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Water use efficiency (WUE) is an important link between carbon and water cycles, which is critical for the forests under future global climatic changes. WUENDVI was calculated by accumulated normalized difference vegetation index (NDVI) and actual evapotranspiration (ET) and could reflect the impacts of climatic changes and human activities on WUE. The three forestry regions of China are the northeast, southwest, and southeast areas. Among them, the northeast forest region is a natural forest region with forest stock accounting for more than 1/4 of China, and the southwest mountainous forest region is another natural forest region in China, with forest stock accounting for more than 1/3 of China, while the southeast forest area is mainly plantations. In 2018, the forest areas over three forestry regions of China were around 1,725,988 km2. This paper evaluated the changes in forest WUE and their relationships with climatic change and human activities over three forestry regions of China during 1961–2019. The main findings of this study were summarized as follows: (1) the spatial changes of WUE were gentle in the artificial forest region but fluctuant sharply in the natural forest regions. In the southwest forest region, the WUE increased with elevation, while it showed the opposite trends in the artificial forest region. Overall, the annual mean forest WUE increased in almost all regions of the study areas during 1961-2019; (2) in the northeast and southeast forest regions, the WUE presented a negative relationship with the temperature. In the southwest forest region, the WUE was positively correlated with the temperature and its increase rate slowed down significantly when the temperature increases by more than 1 °C. The WUE was negatively correlated with precipitation in the three regions and was more sensitive to the decrease of precipitation. The sensitivity of WUE to precipitation reduction was highest in the artificial forest region and lowest in the northeast forest region; (3) the forest WUE and WUENDVI were lowest in the artificial forest region but highest in the northeast forest region, while the net increase in forests area during 1980–2018 was largest in the artificial forest region (155,975 km2) but lowest in the northeast forest region (78,766 km2). In general, human activities had the greatest impact on the forest WUE in the northeast forest region. Human activities and climatic change had quite complex and interactive effects on forest WUE. Therefore, more attention should be paid to the joint influences of climate change and human activities on WUE. [ABSTRACT FROM AUTHOR]

Changes in patterns of meteorological parameters, like precipitations, temperature, wind, etc., are causing significant increases in various extreme events. And these extreme events, i.e., floods, heatwaves, hurricanes, droughts, etc., lead to a shortage of water resources, crop failures, wildfires, and economic losses. However, Global Circulation Models (GCMs) are considered the most important tools for quantifying climate change. Therefore, we selected 20 different GCMs of precipitation in our research, as the frequency of extreme events, like drought and flood, is highly related to changes in precipitation patterns. However, this research introduced a new weighting scheme — MCFSAWS-Ensemble: Monte Carlo Feature Selection Adaptive Weighting Scheme to Ensemble multiple GCMs, whereas, Monte Carlo Feature Selection (MCFS) is one of the most popular algorithms for discovering important variables. However, the proposed weighting scheme (MCFSAWS-Ensemble) is mainly based on two sources. Initially, it evaluates the prior performance of each GCM model to define their relative importance using MCFS. Then, it computes value by value difference between the observed and simulated model. In addition, the application of this paper is based on the monthly time series data of precipitation in the Tibet Plateau region of China. In addition, we used twenty GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to analyze the implications of the MCFSAWS-Ensemble. Further, we compared the performance of the MCFSAWS-Ensemble scheme with Simple Model Averaging (SMA) through Mean Average Error (MAE) and correlation statistics. The results of this research indicate that the proposed weighting scheme (MCFSAWS-Ensemble) is more accurate than the SMA approach. Consequently, we recommend the use of advanced machine learning algorithms such as MCFS for making accurate multi-model ensembles. [ABSTRACT FROM AUTHOR]

Global climate change is expected to have a major impact on the hydrological cycle. Understanding potential changes in future extreme precipitation is important to the planning of industrial and agricultural water use, flood control, and ecological environment protection. In this paper, we study the statistical distribution of extreme precipitation based on historical observation and various global climate models (GCMs), and predict the expected change and the associated uncertainty. The empirical frequency, generalized extreme value (GEV) distribution, and L-moment estimator algorithms are used to establish the statistical distribution relationships and the multi-model ensemble predictions are established by the Bayesian model averaging (BMA) method. This ensemble forecast takes advantage of multi-model synthesis, which is an effective measure to reduce the uncertainty of model selection in extreme precipitation forecasting. We have analyzed the relationships among extreme precipitation, return period, and precipitation durations for 6 representative cities in China. More significantly, the approach allows for establishing the uncertainty of extreme precipitation predictions. The empirical frequency from the historical data is all within the 90% confidence interval of the BMA ensemble. For the future predictions, the extreme precipitation intensities of various durations tend to become larger compared to the historic results. The extreme precipitation under the RCP8.5 scenario is greater than that under the RCP2.6 scenario. The developed approach not only effectively gives the extreme precipitation predictions, but also can be used to any other extreme hydrological events in future climate. [ABSTRACT FROM AUTHOR]

Analyses of the variation characteristics for aridity index (AI) can further enhance the understanding of climate change and have effect on hydrology and agriculture. In this paper, based on the data of 283 standard meteorological stations, the temporal-spatial variations and the influences of climate factors on AI were investigated and the relationship between AI and two climate indices (the Arctic Oscillation (AO); El Nino-Southern Oscillation (ENSO)) were also assessed in northern China (NC) during the period from 1961 to 2012. The results revealed that the annual mean AI decreased at the rate of −0.031 per decade in the past 52 years and the trend was statistically significant at the 0.01 level. The Mann-Kendall (M-K) test presented that the percentages of stations with positive trends and negative trends for AI were 10 and 81.9 % (22.6 % statistically significant), respectively. Spatially, in the western part of 100° E, the extremely dry area declined and the climate tended to become wet obviously. In the eastern part of 100° E, dry area moved toward the east and the south, which resulted in the enhancement of semiarid area and the shrinkage of subhumid area. The contributions of sunshine duration and precipitation to the decline of AI are more than those of other meteorological variables in NC. Moreover, the average temperature has risen significantly and AI decreased in NC, which indicated the existence of 'paradox.' Relationship between climate indices (AO and ENSO) and AI demonstrated that the influence of ENSO on AI overweight the AO on AI in NC. [ABSTRACT FROM AUTHOR]

In this paper, 16 cities representing four major architectural climate zones of China were selected, and the heating and cooling loads of office building during the period of 1961–2017 were simulated by using TRNSYS software. Daily extreme heating and cooling loads were determined by percentile methods, and the climate change impact on extreme loads was analyzed. The results showed that the days of extreme heating load of office building significantly decreased in almost all the selected cities, whereas there were no significant changes in the days of extreme cooling load. The daily extreme heating load was dominantly affected by the temperature (R2 = 0.43–0.79), but the daily extreme cooling load was related to multiple climate factors, including temperature, relative humidity, and solar radiation. Single temperature can only explain 3–37% of the changes of daily extreme cooling load, and the combination of multiple climate factors can explain 58–85%. Importantly, the effect of temperature on extreme cooling load showed decrease from the cold to hot climate zones, but the impacts of relative humidity and solar radiation gradually increased. These results suggest that the maximum design capacity of heating systems can properly decrease, and the design capacity of cooling systems may not largely increase with the climate warming. In addition, the combined effect of multiple climate factors rather than the single temperature, as well as the different responses of extreme cooling energy consumption to climate change in different climate zones, should be considered when making measures for improving operating efficiency of air-conditioning system. [ABSTRACT FROM AUTHOR]

Climate elements are important indicators of climate change in China's main grain-producing areas during the April–September growth season and affect the growth and yield of crops. This paper combines grain concentration and geographical detector to divide the North and South regions of China's main grain production. The linear trend and Morlet wavelet transform methods are used to analyse the characteristics of climate change based on observational climate data from April to September 1981–2015. The results show that the climate in the North region is warm and dry during the growth season, whereas the climate is warm and humid in the South region. The main periods of the change in temperature in the North and South regions are 3 years, and that in precipitation is 5 years, and that in sunshine hours is 3–4 years. Changes in the climate elements in various provinces show complex, varying and regional characteristics of cold-warm and dry-wet cycles. The changes in climate elements are significant and different climatic conditions and regions have various possible impacts on grain production in China during the growth season. For China's agricultural-economy sustainable development and grain security, the study suggests that governments should place more emphasis on climatic element changes during the growth season and invest more money in disaster prevention and mitigation, especially in the main grain-producing areas. [ABSTRACT FROM AUTHOR]

