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Ski tourism is extremely sensitive to climate change and is also heavily affected by socioeconomic conditions. Although some ski areas are still profitable under current climate and socioeconomic conditions, they will become difficult to operate in the face of rising winter temperatures, which will result in further economic losses, resource waste and environmental damage. This study projects variability in the suitability of ski area development across China in the coming decades. Natural suitability under three representative concentration pathway emission scenarios (RCP2.6, RCP4.5 and RCP8.5), socioeconomic suitability under four shared socioeconomic pathways (SSP1, SSP2, SSP3, and SSP5) and integrated suitability under four climatic-socioeconomic scenarios (RCP2.6-SSP1, RCP4.5-SSP2, RCP8.5-SSP3, and RCP8.5-SSP5) are reported. Furthermore, the suitability of 731 existing ski areas in China is assessed. The results show a substantial decline in integrated suitability for most regions of China except for some very cold areas, where higher air temperatures will make visitors feel more comfortable and the relatively poor socioeconomic conditions will improve in the 2030s, 2050s and 2090s. The average higher integrated suitability area (integrated suitability values greater than 0.5) under four climatic-socioeconomic scenarios decreases from the current 29.9%–14.4%, 5.0% and 4.5% by the 2030s, 2050s and 2090s, respectively. Under RCP2.6-SSP1, the higher integrated suitability area is projected to decrease from the current 28.0%–5.2% by the 2050s and then increase to 5.3% by the 2090s. Under RCP4.5-SSP2, RCP8.5-SSP3, and RCP8.5-SSP5, the higher integrated suitability area is projected to continuously decrease from 30.3%, 30.6% and 30.6% in the 2010s to 4.1%, 4.4% and 4.4% in the 2090s, respectively. By the 2090s, 41, 138 and 277 existing ski areas are projected to be closed under RCP2.6-SSP1, RCP4.5-SSP2, and RCP8.5-SSP3/RCP8.5-SSP5, respectively. It is clear that emission pathways and climate change adaptation and mitigation strategies will greatly shape the development of China's regional ski tourism.

The floods caused by the extreme precipitation in the Yangtze River basin (YRB) and Murray–Darling River basin (MDRB), the largest basins in China and Australia, have significant impacts on the society and regional economies. Based on the spatial–temporal analysis of the daily precipitation extremes (DPEs) during 1982–2016, we found that for both basins, the whole-basin-type DPEs have the highest proportion and a synchronous DPE interannual variation characteristic exists in the two basins, with the 3-yr running correlation coefficient of the annual DPE days (DPEDs) reaching almost 0.7 (significant at the 0.01 level). The El Nino–Southern Oscillation (ENSO), which is one of the most significant climate disturbance factors in the world, plays an important role in modulating the variability of the DPEs in the two basins. Singular value decomposition (SVD) analysis revealed that both the YRB and the MDRB’s whole-basin-type DPEs are closely coupled with the procedure that the preceding winter eastern Pacific (EP)-type El Nino faded to a central Pacific (CP)-type La Nina. This means that the DPEs in the YRB and MDRB may synchronously occur more frequently when the above process occurs. Owing to the atmosphere–ocean interaction from the east–west dipole sea surface temperature (SST) anomaly pattern, the atmospheric circulation disturbance exhibits a pattern in which the equatorial eastern Pacific region is a mass source anomaly with a higher pressure, drier air, and weaker convection, while the equatorial western Pacific region is a mass sink anomaly with a lower pressure, wetter air, and stronger convection. Moreover, two wave trains that originated from the tropical western Pacific were found to extend to the YRB and MDRB. The interaction between the wave train’s interphase dynamics and water vapor transport disturbance results in the ascent conditions and enhanced water vapor transport, which leads to the synchronous occurrence of DPEs in the YRB and MDRB on an interannual scale.

Adverse effects of extreme events are the major focus of climate change impact studies. Precipitation-related extremes has substantial socioeconomic impacts under the changing climate. Quantifying population exposure to precipitation extreme is the fundamental aspect of population risk assessments in the climate hotspot of Indus River Basin. This study investigates the population exposure to precipitation extremes at 1.5 °C, 2.0 °C, and 3.0 °C global warmings in the Indus River Basin using daily precipitation data, and projected population under shared socioeconomic pathways (SSPs). The Intensity–Area–Duration method was applied to detect the extreme precipitation event by tracing the rainstorm process, calculated based on five downscaled and bias-corrected Global Climate Model (GCM) outputs from Coupled Model Intercomparison Project Phase 5 (CMIP5) under four Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). The exposure of the population is finally estimated by combing SSP1 with 1.5 °C, SSP2 with 2.0 °C, and SSP5 with 3.0 °C warming levels. Results show that warming over the Indus River Basin is projected to be higher than that of the global average. Both the extreme precipitation events and population exposure are projected to increase with warming level. With regard to the reference period (1986–2005), the frequency, duration, and impacted area of extreme precipitation are projected to increase by 13.2%, 7.4%, and 1.6% annually under 1.5 °C in the Indus River Basin, respectively. Whereas, an additional 0.5 °C and 1.5 °C warming can lead to further increase in the frequency of 16.6%, 17.3%, as well as the duration of 8.6%, 12%, and areal coverage of 2.1%, 5.3%, respectively. The population exposure to extreme precipitation is projected to increase by 72.4%, 122.7%, and 87.6%, respectively, at SSP1 with 1.5 °C, SSP2 with 2.0 °C and SSP5 with 3.0 °C warming levels compare to the reference period. The demographic change is responsible more for the tremendous increment of population exposure in the Indus River Basin. If the population was held constant to the level of 2010, the increase of population exposure would be 4.4%, 8.8%, and 17.6%, respectively, at 1.5 °C, 2.0 °C, and 3.0 °C warming levels. Spatially, the prominent increment of population exposure is projected in the central and southwestern Indus River Basin. This study highlights that limiting the increase of temperature to 1.5 °C can substantially reduce population exposure to extreme precipitation events in the Indus River Basin, compared to an additional warming. Simultaneously, urge paid to formulate policies on population growth to reduce future exposure.

Pennisetum plants (Pennisetum alopecuroides L.), displaying a dwarfing phenotype along with delayed flowering and mosaic symptom on leaves, were found in Beijing, China. Flexuous filamentous particles with a size of approximate 15 × 850 nm were observed in symptomatic leaves via transmission electron microscopy. Deep sequencing of small RNAs (sRNA) from symptomatic leaves and analysis of sRNA populations were then conducted to determine the genome sequence of the viral agent in diseased plant tissues. It showed that the viral agent had one positive-sense and single-stranded RNA genome, which consisted of 9717 nucleotides (nts) excluding poly(A) tail. The complete viral genome contained a large open reading frame, encoding a polyprotein of 3131 amino acids (aa). Sequence comparison and phylogenetic analysis demonstrated that the viral agent belonged to the genus Potyvirus in the family Potyviridae. In the cladogram it was most closely related to johnsongrass mosaic virus, sharing 72% nt and 65% aa sequence identity. This viral agent was provisionally named pennisetum alopecuroides mosaic virus (PalMV). Subsequently, it was confirmed that PalMV is the causal agent of this new disease in P. alopecuroides by Koch’s postulates and reverse transcription-polymerase chain reaction analysis. Moreover, maize, millet, wheat, sorghum and rice plants were experimentally infected by PalMV via rub inoculation. Consequently, we proposed that PalMV could be a potentially dangerous virus threating a wide range of cereal crops.

