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In the context of global warming, the increasing frequency of compound dry–hot extremes pose varying degrees of threats to the natural environment and human society. However, due to the lack of long‐term and high‐accuracy meteorological observations, the characteristics and drivers of compound dry–hot extremes over a century‐long period is still poorly investigated in China. Here we characterize the spatiotemporal variations of growing‐season (May–September) compound dry–hot events (CDHEs) over China using Standardized Dry and Hot Index (SDHI) calculated by monthly temperature and precipitation during 1901–2017. The influences of precipitation and temperature extremes, as well as large‐scale climate indices (i.e., El Niño–Southern Oscillation Index [ENSO], Atlantic Multidecadal Oscillation [AMO], North Atlantic Oscillation [NAO], Pacific Decadal Oscillation [PDO] and North Pacific [NP]) on CDHEs were then explored using the relative contribution analysis, Pearson correlation analysis and cross‐wavelet spectrum analysis. Our findings reveal a significant increase in the occurrence of different severity levels of CDHEs in China with their spatial extent gradually increase, practically since the end of the 20th century. Due to the exacerbation of drought conditions in China since the mid‐20th century, the regions where the Standardized Precipitation Index (SPI) has a more prominent contribution to the SDHI have gradually expanded, predominantly in the eastern, northern and northwestern parts of China. The significant influence of large‐scale climate indices, particularly ENSO and AMO, on the occurrence of compound dry–hot extremes in China is noteworthy, as these indices control the variability of precipitation and temperature, respectively. The study findings demonstrate that AMO exhibits a more significant correlation with SDHI in all subregions of China, while ENSO exhibits marginally stronger periodic coherence with SDHI than the other indices. This study offers valuable insights and references for unravelling long‐term development process of and the underlying influence mechanisms of significant climate patterns on the growing‐season CDHEs in China. [ABSTRACT FROM AUTHOR]

Compound extreme events, such as events with concurrent extreme temperature and precipitation, are often more devastating than single events occurring independently with serious impacts on human society. In this study, we analyzed the future evolution of compound extreme summer days, namely, compound hot–dry days (CHDDs) and compound hot–wet days (CHWDs), in China and explored the relative changes in population and economic exposure based on climate simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The results showed that compound extreme days will be more frequent and severe under different scenarios in which the frequency of CHDDs is relatively high with a relatively high growth rate of CHWDs. The frequency of compound extreme days will continue to increase under the SSP2–4.5 and SSP5–8.5 scenarios but decline after 2070 under the SSP1–2.6 scenario. In general, the growth rate of population exposure to moderate/severe CHDDs ranges from 0 to 10%/30 to 50%. Meanwhile, the increasing rate of population exposure to moderate/severe CHWDs ranges from 0 to 30%/30 to 100%. GDP exposure to moderate/severe CHDDs would increase by 0–50%/100–400%, and severe CHWDs increased GDP exposure by more than 800%. Socioeconomic exposure to CHWDs will increase at a faster rate in the future. Due to the increase in compound extreme days and population decline, the relative contribution of climate change to population exposure is larger. Economic development alongside an increase in the number of compound extreme days will contribute relatively more to the interaction of climate and GDP, increasing GDP exposure. This study offers useful insights into mitigation and adaptation measures for compound extreme events and potential climate change in China. [ABSTRACT FROM AUTHOR]

Excessive heat can cause discomfort, stress even mortality to humans. We investigate the multifaceted characteristics of summer heat and the affected population across China using a composite heat index (HI) based on meteorological observations and the Coupled Model Intercomparison Project Phase 6 climate models. We highlight that HI is only applicable when maximum air temperature is above 26.7 ℃. From 1961 to 2014, China has experienced increasing heat days (1.05 day/10a) and severity (0.15 ℃/10a) with more population influenced by expanding heat extent. Simultaneously, increases in the frequency (7.58–14.80 times), duration (0.46–1.23 days) and intensity (1.00–1.42 ℃/day) of heat events are detected with increased population exposure (9.33 × 105–5.59 × 106 times·persons). In the future, increases in heat severity, spatial extent, and the affected population would be aggravated from 1.5 to 2 to 3 ℃ warming. Dangerous heat events would experience increases in frequency (12.67–70.81 times), duration (0.85–7.21 days), intensity (1.78–8.57 ℃/day), and population exposure (2.06 × 106–3.18 × 107 times·persons) under a warming climate. Some regions over the Tibetan Plateau and southwest China would be affected by expanding cautionary and extremely cautionary heat. Northwest China would experience intensified dangerous heat events whereas southeastern China would face longer-lasting heat events with stronger intensity. Precautionary strategies are essential for these regions under risk. [ABSTRACT FROM AUTHOR]

Microalgae CO2 sequestration has gained considerable attention in the last three decades as a promising technology to slow global warming caused by CO2 emissions. To provide a comprehensive and objective analysis of the research status, hot spots, and frontiers of CO2 fixation by microalgae, a bibliometric approach was recently chosen for review. In this study, 1561 articles (1991–2022) from the Web of Science (WOS) on microalgae CO2 sequestration were screened. A knowledge map of the domain was presented using VOSviewer and CiteSpace. It visually demonstrates the most productive journals (Bioresource Technology), countries (China and USA), funding sources, and top contributors (Cheng J, Chang JS, and their team) in the field of CO2 sequestration by microalgae. The analysis also revealed that research hotspots changed over time and that recent research has focused heavily on improving carbon sequestration efficiency. Finally, commercialization of carbon fixation by microalgae is a key hurdle, and supports from other disciplines could improve carbon sequestration efficiency. [ABSTRACT FROM AUTHOR]

