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The Thirty Years' War, which took place from 1618 to 1648 CE, was an armed military conflict in Europe. It resulted from the culmination of theological differences between advocates of the Roman Catholic and Protestant churches, as well as a power struggle for European political hegemony. This war brought about extensive devastation to Europe. Based on documentary evidence, this paper characterizes the climate, weather extremes, and economic and socio-political events in central Europe during that time. Natural climate forcing indicates a gradual climate deterioration during the first half of the 17th century, associated with a decrease in solar activity towards the Maunder Minimum and increased volcanic activity. The mean temperatures in central Europe from 1618 to 1648 were significantly colder than the reference period of 1961 to 1990 in winter, autumn, and annually, while precipitation and drought means did not differ significantly from the reference period. Summer temperatures, spring precipitation, and drought also exhibited significantly greater variability. As for weather extremes, particularly late winter, late spring and early autumn frosts, floods, intense rain spells, and droughts affected grain, fruit, and vine grape harvests, as well as the yields of other crops. These weather extremes contributed to various human impacts, such as food shortages (reflecting harvests and grain prices), famines, and epidemics. Ultimately, these events, along with the effects of the war, led to a decline in the population. The results obtained are discussed within the broader European context, taking into account climate, weather extremes, and socio-economic impacts. [ABSTRACT FROM AUTHOR]

In this paper we investigate the spatial patterns and features of meteorological droughts in Europe using concepts and methods derived from complex network theory. Using event synchronization analysis, we uncover robust meteorological drought continental networks based on the co-occurrence of these events at different locations within a season from 1981 to 2020 and compare the results for four accumulation periods of rainfall. Each continental network is then further examined to unveil regional clusters which are characterized in terms of droughts' geographical propagation and source–sink systems. While introducing new methodologies in general climate network reconstruction from raw data, our approach brings out key aspects concerning drought spatial dynamics, which could potentially support droughts' forecast. [ABSTRACT FROM AUTHOR]

Satellite-derived agricultural drought indices can provide a complementary perspective of terrestrial vegetation trends. In addition, their integration for drought assessments under future climates is beneficial for providing more comprehensive assessments. However, satellite-derived drought indices are only available for the Earth observation era. In this study, we aim to improve the agricultural drought assessments under future climate change by applying deep learning (DL) to predict satellite-derived vegetation indices from a regional climate simulation. The simulation is produced by the Terrestrial Systems Modeling Platform (TSMP) and performed in a free evolution mode over Europe. TSMP simulations incorporate variables from underground to the top of the atmosphere (ground-to-atmosphere; G2A) and are widely used for research studies related to water cycle and climate change. We leverage these simulations for long-term forecasting and DL to map the forecast variables into normalized difference vegetation index (NDVI) and brightness temperature (BT) images that are not part of the simulation model. These predicted images are then used to derive different vegetation and agricultural drought indices, namely NDVI anomaly, BT anomaly, vegetation condition index (VCI), thermal condition index (TCI), and vegetation health index (VHI). The developed DL model could be integrated with data assimilation and used for downstream tasks, i.e., for estimating the NDVI and BT for periods where no satellite data are available and for modeling the impact of extreme events on vegetation responses with different climate change scenarios. Moreover, our study could be used as a complementary evaluation framework for TSMP-based climate change simulations. To ensure reliability and to assess the model's applicability to different seasons and regions, we provide an analysis of model biases and uncertainties across different regions over the pan-European domain. We further provide an analysis about the contribution of the input variables from the TSMP model components to ensure a better understanding of the model prediction. A comprehensive evaluation of the long-term TSMP simulation using reference remote sensing data showed sufficiently good agreements between the model predictions and observations. While model performance varies on the test set between different climate regions, it achieves a mean absolute error (MAE) of 0.027 and 1.90 K with coefficient of determination (R2) scores of 0.88 and 0.92 for the NDVI and BT, respectively, at 0.11° resolution for sub-seasonal predictions. In summary, we demonstrate the feasibility of using DL on a TSMP simulation to synthesize NDVI and BT satellite images, which can be used for agricultural drought forecasting. Our implementation is publicly available at the project page (https://hakamshams.github.io/Focal-TSMP , last access: 4 April 2024). [ABSTRACT FROM AUTHOR]

