Multiple tipping points in the Earth system could be triggered when global warming exceeds specific thresholds. However, the degree of their impact on the East Asian hydroclimate remains uncertain due to the lack of quantitative rainfall records. Here we present an ensemble reconstruction of East Asian summer monsoon (EASM) rainfall since the Last Glacial Maximum (LGM) using nine statistical and machine learning methods based on multi-proxy records from a maar lake in southern China. Our results define five tipping points in the EASM rainfall since the LGM, which are characterized by abrupt and irreversible regime shifts with a median amplitude of 387 ± 73 mm (24 ± 5 %). Combined with multi-model simulations and existing records, we attribute these tipping points to cascades of abrupt shifts in the Atlantic meridional overturning circulation (AMOC) and Saharan vegetation. Our findings underscore the nonlinear behavior of the EASM and its coupling with other tipping elements. The nonlinear behavior of the East Asian summer monsoon (EASM) remains largely unknown. Here, an ensemble reconstruction of EASM rainfall since the Last Glacial Maximum is presented and five tipping points in this monsoon system are identified.

Understanding the Amazon Rainforest's response to shifts in precipitation is paramount with regard to its sensitivity to climate change and deforestation. Studies using Dynamic Global Vegetation Models (DGVMs) typically only explore a range of socio-economically plausible pathways. In this study, we applied the state-of-the-art DGVM LPJmL to simulate the Amazon forest's response under idealized scenarios, where precipitation is linearly decreased and subsequently increased between current levels and zero. Our results indicate a nonlinear but reversible relationship between vegetation Above Ground Biomass (AGB) and Mean Annual Precipitation (MAP), suggesting a threshold at a critical MAP value, below which vegetation biomass decline accelerates with decreasing MAP. We find that approaching this critical threshold is accompanied by critical slowing down, which can hence be expected to warn of accelerating biomass decline with decreasing rainfall.The critical precipitation threshold is lowest in the northwestern Amazon, whereas the eastern and southern regions may already be below their critical MAP thresholds. Overall, we identify the seasonality of precipitation and the potential evapotranspiration (PET) as the most important parameters determining the threshold value. While vegetation fires show little effect on the critical threshold and the biomass pattern in general, the ability of trees to adapt to water stress by investing in deep roots leads to increased biomass and a lower critical threshold in some areas in the eastern and southern Amazon, where seasonality and PET are high. Our findings underscore the risk of Amazon forest degradation due to changes in the water cycle, and imply that regions that are currently characterized by higher water availability may exhibit heightened vulnerability to future drying.

The Amazon rainforest (ARF) is threatened by deforestation and climate change, which could trigger a regime shift to a savanna-like state. Previous work suggesting declining resilience in recent decades was based only on local resilience indicators. Moreover, previous results are potentially biased by the employed multi-sensor and optical satellite data and undetected anthropogenic land-use change. Here, we show that the spatial correlation provides a more robust resilience indicator than local estimators and employ it to measure resilience changes in the ARF, based on single-sensor Vegetation Optical Depth data under conservative exclusion of human activity. Our results show an overall loss of resilience until around 2019, which is especially pronounced in the southwestern and northern Amazon for the time period from 2002 to 2011. The demonstrated reliability of spatial correlation in coupled systems suggests that in particular the southwest of the ARF has experienced pronounced resilience loss over the last two decades.

One way to warn of forthcoming critical transitions in Earth system components is using observations to detect declining system stability. It has also been suggested to extrapolate such stability changes into the future and predict tipping times. Here, we argue that the involved uncertainties are too high to robustly predict tipping times. We raise concerns regarding (i) the modeling assumptions underlying any extrapolation of historical results into the future, (ii) the representativeness of individual Earth system component time series, and (iii) the impact of uncertainties and preprocessing of used observational datasets, with focus on nonstationary observational coverage and gap filling. We explore these uncertainties in general and specifically for the example of the Atlantic Meridional Overturning Circulation. We argue that even under the assumption that a given Earth system component has an approaching tipping point, the uncertainties are too large to reliably estimate tipping times by extrapolating historical information.