The most basic features of climatological normals and variability are useful for describing observed or likely future climate fluctuations. Pan evaporation (Epan) is an important indicator of climate change; however, current research on Epan has focused on its change in mean rather than its variability. The variability of monthly Epan from 1961 to 2020 at 969 stations in China was analyzed using a theoretical framework that can distinguish changes in Epan variance between space and time. The Epan variance was decomposed into spatial and temporal components, and the temporal component was further decomposed into interannual and intra-annual components. The results show that the variance in Epan was mainly controlled by the temporal component. The time variance was mainly controlled by intra-annual variance, decreasing continuously in the first 30 years, and slightly increasing after the 1990s. This is mainly due to the fact that the decrease of wind speed and the increase of water vapor pressure deficit with the temperature increase offset each other and inhibit the variability of Epan. The variance decreased more in the northern region, whereas it exhibited a small decrease or slight increase in the southern region. The reduction in seasonality was dominated by spring, followed by summer. The differences in Epan variability in space and season were mainly caused by the differing rates of change in evaporation driving forces, such as a greater reduction in wind speed in the northern region and spring. Significance Statement: The purpose of this study is to better understand how the variability of evaporation changes rather than in mean under climate change. This is important because the variability is useful to describe the observed or likely future fluctuations, and a small fluctuation may have large impacts on water practices, such as agricultural production. Our findings showed that the temporal and spatial variability of evaporation decreased due to its drivers offsetting each other. However, because the drivers are numerous and continuously changing under climate change, it is necessary to pay attention to its mean and variability for serving water resources practice. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) at high spatial resolution is crucial for drought monitoring and water resources management, but currently available remote sensing ET products generally have coarse spatial resolution (≥1000 m). To estimate ET at a high spatial resolution, Landsat images, Global Land Surface Satellite (GLASS), Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological forcing data were integrated, and the surface energy balance (SEBS) model was employed to calculate the 16-day average ET at 30 m resolution for China's Tarim River Basin, spanning from 2009 to 2018. The results indicated that the average 16-day ET estimates correlated well with ground observations for land and water surfaces (root mean square error (RMSE) for land = 0.92 mm day−1, RMSE for water = 1.63 mm day−1, mean bias for land = 0.3 mm day−1, mean bias for water = 0.52 mm day−1). Cross validation with GLASS, ETMonitor, and Penman-Monteith-Leuning (PML_V2) ET datasets revealed an overall increasing trend for all four products (PML_V2 = 6.277 mm year−1, GLASS = 2.185 mm year−1, ETMonitor = 3.258 mm year−1, SEBS = 1.441 mm year−1), demonstrating good spatial consistency. The consistent increasing pixels were primarily distributed in the northern, southwestern, and southeastern mountainous regions, accounting for 22.8%, while 0.29% of the consistent decreasing pixels were mainly concentrated in the central desert and mountain-front oasis areas. Inconsistent pixels accounted for 76.9%, with 2.34% of the inconsistent decreasing pixels exhibiting a scattered distribution, while 37.28% of the inconsistent increasing pixels were mainly found in the central desert and some oasis areas. Furthermore, SEBS ET trend analysis indicated that the oasis area experienced more pronounced changes than the mountainous and desert areas during the 2009–2018 period. The SEBS ET estimated in this study can provide high-precision data support and a reference for future research on the water resources management. • The evapotranspiration (ET) dataset with 30 m and 16-day resolution was estimated with surface energy balance method (SEBS). • Consistency assessments were conducted on four types of ET data at different time and spaces. • The annual evapotranspiration shows an increasing trend from 2009 to 2018. [ABSTRACT FROM AUTHOR]

The vulnerability, exposure and resilience of socioeconomic activities to future climate extremes call for high-resolution gridded GDP in climate change adaptation and mitigation research. While global socioeconomic projections are provided mainly at the national level, and downscaling approaches using nighttime light (NTL) images or gridded population data can increase the uncertainty due to limitations. Therefore, we adopt an NTL-population-based approach, which exhibits higher accuracy in socioeconomic disaggregation. Gross regional product of over 800 provinces, which covering over 60% of the global land surface and accounted for more than 80% of GDP in 2005, were used as input. We present a first set of comparable spatially explicit global gridded GDP projections with fine spatial resolutions of 30 arc-seconds and 0.25 arc-degrees for the historical period of 2005 and for 2030–2100 at 10-year intervals under the five SSPs, accounting for the two-child policy in China. This gridded GDP projection dataset can broaden the applicability of GDP data, the availability of which is necessary for socioeconomic and climate change research. Measurement(s) GDP • population • nighttime light images Technology Type(s) SSP database • LandScan Global Population database • Remote sensing Sample Characteristic - Location Globe [ABSTRACT FROM AUTHOR]

Hot and dry extremes have co‐occurred with global warming, causing worse threats than single climate extremes. We analyse the compound hot and dry day (CHDD) and population exposure (Epop) across China based on observations and 11 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6. The bias‐corrected GCMs, particularly the two‐stage multivariate quantile mapping‐corrected ones, perform better than the raw ones in catching changes in CHDD but they all overestimate CHDD and Epop. More CHDDs occur in the southeast (SE), north (NC) and northwest (NW) China with increasing trends over regions stretching from the northeast (NE) to southwest (SW) China. Despite the declined CHDD, historical Epop has generally increased by the increased population. Future projections in the SSP5‐8.5 experiment indicate an overall increase of CHDD and Epop at 1.5°C warming and an increasing Epop to dangerous CHDD at 2°C warming. SW, NE and the Tibetan Plateau need effective measures of adaptation to reduce sufferings from CHDD under climate change. [ABSTRACT FROM AUTHOR]

Multiple indices have been created to measure hot conditions that may cause discomfort, stress even death to humans. However, distinctions among these indices and their performance in measuring heat remain undisclosed. We conduct a comparative study of multiple heat indices and revisit the spatiotemporal changes in summer heat across China. The maximum temperature-based index, more sensitive to average and maximum temperatures, suggests a larger increasing trend (0.42°C/10a) in heat intensity than those average temperature-based ones which are more sensitive to minimum temperature. The absolute threshold-based heat-day indices are not so applicable as the relative ones in measuring the increasing heat days over the Tibetan Plateau. During 1960–2018, significant (p < 0.05) increasing trends in heat intensity (0.11–0.42°C/10a) and heat day (0.63–2.67 days/10a) are revealed with a jump-like increase after the mid-1990s at the country level. Stronger heat intensity occurs over the southeast and north China with larger increasing trends over the Tibetan Plateau and northwest China. Northern China with larger increasing heat intensity and days should take effective measures of adaptation to reduce suffering from the summer heat. Given differences among multiple indices and the performance over different regions, a rational selection of heat index considering the research subject of interest and regional climatology is highly recommended. [ABSTRACT FROM AUTHOR]