Human-caused climate change increases the occurrence and severity of droughts due to increasing temperatures, altered circulation patterns and reduced snow occurrence. For example, Europe has suffered from drought events in the last decade like never since the beginning of weather recording. Here we present soil moisture data from 65 Cosmic-ray neutron sensors (CRNS) in Europe (COSMOS-Europe for short) covering recent drought events. The CRNS sites are distributed across Europe and cover all major land use types and climate zones in Europe. The raw neutron count data from the CRNS stations were provided by 23 research institutions and processed using state-of-the-art methods. The harmonised processing included correction of the raw neutron counts, and a harmonised methodology for the conversion into soil moisture based on available in-situ information. In addition, information on the data uncertainty is provided with the dataset, information that is particularly useful for remote sensing and modelling applications. This paper presents the current spatiotemporal coverage of CRNS stations in Europe and describes the protocols for data processing from raw measurements to consistent soil moisture products as well as first results on how the recent drought events have been captured by the CRNS network. This harmonised European soil moisture dataset will help both hydrologists and climate scientists to study individual drought events, to understand their causes, to evaluate and improve their modelling, and to estimate the extremity of current events. The dataset, entitled “Dataset of COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors”, is shared via Forschungszentrum Jülich: https://doi.org/10.34731/x9s3-kr48 (Bogena and Ney, 2021). [ABSTRACT FROM AUTHOR]

In the 2022 summer, western–central Europe and several other regions in the northern extratropics experienced substantial soil moisture deficits in the wake of precipitation shortages and elevated temperatures. Much of Europe has not witnessed a more severe soil drought since at least the mid-20th century, raising the question whether this is a manifestation of our warming climate. Here, we employ a well-established statistical approach to attribute the low 2022 summer soil moisture to human-induced climate change using observation-driven soil moisture estimates and climate models. We find that in western–central Europe, a June–August root zone soil moisture drought such as in 2022 is expected to occur once in 20 years in the present climate but would have occurred only about once per century during preindustrial times. The entire northern extratropics show an even stronger global warming imprint with a 20-fold soil drought probability increase or higher, but we note that the underlying uncertainty is large. Reasons are manifold but include the lack of direct soil moisture observations at the required spatiotemporal scales, the limitations of remotely sensed estimates, and the resulting need to simulate soil moisture with land surface models driven by meteorological data. Nevertheless, observation-based products indicate long-term declining summer soil moisture for both regions, and this tendency is likely fueled by regional warming, while no clear trends emerge for precipitation. Finally, our climate model analysis suggests that under 2 ∘ C global warming, 2022-like soil drought conditions would become twice as likely for western–central Europe compared to today and would take place nearly every year across the northern extratropics. [ABSTRACT FROM AUTHOR]

We present a method for the analysis and compact description of large-scale multivariate weather extremes. Spatial patterns of extreme events are identified using the tail pairwise dependence matrix (TPDM) proposed by Cooley and Thibaud (2019). We also introduce the cross-TPDM to identify patterns of common extremes in two variables. An extremal pattern index (EPI) is developed to provide a pattern-based aggregation of temperature. A heat wave definition based on EPI is able to detect the most important heat waves over Europe. As an extension for considering simultaneous extremes in two variables, we propose the threshold-based EPI (TEPI) that captures the compound character of spatial extremes. We investigate daily temperature maxima and precipitation deficits at different accumulation times and find evidence that preceding precipitation deficits have a significant influence on the development of heat waves and that heat waves often co-occur with short-term drought conditions. We exemplarily show for the European heat waves of 2003 and 2010 that TEPI is suitable for describing the large-scale compound character of heat waves. [ABSTRACT FROM AUTHOR]