Climate change significantly affects the environmental and socioeconomic conditions in northwest China. Here we evaluate the ability of five general circulation models (GCMs) from 6th phase of the Coupled Model Inter-comparison Project (CMIP6) to reproduce regional temperature and precipitation over northwest China from 1961 to 2014, and project the future temperature and precipitation during 2021 to 2100 under SSPs-RCPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5). The results show that the CMIP6 models can simulate temperature better than precipitation. Projections show that the annual mean temperature will further increase under different SSPs-RCPs scenarios in the 21st century. Future climate changes in the near-term (2021–2040), mid-term (2041–2060) and long-term (2081–2100) are analyzed relative to the reference period (1995–2014). In the long term, warming will be significantly higher than the near and mid-terms. In the long term, annual mean temperature will increase by 1.4°C, 1.9°C, 3.3°C, 5.5°C, 2.7°C, 3.8°C and 6.0°C under SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5, respectively. Spatially, warming in the Junggar Basin will be higher than those in the Tarim Basin. Seasonally, the maximum warming zone will be in the mountainous areas of Tarim Basin during spring and autumn, in the southern basin during winter, and in the east during summer. Precipitation shows an increasing trend under different SSPs-RCPs in the 21st century. In the long term, increase in precipitation will be significantly higher than in the near and mid-terms. Increase in annual precipitation in the long term will be 4.1% under SSP1-1.9, 13.9% under SSP1-2.6, 28.4% under SSP2-4.5, 35.2% under SSP3-7.0, 6.9% under SSP4-3.4, 8.9% under SSP4-6.0, and 27.3% under SSP5-8.5 relative to the reference period of 1995–2014. Spatially, precipitation increase will be higher in the south than the north, especially higher in mountainous regions than the basin under SSP2-4.5, SSP3-7.0, and SSP5-8.5. Seasonally, highest increase can be expected for winter, followed by spring, with significant increase in mountainous regions of southern Tarim Basin. Summer precipitation will reduce in Tian Shan and basins but will significantly increase in the northern margin of the Kunlun Mountain.

Climate change has substantial impacts on regional hydrology in the major river basins. To figure out such latent hydrological impacts of changing climate, more reliable hydrological simulations are imperative. In this study, we evaluated the impacts of climate change on hydrological regime in the Upper Yangtze River Basin based on four downscaled and bias-corrected Global Climate Model outputs from Coupled Model Intercomparison Project Phase 5 under four Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) driving three hydrological models. Two model evaluation approaches were applied: simple and comprehensive. The comprehensive approach was used to evaluate models in the historical period, optimizing objective function at four gauges, and hydrological models were weighted for impact assessment based on their performance. In such a way, projected streamflow time series are obtained under different emission scenarios. Results show that the annual average discharge is projected to increase by 4.1–10.5% under the RCP scenarios at the end of twenty-first century relative to the reference period (1970–1999). Moreover, the high flow is projected to increase and the low flow to decrease indicating a higher probability of flood and drought occurrence in the basin. The severity of floods and droughts may increase. In comparison with the simple one-site model evaluation approach, the comprehensive method reveals that the anticipated extreme flow events would be less severe, and annual mean discharge slightly lower. The projected results imply that application of the comprehensive model evaluation approach could narrow the simulated spreads of projections significantly, and might provide more credible results.

The photoelectrochemical (PEC) water splitting determines by the light absorption and charge extraction/injection. Here, we dispersedly modified the core-shell structured Ni@Niy Fe1-y (OH)2 on Si photoanodes and in-situ electrochemically converted it to Ni@Niy Fe1-y OOH to form a Si/SiOx /Ni@Niy Fe1-y OOH assembly, exhibiting the adjustable band bending and catalytic ability in water oxidation depending closely on the composition of Niy Fe1-y OOH. Combining with the island-like dispersed distribution to maximize the light absorption and the Ni@Niy Fe1-y shell as a high work function and a catalytic layer to simultaneously enlarge charge extraction and injection, the Si/SiOx /Ni@Ni0.7 Fe0.3 OOH assembly achieved an onset potential of 1.0 VRHE , a saturated current density of 35.4 mA cm-2 and a more than 50 h stability in an electrolyte with pH 9 under AM1.5G simulated sunlight irradiation. Our findings suggested that regulating the charge energetics at Si-electrolyte interface by discontinuously modifying a composition-adjustable core-shell structure is a potential route to develop highly efficient PEC devices.

In the warming climate, flood risk is likely to increase over much of the globe. We present projections of changes of flood losses in China for a range of global warming scenarios, from 1.5° to 4.0°C above the preindustrial temperature, with a 0.5°C step. Projections of flood losses in China are based on river runoff simulations by a distributed hydrological model driven by multiple downscaled general circulation models, the national GDP projected at shared socioeconomic pathways, and the “intensity–loss rate” function. When interpreting changes caused by the combined effect of economic and climatic conditions, flood losses in China are projected to soar in the future, particularly in lowland regions subject to rapid economic growth. Under global warming of 1.5° and 4.0°C, in an average year, flood losses are projected to be, respectively, 4 and 17 times that at present. Pursuing the international climate policy target of limiting global warming is projected to reduce exposure to floods in China. In this way, flood losses in China can be reduced by tens of billions of U.S. dollars (on average, US$67 billion and up to 0.04% of GDP) for each 0.5°C that warming is reduced. Our study improves understanding of the impact of climatic and nonclimatic changes on flood risk. Our scientific contribution is the first study to quantify flood impacts across China under different development pathways (shared socioeconomic pathways) for a broad range of global warming levels.

The countries throughout the Belt and Road region account for more than 60% of the world’s population and half of the global economy. Future changes in this area will have significant influences on the global economic growth, industrial structure and resource allocation. In this study, the proportion of the urban population to the total population and the gross domestic product were used to represent the levels of urbanization and economic development, respectively. The population, urbanization and economic levels of the Belt and Road countries for 2020–2050 were projected under the framework of the IPCC’s shared socioeconomic pathways (SSPs), and the following conclusions are drawn. (1) The population, urbanization and economic levels in the Belt and Road region will likely increase under all five pathways. The population will increase by 2%–8%/10a during 2020–2050 and reach 5.0–6.0 billion in 2050. Meanwhile, the urbanization rate will increase by 1.4%–7.5%/10a and reach 49%–75%. The GDP will increase by 17%–34%/10a and reach 134–243 trillion USD. (2) Large differences will appear under different scenarios. The SSP1 and SSP5 pathways demonstrate relatively high urbanization and economic levels, but the population size is comparatively smaller; SSP3 shows the opposite trend. Meanwhile, the economy develops slowly under SSP4, but it has a relatively high urbanization level, while SSP2 exhibits an intermediate trend. (3) In 2050, the population will increase relative to 2016 in most countries, and population size in the fastest growing country in Central Asia and the Middle East countries will be more than double. Urbanization will develop rapidly in South Asia, West Asia and Central Asia, and will increase by more than 150% in the fastest growing countries. The economy will grow fastest in South Asia, Southeast Asia and West Asia, and increase by more than 10 times in some counties with rapid economic development.

Aridity index reflects the exchanges of energy and water between the land surface and the atmosphere, and its variation can be used to forecast drought and flood patterns, which makes it of great significance for agricultural production. The ratio of potential evapotranspiration and precipitation is applied to analyse the spatial and temporal distributions of the aridity index in the Belt and Road region under the 1.5°C and 2.0°C global warming scenarios on the basis of outputs from four downscaled global climate models. The results show that: (1) Under the 1.5°C warming scenario, the area-averaged aridity index will be similar to that in 1986–2005 (around 1.58), but the changes vary spatially. The aridity index will increase by more than 5% in Central-Eastern Europe, north of West Asia, the monsoon region of East Asia and northwest of Southeast Asia, while it is projected to decrease obviously in the southeast of West Asia. Regarding the seasonal scale, spring and winter will be more arid in South Asia, and the monsoon region of East Asia will be slightly drier in summer compared with the reference period. While, West Asia will be wetter in all seasons, except winter. (2) Relative to 1986–2005, both areal averaged annual potential evapotranspiration and precipitation are projected to increase, and the spatial variation of aridity index will become more obvious as well at the 2.0°C warming level. Although the aridity index over the entire region will be maintained at approximately 1.57 as that in 1.5°C, the index in Central- Eastern Europe, north of West Asia and Central Asia will grow rapidly at a rate of more than 20%, while that in West Siberia, northwest of China, the southern part of South Asia and West Asia will show a declining trend. At the seasonal scale, the increase of the aridity index in Central-Eastern Europe, Central Asia, West Asia, South Asia and the northern part of Siberia in winter will be obvious, and the monsoon region in East Asia will be drier in both summer and autumn. (3) Under the scenario of an additional 0.5°C increase in global temperature from 1.5°C to 2.0°C, the aridity index will increase significantly in Central Asia and north of West Asia but decrease in Southeast Asia and Central Siberia. Seasonally, the aridity index in the Belt and Road region will slightly increase in all other seasons except spring. Central Asia will become drier annually at a rate of more than 20%. The aridity index in South Asia will increase in spring and winter, and that in East Asia will increase in autumn and winter. (4) To changes of the aridity index, the attribution of precipitation and potential evapotranspiration will vary regionally. Precipitation will be the major influencing factor over southern West Asia, southern South Asia, Central-Eastern Siberia, the non-monsoon region of East Asia and the border between West Asia and Central Asia, while potential evapotranspiration will exert greater effects over Central-Eastern Europe, West Siberia, Central Asia and the monsoon region of East Asia.