Based on daily mean temperature data from 32 meteorological stations in the study area, this paper discusses the relationship between the changes in the climatic growing season and altitude and the differences in the northern (NSQM) and southern (SSQM) slopes of the Qinling Mountains (QMs) from 1985 to 2015. Our analyses generated three primary results. First, the spatial distribution patterns of the growing season start (GSS), growing season end (GSE), and growing season length (GSL) exhibited an altitudinal gradient and differences between the NSQM and SSQM. The occurrence time of the GSS, GSE, and the GSL of the NSQM was approximately 15 days later, 10 days earlier, and 25 days shorter respectively than that of the SSQM. Second, the three factors exhibited regular changes with an increasing elevation gradient: the GSS, GSE, and GSL were gradually delayed, advanced, and shortened, respectively. In the area below 1800 m above sea level, the GSS, GSE, and GSL of the NSQM was later, earlier, and shorter, respectively, than that of the SSQM; while the changing trends in the three were opposite in the areas above 2700 m; and the three in the areas between 1800 and 2700 m varied little in the NSQM and SSQM. The sensitivities of the GSS, GSE, and GSL of the NSQM and SSQM to elevation also reflected in the trends of inter-annual variability. Third, among the different altitudinal vegetation belts from low-altitude to high-altitude areas, the occurrence time of the GSS and GSE and the duration of the GSL in the alpine meadow areas were all exchanged in the NSQM and SSQM. The GSS, GSE, and GSL of the NSQM were earlier, later, and longer respectively than that of the SSQM. [ABSTRACT FROM AUTHOR]

One of the effects of global climate change is increase in the frequency and severity of drought, which strongly affects the Chinese agricultural production. In order to cope these changes more effectively, it is important to document and analyze the agricultural losses caused by drought. We collected and analyzed conventional meteorological data and agricultural statistics data, in order to outline trends in drought occurrence and decline in agricultural yield. Data were assembled for the period 1960-2010. The study pays particular attention to regional differences between northern and southern China. Our results show the drought-caused agricultural loss rates (DCALR) in China have increased by approximately 0.5% per decade in the past 50 years. The study area in this paper is for the whole of the People's Republic of China, minus the Qinghai-Tibetan Plateau; when we analyzed regional differences, we found that losses increased by approximately 0.6% per decade in northern China, close to twice the increase in southern China. Moreover, drought risks and agricultural losses are rising faster in northern China. Our results also indicate that the agriculture in northern China is more sensitive to changes in precipitation, whereas the agriculture in southern China is more sensitive to temperature changes. [ABSTRACT FROM AUTHOR]

The parameterization of physical processes is one of the critical elements to properly simulate the regional climate over eastern China. It is essential to conduct detailed analyses on the effect of physical parameterization schemes on regional climate simulation, to provide more reliable regional climate change information. In this paper, we evaluate the 25-year (1983-2007) summer monsoon climate characteristics of precipitation and surface air temperature by using the regional spectral model (RSM) with different physical schemes. The ensemble results using the reliability ensemble averaging (REA) method are also assessed. The result shows that the RSM model has the capacity to reproduce the spatial patterns, the variations, and the temporal tendency of surface air temperature and precipitation over eastern China. And it tends to predict better climatology characteristics over the Yangtze River basin and the South China. The impact of different physical schemes on RSM simulations is also investigated. Generally, the CLD3 cloud water prediction scheme tends to produce larger precipitation because of its overestimation of the low-level moisture. The systematic biases derived from the KF2 cumulus scheme are larger than those from the RAS scheme. The scale-selective bias correction (SSBC) method improves the simulation of the temporal and spatial characteristics of surface air temperature and precipitation and advances the circulation simulation capacity. The REA ensemble results show significant improvement in simulating temperature and precipitation distribution, which have much higher correlation coefficient and lower root mean square error. The REA result of selected experiments is better than that of nonselected experiments, indicating the necessity of choosing better ensemble samples for ensemble. [ABSTRACT FROM AUTHOR]

Warming of the climate system is unequivocal, and the change of climate variables will eventually have a great impact on vegetation cover and agricultural practices, especially in the arid area Xinjiang in China, whose agriculture and ecosystems are heavily vulnerable to climate change. In this paper, normalized difference vegetation index (NDVI) was used to study the vegetation growth and its response to climate change in Xinjiang. Firstly, two NDVI datasets (Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging Spectroradiometer (MODIS)) were merged through a pixel-wise regression analysis to obtain a long time series of NDVI data, and then, relationships between yearly NDVI and yearly climate variables, and monthly NDVI and monthly climate variables were extensively investigated for grassland and cropland in northern and southern Xinjiang, respectively. Results show the following: (1) there was an increasing trend in NDVI for both grassland and cropland in both northern and southern Xinjiang over the past decades and trends were significant except that for grassland in northern Xinjiang; (2) precipitation and evaporation were more important than temperature for grassland in northern Xinjiang, while precipitation and temperature were more important than evaporation for grassland in southern Xinjiang and cropland in both northern and southern Xinjiang; (3) NDVI was highly correlated with accumulated monthly precipitation instead of monthly precipitation, and there was a lagged effect of precipitation, temperature, and evaporation on NDVI change. However, lagged effects were only significant in specific months. The results could be helpful to agricultural practices; e.g., based on lagged effect of precipitation, irrigation in July is very important for crop growth. [ABSTRACT FROM AUTHOR]

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration ( PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1-16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by −10.2 to −2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed. [ABSTRACT FROM AUTHOR]

Extreme weather exerts a huge impact on human beings and it is of vital importance to study the regular pattern of meteorological and hydrological factors. In this paper, a selection of seven extreme indices is used to analyze the trend of precipitation extremes of 18 meteorological stations located in Zhejiang Province, east China using the Mann-Kendall test. Then the precipitation trends in the plum season (from May to July) and typhoon season (from August to October) are studied separately. The results show that the precipitation trend varies from east to west. There is a positive trend in the east and a negative one in the west. The largest part of Zhejiang Province shows a positive trend in heavy precipitation and the most significant upward trend is detected in Dinghai with 3.4 mm/year for precipitation on very wet days. Although the upward trend of extreme precipitation is not prevailing, the range of increase in specific areas is apparent, like Dinghai with 1.3 mm/year. Precipitation intensity exhibits an upward trend in most areas and a typical upward trend can be found in Dachendao, Tianmushan, and Yuhuan with 0.04, 0.02, and 0.05 mm/year respectively. Precipitation intensity in both plum and typhoon seasons has increased too, especially for the coastal stations. [ABSTRACT FROM AUTHOR]

This paper focuses on the primary causes of changes in potential evapotranspiration (ETo) in order to comprehensively understand climate change and its impact on hydrological cycle. Based on modified Penman-Monteith model, ETo is simulated, and its changes are attributed by analyzing the sensitivity of ETo to influence meteorological variables together with their changes for 595 meteorological stations across China during the period 1961–2008. Results show the decreasing trends of ETo in the whole country and in most climate regions except the cold temperate humid region in Northeast China. For China as a whole, the decreasing trend of ETo is primarily attributed to wind speed due to its significant decreasing trend and high sensitivity. Relative humidity is the highest sensitive variable; however, it has negligible effect on ETo for its insignificant trend. The positive contribution of temperature rising to ETo is offset by the effect of wind speed and sunshine duration. In addition, primary causes to ETo changes are varied for differing climate regions. ETo changes are attributed to decreased wind speed in most climate regions mainly distributed in West China and North China, to declined sunshine duration in subtropical and tropical humid regions in South China, and to increased maximum temperature in the cold temperate humid region. [ABSTRACT FROM AUTHOR]

Based on homogenized land surface air temperature (SAT) data (derived from China Homogenized Historical Temperature (CHHT) 1.0), the warming trends over Northeast China are detected in this paper, and the impacts of urban heat islands (UHIs) evaluated. Results show that this region is undergoing rapid warming: the trends of annual mean minimum temperature (MMIT), mean temperature (MT), and mean maximum temperature (MMAT) are 0.40 C decade−1, 0.32 C decade−1, and 0.23 C decade−1, respectively. Regional average temperature series built with these networks including and excluding “typical urban stations” are compared for the periods of 1954–2005. Although impacts of UHIs on the absolute annual and seasonal temperature are identified, UHI contributions to the long-term trends are less than 10% of the regional total warming during the period. The large warming trend during the period is due to a regime shift in around 1988, which accounted for about 51% of the regional warming. [ABSTRACT FROM AUTHOR]