Projections of changes in extreme droughts under future climate conditions are associated with large uncertainties, owing to the complex genesis of droughts and large model uncertainty in the atmospheric dynamics. In this study we investigate the impact of global warming on soil moisture drought severity in west-central Europe by employing pseudo global warming (PGW) experiments, which project the 1980–2020 period in a globally warmer world. The future analogues of present-day drought episodes allow for investigation of changes in drought severity conditional on the historic day-to-day evolution of the atmospheric circulation. The 2018 west-central European drought is the most severe drought in the 1980–2020 reference period in this region. Under 1.5, 2 and 3 ∘ C global warming, this drought episode experiences strongly enhanced summer temperatures but a fairly modest soil moisture drying response compared to the change in climatology. This is primarily because evaporation is already strongly moisture-constrained during present-day conditions, limiting the increase in evaporation and thus the modulation of the temperature response under PGW. Increasing precipitation in winter, spring and autumn limits or prevents an earlier drought onset and duration. Nevertheless, the drought severity, defined as the cumulative soil moisture deficit volume, increases considerably, with 20 % to 39 % under 2 ∘ C warming. The extreme drought frequency in the 1980–2020 period strongly increases under 2 ∘ C warming. Several years without noticeable droughts under present-day conditions show very strong drying and warming. This results in an increase in 2003-like drought occurrences, compounding with local summer temperature increases considerably above 2 ∘ C. Even without taking into account a (potentially large) dynamical response to climate change, drought risk in west-central Europe is strongly enhanced under global warming. Owing to increases in drought frequency, severity and compounding heat, a reduction in recovery times between drought episodes is expected to occur. Our physical climate storyline provides evidence complementing conventional large-ensemble approaches and is intended to contribute to the formulation of effective adaptation strategies. [ABSTRACT FROM AUTHOR]

At high concentrations, tropospheric ozone (O 3) deteriorates air quality, inducing adverse effects on human and ecosystem health. Meteorological conditions are key to understanding the variability in O 3 concentration, especially during extreme weather events. In addition to modifying photochemistry and atmospheric transport, droughts and heatwaves affect the state of vegetation and thus the biosphere–troposphere interactions that control atmospheric chemistry, namely biogenic emissions of precursors and gas dry deposition. A major source of uncertainty and inaccuracy in the simulation of surface O 3 during droughts and heatwaves is the poor representation of such interactions. This publication aims at quantifying the isolated and combined impacts of both extremes on biogenic isoprene (C 5 H 8) emissions, O 3 dry deposition, and surface O 3 in southwestern Europe. First, the sensitivity of biogenic C 5 H 8 emissions, O 3 dry deposition, and surface O 3 to two specific effects of droughts, the decrease in soil moisture and in biomass, is analysed for the extremely dry summer 2012 using the biogenic emission model MEGANv2.1 and the chemistry transport model CHIMEREv2020r1. Despite a significant decrease in biogenic C 5 H 8 emissions and O 3 dry deposition velocity, characterized by a large spatial variability, the combined effect on surface O 3 concentration remains limited (between + 0.5 % and + 3 % over the continent). The variations in simulated biogenic C 5 H 8 emissions, O 3 dry deposition, and surface O 3 during the heatwaves and agricultural droughts are then analysed for summer 2012 (warm and dry), 2013 (warm), and 2014 (relatively wet and cool). We compare the results with large observational data sets, namely O 3 concentrations from Air Quality (AQ) e-Reporting (2000–2016) and total columns of formaldehyde (HCHO, which is used as a proxy for biogenic emissions of volatile organic compounds) from the Ozone Monitoring Instrument (OMI) of the Aura satellite (2005–2016). Based on a cluster approach using the percentile limit anomalies indicator, we find that C 5 H 8 emissions increase by + 33 % during heatwaves compared to normal conditions, do not vary significantly during all droughts (either accompanied or not by a heatwave), and decrease by - 16 % during isolated droughts. OMI data confirm an average increase in HCHO during heatwaves (between + 15 % and + 31 % depending on the product used) and decrease in HCHO (between - 2 % and - 6 %) during isolated droughts over the 2005–2016 summers. Simulated O 3 dry deposition velocity decreases by - 25 % during heatwaves and - 35 % during all droughts. Simulated O 3 concentrations increase by + 7 % during heatwaves and by + 3 % during all droughts. Compared to observations, CHIMERE tends to underestimate the daily maximum O 3. However, similar sensitivity to droughts and heatwaves are obtained. The analysis of the AQ e-Reporting data set shows an average increase of + 14 % during heatwaves and + 7 % during all droughts over the 2000–2016 summers (for an average daily concentration value of 69 µ g m -3 under normal conditions). This suggests that identifying the presence of combined heatwaves is fundamental to the study of droughts on surface–atmosphere interactions and O 3 concentration. [ABSTRACT FROM AUTHOR]

