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Drought, as a recurring extreme climatic event, inflicts diverse impacts on ecological systems, agricultural productivity, water resources, and socio-economic progress globally. Discerning the drought patterns within the evolving environmental landscape of the Yellow River Basin (YRB) is imperative for enhancing regional drought management and fostering ecological conservation alongside high-quality development. This study utilizes meteorological drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the self-calibrating Palmer Drought Severity Index (scPDSI), for a detailed spatiotemporal analysis of drought conditions. It examines the effectiveness of these indices in the basin's drought monitoring, offering a comprehensive insight into the area's drought spatiotemporal dynamics. The findings demonstrate the following: (1) SPEI values exhibit distinct fluctuation patterns at varying temporal scales, with more pronounced fluctuations at shorter scales. Drought years identified via the 12-month SPEI time scale include 1965, 1966, 1969, 1972, 1986, 1997, 1999, 2001, and 2006. (2) A modified Mann–Kendall (MMK) trend test analysis of the scPDSI time series reveals a worrying trend of intensifying drought conditions within the basin. (3) Correlation analysis between SPEI and scPDSI across different time scales yields correlation coefficients of 0.35, 0.54, 0.69, 0.76, and 0.62, highlighting the most substantial correlation at an annual scale. Spatial correlation analysis conducted between SPEI and scPDSI across various scales reveals that, within diverse temporal ranges, the correlation peaks at a 12-month time scale, with subsequent prominence observed at 6 and 24 months. This observed pattern accentuates the applicability of scPDSI in the monitoring of medium- to long-term drought phenomena. [ABSTRACT FROM AUTHOR]

Understanding past warm-season drought variability and its underlying climatic mechanisms is crucial for effective drought management and climate adaptation strategies. In this study, we develop a regional chronology (RC) spanning from 1620 to 2017 CE by utilizing dendrochronological techniques and tree-ring data from two stands of Abies pindrow. The RC reveals a significant positive correlation (p < 0.05) with self-calibrated Palmer drought severity index (scPDSI) and precipitation and a significant negative correlation with temperature. We use a simple linear regression model between RC and climate data to reconstruct a 348-year-long (1670–2017 CE) warm-season (April-July) drought variability from central-northern Pakistan. The reconstructed scPDSI reveals a 44% variance of the scPDSI during the common calibrated period 1950–2017 CE. Spatial correlation shows a positive field correlation with central-northern Pakistan, extending predominantly to neighboring regions. MTM (multi-taper method) spectral analysis reveals inter-annual cycles (6.8, 3.2, 2.7, 2.5, and 2.3 years) and multi-decadal cycles (11.7, 15.2, 16.2, 17.9, and 128 years). The internal-annual cycles demonstrate a possible linkage between reconstructed scPDSI and El Niño–Southern Oscillation (ENSO). The reconstructed scPDSI agrees well with the moisture-sensitive tree-ring records from northern Pakistan and neighboring regions. Our reconstruction shows a significant correlation with the South Asia Summer Monsoon Index (SASMI), Atlantic Multi-decadal Oscillation (AMO), ENSO, Pacific Decadal Oscillation (PDO), and solar activity, emphasizing that all these factors have some influence on the drought variability in central-northern Pakistan. This study has important implications for disaster management and proactive measures for mitigating the impact of drought on both natural ecosystems and human populations in central-northern Pakistan and associated regions. [ABSTRACT FROM AUTHOR]

Droughts have posed large threats to crop growth and economic development in the crucial grain-producing region, such as the North China Plain (Huang-Huai-Hai Plain). It is crucial to fully understand the drought characteristics for national food security. Previous studies have relied primarily on the single drought index rather than the multiple drought indices. The single drought index makes it relatively difficult to provide comprehensive and consistent information, compared with the multiple drought indices. However, drought monitoring often varies significantly, because the multiple factors are considered by different drought indices. In this study, four drought indices were utilized to evaluate the spatiotemporal variation of drought in the Huang-Huai-Hai Plain from 1970 to 2020. These indices included the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), self-calibrating Palmer drought severity index (scPDSI), and aridity index (AI). Drought events were fully examined from four aspects: intensity, area ratio, frequency, and duration of drought. Data resources were obtained from 564 meteorological stations in the National Meteorological Information Center, including the average, minimum, and maximum temperature, precipitation, wind speed, relative humidity, and sunshine hours. The effective soil water content was collected from the Chinese soil dataset using the World Soil Database provided by the National Tibetan Plateau Research Center. The research results indicate that the better consistency of four drought indices was achieved to characterize the drought intensity and area. The overall drought intensity shared a decreasing trend from 1970 to 2020. The downward trend was ranked in the order of the SPI

Copyright of Journal of Shenyang Agricultural University is the property of Journal of Shenyang Agricultural University Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Drought, as a recurring extreme climatic event, inflicts diverse impacts on ecological systems, agricultural productivity, water resources, and socio-economic progress globally. Discerning the drought patterns within the evolving environmental landscape of the Yellow River Basin (YRB) is imperative for enhancing regional drought management and fostering ecological conservation alongside high-quality development. This study utilizes meteorological drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the self-calibrating Palmer Drought Severity Index (scPDSI), for a detailed spatiotemporal analysis of drought conditions. It examines the effectiveness of these indices in the basin’s drought monitoring, offering a comprehensive insight into the area’s drought spatiotemporal dynamics. The findings demonstrate the following: (1) SPEI values exhibit distinct fluctuation patterns at varying temporal scales, with more pronounced fluctuations at shorter scales. Drought years identified via the 12-month SPEI time scale include 1965, 1966, 1969, 1972, 1986, 1997, 1999, 2001, and 2006. (2) A modified Mann–Kendall (MMK) trend test analysis of the scPDSI time series reveals a worrying trend of intensifying drought conditions within the basin. (3) Correlation analysis between SPEI and scPDSI across different time scales yields correlation coefficients of 0.35, 0.54, 0.69, 0.76, and 0.62, highlighting the most substantial correlation at an annual scale. Spatial correlation analysis conducted between SPEI and scPDSI across various scales reveals that, within diverse temporal ranges, the correlation peaks at a 12-month time scale, with subsequent prominence observed at 6 and 24 months. This observed pattern accentuates the applicability of scPDSI in the monitoring of medium- to long-term drought phenomena.

Drought is one of the main factors limiting forest productivity, and thus greatly affects the carbon sink capacity of forests. Here we first chose two drought indices including standardized precipitation evapotranspiration index (SPEI) and self-calibrating Palmer drought severity index (scPDSI) to reflect and analyze the spatiotemporal patterns of drought in the subtropical China. Then, the validated CASA (Carnegie-Amer-Stanford Approach) model was applied to estimate forest net primary productivity (NPP) and further quantify the contributions of drought events and their characteristics on forest NPP. The results showed that drought events during 2000–2015 have resulted in a mean decline of forest NPP of 7.2%. Moderate or severe drought events reduced NPP more significantly than extremely severe drought events. In addition, there was 1–2 years of lagging in the NPP responses to drought, and the lagging time varied with forest types. Our study suggests that forest managers and local governments should pay more attention to the places with moderate and severe drought events, and take measures to avoid NPP decline within the 2 years after drought. Our study also provides data support for further identifying the contribution of drought to ecosystem carbon fluxes in the subtropical China.

