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Mountains are key features of the Earth’s surface and host a substantial proportion of the world’s species. However, the links between the evolution and distribution of biodiversity and the formation of mountains remain poorly understood. Here, we integrate multiple datasets to assess the relationships between species richness in mountains, geology and climate at global and regional scales. Specifically, we analyse how erosion, relief, soil and climate relate to the geographical distribution of terrestrial tetrapods, which include amphibians, birds and mammals. We find that centres of species richness correlate with areas of high temperatures, annual rainfall and topographic relief, supporting previous studies. We unveil additional links between mountain-building processes and biodiversity: species richness correlates with erosion rates and heterogeneity of soil types, with a varying response across continents. These additional links are prominent but under-explored, and probably relate to the interplay between surface uplift, climate change and atmospheric circulation through time. They are also influenced by the location and orientation of mountain ranges in relation to air circulation patterns, and how species diversification, dispersal and refugia respond to climate change. A better understanding of biosphere–lithosphere interactions is needed to understand the patterns and evolution of mountain biodiversity across space and time.

In recent decades, an increasing persistence of atmospheric circulation patterns has been observed. In the course of the associated long-lasting anticyclonic summer circulations, heatwaves and drought spells often coincide, leading to so-called hotter droughts. Previous hotter droughts caused a decrease in agricultural yields and an increase in tree mortality. Thus, they had a remarkable effect on carbon budgets and negative economic impacts. Consequently, a quantification of ecosystem responses to hotter droughts and a better understanding of the underlying mechanisms are crucial. In this context, the European hotter drought of the year 2018 may be considered a key event. As a first step towards the quantification of its causes and consequences, we here assess anomalies of atmospheric circulation patterns, maximum temperature, and climatic water balance as potential drivers of ecosystem responses which are quantified by remote sensing using the MODIS vegetation indices (VIs) normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). To place the drought of 2018 within a climatological context, we compare its climatic features and remotely sensed ecosystem response with the extreme hot drought of 2003. The year 2018 was characterized by a climatic dipole, featuring extremely hot and dry weather conditions north of the Alps but comparably cool and moist conditions across large parts of the Mediterranean. Analysing the ecosystem response of five dominant land cover classes, we found significant positive effects of climatic water balance on ecosystem VI response. Negative drought impacts appeared to affect an area 1.5 times larger and to be significantly stronger in July 2018 compared to August 2003, i.e. at the respective peak of drought. Moreover, we found a significantly higher sensitivity of pastures and arable land to climatic water balance compared to forests in both years. We explain the stronger coupling and higher sensitivity of ecosystem response in 2018 by the prevailing climatic dipole: while the generally water-limited ecosystems of the Mediterranean experienced above-average climatic water balance, the less drought-adapted ecosystems of central and northern Europe experienced a record hot drought. In conclusion, this study quantifies the drought of 2018 as a yet unprecedented event, outlines hotspots of drought-impacted areas in 2018 which should be given particular attention in follow-up studies, and provides valuable insights into the heterogeneous responses of the dominant European ecosystems to hotter drought.

The 2022 heatwave in China featured record‐shattering high temperatures, raising questions about its origin and possible link to global warming. Here we show that the maximum temperature anomalies over Central China reached 13.1°C in the summer of 2022, which is ∼4.2σ above the 1981–2010 mean with a return period of tens of thousands of years. Our results suggested that the persistent high‐pressure anomaly and associated extreme heatwave likely resulted mainly from internal variability, although anthropogenic warming has increased the probability of such extreme heatwaves. We also estimate that the 2022‐like heatwave becomes six to seven times more likely under persistent high‐pressure conditions when compared to stochastic circulation states. Due to a shift toward warmer mean temperatures and a flattening of the probability distribution function, such rare extreme heatwaves are projected to become much more common at a global warming level of 4°C, occurring once about every 8.5 years. Plain Language Summary China experienced an extensive and long‐lasting heatwave in the summer of 2022, especially in the middle reaches of the Yangtze River. Using state‐of‐the‐art reanalysis and models, here we show that the 2022 heatwave is among the most severe events ever recorded in China with a return period of tens of thousands of years. The atmospheric circulation patterns associated with the 2022 heatwave are not caused by external forcing, but due to internal atmospheric variability characterized by extremely warm anomalies and positive high‐pressure anomalies around central China, which increase the chance of such events by more than six times. A shift of the temperature distribution toward higher mean values and enlarged variability under global warming would increase the chances of new record‐breaking temperatures in the future. Such rare heatwaves in the natural and present climate could become much more common in the middle reaches of the Yangtze River under anthropogenic warming, occurring at least once every eight years at a global warming level of 4°C. Thus, efforts to build social resilience to extreme heatwaves are therefore urgently needed. Key Points Atmospheric circulation patterns associated with the 2022 heatwave likely resulted from internal variability, enhanced by external forcing The 2022‐like heatwave becomes six to seven times more likely under persistent high‐pressure conditions compared to stochastic circulation states Such rare heatwaves in natural and present climate are projected to become more common by 2100, occurring at least once every eight years