Snow is an important component of a climate system, and very sensitive to climate change, and it can be an indicator of checking and monitoring global change. This paper is concerned with identifying changes in the time series of snowfall in Qinghai, located in western China. We used the Mann-Kendall test to evaluate the annual and monthly trends in snowfall in Qinghai during the periods 1957/58–2006/07 based on data obtained from 25 stations. Significant positive and negative trends at the 90, 95, and 99 percent confidence levels were detected for numerous stations. In order to understand the regional pattern of snowfall in Qinghai, the detected trends are spatially interpolated using the inverse distance weighted interpolation method in a GIS environment. The results indicate that in January snowfall in the most area of Qinghai shows a significant upward trend, especially in the Delingha and Nomhon area in northern Qaidam Basin, as well as southeastern Qinghai, however, there is no significant downward trend area. The trend analysis indicates that annual snowfall has a significant upward trend in Delingha and Nomhon area in northern Qaidam Basin, and the downward trends occurred in the Qilian mountain area and Gonghe Basin. This is especially the case for highlighting the spatial structure of snowfall trends. The research results help in further understanding the regional pattern of snowfall in Qinghai and its response to global climatic warming. [ABSTRACT FROM AUTHOR]

Monthly precipitation data of 42 rain stations over the Pearl River basin for 1960–2005 were analyzed to classify anomalously wet and dry conditions by using the standardized precipitation index (SPI) and aridity index ( I) for the rainy season (April–September) and winter (December–February). Trends of the number of wet and dry months decided by SPI were detected with Mann-Kendall technique. Furthermore, we also investigated possible causes behind wet and dry variations by analyzing NCAR/NCEP reanalysis dataset. The results indicate that: (1) the Pearl River basin tends to be dryer in the rainy season and comes to be wetter in winter. However, different wetting and drying properties can be identified across the basin: west parts of the basin tend to be dryer; and southeast parts tend to be wetter; (2) the Pearl River basin is dominated by dry tendency in the rainy season and is further substantiated by aridity index ( I) variations; and (3) water vapor flux, moisture content changes in the rainy season and winter indicate different influences of moisture changes on wet and dry conditions across the Pearl River basin. Increasing moisture content gives rise to an increasing number of wet months in winter. However, no fixed relationships can be observed between moisture content changes and number of wet months in the rainy season, indicating that more than one factor can influence the dry or wet conditions of the study region. The results of this paper will be helpful for basin-scale water resource management under the changing climate. [ABSTRACT FROM AUTHOR]

The Inner Mongolia grassland of China is representative of semi-arid grasslands in temperate zones. Studying land surface processes in this region will improve the understanding of regional climate formation and the feedback with global climate change. Satellite remote sensing provides an excellent opportunity to study land-atmosphere interactions at the regional scale. It is necessary to develop feasible and reasonable remote sensing-based methods to map surface energy fluxes for a specific study area. In this paper, previously published algorithms and empirical formulae were tested with Landsat 7 ETM+ data to derive the regional distributions of land surface reflectance, surface temperature, NDVI and land surface energy fluxes (net radiation, soil heat flux, sensible heat flux and latent heat flux) over the upper Xilin River watershed in Inner Mongolia, China. A new land use/land cover classification was developed and applied for regionalization analysis. Validation of remote sensing derived surface reflectance, surface temperature, net radiation and sensible heat flux with field measurements shows differences of about 13, 4, 1, and 28%, respectively. This study provides valuable guidance for further investigation of the whole watershed. [ABSTRACT FROM AUTHOR]

There is an urgent need to determine the risk of the reduction in distributional ranges of alpine graminoid species induced by rapid warming, as they are adapted to the cold conditions of mountain areas. Here, taking 79 Kobresia species as a case, with the fuzzy set-based classification method, Monte Carlo scheme, and scenarios data of climate shifts, I identified the uncertainty of climate-induced range shifts of Kobresia species, and recognized which species would be in high danger of shrinking their ranges to critical sizes. Deterministic and stochastic scenarios of climate change would result in their output for the majority of the species but were consistent for at least two species. In deterministic scenarios, compared with the baseline conditions, the richness of 79 species was higher in several sites in Northeast and West China and lower in certain sites in Southwest China. In addition, the richness of studied species that over 80% of their existing ranges reduced was about 2–5, while 75–78 species would occupy over 80% of their total ranges. In stochastic scenarios, with a probability above 0.6, around 10–11% of species would have more than 80% of their existing ranges pruned, and approximately 12–19% of species would lose more than 80% of their total ranges, around 40% of the 79 species would be at risk of extinction due to climate change. The risks were mainly caused by changes in the temperature index. These species will need adaptation measures to cope with future climatic conditions. [ABSTRACT FROM AUTHOR]

Arid, semi-arid, and semi-humid regions (drylands) with fragile ecological balance have undergone dramatic climate change in past decades, and how the desertification will change under a continuous warming background still remain uncertain. In this study, the bias-corrected Community Earth System Model outputs from Coupled Model Intercomparison Project phase 5 were dynamically downscaled using the Weather Research and Forecasting (WRF) model, based on which the evolution trend of desertification over northern China (NC) in the past (1972–2000) and the near future period (2021–2050) under the RCP8.5 scenario were analyzed using the dune mobility index, and the impacts of climate change on the intensification or reversal of desertification over NC in the near future were explored. The results show that WRF downscaling can reproduce the desertification changes over NC in the past. The regions with a high risk of desertification are mainly located on the border of the desert and gobi. Under a rapidly warming climate in the near future, desertification will likely reverse in most regions of NC, especially for regions north of 40°N over NC. Potential evapotranspiration changes will exacerbate desertification, while precipitation changes will promote rehabilitation, and wind speed changes show obvious local impacts on desertification. The results in this study imply that, with rising temperatures in the future, the extent of desertification will not always continue, desertification will likely reverse at the front and margin of deserts and gobi, and responses of desertification to climate change have significant spatial differences. [ABSTRACT FROM AUTHOR]

Hydrological drought is a highly complex and extreme natural disaster, which has increased in deficit, areal extent, and frequency with the penetration of climate change impact. For better anticipating hydrological droughts, it is crucial to evaluate hydrological drought and its teleconnections with large-scale climate indices (LSCI) effectively. This study estimated the dynamics and patterns of hydrological drought in the near-real river networks by virtue of the standardized runoff index (SRI) based on VIC and large-scale routing model in the Xijiang River basin, and revealed their teleconnections with the climate indices. Results show that model simulation can reasonably reveal the hydrological drought evolutions in near-real river networks and effectively expose the drought downward spread along main channels. The drought spread distances in Hongshuihe and Yujiang Rivers are farther under the comprehensive influence of climate, topography, and watershed shape. Hydrological drought evolutions in the upper reaches are mainly manifested as three patterns, including S12 (simultaneous significant changes in drought intensity, concentration degree, and frequency), S7(simultaneous significant changes in drought intensity and frequency), and S1(single significant change in drought intensity). These drought dynamic patterns are majority affected by climate variation patterns M1 (warm and cold AMO), M3 (cold PDO), and M7 (warm AMO/AO). For decision-makers, this work is beneficial for understanding and anticipating hydrological droughts in the river networks, and further selecting management strategies for water resources. Highlights: The quantitative results of model simulation are reliable for drought evaluation. Drought concentration period delays and drought risk increases significantly. Dynamic evolutions of drought mainly manifest as three combinations patterns. Upstream drought is mainly affected by AMO, PDO, and AMO/AO. [ABSTRACT FROM AUTHOR]

Global surface temperature is increasing significantly under climate change with increasingly uneven distribution of precipitation, which has been making an important impact on the sustainable development of the dryland agriculture in semi-arid regions. The Inner Mongolia Autonomous Region (IMAR) has the largest area ratio of semi-arid regions in China, and spring wheat is one of its major grain crops, and the negative impacts of climate change pose a serious threat to its production. In order to reduce this threat, we assessed the impact thresholds and risks posed by the main climatic factors to spring-wheat production, and put forward quantitative adaptive countermeasures. The results showed that, from 1961 to 2012, the appropriate impact thresholds of average temperature, precipitation, fertilization level, and water supply level were 15.6 °C, 333 mm, 319.5 kg/ha, and 743.7 mm, respectively. Compared with the average values in 1996–2012, the maximum fertilization level and water supply level could be increased by 162.2 kg/ha and 406.5 mm, respectively, to improve the adaptive yield of spring wheat. The risks of adverse impacts of temperature rise, precipitation decrease, and their combined effect on spring-wheat production were found to be 11.1%, 9.3%, and 10.3%, respectively. The whole IMAR showed a high risk of adverse impacts of temperature rise and the combined action of temperature rise and precipitation decrease on spring-wheat production. In particular, the spring-wheat production in the northeastern, eastern, and central areas were found to be at the highest risk to the impacts of climate change. Based on the determined appropriate thresholds of fertilization level and water supply level, it was determined that in the northeastern area, the maximum fertilization level and water supply level could be increased by 229.9 kg/ha and 441.4 mm, respectively, to increase the adaptive yield of spring wheat. In the eastern area, the two factors could be increased by 142.2 kg/ha and 464.3 mm, respectively. In the central area, they could be increased by 242.2 kg/ha and 513.7 mm, respectively. In the southwestern area, they could be increased by 41.4 kg/ha and 201.7 mm, respectively. [ABSTRACT FROM AUTHOR]