• Hot-dry wind denotes a significant (p < 0.01) weakening trend from 1960 to 2019 in Northern China. • Hot dry wind has become the primary driver of warm-season dryness in recent decades. • Hot dry wind is more influential than precipitation on variations of surface dryness/wetness in Northwest China. The concurrent occurrence of high temperature, low humidity, and specific wind speed, known as hot-dry wind (HDW), is a widespread agro-meteorological hazard in Northern China. HDW can significantly impact surface dryness/wetness by influencing atmospheric water demand. To understand the divergent effect of HDW and precipitation on the spatiotemporal variations of surface dryness/wetness, we collected meteorological data from 673 meteorological stations across Northern China for the warm season (May to September) during 1960–2019. Results reveal a significant (p < 0.05) wetting trend from 1983 to 2019 and a significant (p < 0.01) weakening of HDW across Northern China from 1960 to 2019. Notably, the primary driver of warm-season dryness has transitioned from precipitation before 1982 to HDW in recent decades. Regionally, the wetting trends observed in Northwest (NW) and North China (NC) are primarily attributed to the weakening HDW. Conversely, in Inner Mongolia (IM), a drying trend is noted due to a decline in precipitation that outweighs the reduction in water consumption caused by weakened HDW. During 1960–2019, our analysis affirms that the relative contribution of HDW to variations in warm-season dryness/wetness surpasses that of precipitation in Northern China, particularly in the hyper-arid NW. The persistent HDW is anticipated to exacerbate warm-season dryness and increase water demand for crop growth and animal husbandry in Northern China. [ABSTRACT FROM AUTHOR]

The co‐occurrence of hot and dry extremes (compound hot and dry extreme, CHDE) has attracted much attention due to the amplified impact on wildfire occurrence, agriculture production and human health. Most existing studies have reported the spatiotemporal variations of CHDE, changes in CHDE on different land surface conditions are barely discussed. The study investigated the spatial and temporal differences of CHDE over different regions and land covers in China during 1957–2018. On average over China, both day‐ and night‐time CHDEs have increased with a more rapid (2.6 times faster) and significant (p <.05) increasing trend in night‐time ones. Increasing trends are mainly distributed in north China with decreasing trends in central China. Moreover, increasing trends in night‐time mildly dry (0.07 per decade) and moderately hot (0.06 per decade) CHDEs are the largest among all dry and hot CHDEs. Regionally, the frequency of CHDE is the highest over the humid and sub‐humid regions for night‐ and day‐time CHDEs, but the lowest for both over the arid region. Meanwhile, CHDE has increased over the humid and sub‐humid regions in the recent decade but decreased over the arid region since 1957. For different land covers, the frequency of CHDE is the highest over forest but the lowest over grassland. Day‐time CHDEs of different hot magnitudes indicate the largest increasing trends over grassland caused by the largest increasing trends of day‐time heatwave. Significant (p < 0.05) increasing trends of day‐ and night‐time CHDEs over forest may increase the risks of tree mortality or forest fires after 2010 and larger increasing trends in night‐time CHDEs over urban may negatively impact human health. [ABSTRACT FROM AUTHOR]

Stationarity is an assumption that permeates training and practice in water-resource engineering. However, with global change, the validity of stationarity as well as uncertainty of nonstationarity in water-resource planning are being questioned; thus, it is critical to evaluate the stationarity of climate variables, especially precipitation. Based on the continuous observation data of precipitation from 1427 stations across China, 593 efficient grid cells (1° × 1°) are constructed, and the annual precipitation stationarities from 1959 to 2018 are analyzed. The evaluated autocorrelation stationarity indicates that 92.24%–96.12% of the grid cells for an autocorrelation coefficient of lag 1–8 years of precipitation are indistinguishable from 0 [90% confidence level (CL)]. The mean stationarity indicates that 97.47% of the grid cells have a stable mean for 30 years (90% CL); beyond the confidence limits, they are mainly located in the northwest of China, where annual precipitation is less, and the average exceeding range is ±3.78 mm. The long-term observation of annual precipitation in Beijing (1819–2018) and Shanghai (1879–2018) also yields autocorrelation and mean stationarities. There is no significant difference in the annual precipitations between the past 20 years (1999–2018) and the past 60 years (1959–2018) over China. Therefore, the annual precipitation in China exhibits a weak stationary behavior that is indistinguishable from the stationary stochastic process. The average variation in precipitation is ±9.55% between 30 successive years and 16.53% between 10 successive years. Therefore, it is valuable and feasible to utilize the historical data of annual precipitation as the basis of water-resources application. [ABSTRACT FROM AUTHOR]

China has begun a rapid move towards Sponge City implementation, which will include widespread installation of various Low Impact Development (LID) stormwater infrastructure. Ambitious goals have been set for all Sponge Cities, including a target capture rate of 80–85% of annual precipitation in Beijing. However, there has so far been limited investigation into whether these goals are obtainable at the catchment scale given the physical restrictions of the existing urban landscape. This paper demonstrates the use of long-term continuous hydrologic modelling to evaluate the potential of meeting rainfall capture goals over a long time period for a case study area in Beijing. Detailed land cover classification derived from satellite imagery aided in the parameterization of a SWMM (Stormwater Management Model) model representing a 133 km2 urban study area. The calibrated and validated model demonstrated satisfactory agreement between computed and observed runoff for a variety of precipitation events ranging from 10 to 207 mm. A synthetic high resolution rainfall time series was generated from historic daily observations then used as input to run the model continuously for a 35 year period. Feasible LID model scenarios based on varying degrees of implementation of rain gardens, permeable pavements and green roofs were compared in terms of their potential volume capture of annual rainfall. Modelling results demonstrated that the conversion of 30% of roof area to green roof, 10% of green areas to rain gardens and 35% of paved areas to permeable pavement could increase the baseline volume capture ratio from 59.9% to 82.2%, indicating that Sponge City goals can be met within the case study area with realistic levels of LID implementation. This study provides a decision-making basis for future planning in the study area. • Satellite imagery based hydrologic model shows good agreement with observed flows. • Continuous modelling approach suggested for evaluation of Volume Capture Ratio. • >80% of annual rainfall captured with moderate catchment wide implementation of LID. [ABSTRACT FROM AUTHOR]

