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This paper analyzes reconstructed data on temperature, precipitation, and extreme drought events in the late fifteenth century in Northern China, as well as historical records on population migration, financial crises, military farms, and national decisions during the Ming dynasty. We specifically examine the socio-economic effects of extreme drought events, which led to long-term changes causing the collapse of the Ming dynasty. Our results indicate that the first Cold Valley and the frequent extreme drought events of the Little Ice Age in the late fifteenth century led to a sharp reduction in the military farm system. Extreme droughts caused a large-scale population migration in Northern China and led to the collapse of the tax payment and corvee systems. To cope with the extreme droughts, the local financial reserve was reduced by 51.3%. As a result, local finances became extremely tight. To alleviate fiscal pressures, the court was forced to change the socioeconomic model implemented in the beginning of the Ming dynasty to the corvee equalization method and silver coin tax collection method. These new measures resulted in a decline of the dynasty’s control over households, to the abandonment of military farms, and to reduced control over the country’s social risks. This article explains the mechanism through which climate events led to the collapse of the Ming dynasty. We specifically explore the relationship between socioeconomic transformation and extreme drought in the late fifteenth century in order to better understand the relationship between climate change and social response.

Case studies on the impacts of extreme weather events at different spatial and temporal resolutions can help further the understanding of the impacts of climate change and serve as references for coping with future climate change challenges as well. We reconstructed the monthly time series data on social impacts of an extreme drought event in the Guanzhong area, Shaanxi Province, China, using newspaper records from 1928 to 1931. Changes in food substitutions, food prices, social unrest, and social resilience are analyzed to show how the drought affected the area. The results show that (1) the evolution of social impacts of the drought can be divided into five stages, and the variation in the impact magnitude is strongly influenced by the summer and autumn harvests; (2) the cumulative effects of the persistent drought are observed, and the level of social resilience declined rapidly and nonlinearly; and (3) there are two kinds of spreading patterns of drought’s impacts across natural, supporting, and humanity systems: hierarchical propagation and cascading effects. They act over different spatial and/or temporal scales and could provide the inspiration for the strategies designed to mitigate the impacts of climate change and extreme weather events today.

The frequency of extreme drought events in northeastern China (NEC) has increased since the 2000s, and such a decadal anomalous trend may lead to significant stress on agriculture and economic development. The correlation between Arctic sea ice loss in spring and extreme summer droughts over NEC was investigated. The results show that the loss of sea ice over the Barents Sea in spring is associated with extreme droughts and positive height anomalies over NEC in summer. The physical processes include two pathways. First, sea ice loss from the Barents Sea to the Kara Sea results in reducing baroclinicity over the ice loss region but increasing baroclinicity over the ice melting region, which is favorable to the wave ridge over northern Europe and negative-phase Summer North Atlantic Oscillation (SNAO). One wave train originates from negative-phase SNAO over North Atlantic–Europe and spreads to central Europe, central Asia, and NEC. Second, another wave motion flux originates from the Barents–Kara Sea propagating eastward, and then disperses southward to NEC. Both wave trains lead to anomalous anticyclonic circulation and westward subtropical high, which favors descending motion and less water vapor flux, thereby contributing to extreme drought.

Climatic extremes have adverse concurrent and lagged effects on terrestrial carbon cycles. Here, a concurrent effect refers to the occurrence of a latent impact during climate extremes, and a lagged effect appears sometime thereafter. Nevertheless, the uncertainties of these extreme drought effects on net carbon uptake and the recovery processes of vegetation in different Tibetan Plateau (TP) ecosystems are poorly understood. In this study, we calculated the Standardised Precipitation–Evapotranspiration Index (SPEI) based on meteorological datasets with an improved spatial resolution, and we adopted the Carnegie–Ames–Stanford approach model to develop a net primary production (NPP) dataset based on multiple datasets across the TP during 1982–2015. On this basis, we quantised the net reduction in vegetation carbon uptake (NRVCU) on the TP, investigated the spatiotemporal variability of the NPP, NRVCU and SPEI, and analysed the NRVCUs that are caused by the concurrent and lagged effects of extreme drought and the recovery times in different ecosystems. According to our results, the Qaidam Basin and most forest regions possessed a significant trend towards drought during 1982–2015 (with Slope of SPEI < 0, P < 0.05), and the highest frequency of extreme drought events was principally distributed in the Qaidam Basin, with three to six events. The annual total net reduction in vegetation carbon uptake on the TP experienced a significant downward trend from 1982 to 2015 (−0.0018 ± 0.0002 PgC year−1, P < 0.001), which was negatively correlated with annual total precipitation and annual mean temperature (P < 0.05). In spatial scale, the NRVCU decrement was widely spread (approximately 55% of grids) with 17.86% of the area displaying significant declining trends (P < 0.05), and the sharpest declining trend (Slope ≤ −2) was mainly concentrated in southeastern TP. For the alpine steppe and alpine meadow ecosystems, the concurrent and lagged effects of extreme drought induced a significant difference in NRVCU (P < 0.05), while forests presented the opposite results. The recovery time comparisons from extreme drought suggest that forests require more time (27.62% of grids ≥ 6 years) to recover their net carbon uptakes compared to grasslands. Therefore, our results emphasise that extreme drought events have stronger lagged effects on forests than on grasslands on the TP. The improved resilience of forests in coping with extreme drought should also be considered in future research.