In China, grape is one of the top five fruit crops for both bearing acreage and production. Recently, national grape production has been stalling because of an increase in drought events. In order to combat the adverse effects of drought on grape production, it is imperative to understand the historical drought trend and frequency during the growing season. In this study, we focused on agricultural drought during the four growth periods of grape: bud break-flowering, flowering-veraison, veraison-berry maturation, and berry maturation-leaf fall. Based on the weather data from 429 meteorological stations, we computed the Crop Water Deficit Index (CWDI) in the five main grape-growing regions of China: Northeast China, North China, Northwest China, Southwest China, and Southeast China. Then, we evaluated the CWDI-based drought distribution and trend in the study regions, as well as the frequency of different degrees of drought. The results showed that exceptional drought was occurring frequently in Xinjiang Uyghur Autonomous Region, northern Gansu province, and northern Ningxia Hui Autonomous Region. Among the four study growth periods of grape, exceptional drought was the most expansive during bud break-flowering. What's more, exceptional drought coverage during bud break-flowering in the study regions was increasing from 1981 to 2016. Analysis of butterfly structure showed that the occurrence of drought was continuous and persistent in northern China. Our study results could serve as guideposts to highlight Chinese grape production industry's vulnerability to agricultural drought against the background of climate change. [ABSTRACT FROM AUTHOR]

The Meiyu/Baiu/Changma is an important and unique persistent rainfall over East Asian during the northward progress of the East Asian summer monsoon (EASM) from late spring to middle summer. In this study, changes of Meiyu system under global warming are examined by MIROC_Hires coupled model. The results reveal that the Meiyu system becomes weaker in the warmer future: the large precipitation center shifts to northern China; ratio of Meiyu rainfall to total summer precipitation ratio decreases. For the three-dimensional atmospheric circulation, the configuration of upper and lower jets benefits the heavy rainfall located over the northern China, associated with abundant water vapor transporting to northern China. The heterogeneous warming over land and sea may be a possible reason for the changes of Meiyu system. Larger thermal contrast is indicated between the Asian continent and the western Pacific during the Meiyu period, which may result in the enhanced southerly with abundant water vapor arriving at northern China. Therefore, rainfall over Meiyu region may be suspended. [ABSTRACT FROM AUTHOR]

Agricultural water safety is foreseen to have more turmoil in the future, and this concern will be driven by agricultural production growth, population growth, and socioeconomic developments accompanied by climatic changes. Our study aimed to develop an index for regional water scarcity evaluation and quantify the present and future agricultural water stress in China. Changes in crop evapotranspiration (ETc) during the baseline period (1990–2015) and future periods (2020–2039, 2040–2059, 2060–2079, and 2080–2099) under two different scenarios (RCPs, 4.5 and 8.5) were introduced. Moreover, we evaluated the precipitation cultivation dependability index (PCDI) and agricultural water stress index (AWSI) in China from 1990 to 2099. A significant increase in ETc between the baseline and future projections will be more than 20 Gm3 in the south and southeastern provinces. The months from April to August shared a proportion that exceeded 70% of the yearly ETc. The PCDI during the autumn season was highest (full) and will increase significantly during all future scenarios, except during 2080–2099 of RCP8.5, which will record a non-significant reduction in the PCDI compared with the baseline. All provinces will have a significant increase in the PDCI under future projections except in 2080–2099 (RCP8.5) compared with the baseline. The AWSI over China recorded medium to high water stress (0.84) for the baseline, but it will increase significantly to very high-water stress (> 1) in all future scenarios. These results suggest that China should guarantee the sustainable use of agricultural water resources by reducing its crop water footprint and minimizing the influence of drought under a warming climate, e.g., via forest plantations. [ABSTRACT FROM AUTHOR]

Exploring the characteristic of the extreme climatic events, especially future projection is considerably important in assessing the impacts of climatic change on hydrology and water resources system. We investigate the future patterns of climate extremes (2001-2099) in the Haihe River Basin (HRB) derived from Coupled General Circulation Model (CGCM) multimodel ensemble projections using the Bayesian Model Average (BMA) approach, under a range of emission scenarios. The extremes are depicted by three extreme temperature indices (i.e., frost days (FD), growing season length (GSL), and T >90th percentile (TN90)) and five extreme precipitation indices (i.e., consecutive dry days (CDD), precipitation ≥10 mm (R10), maximum 5-day precipitation total (R5D), precipitation >95th percentile (R95T), and simple daily intensity index (SDII)). The results indicate frost days display negative trend over the HRB in the 21st century, particularly in the southern basin. Moreover, a greater season length and more frequent warm nights are also projected in the basin. The decreasing CDD, together with the increasing R10, R5D, R95T, and SDII in the 21st century indicate that the extreme precipitation events will increase in their intensity and frequency in the basin. Meanwhile, the changes of all eight extremes climate indices under A2 and A1B scenarios are more pronounced than in B1. The results will be of practical significance in mitigation of the detrimental effects of variations of climatic extremes and improve the regional strategy for water resource and eco-environment management, particularly for the HRB characterized by the severe water shortages and fragile ecological environment. [ABSTRACT FROM AUTHOR]

Normandy is the world's leading producer of flax fiber (Linum usitatissimu L.), which is mainly exported to China for textile manufacturing. Flax is a plant that is cultivated in spring and that grows in an oceanic climate with regular watering and limited thermal excesses. This article aims at projecting the impact of climate change on the phenology of this plant when subjected to climatic hazards that may occur during its development. These projections use two regional climate models (ALADIN-Climate and WRF) based on the two scenarios generated by the latest IPPC report—intergovernmental panel on climate change—(RCP 4.5 and RCP 8.5). The rise in temperatures would result in a time-cycle reduction. Consequently, flax would not be exposed to the early summer water shortage. However, thermal conditions could be unfavorable, especially due to the increased frequency of heat days. Flax is also exposed to the risk of lodging during heavy rainfall episodes; however, the results are somehow contrasted between the two climate models used. This research demonstrates the interest of multidisciplinary impact studies so as to anticipate the consequences of climate change on agricultural crops. [ABSTRACT FROM AUTHOR]

It is of great significance to study on the shift of temperature zone boundaries for revealing the climate change pattern and its environmental effects. Based on daily average temperature data from 32 standard meteorological stations in the Qinling Mountains from 1964 to 2015, the growing season start and end (GSS and GSE) of the climatic growing season parameters were calculated based on a temperature threshold of 10 °C, and the growing season length (GSL) was obtained by subtracting GSE from GSS. We have analyzed the spatiotemporal variations of these parameters in the Qinling Mountains and the shift rules of the warm temperate zone and northern subtropics zone boundaries in China over the past 52 years. Our research generated three primary results. First, the spatial distribution and changing trends of the GSS, GSE, and GSL were significantly different before and after abrupt changes in temperature. After the abrupt change, the coverages of the three were all gradually expanding to the higher altitude areas. The change rates of the three were faster, the trends were more significant, and the differences between the north and the south were obvious, especially in the northern slope. Second, the boundaries of both the warm temperate zone and the northern subtropical zone in China showed upward position shifts, and the area coverage changed along the northern and southern slopes of the Qinling Mountains, and the change amplitudes were even greater after the abrupt change in temperature. Third, there was a significant north–south difference in the response of China's temperature zones to climate change. The temperature zone on the northern slope was more sensitive to climate warming. It is worth emphasizing that the shifts of the temperature zones did not change the fact that the Qinling Mountains are the boundary between China's subtropical and the warm temperate zones. The north subtropical zone is still located on the southern slope of the Qinling Mountains, and the northern slope is still in the warm temperate zone. [ABSTRACT FROM AUTHOR]