Two types of tonoplast proton pumps, H+ -pyrophosphatase (V-PPase) and the H+ -ATPase (V-ATPase), establish the proton gradient that powers molecular traffic across the tonoplast thereby facilitating turgor regulation and nutrient homeostasis. However, how proton pumps regulate development remains unclear. In this study, we investigated the function of two types of proton pumps in Arabidopsis embryo development and pattern formation. While disruption of either V-PPase or V-ATPase had no obvious effect on plant embryo development, knocking out both resulted in severe defects in embryo pattern formation from the early stage. While the first division in wild-type zygote was asymmetrical, a nearly symmetrical division occurred in the mutant, followed by abnormal pattern formation at all stages of embryo development. The embryonic defects were accompanied by dramatic differences in vacuole morphology and distribution, as well as disturbed localisation of PIN1. The development of mutant cotyledons and root, and the auxin response of mutant seedlings supported the hypothesis that mutants lacking tonoplast proton pumps were defective in auxin transport and distribution. Taking together, we proposed that two tonoplast proton pumps are required for vacuole morphology and PIN1 localisation, thereby controlling vacuole and auxin-related developmental processes in Arabidopsis embryos and seedlings.

China is one of the countries where landslides caused the most fatalities in the last decades. The threat that landslide disasters pose to people might even be greater in the future, due to climate change and the increasing urbanization of mountainous areas. A reliable national-scale rainfall induced landslide susceptibility model is therefore of great relevance in order to identify regions more and less prone to landsliding as well as to develop suitable risk mitigating strategies. However, relying on imperfect landslide data is inevitable when modelling landslide susceptibility for such a large research area. The purpose of this study is to investigate the influence of incomplete landslide data on national scale statistical landslide susceptibility modeling for China. In this context, it is aimed to explore the benefit of mixed effects modelling to counterbalance associated bias propagations. Six influencing factors including lithology, slope, soil moisture index, mean annual precipitation, land use and geological environment regions were selected based on an initial exploratory data analysis. Three sets of influencing variables were designed to represent different solutions to deal with spatially incomplete landslide information: Set 1 (disregards the presence of incomplete landslide information), Set 2 (excludes factors related to the incompleteness of landslide data), Set 3 (accounts for factors related to the incompleteness via random effects). The variable sets were then introduced in a generalized additive model (GAM: Set 1 and Set 2) and a generalized additive mixed effect model (GAMM: Set 3) to establish three national-scale statistical landslide susceptibility models: models 1, 2 and 3. The models were evaluated using the area under the receiver operating characteristics curve (AUROC) given by spatially explicit and non-spatial cross-validation. The spatial prediction pattern produced by the models were also investigated. The results show that the landslide inventory incompleteness had a substantial impact on the outcomes of the statistical landslide susceptibility models. The cross-validation results provided evidence that the three established models performed well to predict model-independent landslide information with median AUROCs ranging from 0.8 to 0.9. However, although Model 1 reached the highest AUROCs within non-spatial cross-validation (median of 0.9), it was not associated with the most plausible representation of landslide susceptibility. The Model 1 modelling results were inconsistent with geomorphological process knowledge and reflected a large extent the underlying data bias. The Model 2 susceptibility maps provided a less biased picture of landslide susceptibility. However, a lower predicted likelihood of landslide occurrence still existed in areas known to be underrepresented in terms of landslide data (e.g., the Kuenlun Mountains in the northern Tibetan Plateau). The non-linear mixed-effects model (Model 3) reduced the impact of these biases best by introducing bias-describing variables as random effects. Among the three models, Model 3 was selected as the best national-scale susceptibility model for China as it produced the most plausible portray of rainfall induced landslide susceptibility and the highest spatially explicit predictive performance (median AUROC of spatial cross validation 0.84) compared to the other two models (median AUROCs of 0.81 and 0.79, respectively). We conclude that ignoring landslide inventory-based incompleteness can entail misleading modelling results and that the application of non-linear mixed-effect models can reduce the propagation of such biases into the final results for very large areas.

Vacuoles are organelles in plant cells that play pivotal roles in growth and developmental regulation. The main functions of vacuoles include maintaining cell acidity and turgor pressure, regulating the storage and transport of substances, controlling the transport and localization of key proteins through the endocytic and lysosomal-vacuolar transport pathways, and responding to biotic and abiotic stresses. Further, proteins localized either in the tonoplast (vacuolar membrane) or inside the vacuole lumen are critical for fruit quality. In this review, we summarize and discuss some of the emerging functions and regulatory mechanisms associated with plant vacuoles, including vacuole biogenesis, vacuole functions in plant growth and development, fruit quality, and plant-microbe interaction, as well as some innovative research technology that has driven advances in the field. Together, the functions of plant vacuoles are important for plant growth and fruit quality. The investigation of vacuole functions in plants is of great scientific significance and has potential applications in agriculture.

Blood is deposited in fish muscle during storage, and this deposition accelerates the deterioration of flesh quality. We have examined the effect of blood deposition on the degradation of collagen fibrils and fibers in the ordinary muscle of yellowtail (Seriola quinqueradiata). In this study we compared changes in collagen fibrils and fibers in the upper sides and undersides of yellowtails killed by two different methods (spinal cord destruction with blood removal and suffocation in air without blood removal [SA]). Tests of breaking strength showed that ordinary muscle from the underside of fish in the SA group (SA-under)had a slightly low value than the other groups. Histological observations showed thinner collagen fibers and looser structures in the SA-under groups than in the other groups during storage. In addition, blood-derived gelatinolytic activities were higher in muscle from the the underside of the SA group than in other groups. These results indicate that blood contains gelatinolytic enzymes and that when blood is deposited to the underside from the upper side of fish, these enzymes may participate in accelerating the degradation of collagen fibers during storage.

Summary Sugarcane mosaic virus (SCMV) is a pathogen of worldwide importance that causes dwarf mosaic disease on maize (Zea mays). Until now, few maize genes/proteins have been shown to be involved in resistance to SCMV. In this study, we characterized the role of maize phenylalanine ammonia‐lyases (ZmPALs) in accumulation of the defence signal salicylic acid (SA) and in resistance to virus infection. SCMV infection significantly increased SA accumulation and expression of SA‐responsive pathogenesis‐related protein genes (PRs). Interestingly, exogenous SA treatment decreased SCMV accumulation and enhanced resistance. Both reverse transcription‐coupled quantitative PCR and RNA‐Seq data confirmed that expression levels of at least four ZmPAL genes were significantly up‐regulated upon SCMV infection. Knockdown of ZmPAL expression led to enhanced SCMV infection symptom severity and virus multiplication, and simultaneously resulted in decreased SA accumulation and PR gene expression. Intriguingly, application of exogenous SA to SCMV‐infected ZmPAL‐silenced maize plants decreased SCMV accumulation, showing that ZmPALs are required for SA‐mediated resistance to SCMV infection. In addition, lignin measurements and metabolomic analysis showed that ZmPALs are also involved in SCMV‐induced lignin accumulation and synthesis of other secondary metabolites via the phenylpropanoid pathway. In summary, our results indicate that ZmPALs are required for SA accumulation in maize and are involved in resistance to virus infection by limiting virus accumulation and moderating symptom severity.

Despite massive flood protection efforts in China, undertaken since the ancient times, disastrous floods continue to plague the country. In this paper, we discuss changes in flood hazard and flood risk in China. First, we review published results (including our own works) on change detection in observed records of intense precipitation, high river flow and flood damage in China. We provide information on essential features of extreme floods in last decades – floods on large rivers, urban floods, and flash floods. Next, we review available projections for the future (including our own results), related to intense precipitation, high river flow and flood damage in China. We try to interpret the difference in flood hazard projections obtained in various publications. Since the spread of river flood hazard projections is large, projections have to be interpreted with caution, because of the impact on decisions related to climate change adaptation, flood risk reduction, and water resources management. We review flood risk reduction strategies in China, focusing on the present situation and division of responsibilities. China has embarked upon an ambitious and vigorous task to improve flood preparedness, by both structural (“hard”) defences, such as: dikes, dams and flood control reservoirs, and diversions, as well as non-structural (“soft”) measures: spatial planning and zoning; watershed management (source control), flood forecasting and warning systems; and awareness raising. The strategy of flood mitigation includes flood retention and urban water management to alleviate the burden of flash and urban flooding.