Global climate change is projected to increase the probability of occurrence and severity of droughts. Increased CO2 concentration drives partial closure of plant stomata and reduces evapotranspiration. However, the impact of reduced evapotranspiration due to CO2 on future droughts characteristics in China is unclear. In this study, we have used the Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model simulations (GCMs) under historical period, and four shared socioeconomic pathway scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5) to estimate drought. We used a widely applicable drought index (i.e., the self‐calibrating Palmer Drought Severity Index [scPDSI]) to evaluate the historical and future drought conditions, using the Penman–Monteith formula with and without the CO2 concentrations. The results show that the increasing trend of scPDSI slows down when the CO2 effect is considered in all scenarios, especially in Heilongjiang, northern Xinjiang, and the Qinghai–Tibet Plateau. The divergence in the slowdown trend among the different scenarios becomes greater after 2030, with higher emission scenarios implying a greater slowdown in the increasing trend of scPDSI. After considering CO2, drought characteristics such as the drought frequency, intensity, and drought area decrease. Increased CO2 concentration on vegetation physiological processes could mitigate future drought. Therefore, the effects of CO2 on plant physiology should be considered in studies of future drought trends to develop more realistic response and adaptation policies to future drought changes. [ABSTRACT FROM AUTHOR]

Under global warming, according to results obtained from offline drought indices driven by projections of general circulation models (GCMs), future droughts in China will worsen but the results are not consistent. We analyzed changes in droughts covering the entire hydrologic cycle using outputs of GCMs of the 6th Coupled Model Intercomparison Project (CMIP6) for SSP2-4.5 and SSP5-8.5 climate scenarios, and compared the results with that of popular, offline drought indices [the self-calibrating Palmer Drought Severity Index (scPDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Actual Evapotranspiration Index (SPAEI)]. Among meteorological, agricultural, and hydrological drought indices tested under both SSP scenarios, the results obtained from SPAEI and scPDSI agree better with univariate drought indices than SPEI. scPDSI generally agrees well with agricultural droughts (Standardized Soil Moisture Index with the surface soil moisture content; SSIS). Future droughts estimated using soil moisture analysis are more widespread than that from precipitation and runoff analysis in humid regions of South China by the end of the twenty-first century. In arid northwestern China and Inner Mongolia, drought areas and severity based on scPDSI and SSIS forced with the SSP scenarios show obvious decreasing trends, in contrast to increasing trends projected in South China. Trends projected using SPEI contradict those projected by other drought indices in non-humid regions. Therefore, selecting appropriate drought indices is crucial in project representative future droughts and provides meaningful information needed to achieve effective regional drought mitigation strategies under climate warming impact. [ABSTRACT FROM AUTHOR]

Recent global warming and more frequent droughts are causing significant damage to maize production. A reliable estimate of drought intensity and duration is essential for testing maize hybrids to drought tolerance. For this purpose, the self-calibrating 10-day palmer drought severity index (scPDSI) and standardized precipitation index (SPI) for 1, 2, 3, 6, 9, 18, 27, and 36 10-day scales were used to estimate the effects of drought on grain yield of 32 maize hybrids evaluated in 2017 and 2018 at eight experimental locations in the Pannonian part of Croatia. Time series of observed 10-day mean air temperature, relative humidity, and precipitation totals for a set of "reference" weather stations of the croatian meteorological and hydrological service (DHMZ) for the period 1981–2018 were used to calculate the scPDSI and SPI indices. According to the 10-day scPDSI and SPI for different time scales, 2018 proved to be a "normal year," while 2017 experienced a "mild to moderate drought," which resulted in a 13% reduction in maize grain yield at eight experimental locations compared to 2018. The correlation between grain yield and drought indices for summer months was the highest for the 10-day scPDSI. To some extent, correlations between summer months' SPI for the 3 10-day time scale and maize grain yield were comparable to the corresponding correlations for the 10-day scPDSI. However, for other SPI time scales considered, the corresponding correlations were weaker and less informative. The dependence of grain yield on scPDSI values was not the same for all hybrids, indicating their different tolerance to drought. The reduction in grain yield due to drought was primarily caused by insufficient grain filling (lower 1000-grain weight) and, to some extent, by a reduction in the number of grains. In this study, application of 10-day scPDSI data proved to be more relevant in detecting effects of drought on agronomic traits than application of SPI data for the most time scales. [ABSTRACT FROM AUTHOR]

The insular Caribbean experiences numerous climate and environmental hazards, including but not limited to hurricanes, floods, earthquakes, and drought. While some hazards are well explored in scientific literature, drought is considered one of the neglected hazards because of the lack of studies focusing on its causes and effects. This study identifies the spatial distribution of seasonal drought in insular Caribbean from 1950 to 2017, and its relationship with eastern Pacific (EP) and central Pacific (CP) ENSO, North Atlantic Oscillation (NAO), and Atlantic Meridional Mode (AMM). It brings a new perspective over the region by dividing the Caribbean into Greater Antilles and Bahamas (GA), and the Lesser Antilles (LA) to compare the role of those three teleconnection patterns on drought events over larger versus smaller islands. We used an existing high‐resolution drought atlas (4 km) based on monthly estimates of the self‐calibrating Palmer Drought Severity Index (scPDSI). Results indicate that there is a drying trend in all seasonal‐average scPDSI for both the GA and the LA, but more intense and frequent drought events occur in the LA. The LA is also the region with more widespread drought events, registering 12 years when the mid‐summer dry spell (MSD; July–August) had drought ≥80% of the area, while the GA registered only 2 years of MSD drought that extensive. The peak season AMM had the strongest positive correlation with GA and LA drought during April–November, while NAO was slightly stronger correlated with GA than with LA from July–November. For ENSO, CP El Niño years related stronger with drought in the LA from December–July, while the relationship between the two types of ENSO and the GA was not statistically significant. This effort aims to improve drought forecasts to help the region to better prepare for the prediction of seasonal droughts. [ABSTRACT FROM AUTHOR]

High Mountain Asia (HMA), with its high altitude, widely distributed snow and frozen soil, influences the climate of the northern hemisphere and even the world through thermal balance and the water vapor cycle and is also an indicator of global climate change. The influence of HMA snow cover on its surrounding areas has always been a research hotspot. Taking the Yangtze River Basin (YRB) of China as an example, this paper analyzes the relationship between winter snow depth in HMA and drought and flood in spring and summer in the YRB in the recent 40 years by using Singular Value Decomposition (SVD). The results show that the influence of snow cover on drought and flood in spring is inversely different between eastern and western parts of HMA, while the effect in summer is consistent. When the snow depth is larger (smaller) in the east and smaller (larger) in the west in winter, the YRB is drier (wetter) in spring. When the overall snow depth in HMA is larger (smaller) in winter, the northern part of the middle and lower reaches of the YRB is drier (wetter) in summer. The results provide support for understanding the impact of HMA snow cover on the surrounding climate and some important indicators for drought and flood prediction in the YRB. [ABSTRACT FROM AUTHOR]