Comprehensive knowledge about wind energy potential is critical for decision-making to achieve carbon neutrality and shape future energy pathways. Wind turbine technology advances (e.g., higher hub-heights, larger rotor diameters and rated power) can better support wind energy harvesting and alter wind energy potential. This study established an integrated model to evaluate the impact of wind turbine technology advances on onshore wind energy potentials under different wind resource conditions by using China as a case study. We found that technological advances of wind turbine can significantly impact wind energy potential. Compared with land-based 1.5-MW turbines, the onshore wind energy potential using newer generation turbines (land-based 2.5-MW turbines) would increase by 43% to 14.8 PWh (i.e., 2.0 times the electricity consumption of China in 2020). Importantly, advances in wind turbine technology can significantly increase capacity factor in poor wind resource regions, and thus enable economically viable generation in more areas. This can significantly increase wind energy potential in poor wind resource regions with large electrical load (e.g., Central, South and East China). Moreover, in contrast to the wind production of 0.46 PWh in 2020, China's wind energy potential is projected to hit 20.1 PWh by 2030 under the assumption of developed turbine technology in line with the trends of the past decade. The corresponding potential CO 2 emission reduction would range from 12.6 Gt in 2020 to 21.7 Gt in 2030. These values are 1.3 and 2.2 times higher than China's CO 2 emissions in 2020, respectively. To enhance wind energy contribution toward China's carbon neutrality goal, we recommend that the conversion of wind turbines to be accelerated, especially in poor wind resource regions with large electrical load. • Onshore wind potential for China is 2.0 times national electricity demand of 2020 • Wind turbine technology has more influence on wind potential in low wind regions • China's wind potential reach 20.1 PWh (equivalent to 21.7 Gt CO 2 emission) by 2030 [ABSTRACT FROM AUTHOR]

Measurements of evaporation from pans have traditionally been used to represent the evaporative demand of the atmosphere when estimating the crop water requirements. In China, Pan evaporation (E pan) has been observed routinely at meteorological stations since the 1950 s with D20 pans, but since 2002, the pans have been replaced by E-601B. To explore the effective reconstruction of missing daily D20 E pan over China from 1951 to 2020, this study employed three types of E pan models: the widely used physical model PenPan, two popular machine learning (ML) models (multivariate adaptive regression splines (MARS) and random forest (RF)), and multiple linear regression (MLR). Daily E pan data were predicted based on the daily wind speed (U), atmospheric pressure (AP), relative humidity (Rh), air temperature (Ta), and sunshine hours (n) of 2410 meteorological stations. The results showed that the MARS and RF predictions were superior to those of PenPan, and the results of MLR were the worst. The average determination coefficient for RF, MARS, PenPan, and MLR values were 0.95, 0.91, 0.88, and 0.86, respectively, and the average root-mean-square difference were 0.62, 0.91, 1.17, and 1.15 mm day−1, respectively. Thus, the missing daily E pan were predicted using RF and the reconstructed E pan had the same probability density function as the observed E pan. The annual E pan first showed a downward trend (at a rate of 6.17 mm yr−1) from 1961 to 1993 and then a reverse upward trend (at a rate of 1.84 mm yr−1) from 1994 to 2020. E pan predictions by PenPan are limited by regional characteristics, making it difficult to transfer between regions. However, ML methods are less affected by regional characteristics and can be used across regions. Furthermore, ML methods can effectively reconstruct missing E pan providing support for verification of PenPan, which is beneficial for the study of driving factors of E pan. • Three types methods for accurate prediction of daily pan evaporation were explored. • The D20 pan evaporation were reconstructed effectively with machine learning method. • The annual evaporation shows downward and reverse upward trends from 1951 to 2020. [ABSTRACT FROM AUTHOR]

• A framework for decomposing the contributing factors of extreme droughts is developed for China. • Extreme droughts attributed to rises in temperature, net radiation, precipitation variability. • A smaller rise in extreme droughts per Kelvin in high-latitude regions is due to their high sensitivity to precipitation. Climate change in mean-state or variability could lead to more/less frequency of extreme drought. In this study, we developed a new framework for decomposing the contributing factors of changes in future extreme drought frequency in China in accordance to the Palmer Drought Severity Index (PDSI). We performed a series of numerical experiments to ensure that the sensitivity of trend and variability in individual climatic variables can be distinguished. In addition, an extreme drought rate with warming (EDRW , unit: %·K−1) is defined to quantify the relative change in extreme drought frequency per Kelvin. Overall, the EDRW will increase dramatically by an average of 27.71%·K−1. The ascended EDRW are attributed to increases in temperature (+56.90%·K−1), net radiation (14.80%·K−1) and precipitation variability (+8.23%·K−1); a decrease in relative humidity (+4.61%·K−1), but is partly offset by an increase in precipitation (i.e., "wetting", −60.12%·K−1). A smaller increase in the frequency of extreme droughts is found in high-latitude regions due to their enhanced sensitivity to "wetting". [ABSTRACT FROM AUTHOR]

Declining pan evaporation (Epan) across many continents in the past decades despite global warming is gaining attention of hydrology and climate science communities. While Geo‐detector is considered useful for attributing the spatio‐temporal variation of a certain geography‐related element, it has not been applied for Epan attribution. Based on the Geo‐detector, we first attribute the spatio‐temporal variation of Epan across China in 1961–2001. The results show that relative humidity is the primary factor influencing the temporal dynamics of Epan, followed by sunshine duration, maximum air temperature and wind speed. In the northwest China (south China and east China), wind speed, air temperature and relative humidity (relative humidity, sunshine duration, wind speed and air temperature) are the dominant factors of Epan variations. The results obtained are comparable to the previous studies using other statistical methods (i.e., the partial differential method, Pearson correlation coefficient and multiple regression), which reveal the usefulness of Geo‐detector for attributing and diagnosing the spatio‐temporal variations of Epan. Moreover, more detailed spatial information and interactions among meteorological elements can be obtained using Geo‐detector. These findings should provide helpful references for understanding the mass and energy budgets at different spatial–temporal scales under global warming. [ABSTRACT FROM AUTHOR]