Evapotranspiration (ET) is an important process of water and energy exchanges between land and atmosphere. In this study, a processed-based GLEAM (global land-surface evaporation: the Amsterdam methodology) satellite assimilation product has been validated in the Yangtze River valley on the observations of flux and the water balance method. The changes of total ET and its components, well as the associated dynamics, have been analyzed for the period of 1980–2014. The total ET shows significant increasing trends especially in the middle and lower reaches of the Yangtze River valley, which is mostly due to the increase of transpiration. The spatial and temporal dynamics of total ET are analyzed with respect to temperature, precipitation, and solar radiation. The spatial pattern of total ET in the Yangtze River valley is found to be jointly determined by temperature and precipitation. As for the temporal dynamics, precipitation plays the dominant role in total ET in the source regions of the valley. While in the most regions, solar radiation is suggested to be a main controller, in the positive manner, of total ET. This may provide an in-depth understanding of ET changes in the warming climate, and form a basis for water resource management in the Yangtze River valley.

A novel ferrocene-based monolith with a network structure was fabricated via in situ free radical polymerization using vinyl ferrocene as the co-monomer within a stainless-steel column (50 × 4.6 mm i.d.) for the separation of proteins from complex bio-samples, taking merit of the specific absorption of ferrocene to protein, including human plasma, egg white, and standard proteins. The morphology and pore size distribution indicate that the optimized monolith has a relatively uniform structure with the network. The results showed that 26 fractions were separated from human plasma, and the column efficiency of the aromatic small molecule, naphthalene, was up to 30,560 plates m−1. The homemade monolith showed excellent selectivity for intact proteins, mainly depending on the hydrophobic chromatography mechanism of ferrocene. In addition, the electrostatic interaction and hydrogen-bond interaction were the additional interactions in the chromatographic separation owing to the sandwich structure of ferrocene present in the monolithic column.

Snow depth plays an essential role in the water and energy balance of the land surface. It is of special importance in arid and semi-arid regions of Central Asia. Owing to the limited availability of field observations, the spatial and temporal variations of snow depth are still poorly known. Using the Japanese 55-year (JRA-55) and the ERA-Interim reanalysis snow depth products, we considered four global climate models (GCMs) applied in the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), examining how they represent snow depth in Central Asia during the period 1986–2005 in terms of spatial and temporal characteristics. We also investigated changes of winter (January–March) snow depth in Central Asia, at 1.5 °C and 2 °C global warming levels. Finally, the joint probabilistic behavior of winter temperature and precipitation at 1.5 °C and 2 °C global warming are investigated using the kernel density estimator (KDE). The result shows that the snow depth climatology of Central Asia is generally well simulated in both spatial pattern and temporal (inter-annual and inter-seasonal) pattern. All models approximately simulate the winter maximum and the summer minimum values of snow depth but tend to overestimate the amplitude during October–December. Only the trend in HadGEM2-ES matches fairly well to the JRA-55 reanalysis snow depth. When comparing the projections of spatial distribution of winter snow depth, distinctive spatial pattern is noted at both 1.5 °C and 2 °C global warming levels, when the snow depth is shown to increase in northeastern and to decrease in midwestern regions of Central Asia. According to the joint probability distributions of precipitation and temperature, Central Asia will tend to experience a warmer and wetter winter at both 1.5 °C and 2 °C global warming levels, which can be associated with an increase in snow depth in the northeastern regions.

Soil–water characteristic curves (SWCCs) play a key role in unsaturated soil mechanics. A series of SWCC tests on Yudong silt with different compaction degrees and drying–wetting cycles were conducted using a GCTS pressure plate apparatus. The test results showed that the SWCCs exhibited hysteresis during the drying–wetting cycles and were affected by the compaction degree. The hysteresis area decreased with increasing drying–wetting cycles. The hysteresis area was obviously affected by the first cycle. The second and third cycles had less obvious effects compared with the first one, but their effects could still be seen. The SWCC’s parameters of Van Genuchten model were obtained by using a Lsqacurve fit function. On basis of the relationships among the fitting parameters, compaction degree, and drying–wetting cycles, a practical and novel approach was proposed to predict SWCCs for Yudong silt under different compaction degrees and drying–wetting cycles. The microstructure changes associated with variations in dry density or compaction degree have been photographed by the scanning electron microscopy (SEM). The SEM results show that the increase in dry density or compaction degree would change the macropore and surface roughness of aggregates, which will produce greater interaction among aggregates, and thus increases the air-entry value.

In this paper, uniaxial compression tests and digital image correlation (DIC) are combined to test samples of artificial rocks manufactured with preexisting cracks at different inclinations. The influence of these fractures on the mechanical properties of the rock and the deformation field in the rock were studied by recording and analyzing the forms of fracturing at specimen failure, crack propagation modes, crack initiation angles, and other features. The results show that the rupture modes of the specimens can be divided into two types: splitting and shear slip. The corresponding fracture types are wing fractures and secondary fractures. As the inclination angle of the prefabricated crack is increased, the wing crack propagation angle first decreases and then increases; the propagation angle is smallest when the inclination angle is 30°. The peak stress and the crack initiation stress ratios increases with the increase of the prefabricated fracture inclination angle .As a specimen is failing, the displacement in the specimen is mainly on the left side of the slip surface composed of a prefabricated crack and a wing crack and the lateral strain is mainly concentrated around the slip surface. This time interval (the time between peak stress and first appearance of a crack on the specimen’s surface) and the magnitude of the peak stress display a good positive correlation. DIC technology can be used to monitor this relationship and provide early warning of deformation and failure for a rock mass in a mine or other engineering project.

Pathogens disturb alternative splicing patterns of infected eukaryotic hosts. However, in plants it is unknown if this is incidental to infection or represents a pathogen-induced remodeling of host gene expression needed to support infection. Here, we compared changes in transcription and protein accumulation with changes in transcript splicing patterns in maize (Zea mays) infected with the globally important pathogen sugarcane mosaic virus (SCMV). Our results suggested that changes in alternative splicing play a major role in determining virus-induced proteomic changes. Focusing on maize phytoene synthase1 (ZmPSY1), which encodes the key regulatory enzyme in carotenoid biosynthesis, we found that although SCMV infection decreases total ZmPSY1 transcript accumulation, the proportion of splice variant T001 increases by later infection stages so that ZmPSY1 protein levels are maintained. We determined that ZmPSY1 has two leaf-specific transcripts, T001 and T003, distinguished by differences between the respective 3'-untranslated regions (UTRs). The shorter 3'-UTR of T001 makes it the more efficient mRNA. Nonsense ZmPSY1 mutants or virus-induced silencing of ZmPSY1 expression suppressed SCMV accumulation, attenuated symptoms, and decreased chloroplast damage. Thus, ZmPSY1 acts as a proviral host factor that is required for virus accumulation and pathogenesis. Taken together, our findings reveal that SCMV infection-modulated alternative splicing ensures that ZmPSY1 synthesis is sustained during infection, which supports efficient virus infection.

Let G be a group. Dp(G)=⋂H≤GNG(H′(p)) is defined and, the properties of Dp(G) are investigated. It is proved that Dp(G)=P[A], where P=D(P) is the Sylow p-subgroup and A=N(A) is a Hall p′-subgroup of Dp(G), respectively. Furthermore, it is proved in a group G that (1) Dp(G)=1 if and only if CG(G′(p))=1, (2) Op′(Dp(G))≤Z∞(Op(G)) and (3) if Z(G′(p))=1, then CG(G′(p))=Dp(G).