Droughts are natural hazards that lead to severe impacts in the agricultural sector. Mountain regions are thought to have abundant water, but have experienced unprecedented drought conditions as climate change is affecting their environments more rapidly than other places. The effect radiates by reducing water availability well beyond the mountains' geographical locations. This study aims to improve the understanding of agriculture's vulnerability to drought in Europe's pre-Alpine region, considering two case studies that have been severely impacted in the past. We applied a mixed-method approach combining the knowledge of regional experts with quantitative data analyses in order to define the region-specific vulnerability based on experts' identified factors. We implemented two aggregation methods by combining the vulnerability factors that could be supported with subregional data. Whereas the equal weighting method combines all factors with the same weight, the expert weighting method combines the factors with varying weight based on the expert's opinion. These two methods resulted in vulnerability maps with the expert weighting showing a higher vulnerability, and partly relocating the medium and lower vulnerabilities to other subregions within the case study regions. In general, the experts confirmed the resulting subregions with higher vulnerability. They also acknowledged the value of mapping vulnerability by adopting different aggregation methods confirming that this can serve as a sensitivity analysis. The identified factors contributing most to the regions' vulnerability point to the potential of adaptation strategies decreasing the agriculture's vulnerability to drought that could enable better preparedness. Apart from region-specific differences, in both study regions the presence of irrigation infrastructure and soil texture are among the most important conditions that could be managed to some extent in order to decrease the regions' vulnerability. Throughout the analyses, the study benefited from the exchange with the experts by getting an in-depth understanding of the regional context with feedback relations between the factors contributing to vulnerability. Qualitative narratives provided during the semi-structured interviews supported a better characterization of local vulnerability conditions and helped to better identify quantitative indicators as proxies to describe the selected vulnerability factors. Thus, we recommend applying this mixed-method approach to close the gap between science and practitioners. [ABSTRACT FROM AUTHOR]

In 2018–2019, Central Europe experienced an unprecedented 2-year drought with severe impacts on society and ecosystems. In this study, we analyzed the impact of this drought on water quality by comparing long-term (1997–2017) nitrate export with 2018–2019 export in a heterogeneous mesoscale catchment. We combined data-driven analysis with process-based modeling to analyze nitrogen retention and the underlying mechanisms in the soils and during subsurface transport. We found a drought-induced shift in concentration–discharge relationships, reflecting exceptionally low riverine nitrate concentrations during dry periods and exceptionally high concentrations during subsequent wet periods. Nitrate loads were up to 73 % higher compared to the long-term load–discharge relationship. Model simulations confirmed that this increase was driven by decreased denitrification and plant uptake and subsequent flushing of accumulated nitrogen during rewetting. Fast transit times (<2 months) during wet periods in the upstream sub-catchments enabled a fast water quality response to drought. In contrast, longer transit times downstream (>20 years) inhibited a fast response but potentially contribute to a long-term drought legacy. Overall, our study reveals that severe droughts, which are predicted to become more frequent across Europe, can reduce the nitrogen retention capacity of catchments, thereby intensifying nitrate pollution and threatening water quality. [ABSTRACT FROM AUTHOR]

