Description: The dominant mode of intraseasonal precipitation variability during the South American monsoon is the so-called precipitation dipole between the South Atlantic convergence zone (SACZ) and southeastern South America (SESA). It affects highly populated areas that are of substantial importance for the regional food supplies. Previous studies using principal components analysis or complex networks were able to describe and characterize this variability pattern, but crucial questions regarding the responsible physical mechanism remain open. Here, we use phase synchronization techniques to study the relation between precipitation in the SACZ and SESA on the one hand and southern hemisphere Rossby wave trains on the other hand. In combination with a conceptual model, this approach demonstrates that the dipolar precipitation pattern is caused by the southern hemisphere Rossby waves. Our results thus show that Rossby waves are the main driver of the monsoon season variability in South America, a finding that has important implications for synoptic-scale weather forecasts.

Description: Earth system models (ESMs) are our main tools for quantifying the physical state of the Earth and predicting how it might change in the future under ongoing anthropogenic forcing. In recent years, however, artificial intelligence (AI) methods have been increasingly used to augment or even replace classical ESM tasks, raising hopes that AI could solve some of the grand challenges of climate science. In this Perspective we survey the recent achievements and limitations of both process-based models and AI in Earth system and climate research, and propose a methodological transformation in which deep neural networks and ESMs are dismantled as individual approaches and reassembled as learning, self-validating and interpretable ESM–network hybrids. Following this path, we coin the term neural Earth system modelling. We examine the concurrent potential and pitfalls of neural Earth system modelling and discuss the open question of whether AI can bolster ESMs or even ultimately render them obsolete.

Description: During the last glacial interval, the Northern Hemisphere climate was punctuated by a series of abrupt changes between two characteristic climate regimes. The existence of stadial (cold) and interstadial (milder) periods is typically attributed to a hypothesised bistability in the glacial North Atlantic climate system, allowing for rapid transitions from the stadial to the interstadial state – the so-called Dansgaard–Oeschger (DO) events – and more gradual yet still fairly abrupt reverse shifts. The physical mechanisms driving these regime transitions remain debated. DO events are characterised by substantial warming over Greenland and a reorganisation of the Northern Hemisphere atmospheric circulation, which are evident from concomitant shifts in the δ18O ratios and dust concentration records from Greenland ice cores. Treating the combined δ18O and dust record obtained by the North Greenland Ice Core Project (NGRIP) as a realisation of a two-dimensional, time-homogeneous, and Markovian stochastic process, we present a reconstruction of its underlying deterministic drift based on the leading-order terms of the Kramers–Moyal equation. The analysis reveals two basins of attraction in the two-dimensional state space that can be identified with the stadial and interstadial regimes. The drift term of the dust exhibits a double-fold bifurcation structure, while – in contrast to prevailing assumptions – the δ18O component of the drift is clearly mono-stable. This suggests that the last glacial's Greenland temperatures should not be regarded as an intrinsically bistable climate variable. Instead, the two-regime nature of the δ18O record is apparently inherited from a coupling to another bistable climate process. In contrast, the bistability evidenced in the dust drift points to the presence of two stable circulation regimes of the last glacial's Northern Hemisphere atmosphere.

Description: Observational datasets are increasingly used to detect critical slowing down (CSD) as a measure of stability or resilience changes in key Earth system components. However, most observational datasets have inherent, often non-stationary missing-data-distributions, as well as biases and uncertainties, all of which can influence the CSD analysis. In particular, sea-surface temperature (SST) and salinity-based indices have been used to detect CSD for a possible collapse of the Atlantic Meridional Overturning Circulation (AMOC). Here we present an in-depth uncertainty analysis of AMOC CSD based on SST and salinity fingerprints. We first use uncertainties provided with the HadSST4 and HadCRUT5 SST datasets to generate uncertainty ensembles and estimate the uncertainty of SST-based AMOC fingerprints. We then construct stringent and conservative significance tests on the CSD indicators in the EN4.2.2, HadISST1 and HadCRUT5 datasets. We use surrogate testing that incorporates the influence of data processing steps and non-stationary uncertainties can have on CSD. We find that the properties of the observational datasets could in theory cause false indication of CSD, but that in the cases we examine, CSD indicators in the Atlantic are still present and significant. Our results highlight the importance of taking into account the properties of the specific observational dataset used when calculating higher-order statistics.

Description: Previous glacial intervals were punctuated by abrupt climate transitions between cold (stadial) and warm (interstadial) conditions. Many mechanisms leading to stadial-interstadial variability have been hypothesized with ice volume being a commonly involved element. Here, we test to which extent insolation modulated stadial-interstadial oscillations occurred during the penultimate glacial. We present a replicated and precisely dated speleothem record covering the period between 200 and 130 ka before present from caves located in the European Alps known to be sensitive to millennial-scale variability. We show that the widely proposed relationship between sea level change and stadial-interstadial variability was additionally modulated by solar insolation during this time interval. We find that interstadials occurred preferentially near maxima of Northern Hemisphere summer insolation, even when sea level remained close to its minimum during peak glacial periods. We confirm these observations with model simulations that accurately reproduce the frequency and duration of interstadials for given sea-level and insolation forcing. Our results imply that summer insolation played an important role in modulating the occurrence of stadial-interstadial oscillations and highlight the relevance of insolation in triggering abrupt climate changes.

Description: Characterized by their specific geometry, atmospheric rivers (ARs) are narrow, long, and transient channels of intensive water vapor transport in the lower troposphere. They play an essential role in the water supply for precipitation in the mid-latitudes but can also trigger natural hazards such as floods and landslides by facilitating heavy precipitation events. In this study, we link the occurrence of landslides in western North America (NA) during the past decades to the precipitation triggered by land-falling ARs hitting the western coastline of the region. For this, we use a landslide inventory, rainfall estimates with a daily temporal resolution, and a catalog of land-falling ARs characterized in terms of strength and persistence based on the AR scale by Ralph et al., 2019. We employ two attribution models to relate rainfall to ARs and then landslides to AR-induced rainfall. Our results show that ARs precede between 60% and 100% of the landslides reported along the western coast of North America. Intense and persistent ARs are the most common precursors. As a further analysis, we study the synchronization pattern of landslides and ARs to determine if their association is unique and significant. In the coastal regions, the precedence relation of ARs leading to landslides is statistically significant. Further inland, landslides are less likely, but those that do occur are significantly correlated with very intense and persistent ARs. Understanding and revealing the impacts of ARs on landslides in western North America will lead to better forecasts and risk assessments of these natural hazards.