The Paris Agreement proposes a 1.5 °C target to limit the increase in global mean temperature (GMT). Studying the population exposure to droughts under this 1.5 °C target will be helpful in guiding new policies that mitigate and adapt to disaster risks under climate change. Based on simulations from the Inter- Sectoral Impact Model Intercomparison Project (ISI-MIP), the Standardized Precipitation Evapotranspiration Index (SPEI) was used to calculate drought frequencies in the reference period (1986-2005) and 1.5 °C global warming scenario (2020-2039 in RCP2.6). Then population exposure was evaluated by combining drought frequency with simulated population data from shared socioeconomic pathways (SSPs). In addition, the relative importance of climate and demographic change and the cumulative probability of exposure change were analyzed. Results revealed that population exposure to droughts in the east of China is higher than that in the west; exposure in the middle and lower reaches of the Yangtze River region is the highest, and it is lowest in the Qinghai-Tibet region. An additional 12.89 million people will be exposed to droughts under the 1.5 °C global warming scenario relative to the reference period. Demographic change is the primary contributor to exposure (79.95%) in the 1.5 °C global warming scenario, more than climate change (29.93%) or the interaction effect (9:88%). Of the three drought intensities - mild, moderate, and extreme - moderate droughts contribute the most to exposure (63.59%). Probabilities of increasing or decreasing total drought frequency are roughly equal (49.86% and 49.66%, respectively), while the frequency of extreme drought is likely to decrease (71.83% probability) in the 1.5 °C global warming scenario. The study suggested that reaching the 1.5 °C target is a potential way for mitigating the impact of climate change on both drought hazard and population exposure. [ABSTRACT FROM AUTHOR]

Climate change and its potential threats on water security call for reliable predictions of evapotranspiration (ET) and runoff Q at different time scales, but current knowledge of the differences in their predictability between humid and nonhumid regions is limited.Based on spatially distributed catchments inChina, the authors characterized their predictability and provided plausible explanations. Using the Budyko framework, it was confirmed that annualET is predictable in nonhumid regions but less predictable in humid regions, and annualQ is predictable in humid regions but less reliable in nonhumid regions. Themain cause of the varied predictability lies in the variation of water storage change DS in the water balance equation. It affects both the estimation and the variability ofQin nonhumid catchmentsmore than that in humid catchments, which increases the challenge of predicting annual Q in nonhumid regions, while the opposite effect occurs in annual ET prediction between humid and nonhumid catchments.Moreover, the differences between the controlling factors of ET variability in different regions add more differences in their predictability. The dominant control of precipitation makes it easy to predict annual ET in nonhumid regions. By contrast, precipitation, potential evaporation, and their covariance take considerable effort to determine annualETvariations,which leads to less reliableETestimation and predictability in humid catchments. Therefore, one can accurately predict annual ET in nonhumid catchments andQ in humid catchments based on commonly used hydrological models.With proper consideration of ΔS, the predictability of annual ET and Q in both humid and nonhumid catchments can be improved. [ABSTRACT FROM AUTHOR]

In a warming climate, there was a long-term expectation that the atmospheric evaporative demand would increase, which was challenged by an unexpected discovery two decades ago of decreases in measured pan evaporation, now widely termed as the 'pan evaporation paradox.' In this review, we summarize recent reports on the pan evaporation paradox around the world over the past half century, possible causes, implications for the water cycle, and its possible change in the future. We then present a case study of China based on the latest meteorological datasets and the state-of-the-art General Circulation Models ( GCMs). We confirm that pan evaporation ( Epan) decreases in most parts of China at an average of about −2.60 mm/y2, and this decrease disappears around 1993. We introduce and develop a detrending approach in sensitivity analysis and find that changes in solar radiation, wind speed, and relative humidity overcompensate the positive contribution of increasing air temperature in Epan and lead to the well-known pan evaporation paradox. Positive changes in Epan using 12 state-of-the-art GCMs for 2021-2050 and for 2071-2100 under RCP4.5 and RCP8.5 scenarios, respectively, when compared with their corresponding multiyear mean over 1971-2000 as base line, shows that the evaporation paradox would not appear in the future. We highlight that it is vital and promising to move forward to interpreting how the atmospheric evaporative demand would change in the future. WIREs Water 2017, 4:e1207. doi: 10.1002/wat2.1207 For further resources related to this article, please visit the . [ABSTRACT FROM AUTHOR]

Atmospheric evaporative demand plays a pivotal role in global water and energy budgets, and its change is very important for drought monitoring, irrigation scheduling, and water resource management under a changing environment. Here, future changes of pan evaporation Epan, a measurable indicator for atmospheric evaporative demand, are first projected and attributed over China through a physically based approach, namely, the PenPan model, forced with outputs from 12 state-of-the-art climate models from phase 5 of the Coupled Model Intercomparison Project. An equidistant quantile mapping method was also used to correct the biases in GCMs outputs to reduce uncertainty in Epan projection. The results indicated that Epan would increase during the periods 2021-50 and 2071-2100 relative to the baseline period 1971-2000 under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios, which can mainly be attributed to the projected increase in air temperature and vapor pressure deficit over China. The percentage increase of Epan is relatively larger in eastern China than in western China, which is due to the spatially inconsistent increases in air temperature, net radiation, wind speed, and vapor pressure deficit over China. The widely reported 'pan evaporation paradox' was not well reproduced for the period 1961-2000 in the climate models, before or after bias correction, suggesting discrepancy between observed and modeled trends. With that caveat, it was found that the pan evaporation has been projected to increase at a rate of 117-167 mm yr−1 K−1 (72-80 mm yr−1 K−1) over China using the multiple GCMs under the RCP 4.5 (RCP 8.5) scenario with increased greenhouse gases and the associated warming of the climate system. [ABSTRACT FROM AUTHOR]