Global warming and human activities have intensified the duration, frequency, and extent of climatic extremes. The projected rise in global mean annual temperature of 1.5 °C/2 °C is thought to have severe impacts on the population exposed to droughts. Although these impacts on humans have been widely explored, the impacts associated with the cropland exposed to droughts have not been widely investigated. Here, we have examined the spatiotemporal pattern of China's drought conditions and cropland exposure to droughts under global warming of 1.5 °C and 2 °C, along with the avoided impacts (as evaluated by the cropland exposure to droughts) when limiting the global warming to 1.5 °C instead of 2 °C. Results suggest that compared to the reference period (1995–2014), drought conditions will be alleviated when the projected rise in mean global temperature is limited to 1.5 °C rather than 2.0 °C. Although severe droughts tend to be mainly distributed in northwestern China, drought severities are increasing in southern China, especially in the southeastern region. In addition, the total cropland exposure to droughts across China exhibits an increasing trend in response to the 0.5 °C of additional global warming, especially in northwestern China and Huang−Huai−Hai region. If global warming could be limited to 1.5 °C, the avoided impact will exceed 30%, especially in northwestern China, southwestern China, and the Huang−Huai−Hai Plain. Furthermore, the rising cropland exposure to droughts under the 2 °C global warming is likely to be triggered by the rising frequencies of moderate and extreme droughts. Therefore, climate mitigation strategies are urgently needed to keep the global temperature rise below 1.5 °C, for the future sustainability of China's cropland. [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (PET) is an important part of drought monitoring and evaluation. It is very important to analyze the climatic sensitive factors of PET to reveal the mechanism of hydrological responses to climate change. However, the local sensitivity method commonly used in previous studies is not suitable for nonlinear models and it is difficult to evaluate the interaction among meteorological factors. In this study, based on the monitoring data of 163 meteorological stations in the arid and semi-arid areas of northwest China from 1964 to 2018, we use the Penman-Monteith equation and Sobol global sensitivity to analyze the climatic sensitive factors of PET in the study area and discuss the climatic causes of the PET change. We also calculate the scPDSI and analyze the evolution characteristics of drought in northwest China. The results show that the annual average PET of the study area is 1157.8 mm with substantial spatial variations. The high-value areas are located in the eastern part of Xinjiang and the western part of Inner Mongolia, and the low-value areas are located in the southern part of Qinghai Province. The year 1993 was identified as a turning point, and the PET changed from a significant downward trend to a significant upward trend, which was more apparent in the summer in that year. From 1964 to 1993, the net radiation, wind speed, and relative humidity had a relatively greater impact on PET, while in the period 1994-2018, wind speed and relative humidity had a relatively greater impact on PET. The spatio-temporal distribution of scPDSI show that the drought in northern Xinjiang, central Qinghai and Gansu is becoming less severe, while the drought severity in the southwest part of the Yellow River Basin is becoming more severe, exacerbating regional water resources shortage and threatening ecological security.

Small islands that depend on limited freshwater resources are at significant risk from seasonal drought, which poses a major threat to both their ecosystems and communities. Christmas Island, located in the eastern Indian Ocean, presents an example for which severe drought conditions during the wet season not only affects its freshwater resources but also biodiversity on the island, including the migration pattern of the iconic red crab species. However, short-term instrumental climate records on this island make it hard to quantify drought variability and assess its associated risks. Tree growth is affected by drought via reduced soil moisture, and hydroclimate reconstruction from tree-ring chronologies can therefore provide longer-term information on historical variability of dry and wet periods. Here, we reconstructed the wet season (December-May) self-calibrating Palmer Drought Severity Index (scPDSI) for Christmas Island using 64 remote tree-ring chronologies from Asia, Australia, and New Zealand. scPDSI was reconstructed using the Point-to-Point Regression (PPR) method and compared with regional marine coral proxies for independent verification. The remote tree-ring chronologies explained more than 66 percent of scPDSI variance (R-squared) over the calibration period. The trees identified as significant predictors in the regression model were primarily located in areas affected by the Indo-Pacific climate drivers including the Indian Ocean Dipole (IOD). The reconstructions span 1540 CE to 2000. During the first four centuries of this period, the frequency of extreme (5th percentile) droughts and pluvial events rarely exceeded one event per 13 years. In contrast, the frequency of both extremes experienced an unprecedented increase during the 20th century, and with a notable shift towards dry conditions. These findings highlight a significant shift towards more frequent and severe dry conditions during the wet season on Christmas Island, posing a challenge to water resource management and potentially threatening the island's ecosystem and services to the community. [ABSTRACT FROM AUTHOR]

With rapid economic development and population growth, the impacts of drought continue to affect China and the situation will probably be worsened further under projected climate warming. Therefore, understanding the characteristics of drought conditions and its actual impacts is especially important for disaster prevention and mitigations, under climatic warming. Here, we investigated the spatiotemporal variations of drought, using the self-calibrating Palmer Drought Severity Index (scPDSI) based on two evaluation methods, i.e., scPDSITh (Thornthwaite method for calculating evapotranspiration) and scPDSIPM (Penman–Monteith method for calculating evapotranspiration). Results show the drought severities characterized by these two methods are highly consistent, except that the scPDSITh shows more drought severity than the scPDSIPM in some regions, e.g., Xinjiang, Tibet, Qinghai, and Inner Mongolia. Based on the scPDSIPM and drought disaster statistics, we adopted a downscaling approach to obtain the county level dataset of drought-affected area from the provincial level. Using this finer-scale dataset, we observed spatial agglomeration characteristics of drought-affected area during the study period, denoting by the Moran's I. Moreover, results show that the high-high clusters (high values surrounded by high values) of the drought-affected area are mainly distributed in northern China, and the moving direction of high-high clusters presents the East–West pattern. Combining the meteorological data and disaster statistics, this study can improve the accuracy of drought detection, which is important for disaster prevention and mitigations in China. [ABSTRACT FROM AUTHOR]

Due to the lack of a general drought definition, water users and managers have developed and used different indices. Many studies using drought indices have been made so as to detect drought events or just to compare their results and assess their advantages and disadvantages. In Portugal, these studies have been done for common drought indices; however, an integrated evaluation and comparison using recent data is needed. Therefore, this study is intended to give an updated overview of the behaviour of the proposed indices. This study proposes the usage of PDSI, scPDSI, SPI and SPEI. With the exception of the PDSI, all indices have been calculated through R packages. The results for the studied regions in mainland Portugal suggest that the drought situations are, in general, most significant and frequent than the wet periods. From our results, we can conclude that the SPI model is more sensitive to extreme drought events and can detect them earlier. The PDSI, scPDSI and SPEI are more reliable for drought monitorization at medium and long spells, which might represent the environmental interactions more closely to the reality. Also, the scPDSI tends to reduce the importance of short period recovering. It is then advisable that impact and scientifical studies consider all of these indices or at least some of them to have a broader and complete understanding of the drought situations to be studied. [ABSTRACT FROM AUTHOR]

How hydroclimate will change in the future has been of great interest with the increasing concern of global warming. Acquirement of ample high-resolution proxy-based reconstructions will aid to answer such question by increasing the accuracy of climate prediction models. However, discrepancies among existing reconstructions in the southeast part of China (SEC) has aroused great uncertainty about the hydroclimatic conditions. Here we present an annually-resolved June–August scPDSI reconstruction and a June–July relative humidity reconstruction from 1876 to 2015 in the middle reaches of the Yangtz River, based on accurately-dated tree-ring materials. The reconstructions well reproduce the instrumental records, with explained variance of 48.82% and 46.79%. A secular wetting trend is found in the study area from 1876 to 2000, then it dried quickly. The driest (2006–2015) and wettest (1943–1955) periods both occurred after 1940, and 40% of the top 10 driest years occurred in the twenty-first century. Overall, an increasing intensified hydroclimatic variation is identified, especially significant in the recent decade. The historical summer hydroclimatic fluctuations, which were found closely related to the concurrent temperature variations, show broadly large spatial and temporal synchronicity with existing hydroclimatic reconstructions in SEC, while the intensity of variation is intermittently different. Hydroclimatic variation in the study area might be a comprehensive effect of Pacific Decadal Oscillation (PDO), Western Pacific Subtropical High (WPSH) and El Niño-Southern Oscillation (ENSO) variations. Our reconstruction provides additional support not only for a comprehensive understanding of the spatiotemporal characteristics of hydroclimatic variations, but also for the diagnosis and prediction of hydroclimatic anomalies. [ABSTRACT FROM AUTHOR]

This study forecasts and assesses drought situations in various regions of India (the Araveli region, the Bundelkhand region, and the Kansabati river basin) based on seven simulated climates in the near future (2015–2044). The self-calibrating Palmer Drought Severity Index (scPDSI) was used based on its fairness in identifying drought conditions that account for the temperature as well. Gridded temperature and rainfall data of spatial resolution of 1 km were used to bias correct the multi-model ensemble mean of the Global Climatic Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) project. Equidistant quantile-based mapping was adopted to remove the bias in the rainfall and temperature data, which were corrected on a monthly scale. The outcome of the forecast suggests multiple severe-to-extreme drought events of appreciable durations, mostly after the 2030s, under most climate scenarios in all the three study areas. The severe-to-extreme drought duration was found to last at least 20 to 30 months in the near future in all three study areas. A high-resolution drought index was developed and proven to be a key to assessing the drought situation.

