by the reconstructions. When testing the skill of the reconstructions using 19 ice cores compared to the ones using eight ice cores, we do not find a clear advantage of using a larger data set. This could be due to a more even spatial distribution of the eight ice cores. However, including European tree-ring data to further constrain the summer temperature reconstruction clearly improves the skill for this season, which otherwise is more difficult to capture than the winter season.

Description: In this paper we introduce a Bayesian framework, which is explicit about prior assumptions, for using model ensembles and observations together to constrain future climate change. The emergent constraint approach has seen broad application in recent years, including studies constraining the equilibrium climate sensitivity (ECS) using the Last Glacial Maximum (LGM) and the mid-Pliocene Warm Period (mPWP). Most of these studies were based on ordinary least squares (OLS) fits between a variable of the climate state, such as tropical temperature, and climate sensitivity. Using our Bayesian method, and considering the LGM and mPWP separately, we obtain values of ECS of 2.7 K (0.6–5.2, 5th–95th percentiles) using the PMIP2, PMIP3, and PMIP4 datasets for the LGM and 2.3 K (0.5–4.4) with the PlioMIP1 and PlioMIP2 datasets for the mPWP. Restricting the ensembles to include only the most recent version of each model, we obtain 2.7 K (0.7–5.2) using the LGM and 2.3 K (0.4–4.5) using the mPWP. An advantage of the Bayesian framework is that it is possible to combine the two periods assuming they are independent, whereby we obtain a tighter constraint of 2.5 K (0.8–4.0) using the restricted ensemble. We have explored the sensitivity to our assumptions in the method, including considering structural uncertainty, and in the choice of models, and this leads to 95 % probability of climate sensitivity mostly below 5 K and only exceeding 6 K in a single and most uncertain case assuming a large structural uncertainty. The approach is compared with other approaches based on OLS, a Kalman filter method, and an alternative Bayesian method. An interesting implication of this work is that OLS-based emergent constraints on ECS generate tighter uncertainty estimates, in particular at the lower end, an artefact due to a flatter regression line in the case of lack of correlation. Although some fundamental challenges related to the use of emergent constraints remain, this paper provides a step towards a better foundation for their potential use in future probabilistic estimations of climate sensitivity.

Description: In recent years, many components of the connection between Eurasian autumn snow cover and wintertime North Atlantic Oscillation (NAO) have been investigated, suggesting that November snow cover distribution has strong prediction power for the upcoming Northern Hemisphere winter climate. However, the non-stationarity of this relationship could impact its use for prediction routines. Here we use snow products from long-term reanalyses to investigate interannual and interdecadal links between autumnal snow cover and atmospheric conditions in winter. We find evidence for a negative NAO-like signal after November with a strong west-to-east snow cover gradient, which is valid throughout the last 150 years. This correlation is consistently linked to a weak stratospheric polar vortex state. Nevertheless, decadal evolution of this link shows episodes of decreased correlation strength, which co-occur with episodes of low variability in the November snow index. By contrast, periods with high prediction skill for winter NAO are found in periods of high November snow variability, which co-occur with the Arctic warming periods of the 20th century, namely the early 20th-century Arctic warming between 1920 and 1940 and the ongoing anthropogenic global warming at the end of the 20th century. A strong snow dipole itself is consistently associated with reduced Barents–Kara sea ice concentration, increased Ural blocking frequency and negative temperature anomalies in eastern Eurasia.

Description: Energy balance models (EBMs) are highly simplified models of the climate system, providing admissible conceptual tools for understanding climate changes. The global temperature is calculated by the radiation budget through the incoming energy from the Sun and the outgoing energy from the Earth. The argument that the temperature can be calculated by this simple radiation budget is revisited. The underlying assumption for a realistic temperature distribution is explored: one has to assume a moderate diurnal cycle due to the large heat capacity and the fast rotation of the Earth. Interestingly, the global mean in the revised EBM is very close to the originally proposed value. The main point is that the effective heat capacity and its temporal variation over the daily and seasonal cycle needs to be taken into account when estimating surface temperature from the energy budget. Furthermore, the time-dependent EBM predicts a flat meridional temperature gradient for large heat capacities, reducing the seasonal cycle and the outgoing radiation and increasing global temperature. Motivated by this finding, a sensitivity experiment with a complex model is performed where the vertical diffusion in the ocean has been increased. The resulting temperature gradient, reduced seasonal cycle, and global warming is also found in climate reconstructions, providing a possible mechanism for past climate changes prior to 3 million years ago.

Description: The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×106 km2, compared to 6.46×106 km2 for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×106 km2 for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 % yr−1) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.

Description: A compilation of the published literature on dust content in terrestrial and marine sediment cores was synchronized with pollen data and speleothem growth phases on the Greenland Ice Core Chronology 2005 (GICC05) time axis. Aridity patterns for eight key areas of the global climate system have been reconstructed for the last 60 000 years. These records have different time resolutions and different dating methods, i.e. different types of stratigraphy. Nevertheless, all regions analysed in this study show humid conditions during early Marine Isotope Stage 3 (MIS3) and the early Holocene or deglaciation, but not always at the same time. Such discrepancies have been interpreted as regional effects, although stratigraphic uncertainties may affect some of the proposed interpretations. In comparison, most of the MIS2 interval becomes arid in all of the Northern Hemisphere records, but the peak arid conditions of the Last Glacial Maximum (LGM) and Heinrich event 1 differ in duration and intensity among regions. In addition, we also compare the aridity synthesis with modelling results using a global climate model (GCM). Indeed, geological archives and GCMs show agreement on the aridity pattern for the Holocene or deglaciation, for the LGM and for late MIS3.

Description: In the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), coupled climate models have been used to simulate an interglacial climate during the mid-Piacenzian warm period (mPWP; 3.264 to 3.025 Ma). Here, we compare the Atlantic Meridional Overturning Circulation (AMOC), poleward ocean heat transport and sea surface warming in the Atlantic simulated with these models. In PlioMIP2, all models simulate an intensified mid-Pliocene AMOC. However, there is no consistent response in the simulated Atlantic ocean heat transport nor in the depth of the Atlantic overturning cell. The models show a large spread in the simulated AMOC maximum, the Atlantic ocean heat transport and the surface warming in the North Atlantic. Although a few models simulate a surface warming of ∼ 8–12 ∘C in the North Atlantic, similar to the reconstruction from Pliocene Research, Interpretation and Synoptic Mapping (PRISM) version 4, most models appear to underestimate this warming. The large model spread and model–data discrepancies in the PlioMIP2 ensemble do not support the hypothesis that an intensification of the AMOC, together with an increase in northward ocean heat transport, is the dominant mechanism for the mid-Pliocene warm climate over the North Atlantic.