• Ecohydrological responses to the 1987 fire were re-examined in three forested basins. • A significant decline in most ecohydrological variables was detected in the 1987 fire. • The hydrological systems need longer time to recover from fire than NDVI, LAI and GPP. Understanding how bushfire affects basin-wide ecohydrological processes is critical for ecological restoration and water supply. However, the mechanisms responsible for post-fire streamflow remain poorly explored in forested basins of China due to complex scale-dependent relationships between fire-induced forest changes and ecohydrological processes, lack of reasonable design of paired watershed experiments, and especially data scarcity. Here, we re-examine ecohydrological responses of the Black Dragon fire (one of the largest and most damaging forest fires on record globally) on an annual scale in three forest basins (two fire-impacted basins, namely Emuer and Pangu, and a nearly unimpacted basin, Huma) in the Daxing'an Mountains using multiple most recent datasets and methods. We found that the Black Dragon fire decreased annual- and basin-averaged vegetation leaf area, evapotranspiration, interception loss, transpiration, soil moisture, runoff, and discharge capacity in 1987 in the two fire-impacted basins compared with the unimpacted basin. The annual- and basin-averaged evapotranspiration (runoff) did not reduce (increase) as much as that expected with decreased LAI given the precipitation amount in 1987 in the two fire-impacted basins, which properly linked to the quick postfire regrowth of vegetation in the growing season. Vegetation leaf area and productivity can quickly recover in the following two to three years postfire, but the hydrological systems need more than 10 years to adapt this disturbance. These findings improve the understanding of ecohydrological responses to bushfire disturbance and provide scientific evidence for ecological protection and water resources management under intensified natural and anthropogenic disturbances. [ABSTRACT FROM AUTHOR]

Quantifying the effects of climate change and human activities on runoff changes is the focus of climate change and hydrological research. This paper presents an integrated method employing the Budyko-based Fu model, hydrological modeling, and climate elasticity approaches to separate the effects of the two driving factors on surface runoff in the Luan River basin, China. The Budyko-based Fu model and the double mass curve method are used to analyze runoff changes during the period 1958~2009. Then two types of hydrological models (the distributed Soil and Water Assessment Tool model and the lumped SIMHYD model) and seven climate elasticity methods (including a nonparametric method and six Budyko-based methods) are applied to estimate the contributions of climate change and human activities to runoff change. The results show that all quantification methods are effective, and the results obtained by the nine methods are generally consistent. During the study period, the effects of climate change on runoff change accounted for 28.3~46.8% while those of human activities contributed with 53.2~71.7%, indicating that both factors have significant effects on the runoff decline in the basin, and that the effects of human activities are relatively stronger than those of climate change. [ABSTRACT FROM AUTHOR]

Temperature has long been accepted as the major controlling factor in determining vegetation phenology in the middle and higher latitudes. The influence of water availability is often overlooked even in arid and semi-arid environments. We compared vegetation phenology metrics derived from both in situ temperature and satellite-based normalized difference vegetation index (NDVI) observations from 1982 to 2006 by an example of the arid region of northwestern China. From the satellite-based results, it was found the start of the growing season (SOS) advanced by 0.37 days year and the end of the growing season (EOS) delayed by 0.61 days year in Southern Xinjiang over 25 years. In the Tianshan Mountains, the SOS advanced by 0.35 days year and the EOS delayed by 0.31 days year. There were almost no changes in Northern Xinjiang. Compared with satellite-based results, those estimates based on temperature contain less details of spatial variability of vegetation phenology. Interestingly, they show different and at times reversed spatial patterns from the satellite results arising from water limitation. Phenology metrics derived from temperature and NDVI conclude that water limitation of onset of the growing season is more severe than the cessation. Phenology spatial patterns of four oases in Southern Xingjiang show that, on average, there is a delay of the SOS of 1.6 days/10 km of distance from the mountain outlet stations. Our results underline the importance of water availability in determining the vegetation phenology in arid regions and can lead to important consequences in interpreting the possible change of vegetation phenology with climate. [ABSTRACT FROM AUTHOR]

Abstract: From the water balance analysis using Eagleson''s ecohydrological model in the non-humid regions of China, the allocation of evpotranspiration flux among canopy transpiration, surface interception, and bare soil evaporation is analyzed and the quantitative relationship between the vegetation and soil moisture is derived. It implies that change of vegetation coverage due to climate variation and human activity can be potentially predicted through the soil moisture change. Combination of the Budyko''s water-energy balance model and the Eagleson''s ecohydrological model is used for predicting the impact of climate and vegetation changes on the catchment water balance, which shows that the combined model has the capacity of capturing the regional soil-vegetation-atmosphere interaction, and is useful for assessing the long-term effect of vegetation changes on catchment hydrology, and hence it has implications to the water resources management in the non-humid regions of China. [Copyright &y& Elsevier]

Ecosystem water use efficiency (WUE describes carbon-water flux coupling in terrestrial ecosystems. Understanding response and resilience of WUE to drought are essential for sustainable water resource and ecosystem management under increasing drought risks over China due to climate warming. Here we analyzed the response of ecosystem WUE to drought (spatiotemporal variability and resilience) over China during 1982–2015 based on an evapotranspiration (ET) dataset based on the model tree ensemble (MTE) algorithm using flux-tower ET measurements and satellite-retrieved GPP data. The results showed that the multiyear average WUE was 1.55 g C kg−1 H2O over China. WUE increased in 77.1% of Chinese territory during the past 34 years. During drought periods, the ecosystem WUE increased mainly in the northeast of Inner Mongolia, Northeast China and some regions in southern China with abundant forests but decreased in northwestern and central China. An apparent lagging effect of drought on ecosystem WUE was observed in the east of Inner Mongolia and Northeast China, the west and east regions of North China and the central part of Tibetan Plateau. Some ecosystems (e.g., deciduous needle-leaf forests, deciduous broadleaf forests, evergreen broadleaf forests and evergreen needle-leaf forests) in Central China, Northeast and Southwest China exhibited relatively greater resilience to drought than others by improving their WUE. Our findings would provide useful information for Chinese government to adopt a reasonable approach for maintaining the structure and functions of ecosystems under drought disturbance in future. [ABSTRACT FROM AUTHOR]

With increasing demand for energy, broaden renewable energy of income and reduce expenditure is becoming more and more important. Diffuse radiation ( R d ) is an important consideration in building energy saving. Hundreds of methods were developed to calculate R d because it is seldom available in many countries and its spatial-pattern is strongly station-dependent. There are only 13 stations that monitor both global solar radiation ( R s ) and R d after 1993 across China. Based on 812640 measurements of daily R s and R d collected from 80 stations across China during 1957–2014, we wished to calibrate and validate a simple approach, which can be easily used to predict R d over both daily and monthly periods for all locations in China and gave the accurate values of parameters. The approach, of the case study method, is based on R s and extra-terrestrial solar radiance ( R a ). Results showed that the daily method can be employed well, while the monthly approach was applied well in the Southern Region (SR) only. The monthly approach of the Northern Region (NR) was improved using its regional characteristics. The methods achieved can effectively estimate R d and strongly apply in engineering for only two parameters, which accurate values for all stations has been offered. [ABSTRACT FROM AUTHOR]