Projections of future drought conditions under climate change are an important step in formulating the long‐term climate adaptation strategies. It is therefore valuable to predict the drought conditions in China following the release of the CMIP6 (the phase six of the Coupled Model Inter‐comparison Project). Thus, based on 20 global climate model simulations from CMIP6, we project China's drought conditions and its socioeconomic impacts using the self‐calibrated Palmer Drought Severity Index (scPDSI). Four scenarios are considered in this analysis: SSP1‐2.6 (the low‐level development scenario), SSP2‐4.5 (the middle‐level development scenario), SSP3‐7.0 (the medium to high‐level development scenario) and SSP5‐8.5 (the high‐level development scenario). Under SSP1‐2.6, we observed wetting trends over large areas of China except the arid region during 2020–2099; however, under SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5, significant drying trends are detected in the humid and temperate semi‐humid region, while in other areas there are significant wetting trends. The projected drought conditions are likely to be severe with more frequent monthly occurrences and higher probability of extreme drying conditions, especially in these humid and temperate semi‐humid regions under SSP3‐7.0 and SSP5‐8.5. Consequently, the population exposure to drought in most climatic regions will increase initially up to 2040s and gradually decrease under all the scenarios except SSP3‐7.0; and the humid region will be a future hotspot where the impact of climate on population exposure to drought will be more significant. The economic exposure to drought will increase over the whole China under all four scenarios, especially in the humid and semi‐humid region. Our results have important implications for future drought projections and provide a scientific evidence for developing climate change adaptation strategies and disaster prevention. [ABSTRACT FROM AUTHOR]

High Mountain Asia (HMA), with its high altitude, widely distributed snow and frozen soil, influences the climate of the northern hemisphere and even the world through thermal balance and the water vapor cycle and is also an indicator of global climate change. The influence of HMA snow cover on its surrounding areas has always been a research hotspot. Taking the Yangtze River Basin (YRB) of China as an example, this paper analyzes the relationship between winter snow depth in HMA and drought and flood in spring and summer in the YRB in the recent 40 years by using Singular Value Decomposition (SVD). The results show that the influence of snow cover on drought and flood in spring is inversely different between eastern and western parts of HMA, while the effect in summer is consistent. When the snow depth is larger (smaller) in the east and smaller (larger) in the west in winter, the YRB is drier (wetter) in spring. When the overall snow depth in HMA is larger (smaller) in winter, the northern part of the middle and lower reaches of the YRB is drier (wetter) in summer. The results provide support for understanding the impact of HMA snow cover on the surrounding climate and some important indicators for drought and flood prediction in the YRB.

Global warming and human activities have intensified the duration, frequency, and extent of climatic extremes. The projected rise in global mean annual temperature of 1.5 °C/2 °C is thought to have severe impacts on the population exposed to droughts. Although these impacts on humans have been widely explored, the impacts associated with the cropland exposed to droughts have not been widely investigated. Here, we have examined the spatiotemporal pattern of China’s drought conditions and cropland exposure to droughts under global warming of 1.5 °C and 2 °C, along with the avoided impacts (as evaluated by the cropland exposure to droughts) when limiting the global warming to 1.5 °C instead of 2 °C. Results suggest that compared to the reference period (1995–2014), drought conditions will be alleviated when the projected rise in mean global temperature is limited to 1.5 °C rather than 2.0 °C. Although severe droughts tend to be mainly distributed in northwestern China, drought severities are increasing in southern China, especially in the southeastern region. In addition, the total cropland exposure to droughts across China exhibits an increasing trend in response to the 0.5 °C of additional global warming, especially in northwestern China and Huang−Huai−Hai region. If global warming could be limited to 1.5 °C, the avoided impact will exceed 30%, especially in northwestern China, southwestern China, and the Huang−Huai−Hai Plain. Furthermore, the rising cropland exposure to droughts under the 2 °C global warming is likely to be triggered by the rising frequencies of moderate and extreme droughts. Therefore, climate mitigation strategies are urgently needed to keep the global temperature rise below 1.5 °C, for the future sustainability of China’s cropland.

Copyright of Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to the lack of a general drought definition, water users and managers have developed and used different indices. Many studies using drought indices have been made so as to detect drought events or just to compare their results and assess their advantages and disadvantages. In Portugal, these studies have been done for common drought indices; however, an integrated evaluation and comparison using recent data is needed. Therefore, this study is intended to give an updated overview of the behaviour of the proposed indices. This study proposes the usage of PDSI, scPDSI, SPI and SPEI. With the exception of the PDSI, all indices have been calculated through R packages. The results for the studied regions in mainland Portugal suggest that the drought situations are, in general, most significant and frequent than the wet periods. From our results, we can conclude that the SPI model is more sensitive to extreme drought events and can detect them earlier. The PDSI, scPDSI and SPEI are more reliable for drought monitorization at medium and long spells, which might represent the environmental interactions more closely to the reality. Also, the scPDSI tends to reduce the importance of short period recovering. It is then advisable that impact and scientifical studies consider all of these indices or at least some of them to have a broader and complete understanding of the drought situations to be studied.

Drought is detrimental to both natural systems and human societies. Although definitions of drought vary among different indices, the frequency of drought is likely to enhance in a strong warming climate either because of increased temperature or decreased precipitation. However, for a low warming target such as 1.5°C, drought tendency is uncertain as it depends on the competition between evapotranspiration and precipitation, both of which may show only moderate changes. In this study, future changes of self‐calibrating Palmer Drought Severity Index (scPDSI) in China are projected for the periods of 1.5°C global warming under two different scenarios based on outputs from Coupled Model Intercomparison Project phase 5 (CMIP5). Compared to present day, national average scPDSI decreases by 0.04 ± 0.53 at a high emission scenario but increases by 0.20 ± 0.60 at a low emission scenario to the same 1.5°C global warming. Even with large uncertainties, the multi‐model ensemble scPDSI significantly increases by 0.52 ± 1.07 in the Southeast from the high to low emission scenarios. Such relieved drought is mainly attributed to the increased regional precipitation, which is likely caused by reductions in aerosols following emission regulations. Consequently, an associated control of both carbon and air pollution emissions helps retain the warming target globally and relieve drought risks regionally. [ABSTRACT FROM AUTHOR]

Drought monitoring is challenging, but it is required for improving agricultural production, protecting the ecological environment, and reducing economic losses in drought-prone regions such as the Mongolian Plateau (MP). This study is a systematic analysis of the spatiotemporal changes in the characteristics of drought events (drought duration, severity, intensity, frequency, peak, and starting season) at the sub-regional scale between 1959 and 2018 based on the run theory and using the gridded self-calibrating Palmer Drought Severity Index (scPDSI) dataset. Principal component analysis and Varimax rotation and the Mann–Kendall trend and Sen’s slope were used for the sub-regional division and drought trend analysis, respectively. In addition, wavelet analysis was employed to analyze drought periodicity and determine the influence of large-scale climate indices on regional drought variation. The study results indicate clear differences in the spatial patterns of drought characteristics in the MP. The northern part suffered from droughts with longer duration and higher severity, whereas more drought events with shorter duration and less severity occurred in the southern part. Most of the MP experienced a relatively wet trend in 1996–2018 compared to the period of 1959–1995. The frequency of spring drought events showed an increasing trend in 1996–2018, unlike in 1959–1995. Some drought events simultaneously affected two or several sub-regions. The wavelet analysis results indicated that the drought periodicity in the MP was 10–64 months. The Arctic Oscillation (Pacific Decadal Oscillation) was significantly correlated with drought in the southern (northern) part.