The projections of mean temperature, precipitation (P), and potential evapotranspiration (PET) reflect the probabilities of long-term changes of hydrologic processes and induced extreme events. In this paper, we investigated the future changes in some pivotal climatic variables (mean temperature, precipitation, and potential evapotranspiration) under 1.5 °C, 2.0 °C, and 3.0 °C specific warming levels (SWLs) across the Indus River Basin of South Asia. The seven global climate models output under seven different emission scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5) from the latest Sixth phase of Coupled Model Intercomparison Project (CMIP6) are used for this purpose. The Penman-Monteith approach is applied to estimate PET, and the water balance equation is for reflecting water surplus/deficit. Results indicate that except for precipitation, the greater increases in temperature and PET are inclined to happen with continued global warming. The highest increase in temperature is accounted for 14.6% (2.4 °C), and the enhanced PET is estimated at 5.2% higher than the reference period (1995-2014) under 3.0 °C SWL. While the precipitation is projected to increase by the highest 4.8% for 2.0 °C warming level. The differences in regional climate for an additional 0.5 °C (2.0-1.5 °C) and 1.0 °C (3.0-2.0 °C) of warming, the temperature is projected to increase by 0.4 °C and 0.9 °C in the entire IRB respectively. The highest increase in mean temperature (5.1%) and PET (2.4%) in the IRB are predicted to intensify for an additional 1.0 °C than that of 0.5 °C of warming, but precipitation is intended to decrease by 0.4%. Spatially, the increase in temperature, precipitation, and PET are dominated towards high elevation in the upper basin (north) under all the SWLs. The increased variability in climatological parameters across IRB depicts an evident occurrence of both wet events (upper basin) as well as dry events (lower basin) with the increase in global average temperature rise. However, these findings provide an insightful basis for water resource management as well as initiating mitigation and adaptation measures in the IRB related to water surplus (floods) and water deficit (droughts).

Plant ovule initiation determines the maximum of ovule number and has a great impact on the seed number per fruit. The detailed processes of ovule initiation have not been accurately described, although two connected processes, gynoecium and ovule development, have been investigated. Here, we report that ovules initiate asynchronously. The first group of ovule primordia grows out, the placenta elongates, the boundaries of existing ovules enlarge and a new group of primordia initiates from the boundaries. The expression pattern of different marker genes during ovule development illustrates that this asynchronicity continues throughout whole ovule development. PIN-FORMED1 polar distribution and auxin response maxima correlate with ovule primordia asynchronous initiation. We have established computational modeling to show how auxin dynamics influence ovule primordia initiation. Brassinosteroid signaling positively regulates ovule number by promoting placentae size and ovule primordia initiation through strengthening auxin response. Transcriptomic analysis demonstrates numerous known regulators of ovule development and hormone signaling, and many new genes are identified that are involved in ovule development. Taken together, our results illustrate that the ovule primordia initiate asynchronously and the hormone signals are involved in the asynchrony., Summary: Ovule primordia initiation, which determines the maximum ovule number and subsequent seed number in Arabidopsis, is asynchronous and is regulated by PIN1 polar distribution and the auxin response.

Large-scale multispectral remote sensing data are often unavailable for some practical applications. Spectral resolution enhancement for large-scale multispectral remote sensing images by incorporating small-scale hyperspectral remote sensing images is an alternative way to generate remote sensing images with both large spatial range and high spectral resolution. This paper proposes an improved spectral resolution enhancement method (ISREM) using spectral matrix and weighting the spectral angle of the transformation matrix. ISREM is tested in a typical area of the Three-River Headwaters region (TRHR) to produce a synthetic hyperspectral image (HSI). Two existing spectral resolution enhancement methods, the color resolution improvement software package (CRISP) and spectral resolution enhancement method (SREM), are adopted to compare with ISREM. To further test the practicality of the synthetic HSIs generated by the ISREM, CRISP and SREM, they are used to estimate the coverage of native plant species (NPS) using support vector machines (SVM) and random forest (RF) regressions. The experimental results are as follows. (1) For the Pearson correlation coefficient between the synthetic HSI and original image, ISREM yielded the largest value of 0.9582, followed by CRISP and SREM with values of 0.9480 and 0.9514. For spectral similarity, the HSI generated by the ISREM was the closest to the original reference HSI in the spectral curve. It also showed the best cumulative performance with the use of the three quality evaluation indexes. (2) The identification accuracies of native plant species were 93.51%, 90.91%, 89.61% and 89.61% using generated HSIs and original multispectral image (MSI) within a threshold of 20%, respectively. Compared with original MSI, the synthetic HSI showed better ability to identify NPS in the study area, which further illustrated the effectiveness of the ISREM. (3) The ISREM can reduce the strict requirement of pure pixels and maintain the quality of synthetic HSI by spectral angle weighting. Hence, the proposed ISREM outperforms the existing CRISP and SREM methods in image spectral resolution enhancement of multispectral remote sensing images.

Constructing matrix product operators (MPO) is at the core of the modern density matrix renormalization group (DMRG) and its time dependent formulation. For DMRG to be conveniently used in different problems described by different Hamiltonians, in this work we propose a new generic algorithm to construct the MPO of an arbitrary operator with a sum-of-products form based on the bipartite graph theory. We show that the method has the following advantages: (i) It is automatic in that only the definition of the operator is required; (ii) It is symbolic thus free of any numerical error; (iii) The complementary operator technique can be fully employed so that the resulting MPO is globally optimal for any given order of degrees of freedom; (iv) The symmetry of the system could be fully employed to reduce the dimension of MPO. To demonstrate the effectiveness of the new algorithm, the MPOs of Hamiltonians ranging from the prototypical spin-boson model and Holstein model to the more complicated ab initio electronic Hamiltonian and the anharmonic vibrational Hamiltonian with sextic force field are constructed. It is found that for the former three cases, our automatic algorithm can reproduce exactly the same MPOs as the optimally hand-crafted ones already known in the literature., 31 pages, 6 figures

Using data from the Integrated Global Radiosonde Archive Version 2 (IGRA2) and the Multi Model Ensemble (MME) of four global climate models (GCMs), named CanESM5, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0, within the framework of phase 6 of the Coupled Model Intercomparison Project (CMIP6), we analyzed the changes in atmospheric total column water vapor (TCWV) over Central Asia in the future (2021&ndash, 2100) under SSP-RCPs scenarios: SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5, relative to baseline period (1986&ndash, 2005). Results showed that the annual mean TCWV from IGRA2 was consistent with the model output from 1979 to 2014 in Central Asia. Besides, the spatial distribution of TCWV in Central Asia during the baseline period was consistent between the models. The regional average value of Central Asia was between 10.8 mm and 12.4 mm, and decreased with elevation. TCWV will increase under different SSP-RCPs from 2021 to 2040, but showed different trends after 2040. It will increase under SSP1-1.9 and SSP1-2.6 scenarios from 2021 to 2050, and decrease after that. It will grow from 2021 to 2055 under SSP4-3.4 scenario, and then stay essentially constant. Under SSP2-4.5 and SSP4-6.0 scenarios, TCWV will rise rapidly during 2021&ndash, 2065, but the growth will decline from 2065 to 2100. TCWV will continue to increase under SSP3-7.0 and SSP5-8.5 scenarios, and the largest increase is projected under SSP5-8.5 scenario. Change in near-surface temperature (Ts) matched the change in TCWV, but changes in precipitation and evapotranspiration are not significant during 2021&ndash, 2100. In spite of the large variations in TCWV under different SSP-RCPs, the dominant characteristic in all scenarios shows that a large TCWV increase is demonstrated over areas with small TCWV amounts during the baseline period. On the contrary, increases will be small where the TCWV amounts had been large during the baseline period. The change in TCWV is highly correlated to the increase in Ts in Central Asia. Under SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, the higher the temperature due to higher radiative forcing, the steeper the regression slope between TCWV and Ts change. It is closest to the theoretical value of the Clausius-Clapeyron equation under SSP3-7.0 and SSP5-8.5 scenarios, but not presented under other scenarios. Spatially, steeper regression slopes during 2021&ndash, 2100 have been found around the Caspian Sea in the southwest and in the high-elevation areas in the southeast of Central Asia, which is likely related to the abundant local water supply for evaporation.