The period from around 1450 to 1550 in Europe is extremely interesting from the perspective of research on extreme weather events. It was a period of events that strongly influenced the societies and economies of the Old Continent. So far, the literature has been more focused on western and northern Europe. Concerning the region of central Europe, the greatest attention was paid to the Czech Republic or Hungary. This article revolves around the Polish lands, which experienced their greatest economic boom in the 16th century. We consider whether and how the droughts of the decade from 1531 to 1540 might have affected the country's economic development. We analyse a number of written sources which are the product of the treasury apparatus of the time (tax registers, data from water customs, tax exemptions, inventories of land estates etc.), but also information on fluctuations in product prices in the most important cities in this part of Europe. The work not only provides a detailed account of economic data, but also attempts to reflect on the relevance of linking information on fires in urban centres in the period characterized by weather extremes. [ABSTRACT FROM AUTHOR]

This study focuses on the relationship between satellite-measured fraction of absorbed photosynthetically active radiation (fAPAR) and crop yield cereals in Europe. Different features of the relationship between annual yield and multiple time series of fAPAR, collected during different periods of the year, were investigated. The two key outcomes of the analysis are the identification of the period: (i) from March to October as the one having the highest positive correlation between fAPAR and yield and (ii) from February to May as the period characterised by most of the estimated negative correlation. While both periods align well with the commonly assumed dynamic of the growing season, spatial differences are also observed across Europe. On the one hand, the Mediterranean regions report the highest correlation values (r>0.8) and the longest continuous periods with positive statistically significant results (up to 7 months), covering most of the growing season. On the other hand, the central European region is characterised by the most limited positive correlation values, with only 2 months or less showing statistically significant results. While marked differences in the overall capability to capture the full dynamic of yield are observed across Europe, fAPAR anomalies seem capable of discriminating low-yield years from the rest in most of the cases. [ABSTRACT FROM AUTHOR]

Drought forecasting and early warning systems for water resource extremes are increasingly important tools in water resource management in Europe where increased population density and climate change are expected to place greater pressures on water supply. In this context, the North Atlantic Oscillation (NAO) is often used to indicate future water resource behaviours (including droughts) over Europe, given its dominant control on winter rainfall totals in the North Atlantic region. Recent hydroclimate research has focused on the role of multiannual periodicities in the NAO in driving low frequency behaviours in some water resources, suggesting that notable improvements to lead-times in forecasting may be possible by incorporating these multiannual relationships. However, the importance of multiannual NAO periodicities for driving water resource behaviour, and the feasibility of this relationship for indicating future droughts, has yet to be assessed in the context of known non-stationarities that are internal to the NAO and its influence on European meteorological processes. Here we quantify the time–frequency relationship between the NAO and a large dataset of water resources records to identify key non-stationarities that have dominated multiannual behaviour of water resource extremes over recent decades. The most dominant of these is a 7.5-year periodicity in water resource extremes since approximately 1970 but which has been diminishing since 2005. Furthermore, we show that the non-stationary relationship between the NAO and European rainfall is clearly expressed at multiannual periodicities in the water resource records assessed. These multiannual behaviours are found to have modulated historical water resource anomalies to an extent that is comparable to the projected effects of a worst-case climate change scenario. Furthermore, there is limited systematic understanding in existing atmospheric research for non-stationarities in these periodic behaviours which poses considerable implications to existing water resource forecasting and projection systems, as well as the use of these periodic behaviours as an indicator of future water resource drought. [ABSTRACT FROM AUTHOR]