Observations show that in recent decades, a large area of China has been affected by drought and that frequent droughts have caused damage to the ecological environment and the economy. Because of the differences in data and methods, assessing regional droughts often leads to contradictory conclusions of trending. The self‐calibrated Palmer drought severity index (scPDSI) is based on multiple parameters, and it is considered regionally applicable and is widely used. However, some divergence has been observed in the results of drought in China using different scPDSI_PM (scPDSI based on the Penman–Monteith model) datasets. We establish an integrated scPDSI dataset (scPDSI_PM_INT) by averaging three scPDSI products and analyse the temporal change and spatial characteristics of drought in China from 1950 to 2009. The annual and seasonal drought intensities have increased slightly in the past 60 years, while the disturbed area has broadened significantly, especially in eastern China which has become much drier than before. The drought intensity of most drought‐prone regions is slight and moderate, while severe and extreme droughts occur mostly in the Agro‐Pastoral Transitional Zone and the Beijing–Tianjin–Hebei Region. [ABSTRACT FROM AUTHOR]

The São Francisco River Basin (SFRB) plays a key role for the agricultural and hydropower sectors in Northeast Brazil (NEB). Historically, in the low part of the SFRB, people have to cope with strong periods of drought. However, there are incipient signs of increasing drought conditions in the upper and middle parts of the SFRB, where its main reservoirs (i.e., Três Marias, Sobradinho, and Luiz Gonzaga) and croplands are located. Therefore, the assessment of the impacts of extreme drought events in the SFRB is of vital importance to develop appropriate drought mitigation strategies. These events are characterized by widespread and persistent dry conditions with long-term impacts on water resources and rain-fed agriculture. The purpose of this study is to provide a comprehensive evaluation of extreme drought events in terms of occurrence, persistence, spatial extent, severity, and impacts on streamflow and soil moisture over different time windows between 1980 and 2020. The Standardized Precipitation-Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI) at 3- and 12-month time scales derived from ground data were used as benchmark drought indices. The self-calibrating Palmer Drought Severity Index (scPDSI) and the Soil Moisture and Ocean Salinity-based Soil Water Deficit Index (SWDIS) were used to assess the agricultural drought. The Water Storage Deficit Index (WSDI) and the Groundwater Drought Index (GGDI) both derived from the Gravity Recovery and Climate Experiment (GRACE) were used to assess the hydrological drought. The SWDISa and WSDI showed the best performance in assessing agricultural and hydrological droughts across the whole SFRB. A drying trend at an annual time scale in the middle and south regions of the SFRB was evidenced. An expansion of the area under drought conditions was observed only during the southern hemisphere winter months (i.e., JJA). A marked depletion of groundwater levels concurrent with an increase in soil moisture content was observed during the most severe drought conditions, indicating an intensification of groundwater abstraction for irrigation. These results could be useful to guide social, economic, and water resource policy decision-making processes.

Forest systems provide crucial ecosystem functions to our environment, such as balancing carbon stocks and influencing the local, regional and global climate. A trend towards an increasing frequency of climate change induced extreme weather events, including drought, is hereby a major challenge for forest management. Within this context, the application of remote sensing data provides a powerful means for fast, operational and inexpensive investigations over large spatial scales and time. This study was dedicated to explore the potential of satellite data in combination with harmonic analyses for quantifying the vegetation response to drought events in German forests. The harmonic modelling method was compared with a z-score standardization approach and correlated against both, meteorological and topographical data. Optical satellite imagery from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS) was used in combination with three commonly applied vegetation indices. Highest correlation scores based on the harmonic modelling technique were computed for the 6th harmonic degree. MODIS imagery in combination with the Normalized Difference Vegetation Index (NDVI) generated hereby best results for measuring spectral response to drought conditions. Strongest correlation between remote sensing data and meteorological measures were observed for soil moisture and the self-calibrated Palmer Drought Severity Index (scPDSI). Furthermore, forests regions over sandy soils with pine as the dominant tree type were identified to be particularly vulnerable to drought. In addition, topographical analyses suggested mitigated drought affects along hill slopes. While the proposed approaches provide valuable information about vegetation dynamics as a response to meteorological weather conditions, standardized in-situ measurements over larger spatial scales and related to drought quantification are required for further in-depth quality assessment of the used methods and data.

Drought is a natural hazard caused by long-term precipitation deficiency and high evaporation resulted from high temperature, which is among the most common disasters around the world. In recent decades, with the intensification of climate change and human activities, drought occurrence is becoming more frequent in China, causing negative impacts on agricultural production, ecological environment and social economy. Therefore, it is significant to explore the impact of drought on vegetation for agricultural production and healthy development of ecological systems. In this paper, the response and sensitivity of vegetation to drought in different climatic zones in China were analyzed, and the effects of different climatic factors, including water balance (precipitation-potential evapotranspiration), annual precipitation, mean temperature and sunshine hours, on the relationship between different vegetation types including forestland, grassland and cultivated land and drought were explored, so as to reveal the response mechanism of ecological vegetation to drought from a macro perspective. Using the self-calibrating Palmer drought severity index (scPDSI) and normalized difference vegetation index (NDVI) data for the period of 1982-2015, the response rule and sensitivity of different types of vegetation to drought were analyzed by applying time-delay correlation method, and the influence of various climate factors on the relationship between vegetation and drought was analyzed by applying linear regression method. The results of the research showed that in northwest China, Inner Mongolia, north China plain and southern Qinghai-Tibet plateau, the correlation of shorter lag time scPDSI (1-3 months) and NDVI was close (Rmax>0.4), which indicated that vegetation growth was more sensitive to drought in these regions and that vegetation biomass were influenced mainly by the spatiotemporal characteristics of the water availability. In the humid areas of south China, including the middle and lower reaches of the Yangtze River and the Pearl River basin, the precipitation is abundant so that the correlation between NDVI and scPDSI was negative, and the response of vegetation was not sensitive to drought. The growth of vegetation is mainly controlled by energy factors such as temperature and sunshine hours. The relationship between vegetation and drought was significantly affected by the average annual water balance, precipitation, sunshine hours and temperature, among which the annual water balance was the main water controlling factor (R²=0.45). It can be concluded that the change of water availability was the key factor behind the change of vegetation vigor. Sunshine hours were the main energy controlling factor. When average annual temperature was less than 5, the effect of ℃ temperature on the correlation between scPDSI and NDVI was also significant. The sensitive areas of drought impact on vegetation were mainly in the northern arid regions, while the southern humid areas had strong resilience and resilience to drought. The sensitivity of different types of vegetation to drought varied greatly, and the order of sensitivity is grassland >forestland>cultivated land. The results can provide a scientific basis for the evaluation of the impact of drought on ecological vegetation in different regions of China, and thus help to guide agricultural and environmental production, protect vulnerable ecosystems and provide implications for sustainable socioeconomic development. [ABSTRACT FROM AUTHOR]

Highlights • PDSI is highly correlated with the variations of P and ET 0 on 12-month timescale. • PDSI is more sensitive to P on national scales, except the northeastern China. • PDSI is preferred to recommend to estimate long-term drought in China. Abstract The self-calibrating Palmer Drought Severity Index (sc_PDSI) is developed within the frame of the PDSI model, but is considered to be more appropriate for global drought monitoring. The sc_PDSI can automatically calibrate itself at any location using dynamically computed values and can calculate evapotranspiration using the FAO-56 Penman–Monteith (P–M) equation. However, the correlation of the sc_PDSI(P–M) with some factors that drive drought, such as precipitation (P) and the reference evapotranspiration (ET 0), is still unclear in China. With the aim of solving this issue, we analyzed the correlation of the detrended sc_PDSI(P–M) with the detrended P and ET 0 on different timescales (one, three, six and 12 months) in China for the period 1951–2015. The results show that both the P and ET 0 are highly correlated with the sc_PDSI(P–M) on a 12-month timescale. On this timescale, the sc_PDSI(P–M) is more sensitive to P than to ET 0 on the national scale, except for northeastern China. Thus the sc_PDSI(P–M) may effectively fit the long-term variations in these drivers of drought, especially P. These results provide guidance on the use of the sc_PDSI(P–M) to detect the impacts of climate change on drought severity under the climatic conditions found in China. [ABSTRACT FROM AUTHOR]