Over the past decade, our understanding of the Indian Ocean has advanced through concerted efforts toward measuring the ocean circulation and air–sea exchanges, detecting changes in water masses, and linking physical processes to ecologically important variables. New circulation pathways and mechanisms have been discovered that control atmospheric and oceanic mean state and variability. This review brings together new understanding of the ocean–atmosphere system in the Indian Ocean since the last comprehensive review, describing the Indian Ocean circulation patterns, air–sea interactions, and climate variability. Coordinated international focus on the Indian Ocean has motivated the application of new technologies to deliver higher-resolution observations and models of Indian Ocean processes. As a result we are discovering the importance of small-scale processes in setting the large-scale gradients and circulation, interactions between physical and biogeochemical processes, interactions between boundary currents and the interior, and interactions between the surface and the deep ocean. A newly discovered regional climate mode in the southeast Indian Ocean, the Ningaloo Niño, has instigated more regional air–sea coupling and marine heatwave research in the global oceans. In the last decade, we have seen rapid warming of the Indian Ocean overlaid with extremes in the form of marine heatwaves. These events have motivated studies that have delivered new insight into the variability in ocean heat content and exchanges in the Indian Ocean and have highlighted the critical role of the Indian Ocean as a clearing house for anthropogenic heat. This synthesis paper reviews the advances in these areas in the last decade.

In July–August (JA) of 2016, northeastern China (NEC) suffered from the most severe hot drought event of the past 50 years, leading to profound impacts on agriculture, the ecosystem, and society. Results indicate that the loss of sea ice over the Barents Sea (SICBS) in March might have influenced the hot drought events over NEC in JA for the period of 1997–2016. Further analyses reveal that lower SICBS is closely related to thinner snow depth over western Eurasia (SDWEA) in April. The decline of SDWEA leads to drier soil from the Yangtze River valley to northern China during May–June, which is favorable for precipitation deficiency over NEC in JA. Besides, the loss of SICBS in March and decline of SDWEA in April are closely related to the polar–Eurasia teleconnection pattern and dry soil over NEC in JA, which provides favorable atmospheric circulation patterns for occurrences of hot droughts. The large ensemble simulations from the Community Earth System Model and the numerical experiments based on version 4 of the Community Atmosphere Model further confirmed their connections and the associated possible physical processes. Therefore, snow depth and soil moisture might serve as linkages between Barents Sea ice in March and hot droughts over NEC during JA, and the Barents Sea ice in March might be an important potential predictor for the summer hot droughts over NEC.

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called 'early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.

The driver mechanisms of Dansgaard-Oeschger (DO) events remain uncertain, in part because many climate models do not show similar oscillatory behaviour. Here we present results from glacial simulations of the HadCM3B coupled atmosphere–ocean-vegetation model that show stochastic, quasi-periodical variability on a similar scale to the DO events. This variability is driven by variations in the strength of the Atlantic Meridional Overturning Circulation in response to North Atlantic salinity fluctuations. The mechanism represents a salt oscillator driven by the salinity gradient between the tropics and the Northern North Atlantic. Utilising a full set of model salinity diagnostics, we identify a complex ocean–atmosphere-sea-ice feedback mechanism that maintains this oscillator, driven by the interplay between surface freshwater fluxes (tropical P-E balance and sea-ice), advection, and convection. The key trigger is the extent of the Laurentide ice sheet, which alters atmospheric and ocean circulation patterns, highlighting the sensitivity of the climate system to land-ice extent. This, in addition to the background climate state, pushes the climate beyond a tipping point and into an oscillatory mode on a timescale comparable to the DO events.