Compound hot and dry extremes have drawn extensive attention given the devastating impacts on natural ecosystem and social economy. However, the substantial dependence of compound hot and dry extremes upon individual ones is barely discussed at the daily level. In this study, we present the dependence of compound hot and dry days (CHDDs) and events (CHDEs) upon individual ones using summer (June–July–August) daily temperature and precipitation across China during 1961–2014. Results show more CHDDs and CHDEs over regions from northeast to southwest China, with stronger intensity over the transitional area between Northwest China (NW) and the Tibetan Plateau. Simultaneously, the period with the occurrence of compound extremes generally extends since compound extremes start earlier and end later. On average over China, hot extremes are significantly (p < 0.01) influential on the frequency (r = 0.42–0.83) of compound extremes, which contribute 55–78% to changes in the frequency. Dry extremes are significantly (p < 0.01) influential on the intensity (r = 0.60–0.79) and contribute 63–70% to changes in the intensity. Both hot and dry extremes are influential on the start and end of compound extremes. More importantly, largely influenced by the high probability of dry extremes in North China, the joint probability of compound extremes is higher in NW followed by Inner Mongolia. These findings highlight the new insights into compound extremes defined by relative thresholds at the daily level. • More compound extremes occur from NE to SW, with stronger intensity over the transitional area between NW and TP. • Hot (dry) extremes are more influential on the frequency (intensity) of compound extremes. • Influenced by dry extremes, the joint probability of compound extremes is higher in NW followed by IM. [ABSTRACT FROM AUTHOR]

The rapid increase in world's installed wind energy capacity may have masked the power loss caused by declining global surface wind speed (termed 'global stilling'), particularly for China with huge wind energy investments. Here, we estimated the potential impact of global stilling on wind energy production in China, using data from 1226 meteorological stations between 1971 and 2015. We show that surface wind speeds have on average declined at a rate of 5.5% decade−1, while the corresponding wind power density dropped by 24.5% decade−1. Although the decline in wind speeds has slowed after 1991, the decline in wind power density did not show this slowdown. This was attributed to the absence of slowdown in the declining trend of strong winds. Compared with the wind speed levels in the 2000s, the mean capacity factor would have dropped from 20.7% in 2001 to 14.9% in 2015, with the largest absolute change in the "Three North" regions. Furthermore, wind electricity generation would have declined by 40 TWh/a using the installed capacity of 2015, representing a decrease of 16%. The correlation analysis indicates that the decreased wind speed is most likely caused by changes in the large-scale atmospheric circulation rather than increased surface roughness. • We quantified the influence of global stilling on wind energy in China. • The large-scale circulation variability is probably the main cause of wind stilling over China. • We proposed some strategies for wind energy to cope with climate system change. [ABSTRACT FROM AUTHOR]

• We explored some methods for accurate estimation of daily surface solar radiation. • We reconstructed the solar radiation data in China with high spatiotemporal resolution. • We identified areas with strong potential for solar energy production in China. Accurate estimation of surface solar radiation (SSR) is crucial for photovoltaic (PV) systems design and solar PV power plants site selection. However, the SSR observations often suffer from inhomogeneity issues (e.g., aging equipment and instrument replacement) and low spatial–temporal coverage, which constrained the management and development of PV systems, particularly for countries with huge solar energy investments (e.g., China). To address them, we proposed seven different models (including four machine learning models, two empirical models and a multiple linear regression model) for accurate prediction of daily SSR using conventional meteorological data. Our results showed that the support vector machine (SVM) outperformed other models in estimating daily SSR. Based on SSR data corrected by the SVM model, the sharp downtrend in SSR (-9.64 W m−2 decade-1) due to the sensitivity drift of instrument aging before 1990 was moderated (-2.36 W m−2 decade-1) in China; and the abnormal jump caused by instrument replacement in SSR observations during 1990–1993 was removed. Furthermore, by combining the advantages of large network of conventional meteorological data and SVM model, we extended the limited station-based SSR data (∼100 meteorological stations) to include longer period and larger spatial coverage (2185 meteorological stations, 1971–2016) in China. By coupling the grid-based method and PV power model, we created reliable SSR and PV power maps with higher temporal and spatial resolution over China. Spatially, the main distribution of high SSR and PV power were in the northwestern China, Tibetan Plateau and some coastal areas in the southern China. Temporally, the PV power experienced a significant drop during 1971–2016 (-1.94 kWh m−2 decade-1) due to the significant decline in SSR (-0.91 W m−2 decade-1). Above all, the new maps of SSR and PV power prepared here should support PV investments within the Chinese territory. [ABSTRACT FROM AUTHOR]

The wide application of satellite-based and reanalysis-based precipitation data has greatly promoted hydrometeorological research in areas where precipitation observations are scarce. However, the suitability of such precipitation products needs to be carefully evaluated before applications in certain basins because their inherited errors vary with different climate zones, seasonal cycles and land surface conditions; in addition, precipitation products have not been evaluated in the Xihe River basin, China. In this paper, two representative satellite-based precipitation products (Tropical Rainfall Measuring Mission (TRMM) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (CDR)) and two reanalysis-based precipitation products (China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) and National Centers for Environmental Prediction - Climate Forecast System Reanalysis (CFSR)) were selected for evaluation and corrected against gauge-observed data (OBS). Furthermore, the performances of precipitation products in hydrological simulations were also assessed using the SWAT model calibrated with OBS forcing and not with individual precipitation products. The results show that satellite-based precipitation has a higher quality than reanalysis-based precipitation. The CFSR and CDR overestimate precipitation (the overestimation of CDR precipitation is mainly concentrated in the precipitation intensity range of 1 mm/d to 5 mm/d), while the TRMM and CMADS underestimate precipitation in the Xihe River basin. The TRMM precipitation performs best during the wet season, while the CDR precipitation performed best during the dry season. After bias correction, the quality of TRMM precipitation improves significantly. The Nash-Sutcliffe coefficient (NS) (the percent bias (|PBIAS|)) increases (decreases) by 0.61 (77.27%) and 0.7 (39.15%) under the two different correction scenarios during 2009–2015. Overall, the above original precipitation products cannot be used as supplements to the OBS in the Xihe River basin unless they are corrected by the OBS. • Four precipitation products (TRMM, CDR, CMADS and CFSR) were selected for evaluation and corrected against OBS. • The hydrological simulation results show that satellite-based precipitation performs better than reanalysis precipitation. • TRMM performs best during the wet season, while CDR performes best during the dry season. [ABSTRACT FROM AUTHOR]