Extreme climatic events such as drought and high temperatures are frequently occurring under the global climate change scenarios causing severe threats to crop yield. Several studies have used individual events, e.g., meteorological drought (dry event), high temperatures (hot event), or compound dry–hot events as predictors of agricultural drought severity. However, only a few studies considered the situation when at least one dry event or hot event appeared. Moreover, the ability to depict drought phenomena, in terms of duration and severity, with the same drought index for different time scales was often inconsistent. This study adopted the meta-Gaussian model (MG) to predict agricultural drought severity for the crops and vegetation growing seasons (from April to September) from the year 1948 to 2014 in China by using two predictors, namely, standardized dry or hot events index (SDHEI) and joint soil moisture deficit index (JSDI). The SDHEI was built based on monthly precipitation and daily temperature, and the JSDI was calculated by combining 1-, 3-, 6-, 9-, and 12-month standardized soil moisture index (SSI) based on monthly root zone soil moisture. The prediction performance of the MG was assessed by employing the Brier skill score (BSS), Nash–Sutcliffe efficiency coefficient (NSE), and root mean square error (RMSE). The severe agricultural drought in the months of April–September of 2010 in China was used as a case study. A visual comparison of this event indicated that the lead JSDI predictions for 1–3 months showed a resembled behavioral pattern with corresponding historical observations for most of the areas of China; however, it had some disagreements in the spatial extent and severity of the agricultural drought in some of the regions. The MG had a great performance with BSS > 0.4, NSE > 0.6, and RMSE < 0.6 for the 1-month lead prediction of JSDI in most of the study areas; however, it turned to be weaker in some regions for the 3-month lead prediction. Overall, the prediction performance of MG in April–June outperformed the same in July–September under the same lead prediction of JSDI. The outcomes of this study might provide scientific guidance for agricultural drought monitoring, early warning, and drought decision-making in China or other countries. [ABSTRACT FROM AUTHOR]

Runoff and sediment discharge have displayed great reductions due to climate change and enhanced various human activities during recent decades in the Jialing River, China, with significant environmental and social implications. The water balance equation, double mass curve, and linear regression analysis were employed to quantify the contributions of climate change and human activities to runoff and sediment discharge reductions in the Jialing River during 1960–2017. The results indicated that the annual runoff of the Jialing River exhibited a significant decreasing trend of − 2.75 × 108 m3 every year (P < 0.05) but no significant abrupt change occurred, while annual sediment discharge significantly decreased by 0.03 × 108 t every year (P < 0.05) with a significant abrupt change in 1990 (P < 0.05). Climate change led to a great reduction (82.2%) in annual runoff from 1960 to 2017 in the Jialing River, whereas the contribution of climate change to sediment discharge reduction in the human-affected period (1990–2017) was only 4.55% and precipitation inclined to increase sediment discharge in recent years (2010–2017). The reduced sediment discharge in the 1990s was mostly due to the implementation of soil–water conservation programs and the reduction after 2000 was due to the development of reservoirs as well as the implementation of soil–water conservation programs. The results provided references to develop various human activities better and drew great attention to strengthening basin management. [ABSTRACT FROM AUTHOR]

The land use and land cover change (LULCC) presents the large-area features since the 1980s in East Asia, particularly over China, where the largely complicated LULCC has happened for the simultaneous interconversion of croplands, forests, grasslands, and urban lands. In this study, the regional coupled model AVIM-RIEMS2.0 with dynamic vegetation process is employed to examine the impacts of LULCC on regional climate over East Asia. The results show that regional climate and terrestrial surface processes exhibit significantly seasonal and interdecadal signals in East Asia. With the influences of LULCC, forest increased 33.3% and 20.3% from the 1980s to 1990s and from the 1990s to 2000s, respectively. Meanwhile, cropland decreased 17.8% in the 1990s (compared to the 1980s) and 24.8% in the 2000s (compared to the 1990s), respectively. These transitions of land surface processes are roughly coincident with the interdecadal variations in temperature and precipitation, which trigger generally opposite changes in the 1980s as compared to the 1990s, especially over eastern China. The seasonal variability of climatic components is more evident in winter than summer, except for the precipitation. The climate change is also somewhat remarkable under the non-LULCC conditions, combined with the changes in wind fields at the 850 hPa from the simulations during three decades; they together suggest that climate change is also modulated by other controlling factors, such as East Asian monsoon circulations in addition to LULCC conversions. These results highlight the importance of LULCC in regional modeling studies, which would have practical significance in climate mitigation and adaptation over East Asia. [ABSTRACT FROM AUTHOR]

Global warming has accelerated surface water loss around the world. This study investigates in detail the change and attribution of potential evapotranspiration (PET) across China from 1901 to 2100 by the Hargreaves model, based on a 1-km temperature dataset downscaled from the low-spatial-resolution datasets using a Delta downscaling framework. Results showed that (1) relative to 1961–1990, PET increased by 0.62% in the historic period (1901–2017) and 6.43–12.89% for the future period (2018–2100), suggesting considerable future drying for China. Moreover, these increments had strong spatial variations and the largest increases were detected in high-elevation regions; (2) PET over entire China demonstrated a nonsignificant upward trend during the historic period and significant upward trends for the future period. For each period and GCM, significant upward PET trends occupied a much larger percent area than significant downward trends; (3) PET variations during the historic period were most sensitive to mean temperature (TMP), while in the future period it was more sensitive to maximum temperature (TMX), suggesting a change in the primary sensitivity factor due to global warming; (4) minimum temperature (TMN) made the largest contribution (45%) to PET variations during the historic period, while TMX had the largest contribution (36–40%) in the future period. Therefore, the primary contributing factor might transform from TMN to TMX under climate change; and (5) PET variations exhibited strong spatial heterogeneity, detected on fine geographic scales, due to the use of downscaled dataset. Overall, the results present a deep insight for planning coping strategies of global warming in China. [ABSTRACT FROM AUTHOR]

In this study, a stepwise-clustered statistical downscaling model is established to simulate future apparent temperatures based on NCEP reanalysis data and four global climate models (GCMs). AP is a metric used to quantify thermal comfort or discomfort. The model can express nonlinear relationships between variables at large scale and local scale. The model is employed for projecting future apparent temperature changes over the Pearl River Delta (PRD), on the south coast of China, under three representative concentration pathways (RCP) scenarios. The cluster tree generated for the daily apparent temperature is calibrated for the period 1971–1990 and validated for the period 1991–2000. The R2 values obtained for the validation period at eight selected cities for four GCMs (i.e., CanESM2, CNRM-CM5, CSIRO-Mk3-6-0, and IPSL-CM5A-LR) are 0.88, 0.87, 0.86, and 0.87, respectively. The results reflected that apparent temperature is projected to have a constant increment over the PRD in the future period (2035–2095). Moreover, the monthly apparent temperature in April has the largest expected increment in the future period, while the smallest increment is found in January. The results also indicated that the apparent temperature increases faster than the air temperature under the RCP4.5 and the RCP8.5 scenarios in the PRD. The findings illuminate that the expected increase in apparent temperature over the PRD can be mainly explained by increasing air temperatures and decreasing wind speeds. The results can provide decision makers with useful information for urban health risk assessments. [ABSTRACT FROM AUTHOR]

Objective evaluation of the relationships among different types of droughts remains a challenging task due to the combined impacts of climate change and land surface modification caused by human activities. Based on the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) at the 3- and 6-month timescales, this study presents a systematic analysis of the relationships between the severity (S) and duration (D) of meteorological (MD) and hydrological droughts (HD) in the three catchments of the upper Huai River Basin in China. The relation between SPI and SRI is explored by the maximal information coefficient and the mutual entropy. The spatial propagation mechanism of MD is identified by the centroid trajectory, and the response of HD to MD is quantified by the model averaging method. The results indicate a drying (wetting) trend in the upstream (downstream) area, while the centroid trajectory of MD is found in the midstream area, but not associated with the large (or small) S and D simultaneously. There is a strong correlation (determination coefficient > 0.55) between SPI and SRI in all three subareas, particularly at the 6-month timescale. The increasing influences of human activities (e.g., regulation of water conservancy facilities) from upstream to downstream lead to a weaker correlation between SPI and SRI as well as a decreasing threshold of D for MD to trigger HD in downstream. By contrast, the drier climatic conditions are the main reason for the increasing threshold of S for MD to trigger HD from upstream to downstream. [ABSTRACT FROM AUTHOR]