Seed weight and number ultimately determine seed yield. Arabidopsis seed number comprised of silique number and seed number per silique (SNS). Comparing seed development and weight, determinants of seed number remain largely uncharacterized. In this study, taking advantage of 107 available Arabidopsis accessions, genome-wide association analysis (GWAS) was employed to identify the candidate genes regulating SNS. GWAS-based genotype and phenotype association analysis identified 38 most significant SNPs marker sites that were mapped to specific chromosomal positions and allowed us to screen for dozens of candidate genes. One of them (PIN3) was selected for functional validation based on gene expression analysis. It is a positive regulator of Arabidopsis SNS. Although silique length of PIN3 loss of function mutant was not significantly changed, its SNS and seed density (SD) were significantly reduced as compared with the wild type. Notably, PIN3 overexpression lines driven by a placenta-specific promoter STK exhibited significantly shorter siliques, slightly reduced SNS, but significant increased SD compared with wild type, suggesting that PIN3 positively regulates SD through inducing ovule primordia initiation regardless of the placenta size. Ovule initiation determines the maximal possibility of SNS, and new genes and mechanism regulating SNS through modulating ovule initiation is worth further investigated.

We present a novel methodology through casting the dynamical density matrix renormalization group (DDMRG) into the matrix product state (MPS) formulation to calculate the spectroscopy at finite temperature for molecular aggregates. The frequency domain algorithm can avoid the time evolution accumulation of error and is naturally suitable for parallelization, in addition to facile graphic processing unit (GPU) acceleration. The high accuracy is demonstrated by simulating the optical spectra of vibronic model systems ranging from an exactly solvable dimer model to a more complex real-world perylene bisimide (PBI) J-aggregate. The relationship between the 0-0 emission strength and the exciton thermal coherent length is discussed for linearly stacked aggregates. The computing performance largely boosted by GPU demonstrates that DDMRG emerges as a promising method to study dynamical properties for complex systems.

The application of groundwater relief, i.e., dewatering, ascending wells, drilled upward from the mining tunnel into the overlying aquifer, is common in underground mining engineering. In this study, the seepage characteristics of single ascending partially and fully penetrating relief wells are investigated using a series of laboratory sand-tank experiments and numerical simulations. The seepage characteristics of ascending wells dewatering an overlying aquifer are different from those of conventional pumping wells descending from the ground surface into the underlying aquifer, because of the pronounced influence of the seepage face boundary condition along the seepage boundary of the ascending dewatering well. The seepage face of the ascending well is formed as the well casing remains open and water is discharged under the action of gravity through the well casing. The results of laboratory sand-tank experiments and modeling show that when the degree of penetration of an ascending relief well does not exceed a critical value, the effect of the seepage face cannot be ignored. In particular, the seepage flux increases as the degree of penetration increases following an exponential function, and the relationship between the seepage flux and the well radius can be described using a power law function. The results of numerical simulations are used to develop a series of type curves to evaluate the effects of the critical degree of penetration for different well radii and different aquifer water levels. Modified versions of the Dupuit and Dupuit&ndash, Thiem formulae for a single ascending partially well for the degree of penetration less than the critical one for the unconfined, confined, and confined-unconfined aquifers are developed.

Symmetric solid state supercapacitors attract increasing attention. We report one kind of high performance symmetric solid state supercapacitor composed with RuxNi1-xCo2O4 electrode. Ruthenium (Ru) element is doped into nickel cobaltite (NiCo2O4), and the material is grown on conductive nickel foam directly to act as electrode. The synthesis involves two procedure: one hydrothermal procedure to fabricate metal oxide precursor, and another annealing procedure to transform precursor into RuxNi1-xCo2O4. Chemical composition, crystal structure, morphology and specific superficial area are characterized through various techniques. Doping of ruthenium improve the electrochemical performance of electrode in a large extent. RuxNi1-xCo2O4(x = 0.1) electrodes deliver lower electric resistance than NiCo2O4, superior specific capacitance (1526.8 F g-1 at current density of 1 A g−1 in 2.0 M KOH) to NiCo2O4 (831.3 F g-1 at 1 A g−1), and better stability (94.3% retention after 3000 cycles at 10A g−1) than NiCo2O4 (91.9% retention). We assemble symmetric solid state supercapacitors, which deliver an outstanding energy density (48.5 Wh kg−1 at a power density of 2000 W kg−1 and 8.44 Wh kg−1 at 15000 W kg−1). These superior merits suggest their wide potential application in industrial area.

Tropical cyclones caused significant national economic losses in China in recent decades. For alleviating these hydro-meteorological disasters, the spatiotemporal distributions of losses per economic sector and the associated rainfall and wind patterns of such influential tropical cyclones (ITCs) were estimated for China. Based on multiple reference databases and socio-economic data, ITCs losses for major economic sectors have been deduced. The obtained information plays an important role in the projection of sector losses of future ITCs affecting China. The total economic losses have been split into five major sector loss categories, comprising agriculture, industry, construction, transport, and business & others. About 37% of the total loss occurred in the industrial sector, occupying the largest proportion. High values were primarily distributed in the urban agglomerations of the Pearl River and Yangtze River deltas and along the mainland coast of the Taiwan Strait, with over 1 billion CNY per year. Significant upward trends are found in all of sectors except in agriculture, which shows a decreasing tendency for the period of 1984–2014. The years with the highest losses occurred in the mid-1990s, mid-2000s, and early 2010s, consistently affecting all sectors in all regions along the mainland coast. The southern part of China was most frequently affected by ITCs, with increasing trends in sector losses for most areas. The relationships between wind speed, rainfall and sector losses can be presented in the form of an exponential function. The results show that rainfall is more positively correlated with ITCs losses than wind speed. Here, the industry sector shows the largest correlation coefficient and highest growth rate, whereas the construction sector shows the lowest. In future, research should pay more attention on impacts of heavy rainfall triggered by ITCs in China.

Significance We project drought losses in China under global warming of 1.5 °C and 2.0 °C. To assess future drought losses, we project the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration patterns. With increasing drought intensity and areal coverage across China, drought losses will increase considerably. The estimated losses in a sustainable development pathway at 1.5 °C warming will be 10 times higher than in the reference period 1986–2005 and three times higher than in 2006–2015. Yet, climate change mitigation, limiting the temperature increase to 1.5 °C, can considerably reduce the annual drought losses in China, compared with 2.0 °C warming., We project drought losses in China under global temperature increase of 1.5 °C and 2.0 °C, based on the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI), a cluster analysis method, and “intensity-loss rate” function. In contrast to earlier studies, to project the drought losses, we predict the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration pattern for the 1.5 °C and 2.0 °C global warming above the preindustrial at 2020–2039 and 2040–2059, respectively. With increasing drought intensity and areal coverage across China, drought losses will soar. The estimated loss in a sustainable development pathway at the 1.5 °C warming level increases 10-fold in comparison with the reference period 1986–2005 and nearly threefold relative to the interval 2006–2015. However, limiting the temperature increase to 1.5 °C can reduce the annual drought losses in China by several tens of billions of US dollars, compared with the 2.0 °C warming.

We used daily maximum temperature data (1986–2100) from the COSMO-CLM (COnsortium for Small-scale MOdeling in CLimate Mode) regional climate model and the population statistics for China in 2010 to determine the frequency, intensity, coverage, and population exposure of extreme maximum temperature events (EMTEs) with the intensity–area–duration method. Between 1986 and 2005 (reference period), the frequency, intensity, and coverage of EMTEs are 1330–1680 times yr–1, 31.4–33.3°C, and 1.76–3.88 million km2, respectively. The center of the most severe EMTEs is located in central China and 179.5–392.8 million people are exposed to EMTEs annually. Relative to 1986–2005, the frequency, intensity, and coverage of EMTEs increase by 1.13–6.84, 0.32–1.50, and 15.98%–30.68%, respectively, under 1.5°C warming; under 2.0°C warming, the increases are 1.73–12.48, 0.64–2.76, and 31.96%–50.00%, respectively. It is possible that both the intensity and coverage of future EMTEs could exceed the most severe EMTEs currently observed. Two new centers of EMTEs are projected to develop under 1.5°C warming, one in North China and the other in Southwest China. Under 2.0°C warming, a fourth EMTE center is projected to develop in Northwest China. Under 1.5 and 2.0°C warming, population exposure is projected to increase by 23.2%–39.2% and 26.6%–48%, respectively. From a regional perspective, population exposure is expected to increase most rapidly in Southwest China. A greater proportion of the population in North, Northeast, and Northwest China will be exposed to EMTEs under 2.0°C warming. The results show that a warming world will lead to increases in the intensity, frequency, and coverage of EMTEs. Warming of 2.0°C will lead to both more severe EMTEs and the exposure of more people to EMTEs. Given the probability of the increased occurrence of more severe EMTEs than in the past, it is vitally important to China that the global temperature increase is limited within 1.5°C.