Since the beginning of this century, Europe has been experiencing severe drought events (2003, 2007, 2010, 2018 and 2019) which have had adverse impacts on various sectors, such as agriculture, forestry, water management, health and ecosystems. During the last few decades, projections of the impact of climate change on hydroclimatic extremes have often been used for quantification of changes in the characteristics of these extremes. Recently, the research interest has been extended to include reconstructions of hydroclimatic conditions to provide historical context for present and future extremes. While there are available reconstructions of temperature, precipitation, drought indicators, or the 20th century runoff for Europe, multi-century annual runoff reconstructions are still lacking. In this study, we have used reconstructed precipitation and temperature data, Palmer Drought Severity Index and available observed runoff across 14 European catchments in order to develop annual runoff reconstructions for the period 1500–2000 using two data-driven and one conceptual lumped hydrological model. The comparison to observed runoff data has shown a good match between the reconstructed and observed runoff and their characteristics, particularly deficit volumes. On the other hand, the validation of input precipitation fields revealed an underestimation of the variance across most of Europe, which is propagated into the reconstructed runoff series. The reconstructed runoff is available via Figshare, an open-source scientific data repository, under the DOI 10.6084/m9.figshare.15178107,. [ABSTRACT FROM AUTHOR]

Three-hourly net ecosystem exchange (NEE) is estimated at spatial scales of 0.25 ∘ over the European continent, based on the pre-operational inverse modelling framework "CarboScope Regional" (CSR) for the years 2006 to 2019. To assess the uncertainty originating from the choice of a priori flux models and observational data, ensembles of inversions were produced using three terrestrial ecosystem flux models, two ocean flux models, and three sets of atmospheric stations. We find that the station set ensemble accounts for 61 % of the total spread of the annually aggregated fluxes over the full domain when varying all these elements, while the biosphere and ocean ensembles resulted in much smaller contributions to the spread of 28 % and 11 %, respectively. These percentages differ over the specific regions of Europe, based on the availability of atmospheric data. For example, the spread of the biosphere ensemble is prone to be larger in regions that are less constrained by CO 2 measurements. We investigate the impact of unprecedented increase in temperature and simultaneous reduction in soil water content (SWC) observed in 2018 and 2019 on the carbon cycle. We find that NEE estimates during these 2 years suggest an impact of drought occurrences represented by the reduction in net primary productivity (NPP), which in turn leads to less CO 2 uptake across Europe in 2018 and 2019, resulting in anomalies of up to 0.13 and 0.07 PgC yr -1 above the climatological mean, respectively. Annual temperature anomalies also exceeded the climatological mean by 0.46 ∘ C in 2018 and by 0.56 ∘ C in 2019, while Standardised Precipitation–Evaporation Index (SPEI) anomalies declined to -0.20 and -0.05 SPEI units below the climatological mean in both 2018 and 2019, respectively. Therefore, the biogenic fluxes showed a weaker sink of CO 2 in both 2018 and 2019 (-0.22 ± 0.05 and -0.28 ± 0.06 PgC yr -1 , respectively) in comparison with the mean -0.36 ± 0.07 PgC yr -1 calculated over the full analysed period (i.e. 14 years). These translate into a continental-wide reduction in the annual sink by 39 % and 22 %, respectively, larger than the typical year-to-year standard deviation of 19 % observed over the full period. [ABSTRACT FROM AUTHOR]