Regional assessments of droughts are limited, and meticulous assessments over larger spatial scales are generally not substantial. Understanding drought variability on a regional scale is crucial for enhancing the resiliency and adaptive ability of water supply and distribution systems. Moreover, it can be essential for appraising the dynamics and projection of droughts based on regional climate across various spatial and temporal scales. This work focuses on drought analysis using a high-resolution dataset for three drought-prone regions of India between 1950 and 2016. This study also uses monthly values of the self-calibrating Palmer Drought Severity Index (scPDSI), incorporating Penman–Monteith approximation, which is physically based on potential evapotranspiration. Climate data are statistically downscaled and formulated to form a timeline for characterizing major drought events. The downscaled climate data hold a good statistical agreement with station data with correlation coefficients (R) ranging from 0.91 to 0.96. Drought analysis indicates and identifies several major incidences over the analysis time period considered in this work, which truly adheres to the droughts recorded in reports of various literatures for those regions.

Long-duration droughts are usually tied to persistent local or remote forcings; for example, persistent droughts over California are frequently observed along with the ‘ ridiculously resilient ridge’ over the West Coast. It is now evident that some oceanic forcings (e.g. El Niño–Southern Oscillation) have global reaches and affect multiple regions concurrently during their progression. Here, we show robust significant temporal concordancy of persistent droughts in many regions, revealing multiple teleconnections (distant regions experiencing droughts concurrently), such as the ‘Western North America–Mediterranean (WNA–MED)’ and the ‘Southeast Asia–Southern Africa (SEA–SAF)’ teleconnections. Composite pressure and sea surface temperature anomalies during concurrent droughts in WNA and the MED reveal a persistent weather regime that resembles the positive phase of Arctic Oscillation and negative phase of Pacific Decadal Oscillation. During concordant droughts of SEA and SAF, composite pressure anomalies remarkably resemble the El Niño pattern, which we infer as the leading cause of the teleconnection. The insights gained here offer a new dimension to understanding droughts and improving their long-term predictability.

The recent 2015-2016 El Niño (EN) event was considered as strong as the EN in 1997-1998. Given such magnitude, it was expected to result in extreme warming and moisture anomalies in tropical areas. Here we characterize the spatial patterns of temperature anomalies and drought over tropical forests, including tropical South America (Amazonia), Africa and Asia/ Indonesia during the 2015-2016 EN event. These spatial patterns of warming and drought are compared with those observed in previous strong EN events (1982-1983 and 1997-1998) and other moderate to strong EN events (e.g. 2004-2005 and 2009-2010). The link between the spatial patterns of drought and sea surface temperature anomalies in the central and eastern Pacific is also explored. We show that indeed the EN2015-2016 led to unprecedented warming compared to the other EN events over Amazonia, Africa and Indonesia, as a consequence of the background globalwarming trend. Anomalous accumulated extreme drought area over Amazonia was found during EN2015-2016, but this value may be closer to extreme drought area extents in the other two EN events in 1982-1983 and 1997-1998. Over Africa, datasets disagree, and it is difficult to conclude which EN event led to the highest accumulated extreme drought area. Our results show that the highest values of accumulated drought area over Africa were obtained in 2015-2016 and 1997-1998, with a long-term drying trend not observed over the other tropical regions. Over Indonesia, all datasets suggest that EN 1982-1983 and EN 1997-1998 (or even the drought of 2005) led to a higher extreme drought area than EN2015-2016. Uncertainties in precipitation datasets hinder consistent estimates of drought severity over tropical regions, and improved reanalysis products and station records are required. This article is part of a discussion meeting issue 'The impact of the 2015/ 2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'. [ABSTRACT FROM AUTHOR]

Recent warming has stimulated the productivity of boreal and Arctic vegetation by reducing temperature limitations. However, several studies have hypothesized that warming may have also increased moisture limitations because of intensified summer drought severity. Establishing the connections between warming and drought stress has been difficult because soil moisture observations are scarce. Here we use recently developed gridded datasets of moisture variability to investigate the links between warming and changes in available soil moisture and summer vegetation photosynthetic activity at northern latitudes (>45°N) based on the Normalized Difference Vegetation Index (NDVI) since 1982. Moisture and temperature exert a significant influence on the interannual variability of summer NDVI over about 29% (mean r2 = 0.29 ± 0.16) and 43% (mean r2 = 0.25 ± 0.12) of the northern vegetated land, respectively. Rapid summer warming since the late 1980s (~0.7 °C) has increased evapotranspiration demand and consequently summer drought severity, but contrary to earlier suggestions it has not changed the dominant climate controls of NDVI over time. Furthermore, changes in snow dynamics (accumulation and melting) appear to be more important than increased evaporative demand in controlling changes in summer soil moisture availability and NDVI in moisture-sensitive regions of the boreal forest. In boreal North America, forest NDVI declines are more consistent with reduced snowpack rather than with temperature-induced increases in evaporative demand as suggested in earlier studies. Moreover, summer NDVI variability over about 28% of the northern vegetated land is not significantly associated with moisture or temperature variability, yet most of this land shows increasing NDVI trends. These results suggest that changes in snow accumulation and melt, together with other possibly non-climatic factors are likely to play a significant role in modulating regional ecosystem responses to the projected warming and increase in evapotranspiration demand during the coming decades.

Chinese pine (Pinus tabulaeformis Carr.) plays an important role in maintaining ecosystem health and stability in western Liaoning Province and the southern Horqin sand land, Northeast China, with benefits including sand fixation and soil erosion. In the context of climate change, developing a better understanding of the relationship between climate factors and growth rates of this species will be extremely valuable in guiding management activities and meeting regional conservation objectives. Here, the results based on two groups of tree-ring samples show that the radial growth of Chinese pine is controlled primarily by water conditions. The longer chronology had the highest correlation coefficient with the January−September mean self-calibrating Palmer Drought Severity Index (scPDSI); therefore, drought variability was reconstructed for the period 1859−2014. Statistical analysis showed that our model explained 41.9% of the variance in radial growth during the 1951−2014 calibration period. Extreme dry and wet events, defined as the criteria of one standard deviation less or greater than the mean value, accounted for 19.9% and 18.6% of the 156-year climate record, respectively. During the past century, the regional hydroclimate experienced significant long-term fluctuations. The dry periods occurred from the early-1900s−1930s and 1980s−2000s, and the wet periods occurred from the 1940s−1970s. The drought reconstruction was consistent with the decreasing trend of the East Asian summer monsoon since the late 1970s. The reconstructed temporal patterns in hydroclimate in western Liaoning were closely related to the large-scale climate drivers in the North Pacific and the tropical equatorial Pacific. The teleconnections were confirmed by spatial correlations between the reconstructed sequence and sea surface temperature (SST) in the North Pacific, as well as the correlations with the Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO) indices. Aerosols played an important role in affecting drought variations over the past several decades. Moisture stress caused by global warming and interdecadal changes in the PDO will have long-term effects on the growth of pines in the study area in the future.