Extreme drought events can impact human health, notably triggering epidemics that impose significant global health and economic burdens. Understanding these effects and developing response strategies is crucial. However, there is limited epidemiological evidence on how climate change influenced ancient epidemics before large-scale urbanization and frequent population movements. In this study, we utilized the Reconstructed East Asian Climate Historical Encoded Series (REACHES) climate database and the self-constructed ancient Chinese epidemics database to examine extreme drought events in ancient China from 1784–1787 CE. We analyzed factors like grain prices, population density, and socioeconomic conditions to explore the temporal and spatial mechanism and influence the degree of extreme drought events on epidemics outbreaks. The results show that there is a clear positive link between drought and the spread of epidemics, with a notable one-year lag effect of drought. Drought impacts epidemics directly and indirectly through locust plague, famine, crop failure, and social turmoil, with famine being the most crucial factor. Official disaster management can mitigate epidemics. This study intuitively shows the relationship between extreme drought events and epidemics in ancient China and offering insights into the climate change-epidemic relationship. Placing the conclusions of this paper in a broader context has global implications, providing historical experience for polycrisis and modern challenges.

Douglas-fir ( (Mirb.) Franco) is considered an important non-native substitute tree species in Europe, especially for Norway spruce ( (L.) Karst.), mainly due to its higher drought tolerance. However, Douglas-fir has also shown increasing mortality in certain regions of the world. One of the main reasons is the increase in drought and heat periods due to climate change. There is still a need for research on the influence of important soil properties and rooting characteristics on the drought tolerance of Douglas-fir. Therefore, we analyzed the influence of soil texture, plant-available water capacity (PAWC), fine root density, and effective rooting depth on water status and thus drought stress in Douglas-fir during the extreme drought of 2018. We selected seven closely spaced sites along a soil texture gradient from sand to clay at an elevation of ca. 500 m a.s.l. in southern Germany and determined soil physical and rooting characteristics. Water status parameters and growth duration were derived from dendrometer data at five Douglas-firs per site. The influence of soil and rooting characteristics on these drought stress-related parameters was analyzed using mixed-effects models. The focus was on two summer drought periods in 2018. In the initial stage of the extreme summer drought of 2018 (in June), a higher PAWC and a higher fine root density reduced drought stress. However, these influences were no longer noticeable in the later stage of drought (in August), probably due to deeper soil desiccation. In August, a higher effective rooting depth reduced drought stress. Soil texture had a significant influence, particularly on growth duration. This study provides information on site selection for Douglas-fir cultivation under the predicted increase in severe drought, showing the importance of deep and intensive rooting, and points to the need for combined above- and belowground investigations for a better understanding of the drought response patterns of tree species.

Accurate estimation of non-seasonal signals (NSSs) of Terrestrial Water Storage Anomaly (TWSA) from Gravity Recovery and Climate Experiment monthly gravity field models is essential for identifying and understanding extreme hydrological phenomena. However, significant north-south striped noise in the models necessitates spectral filtering before estimating NSSs, resulting in signal attenuation and leakage. In this paper, we propose a one-step approach (OSA) that iteratively filters noise and estimates NSSs alongside trends and seasonal signals starting from unfiltered regional TWSA signals, where the covariance matrices of NSSs are populated using distance-based exponential functions. The non-seasonal TWSA signals in Southeastern China, estimated by OSA from April 2002 to December 2024, effectively preserves signal integrity with reduced spatial leakage and enhanced signal strength, aligning closely with those of the RL06 mascon products from CSR (Center for Space Research) and JPL (Jet Propulsion Laboratory), achieving Nash-Sutcliffe Efficiency (NSE) of 0.91 and 0.90. Moreover, we introduce a Standardized NSS (SNSS) index from OSA, which enhances the consistency with the standardized streamflow index, identifying the extreme wetness in pearl river basin (PRB) and Southeastern River Basin (SERB) from August 2015 to June 2016, and the extreme drought in Middle and Lower Yangtze River Basin (MLYRB) from July 2022 to April 2023. SNSS also exhibits enhanced correlations with nine key climate indices, especially for ENSO (El Niño-Southern Oscillation) and TIOS (Tropical Indian Ocean Sea Surface Temperature Anomaly), with cross-correlations of 0.99 and 0.96 for PRB, 0.97 and 0.94 for SERB during extreme wetness, and 0.96 and 0.90 for MLYRB during extreme drought.