Global warming is typically evaluated using trends in mean temperature. However, temperature is affected quite differently on sunny and cloudy days, with sunny days typically showing higher maximum temperature and greater diurnal temperature range. Here, we show that global warming is considerably stronger on sunny days. To do so, we evaluated warming trends using observations from meteorological stations in China and distinguish between sunny and cloudy days using rainfall records as a proxy. We find that warming trends on sunny days are about 50% higher than on cloudy days, and that 70-80% of the total temperature increase is contributed by sunny days. The main reason is likely to be a stronger sensitivity of atmospheric emissivity to water vapor on sunny days, which would be dominated by clouds on cloudy days, resulting in a stronger water vapor feedback on sunny days. Our results are consistent with observations that drier regions show stronger warming trends and imply that the anticipated greater frequency of heatwaves under global warming may mostly be attributable to this greater sensitivity of sunny days to the greenhouse forcing. [ABSTRACT FROM AUTHOR]

• Bias-corrected precipitation and temperature forcing show better performance in three headwater catchments of the Tarim River. • A revised glacier melt scheme is coupled in the VIC model to improve streamflow and flood simulations. • The contribution of glacier melt to annual streamflow is dominant in three headwater catchments of the Tarim River. • The characteristics of floods are inconsistent among the three catchments, except that floods mainly occur in summer. Understanding hydrological changes, especially those of snow and/or glacier melt-induced floods, is vital for early flood warnings in alpine regions. However, there is limited information available regarding warming-induced changes in hydrological and flooding processes in high-mountain regions owing to data scarcity and inadequate considerations within hydrological models. This study aims to improve streamflow and flood simulations in three high-mountain headwater catchments of the Tarim River in northwest China. An improved scheme for calculating glacier melt (GM2) was coupled in the Variable Infiltration Capacity model (named VIC-GM2). Driven by bias-corrected meteorological data, VIC-GM2 exhibited good performance, as evidenced by NS , KGE and PBIAS values between the simulated and observed daily streamflow ranging from 0.69 to 0.79, 0.70 to 0.81 and −2.68% to 19.6%, respectively. In addition, annual contributions of glacier melt and snow melt to total streamflow were greater than 80% and less than 16% among the three catchments, respectively. The flood characteristics were inconsistent among the three catchments, except that flooding mainly occurred in summer. The MAF (mean annual flood) in the Yarkand River was largest, followed by that in the Yurungkax River and the Qaraqash River. The FPOT (frequency of peak over threshold) and FQ99 (frequency of Q99) (times/year) fluctuated within 1 – 1.75 and 0.25 – 1 in the three catchments, respectively. This study provides references for understanding cryosphere hydrological processes and quantifying the contribution of different components (i.e., glacier melt, snow melt and rainfall) to streamflow under a changing climate in the upper Tarim River. [ABSTRACT FROM AUTHOR]

Microalgae CO 2 sequestration has gained considerable attention in the last three decades as a promising technology to slow global warming caused by CO 2 emissions. To provide a comprehensive and objective analysis of the research status, hot spots, and frontiers of CO 2 fixation by microalgae, a bibliometric approach was recently chosen for review. In this study, 1561 articles (1991-2022) from the Web of Science (WOS) on microalgae CO 2 sequestration were screened. A knowledge map of the domain was presented using VOSviewer and CiteSpace. It visually demonstrates the most productive journals (Bioresource Technology), countries (China and USA), funding sources, and top contributors (Cheng J, Chang JS, and their team) in the field of CO 2 sequestration by microalgae. The analysis also revealed that research hotspots changed over time and that recent research has focused heavily on improving carbon sequestration efficiency. Finally, commercialization of carbon fixation by microalgae is a key hurdle, and supports from other disciplines could improve carbon sequestration efficiency., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Since the early 2000s, China has carried out extensive "grain-for-green" and grazing exclusion practices to combat desertification in the desertification-prone region (DPR). However, the environmental and socioeconomic impacts of these practices remain unclear. We quantify and compare the changes in fractional vegetation cover (FVC) with economic and population data in the DPR before and after the implementation of these environmental programmes. Here we show that climatic change and CO 2 fertilization are relatively strong drivers of vegetation rehabilitation from 2001-2020 in the DPR, and the declines in the direct incomes of farmers and herders caused by ecological practices exceed the subsidies provided by governments. To minimize economic hardship, enhance food security, and improve the returns on policy investments in the DPR, China needs to adapt its environmental programmes to address the potential impacts of future climate change and create positive synergies to combat desertification and improve the economy in this region., (© 2023. The Author(s).)

Water use efficiency (WUE) is a central parameter for linking carbon and water exchange processes in terrestrial ecosystems. The Beijing-Tianjin Sand Source Region (BTSSR) in China has undergone tremendous vegetation restoration and climate change. Understanding the WUE responses to climate change and human activity and their relative contributions to the trends and inter-annual variations (IAVs) in WUE is necessary to improve water use efficiency and strengthen water resource management. The evapotranspiration (ET) dataset based on the model tree ensemble (MTE) algorithm which was a machine learning approach using flux-tower ET measurements and the GLASS GPP dataset, as well as the variance decomposition method, were used to analyze the spatiotemporal changes in water use efficiency and inherent water use efficiency (IWUE) and the impacts of climate change and human activities. The results showed that the annual WUE and IWUE exhibited significantly increase in most regions of the BTSSR. The trend of human activity played the most important role in the increases of WUE and IWUE, with relative contributions of 88.2% and 85.9%, respectively, followed by the IAV of human activity for WUE (6.1%) and the trend of climate change (8.7%) for IWUE. The contribution of IAV to climate change was relatively small. Moreover, WUE and IWUE were all positively correlated with precipitation and temperature in most regions. Our results indicated that ecological restoration projects had significantly improved water use efficiency in BTSSR and may decrease the water burden in the BTSSR., (Copyright © 2019 Elsevier B.V. All rights reserved.)