Drought is one of the most widespread and threatening natural disasters in the world, which has terrible impacts on agricultural irrigation and production, ecological environment, and socioeconomic development. As a critical ecologically fragile area located in southwest China, the Yarlung Zangbo River (YZR) basin is sensitive and vulnerable to climate change and human activities. Hence, this study focused on the YZR basin and attempted to investigate the spatiotemporal variations of drought and associated multi-scale response to climate change based on the scPDSI (self-calibrating Palmer drought severity index) and CRU (climate research unit) data. Results showed that: (1) The YZR basin has experienced an overall wetting process from 1956 to 2015, while a distinct transition period in the mid 1990s (from wet to dry) was detected by multiple statistical methods. (2) Considering the spatial variation of the scPDSI, areas showing the significantly wetting process with increasing scPDSI values were mostly located in the arid upstream and midstream regions, which accounted for over 48% area of the YZR basin, while areas exhibiting the drying tendency with decreasing scPDSI values were mainly concentrated in the humid southern part of the YZR basin, dominating the transition period from wet to dry, to which more attention should be paid. (3) By using the EEMD (ensemble empirical mode decomposition) method, the scPDSI over the YZR basin showed quasi-3-year and quasi-9-year cycles at the inter-annual scale, while quasi-15-year and quasi-56-year cycles were detected at the inter-decadal scale. The reconstructed inter-annual scale showed a better capability to represent the abrupt change characteristic of drought, which was also more influential to the original time series with a variance contribution of 55.3%, while the inter-decadal scale could be used to portray the long-term drought variation process with a relative lower variance contribution of 29.1%. (4) The multi-scale response of drought to climate change indicated that changes of precipitation (PRE) and diurnal temperature range (DTR) were the major driving factors in the drought variation at different time scales. Compared with potential evapotranspiration (PET), DTR was a much more important climate factor associated with drought variations by altering the energy balance, which is more obvious over the YZR basin distributed with extensive snow cover and glaciers. These findings could provide important implications for ecological environment protection and sustainable socioeconomic development in the YZR basin and other high mountain regions.

In the first section of this study, we explored the relationship between ring width index (RWI) and normalized difference vegetation index (NDVI) time series on varying timescales and spatial resolutions, hypothesizing positive associations between RWI and current and previous-year NDVI at 69 forest sites scattered in the Northern Hemisphere. We noted that the relationship between RWI and NDVI varies over space and between tree types (deciduous versus coniferous), bioclimatic zones, cumulative NDVI periods, and spatial resolutions. The high-spatial-resolution NDVI (MODIS) reflected stronger growth patterns than those with coarse-spatial-resolution NDVI (GIMMS3g). In the second section, we explore the link between RWI, climate and NDVI phenological metrics (in place of NDVI) for the same forest sites using random forest models to assess the complicated and nonlinear relationships among them. The results are as following (a) The model using high-spatial-resolution NDVI time series explained a higher proportion of the variance in RWI than that of the model using coarse-spatial-resolution NDVI time series. (b) Amongst all NDVI phenological metrics, summer NDVI sum could best explain RWI followed by the previous year's summer NDVI sum and the previous year's spring NDVI sum. (c) We demonstrated the potential of NDVI metrics derived from phenology to improve the existing RWI-climate relationships. However, further research is required to investigate the robustness of the relationship between NDVI and RWI, particularly when more tree-ring data and longer records of the high-spatial-resolution NDVI become available. [ABSTRACT FROM AUTHOR]

Increasing frequency and intensity of drought extremes associated with global change are a key challenge for forest ecosystems. Consequently, the quantification of drought effects on tree growth as a measure of vitality is of highest concern from the perspectives of both science and management. To date, a multitude of drought indices have been used to accompany or replace primary climatic variables in the analysis of drought-related growth responses. However, it remains unclear how individual drought metrics compare to each other in terms of their ability to capture drought signals in tree growth. In our study, we employ a European multispecies tree ring network at the continental scale and a set of four commonly used drought indices (De Martonne Aridity Index, self-calibrating Palmer Drought Severity Index, Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index, the latter two on varying temporal scales) to derive species-specific growth responses to drought conditions. For nine common European tree species, we demonstrate spatio-temporal matches and mismatches of tree growth with drought indices subject to species, elevation and bioclimatic zone. Forests located in the temperate and Mediterranean climate were drought sensitive and tended to respond to short- and intermediate-term drought (<1 year). In continental climates, forests were comparably more drought resistant and responded to long-term drought. For the same species, stands were less drought sensitive at higher elevations compared to lower elevations. We provide detailed information on the month-wise performance of the four drought indices in different climate zones allowing users the selection of the most appropriate index according to their objective criteria. Our results show that species-specific differences in responses to multiple stressors result in complex, yet coherent patterns of tree growth. [ABSTRACT FROM AUTHOR]

Yellow River Basin (YRB) in China has been frequently featured as one of the most vulnerable areas to climate change and climatic extremes, mainly due to its fragile arid and semiarid ecosystems.While previous researches mainly focused on the evaluation of historical drought periods, it is also meaningful to understand future drought conditions in YRB, in particular, alleviated drought trends under carbon peak and carbon neutrality periods. Based on climate outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we projected future climate conditions and drought characteristics in YRB, especially under the three SSPs (the Shared Socioeconomic Pathways) (e.g., SSP1–2.6, SSP2–4.5, and SSP5–8.5). For this, the monthly climate variables from CMIP6 models are in better agreement with the observation from 1961 to 2014, after (Equidistant Cumulative Distribution Functions) EDCDF Bias Correction method (e.g., the RMSE is reduced by 50% and 25% - 67% for temperature and precipitation, respectively). From 2015 to 2100, an increasing trend in temperature and precipitation is anticipated in YRB. When comparing with the reference period (1995–2014), drought conditions after 2040s will markedly be alleviated under the listed three SSPs. There will be a slight drying trend in YRB for all the three SSPs under four warming scenarios (e.g., 1.5 °C and 2.0 °C global warming, carbon peak and carbon neutrality) compare with the reference period. Drought conditions under carbon neutrality will be mostly alleviated among all the four warming scenarios. By 2100, YRB areas will witness a drier tendency, mainly in upstream and northern region (e.g., Inner Mongolia). We argue that reaching the carbon neutrality goal by the end of this century is essential for mitigating the impacts of climate-induced disasters on society, as such goal would help people coping with challenges posed by climatic extremes and drought conditions in a sustainable way. • CMIP6 model simulations reveal an increase in temperature and precipitation in Yellow River Basin till 2100. • Slightly enhanced drought is projected in the Yellow River Basin under future warming scenarios. • Drought conditions under carbon neutrality will be mostly alleviated among all the four warming scenarios. • By 2100, upstream and northern part of Yellow River Basin will witness a drier tendency. [ABSTRACT FROM AUTHOR]

ABSTRACT This study presents a detailed analysis on the role of snow cover during the cold season (October-March) on soil moisture deficit and drought development during the growing season (April-September) in the lowland and highland sites in the Czech Republic. Besides daily, weekly and seasonal series of basic snow-cover characteristics [the first day and the last day of snow cover, the number of days with snow cover ( DSC), snow depth and snow water equivalent ( SWE)] and soil water content measurements, six drought indices have been used in this study to quantify drought. Accumulations of years with significantly below average DSC/ SWE were recorded in the early 1960s, mid-1980s, late 1990s and most of the 2000s. The trend towards an earlier end date of snow cover is found in both lowland and highland sites. However, the most significant shift in the dates of early end of snow cover has been identified to occur mostly in the hilly areas while in the lowland areas, these changes are not that evident. Liquid precipitation more than solid precipitation (snowfall) during the cold season lead to weakening correlation between SWE/ DSC and the subsequent early summer (April-May-June, AMJ) soil moisture. Snow-cover characteristics can significantly influence soil water saturation during the first part of the growing season, while seasonal amount of SWE can explain up to 45% of soil moisture variability during AMJ season. More than 52% of dry AMJ followed after cold seasons with poor snow, and 42% of wet AMJ season followed after cold seasons with abundant snow. The strength of correlation between drought indices and soil moisture anomalies is higher in later summer. The negative anomalous snow characteristics in conjunction with winter and AMJ drought amplify lingering impact on the depletion of soil moisture in the later summer. [ABSTRACT FROM AUTHOR]