In this study, the complementary relationship between actual evapotranspiration (ETa) and potential evapotranspiration (ETp) was verified in the Tarim River basin (TRB) in northwest China. The advection–aridity (AA) model that is based on the complementary relationship (CR) was used to calculate ETa. Spatial and temporal trends in the estimated annual ETa and the factors that influenced ETa were investigated. The multiyear average ETa in the TRB for the period from 1961 to 2014 was 178.5 mm. There was an overall significant increasing trend (at a rate of 10.6 mm decade−1) in ETa from 1961 to 2014; ETa increased at a rate of 22.9 mm decade−1 from 1961 to 1996 and decreased at a rate of 33.9 mm decade−1 from 1996 to 2014. Seasonally, ETa was strongest in summer, followed by spring and autumn. The spatial distributions of the annual and seasonal ETa were mostly consistent, with higher ETa values in the northeast, northwest, and southwest of the TRB, and lower ETa values in the mostly desert lands in the central and southeastern areas. While the energy budget (indicated by net radiation Rn) had little influence on ETa over time, the advection budget (indicated by the drying power of the air Ea) played an important role, explainable by Bouchet’s complementary relationship. In the Aksu River basin (ARB), ETa has increased because of an increase in the surface water supply (SWS). The change in ETa between 1996 and 1998 may have been caused by changes in the SWS and the advection budget during the same time period.

Purpose The purpose of this paper is to examine the impacts of future climate change and the corresponding adaptation activities on grain production and its regional distribution in China. Design/methodology/approach This paper applied the Chinese Agricultural Policy Analysis model, in combination with the findings from agronomic literature with highly detailed agricultural census data, to conduct equilibrium analysis under alternative impact (seasonal drought and climate warming) scenarios and adaptation scenarios (promoting water-saving irrigation, introducing new varieties, and the integrated) associated with climate change. Findings Simulation results indicate that climate change-induced seasonal drought and the resulting yield reduction will incur substantial losses to China’s grain production (by ~8 percent at a national scale). The application of water saving techniques can be an effective solution to seasonal drought. Introducing new varieties will increase the combination of promoting water-saving irrigation and new variety adoption will increase combination of promoting water-saving irrigation and new variety adoption constitute an effective approach to offsetting the negative effects of climate change on grain production. Research limitations/implications Simulation results indicate that climate change-induced seasonal drought and the resulting sown area reduction will incur substantial losses to China’s grain production by approximately 8 percent, despite farmers’ adaptation activities of switching from water use-intensive crops to drought-tolerant crops to mitigate this negative effect. The application of water saving techniques is an effective solution to seasonal drought; it can lead to a nationwide increase in the sown area by 3.48 percent and in the grain production by 4.15 percent. Introducing new varieties will increase grain outputs and change the spatial distribution of crop production across the country. The combination of promoting water-saving irrigation and new variety adoption will increase the national grain production by 19.6 percent, and thus constitute an effective approach to offsetting the negative effects of climate change on grain production. Originality/value Results from this study provide practical implications formulate strategies in response to climate change. Central government should reinforce the policies such as new varieties promotion and improve the subsidy method to guide the introduction of new varieties.

Understanding the patterns of dryness/wetness in the warming context is important for stakeholders to formulate adaptation strategies to minimize the impacts of floods and droughts. Spatial and temporal characteristics of regional temperature, precipitation, potential evapotranspiration (PET) and dryness/wetness variation were investigated for the period from 2015 to 2100 under SSPs-RCPs in Northwest China. Results show that annual mean temperature, precipitation and PET are projected to increase during 2015–2100, with increases higher in the long-term (2081–2100) than the near-term (2021–2040) and mid-term (2041–2060). Increase rate under SSP5–8.5 and SSP3–7.0 will significantly higher than other scenarios. Relative to the reference period (1995–2014), annual SPEI12 is projected to show a decreasing trend during 2015–2100. Trend will decrease highest under SSP5–8.5 scenario whereas the lowest under SSP1–1.9 and SSP1–2.6 scenarios. The state of drought in Northwest China is near normal during the reference period, drought will significantly escalate and moderate and severe drought will dominate the most of Northwest China with the increase of radiative forcing under SSPs-RCPs during 2015–2100. SSP5–8.5 will have the largest drought area than other scenarios. Observation shows Northwest China characterized a warmer and humid trend during 1961–2014, while GCMs projected that Northwest China will experience significant dryness trend during 2015–2100 under SSPs-RCPs, and SSP3–7.0, SSP4–3.4, SSP4–6.0 and SSP5–8.5 scenarios will be much drier than SSP1–1.9, SSP1–2.6 and SSP2–4.5 scenarios.

Drought has a substantial socioeconomic impact under the changing climate. The estimation of population exposure to drought could be the pivotal signal to predict future water scarcity in the climate hotspot of South Asia. This study examines the changing population exposure to drought across South Asia using 20 climate model ensembles from the latest CMIP6 and demographic data under shared socioeconomic pathways (SSPs). Underpinning the latest version of the IPCC 6th Assessment Report (AR6), this paper focuses on the 2021-2040 (near-term), 2041-2060 (mid-term), and 2081-2100 (long-term) periods to project population exposure changes relative to the reference period (1995-2014) under four SSP-RCP scenarios. Drought events are detected by adopting the standardized precipitation evapotranspiration index (SPEI) and run theory method. Model validation suggests that CMIP6-GCM performs well in projecting climate variables and capturing drought events. The results show that the projected increases in frequent drought events and affected areal coverage are stronger during the early part of the century and weaker at the end under all scenario combinations. In relative terms, the projected increase in the number of people exposed to drought is dominant (>1.5-fold) in the near-term and mid-term periods but decreases in the long-term period. Compared to the reference period, the leading increase in population exposure (2.3-fold) is projected under the newly designed gap scenario (SSP3-7.0) in the mid-term period. A surprising decline in the number of exposed populations was estimated to be 18.8% under SSP5-8.5 by the end of the century. The mitigating effect of the predicted heavy precipitation will decrease droughts in the late future. Spatially, increasing exposure will become more pronounced across India and Afghanistan. Furthermore, the population change effect is mainly responsible for the exposure changes in South Asia. However, this study strongly recommends future 'plausible world' regional rivalry pathways (SSP3) scenario-combinations into consideration for policymaking in regard to water management as well as migration planning over South Asia.

The realistic simulation and projection of the Amundsen Sea Low (ASL) are essential for understanding the Antarctic climate and global climate change. Using 14 models that participated in phase 6 of the Coupled Model Intercomparison Project (CMIP6), this study evaluates the climatological characteristics of ASL with comparison to the ERA5 reanalysis and their CMIP5 versions and assesses the future change of ASL under 1.5 °C–4 °C global warming. The climatological spatial distribution of ASL is captured reasonably but with underestimated intensity by CMIP6 multi-model ensemble (MME). Among the CMIP6 models, EC-Earth3 has most accurate representation of ASL according to the pattern correlation and biases. The seasonal variation of the ASL depth and location are found to be reasonably reproduced by the CMIP6 models. CMIP6 MME has higher skills in simulating the seasonal cycle of absolute depth and zonal migration of the ASL center. The relative central pressure of ASL is underestimated in all seasons and there is a 4-degree northward shift bias of the ASL center in austral winter, which were also evident in the CMIP5. The semiannual cycle of ASL absolute depth with two deepest pressure in April and October is also captured by CMIP6 MME. However, the observed peak of pressure between the two months occurs in June, while it delays one month and appears until July in CMIP6 MME. Compared with CMIP5, CMIP6 MME exhibit evident reduced uncertainties and overall improvement in simulating absolute depth and location of the ASL center, which might be attributed to models' capability of representing the location of Southern Hemisphere westerlies, while the biases in relative depth become even large in CMIP6 MME. In response to future warming from 1.5 °C to 4 °C above pre-industrial levels, the absolute depth of ASL will very likely deepen with larger amplitude in all seasons, while the relative depth might enhance only under high-level warmer world in austral autumn to winter. The CMIP6 MME also projects that the ASL will shift poleward constantly in austral summer and migrate southwestward during austral autumn with the rising global mean temperature. Among all the seasons, the most prominent future changes in intensity and location of ASL are found in autumn. The enhancement and poleward movement of ASL could also be identified during the Ross Sea ice advance season under 1.5 °C–4 °C global warming. The results reveal the potential of CMIP6 models in the ASL study and the impact of ASL on Antarctic climate under different global warming levels.