From July 19 to 21, 2021, Henan, a province in northern China (NC), was affected by severe flooding (referred to hereafter as “21·7”) caused by a prolonged record-breaking extreme precipitation (EP) event. Understanding the extremes of the large-scale circulation pattern during “21·7” is essential for predicting EP events and preventing future disasters. In this study, daily atmospheric large-scale circulations over NC in the summers from 1979 to 2021 were investigated using the circulation classification method of an obliquely rotated principal component analysis in T-mode (PCT). The geopotential height at 500 hPa and 925 hPa were applied successively in classification. Among the nine summer circulation patterns at 500 hPa were found, the 3 days of “21·7” belonged to the Type 8 pattern, which had the second highest probability of EP days among all patterns. It was characterized by a southeasterly wind toward North China Plain driven by a dipole geopotential height field, with the West Pacific subtropical high (WPSH) extending far north to 30°N and low to the south near NC. Tropical cyclones (TCs) occurred on 72.5% of EP days, in which larger amounts of precipitation and a longer duration of EP days were found along the mountains in NC, as compared with other patterns. The distribution of EP events under this pattern was mainly influenced by the location of the low at 925 hPa in the dipole. The subtype 8−3 circulation, with lows in the east of Taiwan Island, included “21·7” and accounted for 1.6% of all summer days. Typhoon In-fa, together with the WPSH, gave rise to intense column integrated moisture flux convergence (IMFC) via the southeasterly wind to Henan, which occurred continuously during the 3 days of “21·7”, resulting in the largest (second largest) mean IMFC among 3 consecutive EP days under type 8 (all types) during the past 43 summers in NC. Further analysis revealed that the large-scale dynamic process could not completely explain the record-breaking EP during “21·7”, indicating possible contributions of other dynamic processed related to meso-scale convective storms.

Utilizing a recent observational dataset of particulate matter with diameters less than 2.5 µm (PM2.5) in North China, this study reveals a distinct seesaw feature of abnormally high and low PM2.5 concentrations in the adjacent two months of December 2015 and January 2016, accompanied by distinct meteorological modulations. The seesaw pattern is postulated to be linked to a super El Niño and the Arctic Oscillation (AO). During the mature phase of El Niño in December 2015, the weakened East Asian winter monsoon (EAWM) and the associated low-level southerly wind anomaly reduced planetary boundary layer (PBL) height, favoring strong haze formation. This circulation pattern was completely reversed in the following month, in part due to a sudden phase change of the AO from positive to negative and the beginning of a decay of the El Niño, which enhanced the southward shift of the upper tropospheric jet from December to January relative to climatology, leading to an enhanced EAWM and substantially lower haze formation. This sub-seasonal change in circulation is also robustly found in 1982–1983 and 1997–1998, implicative of a general physical mechanism dynamically linked to El Niño and the AO. Numerical experiments using the Weather Research and Forecasting (WRF) Community Multiscale Air Quality (CMAQ) model were used to test the modulation of the meteorological conditions on haze formation. With the same emission, simulations for three super El Niño periods (1983, 1997 and 2015) robustly show higher PM2.5  concentrations under the mature phase of the super El Niño, but substantially lower PM2.5 concentrations during the decay phase of El Niño (and the sudden AO phase change), further verifying the modulation effect of the sub-seasonal circulation anomaly on PM2.5 concentrations in North China.

An empirical orthogonal function (EOF) analysis was conducted for spring precipitation gauge data over northeast China (NEC). The first EOF mode is characterized by a homogenous rainfall pattern throughout NEC. The corresponding principal component has both significant interannual and interdecadal variations. This leading mode explains a large portion of the total NEC spring rainfall (NECSR) variances and is statistically independent from other higher modes. The physical processes responsible for the interannual and interdecadal variabilities were investigated via observational diagnoses and numerical experiments. On the interannual time scale, NECSR is mainly affected by the SST anomalies (SSTAs) in the northern tropical Atlantic Ocean. When the SSTAs are positive, the subsequently induced positive precipitation and convection can stimulate two quasi-barotropic Rossby wave trains over the mid- to high latitudes. A cyclonic anomaly center of the Rossby wave train appears over northeastern Asia, leading to a positive rainfall anomaly in the region. On the interdecadal time scale, NECSR is mainly influenced by the SSTAs over the warm-pool region. Positive SSTAs in the warm-pool region result in enhanced convection (ascending motion) around the Maritime Continent and suppressed convection (descending motion) over the central equatorial Pacific Ocean. This zonal dipole convection pattern stimulates a quasi-barotropic circulation pattern with an anticyclonic anomaly over the Tibetan Plateau and a cyclonic anomaly over northeastern Asia. The cyclonic anomaly over northeastern Asia enhances the NECSR. Numerical experiments further suggested that the convective heating anomaly over the Maritime Continent, rather than cooling over the central equatorial Pacific, plays a more essential role in driving the interdecadal rainfall variability of NECSR.