Observed alternation of global and local meteorological patterns governs increasing drought impact, which puts at risk ecological balance and biodiversity of the alpine forest. Despite considerable attention, drought impact on forest ecosystems is still not entirely understood, and comprehensive forest drought monitoring has not been implemented. In this study, we proposed to bridge this gap exploiting a time-domain synergetic use of medium resolution MODSI NDVI (Normalized Difference Vegetation Index) and NDII7 (Normalized Difference Infrared Index band 7) time series as well as on-station temperature and precipitation measures combined in the scPDSI (self-calibrated Palmer Drought Severity Index) datasets. Analysis employed the S-mode Principal Component Analysis (PCA) examined under multiple method settings and data setups. The investigation performed for South Tyrol (2001-2012) indicated prolonged meteorological drought condition between 2003 and 2007, as well as general drying tendencies. Corresponding temporal variability was identified for local mountain forest. The former response was fostered more often by NDII7, which is related to foliage water content, whereas NDVI was more prone to report on an overall downturn and implied drop in forest photosynthetic activity. Among tested approaches, the covariance-matrix based S-mode PCA of z-score normalized vegetation season NDVI and NDII7 time series ensured the most prominent identification of drought impact. Consistency in recognized temporal patterns confirms integrity of the approach and aptness of used remote-sensed datasets, suggesting great potential for drought oriented environmental analyses. [ABSTRACT FROM AUTHOR]

In recent decades, frequent droughts have been detected in some places in China along with the global climate change, which cause great damage to the development of social economy. Thus, it’s high time to investigate the spatio-temporal evolution of droughts. Based on the newly published scPDSI PM (self-calibrating Palmer drought severity index based on Penman-Monteith) dataset with high spatial resolution, the annual and seasonal variations of droughts in China from 1961 to 2009 were researched. Other research methods like linear regression, Mann-Kendall method, wavelet analysis as well as REOF (rotated empirical orthogonal function) were adopted to investigate the spatio-temporal pattern of droughts in China, and find out how droughts changed under the influence of the general circulation of atmosphere, in order to provide the foundation for drought control and drought resistance. The results indicated that: 1) In 1961-2009, China as a whole became moist significantly at annual and seasonal scale with the mutations of turning drought to wetness detected in early 1970s. 2) Period analysis illustrated that the oscillation period of seasonal and annual drought remained generally unanimous, and the dominant period of annual drought was 6.2 years, while drought in spring, autumn and winter generally had the periods of 2.6 and 6.2 years with 6.2 years as the dominant period; otherwise, drought in summer presented a dominant period of 4.4 years. 3) In the light of the spatial modes disassembled from REOF, the entire country was divided into 8 regions with different characteristics of drought or wetness, which were Northwest China, Northeast - Inner Mongolia Plateau area, the Greater Khingan Range area, the northern Qinghai-Tibet Plateau area, the southern Qinghai-Tibet Plateau area, the Middle China (including Sichuan Basin, Hanzhong Basin and Loess Plateau), Huang-Huai-Hai Plain and Southeast China. It was found that the sub-regions of REOF could primely manifest the geographical features of different regions, and hence objectively testify the actual drought condition in China. Among the 8 regions, the Greater Khingan Range area, Southeast China, the southern Qinghai-Tibet Plateau area, and Northwest China were getting moist while the latter 2 areas had a significant trend (P<0.05); Northeast - Inner Mongolia Plateau area, the northern Qinghai-Tibet Plateau area, the Middle China and Huang-Huai-Hai Plain were getting dry, and except Huang-Huai-Hai Plain, the former 3 regions were prominently getting dry. Take the regions as the objects, no matter at annual or seasonal scale, Northwest China was getting moist, while the Middle China was getting arid (P<0.05). Although the geographical positions of the 8 regions resulted in the discrepancy of influence under different climate factors, the 8 regions generally had the oscillation period of 2-9 years. 4) M-K test (Mann-Kendall test) on the 8 regions showed that the seasonal MK values of different regions varied with each other, which indicated that drought-wet degree of different regions had obvious seasonal feature, and yet most regions had a tendency of getting drought in spring and getting moist in summer. 5) Good correlations were found between polar vortex index and drought in most areas. Correlation analysis indicated that droughts in Northwest China may be affected by the polar vortex, Indian Ocean Dipole (IOD) and Pacific Oscillation (PDO). Droughts in Northeast - Inner Mongolia Plateau area, the Qinghai-Tibet Plateau area and the Middle China were significantly influenced by IOD, and drought of Huang-Huai-Hai Plain was negatively correlated with PDO. Unlike the conventional PDSI index, scPDSI integrates solar radiation and air speed into account, which will be of scientific and practical importance to forecast and distinguish different drought conditions. [ABSTRACT FROM AUTHOR]

In the first section of this study, we explored the relationship between ring width index (RWI) and normalized difference vegetation index (NDVI) time series on varying timescales and spatial resolutions, hypothesizing positive associations between RWI and current and previous- year NDVI at 69 forest sites scattered in the Northern Hemisphere. We noted that the relationship between RWI and NDVI varies over space and between tree types (deciduous versus coniferous), bioclimatic zones, cumulative NDVI periods, and spatial resolutions. The high-spatial-resolution NDVI (MODIS) reflected stronger growth patterns than those with coarse-spatial-resolution NDVI (GIMMS3g). In the second section, we explore the link between RWI, climate and NDVI phenological metrics (in place of NDVI) for the same forest sites using random forest models to assess the complicated and nonlinear relationships among them. The results are as following (a) The model using high-spatial-resolution NDVI time series explained a higher proportion of the variance in RWI than that of the model using coarse-spatial-resolution NDVI time series. (b) Amongst all NDVI phenological metrics, summer NDVI sum could best explain RWI followed by the previous year’s summer NDVI sum and the previous year’s spring NDVI sum. (c) We demonstrated the potential of NDVI metrics derived from phenology to improve the existing RWI-climate relationships. However, further research is required to investigate the robustness of the relationship between NDVI and RWI, particularly when more tree-ring data and longer records of the high-spatial-resolution NDVI become available.

Recent warming has stimulated the productivity of boreal and Arctic vegetation by reducing temperature limitations. However, several studies have hypothesized that warming may have also increased moisture limitations because of intensified summer drought severity. Establishing the connections between warming and drought stress has been difficult because soil moisture observations are scarce. Here we use recently developed gridded datasets of moisture variability to investigate the links between warming and changes in available soil moisture and summer vegetation photosynthetic activity at northern latitudes (>45°N) based on the Normalized Difference Vegetation Index (NDVI) since 1982. Moisture and temperature exert a significant influence on the interannual variability of summer NDVI over about 29% (mean r² = 0.29 ± 0.16) and 43% (mean r² = 0.25 ± 0.12) of the northern vegetated land, respectively. Rapid summer warming since the late 1980s (~0.7 °C) has increased evapotranspiration demand and consequently summer drought severity, but contrary to earlier suggestions it has not changed the dominant climate controls of NDVI over time. Furthermore, changes in snow dynamics (accumulation and melting) appear to be more important than increased evaporative demand in controlling changes in summer soil moisture availability and NDVI in moisture-sensitive regions of the boreal forest. In boreal North America, forest NDVI declines are more consistent with reduced snowpack rather than with temperature-induced increases in evaporative demand as suggested in earlier studies. Moreover, summer NDVI variability over about 28% of the northern vegetated land is not significantly associated with moisture or temperature variability, yet most of this land shows increasing NDVI trends. These results suggest that changes in snow accumulation and melt, together with other possibly non-climatic factors are likely to play a significant role in modulating regional ecosystem responses to the projected warming and increase in evapotranspiration demand during the coming decades. [ABSTRACT FROM AUTHOR]