Previous studies revealed that building climatic zoning has largely changed in China due to the influence of climate change. However, the possible impacts of changing building climatic zoning on energy consumption for cooling or heating are not clear. In this study, eight representative cities were selected from changed climate zones, and the heating and cooling energy consumption of office and residential buildings of the representative cities under the conditions of the current and new climate zones was simulated to reveal the effect of the climate zone change on building energy consumption. The results showed that there was no heating or cooling energy consumption with the climates changing from hot summer and cold winter (HSCW) and cold (C) to mild (M). Also, no heating energy consumption occurred with the climate zones changing from HSCM to hot summer and warm winter (HSWW), whereas the cooling energy consumption showed a weak decrease. For the climate zones that shifted from severe cold (SC) to C, decreasing heating energy consumption and increasing cooling energy consumption trends were observed, and the total energy use exhibited a decreasing trend. However, in the climate zones changing from C to HSCW, the heating and cooling energy consumption increased, especially for residential buildings (e.g., the heating energy consumption of Zhengzhou and Baoji increased 78.7% and 77.7%, respectively). This study suggests that new climate zones should be fully considered and the new design standard according to the changes of climate zones should be adopted to improve building energy efficiency. The design of residential buildings in the climate zones changing from C to HSCW may not consider the changes of climate zone. [ABSTRACT FROM AUTHOR]

To combat desertification, an understanding of its current development is necessary, including that of causative factors associated with climate change and increasing human activity. Whereas, there is an ongoing debate surrounding impact factors for change in vegetation and desertification in arid regions. The present study assesses the spatiotemporal characteristics of vegetation change in the Ulan Buh Desert, northwest China. Driving factors for desertification were discussed using the Global Inventory Monitoring and Modeling System Normalized Difference Vegetation Index (GIMMS NDVI) and SPOT Vegetation NDVI datasets, high-resolution satellite images, and meteorological and socioeconomic data in the period 1982–2018. The results show a trend of overall greening, with increasing trends at rates between 0.0008/year and 0.0013/year indicated by the two NDVI datasets and with a corresponding reduction in dune activity. The spatial variations of two NDVI datasets verified the significantly greening trend in the northern and southern areas of the desert. Human activity was observed to have impacted vegetation dynamics. It is predicted that the implementation of ecological projects will contribute to the restoration of vegetation during a warmer, wetter climate trend. However, the reduction of wind strength played a dominant role in vegetation greenness and dune stability in the Ulan Buh Desert. The present study revealed the spatiotemporal characteristics of vegetation variations and the driving factors for desertification in arid regions. [ABSTRACT FROM AUTHOR]

Against the background of global warming, extreme agrometeorological events have become more intense and frequent during the growing season of maize (Zea mays L.). In this study, we focused on the five types of extreme agrometeorological events that greatly affect maize production in Northeast China, including chilling injury, drought, rainstorm, frost, and gale. We averaged the actual timing of phenological events from the study agrometeorological stations and divided the maize growing season into four growth stages: emergence—jointing, jointing—flowering, flowering—kernel milk, and kernel milk—physiological maturity. Based on the historical weather data from 1960 to 2017 in the study region, we derived the values of pertinent indices for the five types of study extreme agrometeorological events during the four selected maize growth stages. The results showed that chilling injury and drought were relatively more frequent during the four growth stages of maize from 1960 to 2017 in the Northeast China. As time goes on during the growing season of maize, the spatial coverage of chilling injury, frost, and gale all showed a decreasing trend. By contrast, the spatial coverage of drought showed an increasing trend during the study growth stages of maize. During growth stages of maize, chilling injury was the main extreme agrometeorological event before the 2000s, while drought became the main extreme agrometeorological event after the 2000s. Identifying the main extreme climate events that could cause yield loss is imperative, and it is important for farmers to acknowledge ongoing changes in these extreme climate events in order to take preventive measures if necessary. [ABSTRACT FROM AUTHOR]

Wheat production in the North China Plain (NCP) is critical to food security in China; however, it is affected by climate change. Understanding the spatiotemporal distribution of climate suitability of wheat in NCP may help to rationally use climatic resources as well as reduce natural disasters. Out of 30 general circulation models in the Coupled Model Intercomparison Project Phase 5, the 5 best GCMs were selected for each meteorological factor to project daily data in 2021–2100 under representative concentration path 4.5 (RCP4.5) and RCP8.5 for 23 national climatic stations in NCP. Based on agricultural climatic suitability theory and the fuzzy mathematics method, the suitability of water, temperature, and solar radiation was analyzed. The results showed that the water suitability increases from 0.30 at present to 0.40 for 2021–2100 under both RCP4.5 and RCP8.5 with the lowest mostly distributed in the northwest. The temperature suitability varies from 0.80 at present to 0.75 for 2021–2100 and generally increases from north to south; however, at stage 2 (from overwintering to greening), it drops from 0.67 to 0.50 under RCP4.5 and 0.20 under RCP8.5 for 2081–2100. The decreases of water suitability at stage 5 (from heading to milking) and temperature suitability at stage 2 show negative effect of climate change to winter wheat. The solar radiation suitability shows an increasing trend under two scenarios in the future. Finally, the integrated climate suitability shows a little increasing trend, indicating climate condition of winter wheat in NCP will be slightly improved. [ABSTRACT FROM AUTHOR]

Quantifying the uncertainty and risk of reducing distribution ranges of the birds in a shifting climate is crucial regarding decision-making on the adaptation of biodiversity to climate warming. By using the representative concentration pathway scenarios of changing climate, fuzzy set classifications, and Monte Carlo techniques, an investigation of the uncertainty and risk of shifting ranges for 114 endemic birds in China from climate change was conducted. In response to non-stochastic changing climate conditions, the abundance of 114 species would increase in some locations of western and northeastern China and would decline in some sites of southeastern, eastern, northern, and central China; approximately 40–60 species would lose less than 20% or 20–40% of their current suitable areas, and about 110 species would exhibit distributions covering more than 80% of their total ranges. For stochastic changing climate scenarios, the number of the birds that lost distinct extents of the suitable ranges decreased with enhancing the likelihood; with a probability of beyond 0.6, the number of the birds that lost less than 20%, 20–40%, 40–60%, 60–80%, and greater than 80% of their present ranges was approximately 13–20, 10–22, 1–8, 1–3, and 5–8, respectively, and the number of the birds that inhabited less than 20%, 20–40%, 40–60%, 60–80%, and over 80% of their all suitable ranges was approximately 7–10, 15–25, 6–11, 1–4, and 26–30, respectively. Approximately 36 species of 114 endemic bird species will be posed extinction risk by climate warming if without any adaptation measures. [ABSTRACT FROM AUTHOR]

There are various types of climate transitional zones on the earth's surface. The East Asian summer monsoon transition zone (EASMTZ) has attracted much attention due to its multiple roles. It is where most of the semi-arid regions locate in China, and semi-arid climate is unstable relative to the arid climate to its north and humid climate to its south. Therefore, EASMTZ is very sensitive to climate changes, and its land-atmosphere interaction (LA-I) is active and crucial. The LA-I is significantly affected by the complex land surface conditions and closely related to the summer monsoon climate dynamics. The LA-I and its response to summer monsoon activities is thus complicated. It includes multi-feedback mechanisms, which involve the land surface thermal-hydrological-ecological couplings, multi-interface exchanges from near surface to the free atmosphere. These feedbacks are sensitive to the summer monsoon activities. Based on a summary of the unique characteristics of EASMTZ and the main research progresses in LA-I in recent years, the issues related to LA-I are discussed in this region. Finally, the key scientific issues faced by the LA-I are proposed, and the future focuses are summarized. This work should help for the future study on the LA-I and its response to summer monsoon activities in the EASMTZ, which should contribute to the understanding of the increasing drought frequency associated with the significant warming trend in this region. [ABSTRACT FROM AUTHOR]