Drought events and their impacts vary spatially and temporally due to diverse pedo-climatic and hydrologic conditions, as well as variations in exposure and vulnerability, such as demographics and response actions. While hazard severity and frequency of past drought events have been studied in detail, little is known about the effect of drought management strategies on the actual impacts and how the hazard is perceived by relevant stakeholders. In a continental study, we characterised and assessed the impacts and the perceptions of two recent drought events (2018 and 2019) in Europe and examined the relationship between management strategies and drought perception, hazard, and impact. The study was based on a pan-European survey involving national representatives from 28 countries and relevant stakeholders responding to a standard questionnaire. The survey focused on collecting information on stakeholders' perceptions of drought, impacts on water resources and beyond, water availability, and current drought management strategies on national and regional scales. The survey results were compared with the actual drought hazard information registered by the European Drought Observatory (EDO) for 2018 and 2019. The results highlighted high diversity in drought perception across different countries and in values of the implemented drought management strategies to alleviate impacts by increasing national and sub-national awareness and resilience. The study identifies an urgent need to further reduce drought impacts by constructing and implementing a European macro-level drought governance approach, such as a directive, which would strengthen national drought management and mitigate damage to human and natural assets. [ABSTRACT FROM AUTHOR]

In 2018 and 2019, central Europe was affected by two consecutive extreme dry and hot summers (DH18 and DH19). The DH18 event had severe impacts on ecosystems and likely affected vegetation activity in the subsequent year, for example through depletion of carbon reserves or damage from drought. Such legacies from drought and heat stress can further increase vegetation susceptibility to additional hazards. Temporally compound extremes such as DH18 and DH19 can, therefore, result in an amplification of impacts due to preconditioning effects of past disturbance legacies. Here, we evaluate how these two consecutive extreme summers impacted ecosystems in central Europe and how the vegetation responses to the first compound event (DH18) modulated the impacts of the second (DH19). To quantify changes in vegetation vulnerability to each compound event, we first train a set of statistical models for the period 2001–2017, which are then used to predict the impacts of DH18 and DH19 on enhanced vegetation index (EVI) anomalies from MODIS. These estimates correspond to expected EVI anomalies in DH18 and DH19 based on past sensitivity to climate. Large departures from the predicted values can indicate changes in vulnerability to dry and hot conditions and be used to identify modulating effects by vegetation activity and composition or other environmental factors on observed impacts. We find two regions in which the impacts of the two compound dry and hot (DH) events were significantly stronger than those expected based on previous climate–vegetation relationships. One region, largely dominated by grasslands and crops, showed much stronger impacts than expected in both DH events due to an amplification of their sensitivity to heat and drought, possibly linked to changing background CO2 and temperature conditions. A second region, dominated by forests and grasslands, showed browning from DH18 to DH19, even though dry and hot conditions were partly alleviated in 2019. This browning trajectory was mainly explained by the preconditioning role of DH18 on the impacts of DH19 due to interannual legacy effects and possibly by increased susceptibility to biotic disturbances, which are also promoted by warm conditions. Dry and hot summers are expected to become more frequent in the coming decades, posing a major threat to the stability of European forests. We show that state-of-the-art process-based models could not represent the decline in response to DH19 because they missed the interannual legacy effects from DH18 impacts. These gaps may result in an overestimation of the resilience and stability of temperate ecosystems in future model projections. [ABSTRACT FROM AUTHOR]

Europe was affected by an extreme drought in 2018, compounding with an extensive heat wave in the same and subsequent years. Here we provide a first assessment of the impacts this compounding event had on forest disturbance regimes in Europe. We find that the 2018 drought caused unprecedented levels of forest disturbance across large parts of Europe, persisting up to 2 years post-drought. The 2018 drought pushed forest disturbance regimes in Europe to the edge of their past range of variation, especially in central and eastern Europe. Increased levels of forest disturbance were associated with low soil water availability in 2018 and were further modulated by high vapor pressure deficit from 2018 to 2020. We also document the emergence of novel spatiotemporal disturbance patterns following the 2018 drought (i.e., more and larger disturbances, occurring with higher spatiotemporal autocorrelation) that will have long-lasting impacts on forest structure and raise concerns about a potential loss of forest resilience. We conclude that the 2018 drought had unprecedented impacts on forest disturbance regimes in Europe, highlighting the urgent need to adapt Europe's forests to a hotter and drier future with more disturbance. [ABSTRACT FROM AUTHOR]