This study examines the effects of the extreme drought and heatwaves that occurred in Romania during the summer of 2024 on the microbiological and mycotoxicological quality of wheat (Triticum aestivum) stored until April 2025, as well as on the quality of wholemeal flour and bread derived from it. Comparative analyses were conducted against the contamination in wheat harvested in 2024. The hot and dry conditions significantly influenced the microbial and mycotoxicological contamination of both freshly harvested and stored wheat, as well as the derived flour and bread, due to their notably reduced moisture content and water activity. Although levels of total fungi, Fusarium-damaged kernels, and mycotoxins deoxynivalenol, aflatoxin B1, and ochratoxin A remained well below regulatory thresholds, higher contamination was observed in Transylvania and Moldavia—particularly in the Curvature Carpathians, likely due to their cooler and wetter microclimates. The observed quality changes were strongly associated with alterations in physico-chemical, rheological, and colorimetric parameters, posing potential economic challenges for the milling and baking industries. The study recommends implementing integrated regional strategies to enhance wheat resilience, optimize production systems, and improve contamination control in response to increasing climate stress across Southeastern Europe.

In the context of ongoing global climate warming, researchers have observed an intricate relationship between the variability of Terrestrial Water Storage (TWS) on the Tibetan Plateau (TP) and climate anomalies. In this study, we utilize a combination of Global Navigation Satellite System (GNSS), Gravity Recovery and Climate Experiment (GRACE), and precipitation data to investigate the response of TWS on the TP to extreme climate changes, with a focus on seasonal and interannual variations. Our findings reveal that the first Common Mode Component (1st CMC) extracted from GNSS coordinate time series exhibits strong interannual fluctuations. Additionally, both GNSS and GRACE-inferred TWS demonstrate noticeable anomalous changes during the 2015/2016 period. The estimated periods of the 1st CMC of GNSS and GRACE-inferred TWS are approximately 5 and 7 years, respectively. Both reach a minimum during the extreme climate event in 2015/2016. Furthermore, we investigate the spatial variation of summer precipitation before and after the extreme drought event on the TP. It reveals that the inflection point of TWS occurs approximately 1 year prior to the drought event, suggesting a consistent spatial propagation process between precipitation and TWS. This indicates that the changes of TWS during this drought event were primarily influenced by precipitation. Finally, we evaluate the response of 12 sub-basins on the TP to the drought event that occurred in 2015/2016. The regions experiencing significant abnormal fluctuations in TWS are mainly located in inner and northeastern plateau. These regions show rapid upward changes in the TWS and demonstrate a strong spatial consistency with summer precipitation.

The Peruvian Altiplano Region (RAP) is a high plateau area surrounded by the Western and Eastern Andes mountain ranges. This study examines the relationship between extreme droughts in the region and the interdecadal Pacific Oscillation (IPO) over the past century. Previous research has shown that precipitation patterns in the region follow a decreasing trend, with systematic increases in precipitation on the western slope and decreases in the eastern, southern, and central parts. The temporal and spatial variability of precipitation in the Altiplano region is influenced by the easterly moisture flux and the interaction between the El Niño Southern Oscillation (ENSO) and below-average values. The study utilizes water level data for Lake Titicaca and IPO data from 1914 to 2015. The analysis employs wavelet transform and empirical orthogonal function (EOF) techniques to identify the relationship between water levels and IPO. The results indicate multidecadal variability in water levels associated with El Niño/La Niña events and the IPO. The negative phase of the IPO aligns with extreme drought periods, suggesting a connection between the IPO climate index and drought events. The EOF analysis shows a moderate positive correlation between water levels and IPO. The findings highlight the importance of considering IPO and its interaction with ENSO in understanding drought patterns in the Altiplano region. However, other atmospheric conditions also influence precipitation in the region. The study contributes to a better understanding of the factors affecting water levels and droughts in the Peruvian Altiplano, with implications for water resource management in the region.