Drought has become one of the most serious meteorological disasters for agricultural production in many areas around the world, and the situation could be worse under the impact of climate change. To facilitate better adaptation planning, this study proposed a drought assessment framework integrating downscaling method, drought index, copula technique, and bivariate frequency analysis, and applied it to investigate the change of the drought characteristics and drought risks from the past to the future in Huang-Huai-Hai River basin (HRB), North China. Drought was firstly defined by standardized precipitation evapotranspiration index (SPEI) based on 1497 observed grid data from 1979 to 2004. Then, we constructed the joint distribution of drought duration and severity based on copulas to detect and quantify the drought risks. To address the effect of climate change, similar calculation process was applied to the future climate data, which was downscaled using delta change method from representative concentration pathway (RCP 8.5) of 12 general circulation models (GCMs). The study results suggested that, under climate change condition, most irrigation districts over HRB would generally experience lower frequency of drought events but with extended duration; some districts would have more serious drought, but majority would experience similar or even lower level of severity. In light of the mean joint occurrence probability, the irrigation district at the south part of Huai River basin would likely experience the highest increase of drought risks in near future (by 0.86%) and distant future (by 0.76%), while most of other districts over HRB would face low risk of serious drought risks. The obtained results offer useful information to agricultural managers or water resources authorities who are interested in the development of effective long-term adaptation strategies for drought management. [ABSTRACT FROM AUTHOR]

It has been widely accepted that the global climate will change, with a 'dry gets drier, wet gets wetter' pattern. Recent studies found that such changes were overestimated. Drought/wetting variations were detected in a semiarid and sub-humid transitional region of China. The aridity index based on precipitation and reference evapotranspiration was applied to estimate drought/wetting variations. The results showed that the climate in the annual mean of the Zhangjiakou region showed a wetting trend from 1960 to 2017. The wetting trend also occurred in January, February, May and the wet season, especially in June, and in September, October, December and the dry season, and the wetting trend was significant. However, the drought trend occurred in March, April, July, August and November. Moreover, the most obvious wetting and drought changes occurred in September and August, respectively. Climate drought/wetting conditions are primarily driven by precipitation. Although increasing temperatures resulted in enhanced evaporation, precipitation increased, which could offset the increase in evaporation. In addition to precipitation and temperature, humidity was an important influencing factor on drought/wetting variation. The impact of humidity on drought/wetting conditions was greater than that of temperature in January, February, July, August and September. The influencing factors of drought/wetting variations are complicated in the Zhangjiakou region and are mainly influenced by the southeast monsoon, southwest monsoon and plateau monsoon in the Tibetan Plateau, westerly circulation and West Pacific subtropical high. [ABSTRACT FROM AUTHOR]

Northeast China is the main crop production region in China, and future climate change will directly impact crop potential yields, so exploring crop potential yields under future climate scenarios in Northeast China is extremely critical for ensuring future food security. Here, this study projected the climate changes using 12 general circulation models (GCMs) under two moderate Representative Concentration Pathway (RCP) scenarios (RCP 4.5 and 6.0) from 2015 to 2050. Then, based on the Global Agro-ecological Zones (GAEZ) model, we explored the effect of climate change on the potential yields of maize and paddy rice in Northeast China during 2015–2050. The annual relative humidity increased almost throughout the Northeast China under two RCPs. The annual precipitation increased more than 400 mm in some west, east, and south areas under RCP 4.5, but decreased slightly in some areas under RCP 6.0. The annual wind speed increased over 2 m/s in the west region. The annual net solar radiation changes varied significantly with latitude, but the changes of annual maximum temperature and minimum temperature were closely related to the terrain. Under RCP 4.5, the average maize potential yield increased by 34.31% under the influence of climate changes from 2015 to 2050. The average rice potential yield increased by 16.82% from 2015 to 2050. Under RCP 6.0, the average maize and rice potential yields increased by 25.65% and 6.34% respectively. The changes of maize potential yields were positively correlated with the changes of precipitation, wind speed, and net solar radiation (the correlation coefficients were > 0.2), and negatively correlated with the changes of relative humidity, minimum and maximum temperature under two RCPs. The changes of rice potential yields were positively correlated with the changes of precipitation (correlation coefficient = 0.15) under RCP 4.5. Under RCP 6.0, it had a slight positive correlation with net solar radiation, relative humidity, and wind speed. [ABSTRACT FROM AUTHOR]

Water scarcity has a destructive impact on the social and economic development around the world. The present study investigated the variations of drought conditions during 1961–2016 in the Zoige Wetland of Southwest China by adapting the Mann–Kendall (MK) analysis, the Theil–Sen slope estimator, continuous wavelet transforms (CWT), and the inverse distance weighting (IDW) algorithm. The partial correlation coefficient (PC) was also used to understand the causes of Standardized Precipitation Evapotranspiration Index (SPEI) characteristics from different climate factors. The results showed that the majority of the wetland had a drying trend with a − 0.142/(10 years) rate of SPEI on annual scale, while a 2–8-year significant period was observed on both annual and seasonal scales. In spring, the wetland presented dryness and had a tendency of mitigation except for the northeastern area. In summer, the wetland mainly presented humidity, but it had a drying trend except for the southern area. In autumn, the overall wetland was humid with an abrupt change towards dryness occurring around 1983 and the whole wetland showed a manifest drying trend. In winter, most areas showed drought while the Jiuzhi County and part of the southern wetland had an alleviating trend of drought. The decrease of annual SPEI was primarily due to the decrease in precipitation, the mean temperature increase, and relative humidity decrease that offset the reversed impact of wind speed decrease and sunshine duration decrease. The change of SPEI on a seasonal scale was the consequence of the significant change in precipitation only in winter. The results of this study would be of use for understanding the characteristics of climate variation and water resources management across the Zoige Wetland in a changing environment. [ABSTRACT FROM AUTHOR]

Drought projection is of critical significance for designing long-term drought adaptation strategies to cope with changing climate. This study presents an application of multi-class models for characterizing future droughts in the Yellow River basin (YRB). Using meteorological observations and simulations of three CMIP5 climatic models as input into VIC hydrologic model, the standardized Palmer drought index-based joint drought index (SPDI-JDI) is calculated to investigate spatiotemporal patterns and possible changes of future drought in the YRB, through an approach of bivariate modeling and analysis. It is concluded that moderate drought will be alleviated with decreased duration and severity, but extreme drought risk is likely to increase for future climate scenarios (2021–2050) relative to baseline period (1961–2000). From the perspective of bivariate analyses, the concurrence probability of drought events with extreme duration and severity might rise in the future, while increasing variability and heterogeneity of duration, severity and bivariate joint/concurrent return period would also increase the stochastic occurrence of extreme drought over time and space. These findings can provide insights into projection of climate change impacts on drought trends for the next 30 years, and help to preparations for strict control of socio-economic water consumption as well as eco-environmental protection and restoration in the YRB. [ABSTRACT FROM AUTHOR]

Based on daily mean temperature data from 32 meteorological stations in the Qinling Mountains (QMs) of China, we analyzed the characteristics and differences of the spatiotemporal changes in the climatic growing season (CGS) in the QMs from 1964 to 2015. Our results are as follows. First, over the past 52 years, the temperature of the QMs significantly increased at a mean rate of 0.22 °C/decade (P < 0.01) in over 98.04% of the area. Significant north–south spatial differences were observed in temperature changes; also, significant differences in the temperature changing trends were observed before and after the abrupt change in temperature. Second, the spatial distributions of the mean growing season start (GSS), end (GSE), and length (GSL) in the QMs varied based on regional differences in latitude and topography. Notably, the GSS, GSE, and GSL were gradually delayed, advanced, and shortened, respectively, as latitude and elevation increased. After the abrupt change in temperature, whether it is in the NSQM (northern slopes of the QMs) or the SSQM (southern slopes of the QMs), the GSS, GSE, and GSL expanded into high-elevation areas. Third, over the past 52 years, the GSS in the QMs exhibited a significant advancing trend of 2.7 days/decade, the GSE was delayed at a rate of 0.66 days/decade, and the GSL displayed a significant extension of 3.36 days/decade. Before the abrupt change in temperature, the GSS, GSE, and GSL exhibited non-significant changing trends; however, the trends in the GSS, GSE, and GSL were more significant after the abrupt change than before. Fourth, the GSS, GSE, and GSL trends in the QMs were significantly different in the NSQM and SSQM regions. After the abrupt change, the GSS, GSE, and GSL trends along the NSQM were more significant than those along the SSQM. [ABSTRACT FROM AUTHOR]

