East Asia has experienced strong warming since the 1960s accompanied by an increased frequency of heat waves and shrinking glaciers over the Tibetan Plateau and the Tien Shan. Here, we place the recent warmth in a long-term perspective by presenting a new spatially resolved warm-season (May-September) temperature reconstruction for the period 1–2000 CE using 59 multiproxy records from a wide range of East Asian regions. Our Bayesian Hierarchical Model (BHM) based reconstructions generally agree with earlier shorter regional temperature reconstructions but are more stable due to additional temperature sensitive proxies. We find a rather warm period during the first two centuries CE, followed by a multi-century long cooling period and again a warm interval covering the 900–1200 CE period (Medieval Climate Anomaly, MCA). The interval from 1450 to 1850 CE (Little Ice Age, LIA) was characterized by cooler conditions and the last 150 years are characterized by a continuous warming until recent times. Our results also suggest that the 1990s were likely the warmest decade in at least 1200 years. The comparison between an ensemble of climate model simulations and our summer reconstructions since 850 CE shows good agreement and an important role of internal variability and external forcing on multi-decadal time-scales.

Abstract. Quantifying precipitation variability beyond the instrumental period is essential for putting current and future fluctuations into long-term perspective and providing a test bed for evaluating climate simulations. For south-eastern Asia such quantifications are scarce and millennium-long attempts are still missing. In this study we take a pseudo-proxy approach to evaluate the potential for generating summer precipitation reconstructions over south-eastern Asia during the past millennium. The ability of a series of novel Bayesian approaches to generate reconstructions at either annual or decadal resolutions and under diverse scenarios of pseudo-proxy records' noise is analysed and compared to the classic analogue method. We find that for all the algorithms and resolutions a high density of pseudo-proxy information is a necessary but not sufficient condition for a successful reconstruction. Among the selected algorithms, the Bayesian techniques perform generally better than the analogue method, the difference in abilities being highest over the semi-arid areas and in the decadal-resolution framework. The superiority of the Bayesian schemes indicates that directly modelling the space and time precipitation field variability is more appropriate than just relying on a pool of observational-based analogues in which certain precipitation regimes might be absent. Using a pseudo-proxy network with locations and noise levels similar to the ones found in the real world, we conclude that performing a millennium-long precipitation reconstruction over south-eastern Asia is feasible as the Bayesian schemes provide skilful results over most of the target area.

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Abstract. We propose a reduced-complexity process-based model for the long-term evolution of the global ice volume, atmospheric CO2 concentration, and global mean temperature. The model's only external forcings are the orbital forcing and anthropogenic CO2 cumulative emissions. The model consists of a system of three coupled non-linear differential equations representing physical mechanisms relevant for the evolution of the climate–ice sheet–carbon cycle system on timescales longer than thousands of years. Model parameters are calibrated using paleoclimate reconstructions and the results of two Earth system models of intermediate complexity. For a range of parameters values, the model is successful in reproducing the glacial–interglacial cycles of the last 800 kyr, with the best correlation between modelled and global paleo-ice volume of 0.86. Using different model realisations, we produce an assessment of possible trajectories for the next 1 million years under natural and several fossil-fuel CO2 release scenarios. In the natural scenario, the model assigns high probability of occurrence of long interglacials in the periods between the present and 120 kyr after present and between 400 and 500 kyr after present. The next glacial inception is most likely to occur ∼50 kyr after present with full glacial conditions developing ∼90 kyr after present. The model shows that even already achieved cumulative CO2 anthropogenic emissions (500 Pg C) are capable of affecting the climate evolution for up to half a million years, indicating that the beginning of the next glaciation is highly unlikely in the next 120 kyr. High cumulative anthropogenic CO2 emissions (3000 Pg C or higher), which could potentially be achieved in the next 2 to 3 centuries if humanity does not curb the usage of fossil fuels, will most likely provoke Northern Hemisphere landmass ice-free conditions throughout the next half a million years, postponing the natural occurrence of the next glacial inception to 600 kyr after present or later.

We use a coupled model to estimate the natural variability of summertime rainfall over South America and to determine the time horizon when anthropogenic forcing will start having an effect on it. We use a combination of three experiments: preindustrial, 20th century, and the projected changes under A1B scenario. The first empirical orthogonal function of rainfall in December-February is used to characterize summertime variability. The model can display two different regimes of natural variability of this mode. In one regime, there is a strong coupling between the South Atlantic convergence zone (SACZ) and the Atlantic Ocean. In the other regime, the SACZ is dominated by internal atmospheric variability. The detection of the impact of anthropogenic forcing is calculated comparing the probability density functions (pdfs) of the preindustrial run with the one under the A1B scenario. We found that the detection strongly depends on the pdf used to characterize internal climate variability. If the pdf of the mode with coupling between the SACZ and the Atlantic Ocean is used, the anthropogenic influence is felt very early within the future scenario (in less than 30 years). On the contrary, with the pdf that characterizes an SACZ dominated by internal atmospheric variability, the forcing is detected only several (almost 50) years into the scenario.

In this study, we analyzed the influence of interannual variability in sea surface temperature (SST) on the climate of southeastern South America (SESA) during austral summer. We found that the correlation between the El Niño Southern Oscillation (ENSO) and rainfall over southern Brazil-northern Uruguay (SB-NU) was not statistically significant between 1949 and 1978, but it was significant between 1979 and 2009. The results show that this change in correlation was largely due to the modified rainfall response over SB-NU to La Niña events. A cluster analysis for all summers between 1949 and 2009 identified a turning point of La Niña events in 1979. We document the atmospheric circulation patterns associated with the strong correlation between ENSO and the rainfall over SB-NU after 1979 and hypothesize causes of the weaker correlation in the earlier period. In particular, numerical simulations produced using the UCLA atmospheric general circulation model showed important differences between upper tropo spheric circulation patterns during ENSO cold episodes after the late 1970s relative to the earlier period. Such differences were consistent with changes in the impacts of La Niña events on SESA. The differences in Indian Ocean SST anomalies largely explained these results.

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