Observations are increasingly used to detect critical slowing down (CSD) to measure stability changes in key Earth system components. However, most datasets have non-stationary missing-data distributions, biases and uncertainties. Here we show that, together with the pre-processing steps used to deal with them, these can bias the CSD analysis. We present an uncertainty quantification method to address such issues. We show how to propagate uncertainties provided with the datasets to the CSD analysis and develop conservative, surrogate-based significance tests on the CSD indicators. We apply our method to three observational sea-surface temperature and salinity datasets and to fingerprints of the Atlantic Meridional Overturning Circulation derived from them. We find that the properties of these datasets and especially the specific gap filling procedures can in some cases indeed cause false indication of CSD. However, CSD indicators in the North Atlantic are still present and significant when accounting for dataset uncertainties and non-stationary observational coverage.

A collapse of the Atlantic Meridional Overturning Circulation (AMOC) would have substantial impacts on global precipitation patterns, especially in the vulnerable tropical monsoon regions. We assess these impacts using four state-of-the-art climate models with bistable AMOC. Spatial and seasonal patterns of precipitation change are remarkably consistent across models. We focus on the South American Monsoon (SAM), the West African Monsoon (WAM), the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM). Models consistently suggest substantial disruptions for WAM, ISM and EASM with shorter wet and longer dry seasons (-29.07\%,-18.76\% and -3.78\% ensemble mean annual rainfall change, respectively). Models also agree on changes for the SAM, suggesting rainfall increases overall, in contrast to previous studies. These are more pronounced in the southern Amazon (+43.79\%), accompanied by decreasing dry-season length. Consistently across models, our results suggest major rearranging of all tropical monsoon systems in response to an AMOC collapse.

Abstract The Amazon rainforest is threatened by both anthropogenic climate and land use change. Observations and some modelling results suggest that the Amazon rainforest might abruptly transition to a savanna-like state and that this transition would be practically irreversible. Here, we analyze observations of precipitation, temperature and tree cover together with high-resolution simulations of several comprehensive climate models to investigate the combined effect global warming and a potential collapse of the Atlantic Meridional Overturning Circulation (AMOC) will have on the Amazon. Our results show that, while high levels of warming lead to forest dieback, an AMOC collapse would tend to stabilize the forest by increasing rainfall and decreasing temperature in most of the Amazon basin. Although an AMOC collapse would have devastating impacts globally, our results hence suggest that it may delay or even prevent parts of the Amazon rainforest from transitioning to a savanna-like state.

Observations and models suggest that the Amazon rainforest might transition to a savanna-like state in response to anthropogenic climate and land use change. Here, we combine observations of precipitation, temperature and tree cover with high-resolution comprehensive climate model simulations to investigate the combined effect of global warming and a potential Atlantic Meridional Overturning Circulation collapse on the Amazon. Our results show that, while strong warming lead to forest dieback, an Atlantic Meridional Overturning Circulation collapse would stabilize the Amazon by increasing rainfall and decreasing temperature in most parts. Although an Atlantic Meridional Overturning Circulation collapse would have devastating impacts globally, our results suggest that it may delay or even prevent parts of the Amazon rainforest from dieback. Besides the many negative consequences of its collapse, the interactions we identify here make a tipping cascade, i.e., that an Atlantic Meridional Overturning Circulation collapse would trigger Amazon dieback, appear less plausible.

Ice core records from Greenland provide evidence for multiple abrupt warming events recurring at millennial time scales during the last glacial interval. Although climate transitions strongly resembling these Dansgaard-Oeschger (DO) transitions have been identified in several speleothem records, our understanding of the climate and ecosystem impacts of the Greenland warming events in lower latitudes remains incomplete. Here, we investigate the influence of DO transitions on the global atmospheric circulation pattern. We comprehensively analyse d18O changes during DO transitions in a globally distributed dataset of speleothems (SISALv2; Comas-Bru et al., 2020). Speleothem d18O signals mostly reflect changes in precipitation amount and moisture source. Thereby this proxy allows us to infer spatially resolved changes in global atmospheric dynamics that are characteristically linked to DO transitions. We confirm the previously proposed shift of the Intertropical Convergence Zone towards more northerly positions. In addition, we find evidence for a similar northward shift of the westerly winds of the Northern Hemisphere. Furthermore, we identify a decreasing trend in the transition amplitudes with increasing distances from the North Atlantic region. This confirms previous suggestions of this region being the core and origin of these past abrupt climate changes. References: Comas-Bru et al., 2020, Earth System Science Data 12, 2579–2606