The impacts of climate change on future drought properties in various regions across China are accessed using multiple statistical approaches, based on 20 downscaled global climate models provided by NASA (NEX-GDDP) under Representative Concentration Pathways (RCP) 4.5 and RCP8.5 emission scenarios. Results show that temperature plays a crucial role on the variability of drought conditions in China by comparing the discrepancies between Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI). Unobvious variability of drought extent is projected for SPI, while the drought extent for SPEI is remarkable. Based on SPEI, a considerable aggravation in spatial extent and severity of future drought events are found in the majority of regions, particularly in northwest and northeast China, except for winter over northeast region. The drought extent increases more significantly after late 2070s under RCP8.5 scenario, and the differences of drought extent are not significant between RCP4.5 and RCP8.5 scenarios in the early and mid-twenty-first century. More than 85% of the regions show a decreasing trend for SPEI in spring, summer, and autumn, suggesting drought tendency in most of China, and drought frequency also increases significantly in north and northwest China except for winter. The dramatic aggravation of drought attribution is mainly projected to the increases in potential evapotranspiration (PET) in northwestern and northern regions of China, whereas in northwestern region, the exacerbating drought conditions are expected to the attribution of deficiencies of rainfall. At national scale, PET plays a more dominant role to the future severe and widespread droughts across China in the context of climate change. [ABSTRACT FROM AUTHOR]

Historical temperature records are often partially biased by the urban heat island (UHI) effect. However, the exact magnitude of these biases is an ongoing, controversial scientific question, especially in regions like China where urbanization has greatly increased in recent decades. Previous studies have mainly used statistical information and selected static population targets, or urban areas in a particular year, to classify urban-rural stations and estimate the influence of urbanization on observed warming trends. However, there is a lack of consideration for the dynamic processes of urbanization. The Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) are three major urban agglomerations in China which were selected to investigate the spatiotemporal heterogeneity of urban expansion effects on observed warming trends in this study. Based on remote sensing (RS) data, urban area expansion processes were taken into consideration and the relationship between urban expansion rates and warming trends was investigated using data from 975 meteorological stations throughout China. Although urban areas constitute less than 1% of land in China, more than 90% of the meteorological stations experienced urban land use change and the average urban expansion rate was 0.33%/a. There was also a significant positive relationship between observed warming trends and urban expansion rates. Background warming, without the influence of urbanization and extra warming induced by urbanization processes, was estimated using a linear regression model based on observed warming trends and urban expansion rates. On average, urbanization led to an additional annual warming of 0.034 ± 0.005 °C/10a. This urbanization warming effect was 0.050 ± 0.007 °C/10a for minimum temperatures and 0.008 ± 0.004 °C/10a for maximum temperatures. Moreover, it appeared that urbanization induced greater warming on the minimum temperature during the cold season and maximum temperature during the warm season. [ABSTRACT FROM AUTHOR]

Gridded climatic datasets with fine spatial resolution can potentially be used to depict the climatic characteristics across the complex topography of China. In this study, we collected records of monthly temperature at 1153 stations and precipitation at 1202 stations in China and neighboring countries to construct a monthly climate dataset in China with a 0.025° resolution (~ 2.5 km). The dataset, named LZU0025, was designed by Lanzhou University and used a partial thin plate smoothing method embedded in the ANUSPLIN software. The accuracy of LZU0025 was evaluated based on three aspects: (1) Diagnostic statistics from the surface fitting model during 1951–2011. The results indicate a low mean square root of generalized cross validation (RTGCV) for the monthly air temperature surface (1.06 °C) and monthly precipitation surface (1.97 mm1/2). The method used variable square root transformation for the spline surface fitting to reduce positive skewness in the measured precipitation values and no variable transformation in air temperature case. This indicates that the surface fitting models are accurate. (2) Error statistics of comparisons between interpolated monthly LZU0025 with the withholding of climatic data from 265 stations during 1951–2011. The results show that the predicted values closely tracked the real true values with values of mean absolute error (MAE) of 0.59 °C and 70.5 mm and standard deviation of the mean error (STD) of 1.27 °C and 122.6 mm. In addition, the monthly STDs exhibited a consistent pattern of variation with RTGCV. (3) Comparison with other datasets. This was done in two ways. The first was via comparison of standard deviation, mean, and time trend derived from all datasets to a reference dataset released by the China Meteorological Administration (CMA), using Taylor diagrams. The second was to compare LZU0025 with the station dataset in the Tibetan Plateau. Taylor diagrams show that the standard deviation derived from LZU had a higher correlation with that produced by the CMA (R = 0.76 for air temperature, and R = 0.96 for precipitation) compared to those from other datasets. The standard deviation for the index derived from LZU was more close to that induced from CMA, and the centered normalized root-mean-square difference for this index derived from LZU and CMA was lower. A similar superior performance of LZU was found in the comparison of mean and time trend derived from LZU and those from other datasets. LZU0025 had high correlation with the Coordinated Energy and Water Cycle Observation Project (CEOP)—Asian Monsoon Project (CAMP) Tibet surface meteorology station dataset for air temperature, despite a non-significant correlation for precipitation at a few stations. Based on this comprehensive analysis, we conclude that LZU0025 is a reliable dataset. LZU0025, which has a fine resolution, can be used to identify a greater number of climate types, such as tundra and subpolar continental, along the Himalayan Mountain. We anticipate that LZU0025 can be used for the monitoring of regional climate change and precision agriculture modulation under global climate change. [ABSTRACT FROM AUTHOR]

Global warming has considerably challenged the natural environment and livelihood conditions. Understanding potential future changes in critical climatic variables, such as temperature and precipitation, is important for regional agricultural and water resource management. This study proposes a new approach to the application of the Long Ashton Research Station Weather Generator (LARS-WG) in Coupled Model Intercomparison Project Phase 5 (CMIP5) emission scenarios and aims to test its applicability in cold areas and to evaluate the response of temperature and precipitation, in amount and form, under future warmer climate trends. Three stations in northeastern China are set as case sites, and 50 years of daily weather observations are used for model calibration and validation. Future synthetic time-series of daily precipitation and daily maximum and minimum temperatures is generated by the calibrated LARS-WG based on three Representative Concentration Pathway (RCP) scenarios with various radiative forcing levels of 14 general circulation models (GCMs) outputs for the periods 2041–2060 (2050s) and 2061–2080 (2070s). The results show that the CMIP5 scenarios can be successfully used in a LARS-WG model and that the model performs well in cold weather conditions to repeat the current status of the case sites; the model is able to provide downscaling analysis for future daily weather generation via updating calibrated model parameters based on various GCM outputs. A generally warming and wetting conversion would last into the future for the study sites, but there is great inconsistency among different GCMs. An ensemble approach is adopted with mean values of multi-GCMs to avoid the uncertainty associated with using a single GCM, based on which the changes in the form of precipitation are further estimated. As a result of the decrease in freezing conditions, although annual precipitation will continue to increase in the future, there will be relatively less annual snowfall, which will be primarily focused in deep winter. Such changes in snow cover conditions will potentially disturb the original rules of local overwintering agriculture. In addition, more intense and earlier snowmelt discharge and more rainfall in summer will latently impact the watershed hydrologic process. The influences of climate change are significant, and related projects for agricultural and water resource management should be of great concern in local decision-making. [ABSTRACT FROM AUTHOR]

Studying the shifts of vegetation phenology and the response of vegetation phenology to climate change helps to understand the dynamics of future ecosystems. However, since previous studies mostly focused on temperate ecosystems, much less is known about the biogeographic phenological shifts in sub-tropical regions, which have abundant biodiversity. The Yangtze River Basin (YRB) is located in the subtropical region of China and has abundant natural resources, a large population, and rapid economic development. Studying the variation characteristics of phenology and its responses to recent climate changes in YRB are important for understanding the impact of regional climate on subtropical ecosystems. In this study, we extracted the phenological parameters using Global Inventory Modeling and Mapping Studies (GIMMS) data to investigate the spatial and temporal variations of vegetation phenology across YRB during 1982–2015 and to examine how vegetation phenology responds to climate within different ecological zones. The results revealed that the start of growing season (SOS) was significantly advanced by 0.2 days/year (p < 0.01). However, there has been no significant trend in the end of growing season (EOS) throughout the whole study area for the past 34 years. The spatial pattern of the phenology metrics showed a high spatial heterogeneity: the SOS in the central YRB was earlier than that in other regions; the EOS in the southeast YRB was later than that in any other regions. Meanwhile, the SOS had a higher correlation with temperature than with precipitation. In particular, the spring temperature had a strong impact on the SOS and the effects of winter temperatures cannot be ignored. Although there were no significant correlations between the EOS and precipitation/temperature, it is interesting to note that when examining the interactions between phonological parameters, the EOS was positively correlated with the SOS. Furthermore, the pre-season temperature had a lag effect on the SOS, but no significant lag effect was observed for the EOS in YRB. In all, the present study can enhance our understanding of phenology dynamics and its relationship with climate in YRB and provide a useful reference to put forward a corresponding ecological protection policy. [ABSTRACT FROM AUTHOR]