In the discussion of climate impacts, 1.5 and 2 °C have become iconic values. This study examines the impacts of 1.5 and 2 °C global warming on water availability, runoff seasonality, and extreme monthly and daily runoff in two catchments, using the semi-distributed hydrological model Hydrologiska Byrans Vattenbalansavdelning-D, based on a combination of five global climate models (GCMs) and four representative concentration pathways (RCPs). Subsequently, quantitative assessments were made for projection uncertainties from GCMs and RCPs. The two catchments are the Yiluo River catchment (YLC) in northern China and the Beijiang River catchment (BJC) in southern China. The results indicate wetter flood seasons for YLC and warmer mean annual temperatures, drier springs, and more severe floods over long return periods (25 and 50 years) for both catchments. The change magnitude of most indicators is expected to be larger in YLC than in BJC. Mean annual temperatures in both catchments are expected to have smaller changes under the 1.5 °C scenario than under the 2.0 °C scenario. However, the change magnitude of the other hydrological variables is projected to be approximately equivalent for both catchments under both scenarios. Uncertainties of projected impacts from GCMs are generally larger than those from RCP scenarios, for both catchments and warming scenarios, with the exception of mean annual temperature of BJC. These findings indicate that effective measures are required to address increasing annual temperatures, more severe flood events (25- and 50-year return periods), and drier spring seasons in both catchments and wetter flood seasons in YLC.

Changes in maximum and minimum temperature (Tmax and Tmin) are analysed to assess the regional extent of global warming in Xinjiang autonomous region, China, for the period of 1961–2015. Two nonlinear, non-stationary signal-processing methods – the Bernaola-Galvan algorithm and the ensemble empirical mode decomposition method – are applied on daily time series of observations from 53 meteorological stations. Statistically significant abrupt change points are identified in 1996 in both annual Tmax and Tmin time series averaged for the whole province, while another one is identified in 1976 in the annual Tmin time series only. At local scale, most stations experience one abrupt change point in annual Tmax in the 1990s, but two or three change points in annual Tmin, mainly in the 1980s and 1990s. After the abrupt change points, the frequency and probability density of Tmax in summer and Tmin in winter are skewed towards the hotter part of the probability distribution. It is found that the hot temperature extremes in summer occur concurrently with El Nino events. Further results suggest that anomalies in geopotential height at 500 hPa can be associated with the hottest and coldest months. The key regions of the anomalies are over the east of the Ural Mountains and the North Atlantic, while the geopotential height anomalies over Greenland and the east of the Ural Mountains are closely related to the hot and cold spells.

In this paper, the intensity, area and duration of future droughts in China are analyzed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SPI and SPEI are used to evaluate the simulation ability of drought characteristics with the regional climate model COSMO-CLM (CCLM). The projected intensity and duration of future drought events are analyzed for the period 2016–2050 under three different respective concentration pathways (RCPs). The simulated and projected drought events are analyzed by applying the intensity-area-duration method. The results show that CCLM has a robust capability to simulate the average drought characteristics, while some regional disparities are not well captured, mainly the simulation of more drought events of shorter duration in Northwest China. For the future period 2016–2050, more intense dryness conditions are projected for China. An increase in evapotranspiration is found all over China, while a reduction in precipitation is apparent in the southern river basins. The increase in evapotranspiration plays an important role in the changes of future droughts over the northern river basins and southern river basins. Under RCP2.6, drought events of longer duration and with higher frequency are projected for the southwest and southeast of China. Under RCP4.5 and RCP8.5, a continuing tendency to more dry conditions is projected along a dryness band stretching from the southwest to the northeast of China. More frequent drought events of longer duration are projected in the southwestern river basins. For all future droughts, larger extents are projected, especially for events with long-term duration. The projected long-term drought events will occur more often and more severe than during the baseline period, and their central locations will likely shift towards Southeast China. The results of this study can be used to initiate and strengthen drought adaptation measures at regional and local scale, especially in the south of China.

Based on hourly rainfall observational data from 442 stations during 1960–2014, a regional frequency analysis of the annual maxima (AM) sub-daily rainfall series (1-, 2-, 3-, 6-, 12-, and 24-h rainfall, using a moving window approach) for eastern China was conducted. Eastern China was divided into 13 homogeneous regions: Northeast (NE1, NE2), Central (C), Central North (CN1, CN2), Central East (CE1, CE2, CE3), Southeast (SE1, SE2, SE3, SE4), and Southwest (SW). The generalized extreme value performed best for the AM series in regions NE, C, CN2, CE1, CE2, SE2, and SW, and the generalized logistic distribution was appropriate in the other regions. Maximum return levels were in the SE4 region, with value ranges of 80–270 mm (1-h to 24-h rainfall) and 108–390 mm (1-h to 24-h rainfall) for 20- and 100 yr, respectively. Minimum return levels were in the CN1 and NE1 regions, with values of 37–104 mm and 53–140 mm for 20 and 100 yr, respectively. Comparing return levels using the optimal and commonly used Pearson-III distribution, the mean return-level differences in eastern China for 1–24-h rainfall varied from −3–4 mm to −23–11 mm (−10%–10%) for 20-yr events, reaching −6–26 mm (−10%–30%) and −10–133 mm (−10%–90%) for 100-yr events. In view of the large differences in estimated return levels, more attention should be given to frequency analysis of sub-daily rainfall over China, for improved water management and disaster reduction.

Since the 1950s, the population in the arid to hyperarid Tarim River basin has grown rapidly concurrent with an expansion of irrigated agriculture. This threatens the Tarim River basin's natural ecosystems and causes water shortages, even though increased discharges in the headwaters have been observed more recently. These increases have mainly been attributed to receding glaciers and are projected to cease when the glaciers are unable to provide sufficient amounts of meltwater. Under these circumstances water management will face a serious challenge in adapting its strategies to changes in river discharge, which to a greater extent will depend on changes in precipitation. In this paper, we aim to develop accurate seasonal predictions of precipitation to improve water resources management. Possible predictors of precipitation for the Tarim River basin were either downloaded directly or calculated using NCEP/NCAR Reanalysis 1 and NOAA Extended Reconstructed Sea Surface Temperature (SST) V3b data in monthly resolution. To evaluate the significance of the predictors, they were then correlated with the monthly precipitation dataset GPCCv6 extracted for the Tarim River basin for the period 1961 to 2010. Prior to the Spearman rank correlation analyses, the precipitation data were averaged over the subbasins of the Tarim River. The strongest correlations were mainly detected with lead times of four and five months. Finally, an artificial neural network model, namely a multilayer perceptron (MLP), and a multiple linear regression (LR) model were developed each in two different configurations for the Aksu River subbasin, predicting precipitation five months in advance. Overall, the MLP using all predictors shows the best performance. The performance of both models drops only slightly when restricting the model input to the SST of the Black Sea and the Siberian High Intensity (SHI) pointing towards their importance as predictors.

The impacts of climate change on streamflow in the upper Yangtze River basin were studied using four hydrological models driven by bias-corrected climate projections from five General Circulation Models under four Representative Concentration Pathways. The basin hydrological responses to climate forcing in future mid-century (2036–2065) and end-century (2070–2099) periods were assessed via comparison of simulation results in these periods to those in the reference period (1981–2010). An analysis of variance (ANOVA) approach was used to quantify the uncertainty sources associated with the climate inputs and hydrological model structures. Overall, the annual average discharge, seasonal high flow, and daily peak discharge were projected to increase in most cases in the twenty-first century but with considerable variability between models under the conditions of increasing temperature and a small to moderate increase in precipitation. Uncertainties in the projections increase over the time and are associated with hydrological model structures, but climate inputs represent the largest source of uncertainty in the upper Yangtze projections. This study assessed streamflow projections without considering water management practices within the basin.