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As an important part of the Earth's environmental system, sandy soils are particularly sensitive to changes in the climatic environment. As one of the four major desert regions in China, the MuUs desert has transformed from a desert to an oasis after more than half a century of ecological management. In this paper, we analyzed the spatial and temporal patterns of surface albedo, evapotranspiration, and fraction vegetation cover in the MuUs desert based on the Global Land Surface Satellite (GLASS) product with high spatial and temporal resolution and assessed the relationships between their variability and snow cover, air temperature, and precipitation. It is of great significance to understand the effect of desertification control and climate change after the conversion of land surface types in the MuUs region. The results show that the desertification control in the MuUs area has achieved remarkable results since 1982. The fraction vegetation coverage of the MuUs desert showed a significant increasing trend, with an interannual change rate of 1.32% each decade−1. The surface albedo of MuUs desert decreased significantly. Affected by vegetation and snow cover, it was lower in summer and higher in winter. The evapotranspiration showed a significant upward trend, higher in summer and lower in winter, which is significantly correlated with the changes in surface albedo, air temperature, and vegetation. In addition, the local-scale biophysical effects caused by vegetation change have influenced the climate of the MuUs region, manifested as the increase in precipitation and air temperature. In general, with the support of relevant policies and human construction projects, the overall ecological environment in the MuUs desert is developing in a good way. [ABSTRACT FROM AUTHOR]

This paper looks at regional water security in eastern China in the context of global climate change. The response of runoff to climate change in the Qinhuai River Basin, a typical river in eastern China, was quantitatively investigated by using the Soil and Water Assessment Tool (SWAT) model and the ensemble projection of multiple general circulation models (GCMs) under three different shared socioeconomic pathways (SSPs) emission scenarios. The results show that the calibrated SWAT model is applicable to the Qinhuai River Basin and can accurately characterize the runoff process at daily and monthly scales with the Nash–Sutcliffe efficiency coefficients (NSE), correlation coefficients (R), and the Kling–Gupta efficiency (KGE) in calibration and validation periods being above 0.75 and relative errors (RE) are ±3.5%. In comparison to the baseline of 1980–2015, the mean annual precipitation in the future period (2025–2060) under the three emission scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5 will probably increase by 5.64%, 2.60%, and 6.68% respectively. Correspondingly, the multiple-year average of daily maximum and minimum air temperatures are projected to rise by 1.6–2.1 °C and 1.4–2.0 °C, respectively, in 2025–2060. As a result of climate change, the average annual runoff will increase by 16.24%, 8.84%, and 17.96%, respectively, in the period of 2025–2060 under the three SSPs scenarios. The increase in runoff in the future will provide sufficient water supply to support socioeconomic development. However, increases in both rainfall and runoff also imply an increased risk of flooding due to climate change. Therefore, the impact of climate change on flooding in the Qinhuai River Basin should be fully considered in the planning of flood control and the basin's development. [ABSTRACT FROM AUTHOR]

Gradually increasing durations of high temperature caused by climate change harm the health of individuals and then lead to death. This study aimed to investigate the relationship between durations of different daily mean air-temperature categories and mortality in China and forecast future mortality changes in China for 2020–2050 under Representative Concentration Pathways (RCP)4.5 and RCP8.5 scenarios. The daily mean air temperature was divided into 10 categories, and the days under each air-temperature category were counted during the period of 2000–2015. Then, the connection between the days of each of the 10 air-temperature categories and mortality was established using the semi parametric regression model. Results indicate that the days of the >32 °C category have the largest impact on mortality in China, with the death rate increasing by 23‰ for one additional day. Predictions reveal that mortality in China will increase 25.48% and 26.26% under the RCP4.5 and RCP8.5 scenarios, respectively. Moreover, the mortality of 86 regions in western China will increase 30.42%. Therefore, in the future, the increasing duration of days of high temperatures will raise the mortality rate in China and aggravate the mortality gap between developed and underdeveloped regions. [ABSTRACT FROM AUTHOR]

There are few studies on the climate and glacial scale in the mountains east of the Qinghai–Tibet Plateau. So, we used glacial features to determine the range of the area's paleoglaciers and the equilibrium line altitude (ELA) of theGlA modern and paleoglaciers in the Tianchi area of the Changbai Mountains. Then, the GlaRe toolbox 2015 () was used to reconstruct the surface of the paleoglaciers. The probable air temperature during the glacial advances of the LGM was calculated by applying the P-T and LR models. The results showed the following: (1) the change in ELA is 950 m in the Tianchi area of the Changbai Mountains; (2) glacial coverage in the Tianchi area of the Changbai Mountains during the LGM period was ~27.05 km2 and the glacial volume was ~9.94 km3; and (3) the mean temperature in the Tianchi area of the Changbai Mountains during the LGM was 6.6–9.0 °C lower than today's, and was the principal factor controlling the growth of glaciers. There is a difference in the climate change in monsoon-influenced mountains during the LGM, and this difference may be related to the precipitation in the mountains. [ABSTRACT FROM AUTHOR]

As global warming produces dramatic climate changes, water management is facing increasingly serious challenges. Given to the process of climate change and its complex effects on watershed hydrology, this paper investigates the spatial and temporal variation characteristics of major climatic factors (i.e., precipitation and temperature) over the upper Yangtze River basin (UYRB), China. The statistical analyses are based on annual and seasonal scales during 1951–2020 with a recorded period of seven decades. The Mann–Kendall nonparametric test and R/S analysis are used to record the temporal trends (past and future) of climate variables; the Pettitt test, standard normal homogeneity test and Buishand test are used to detect the homogeneity in climate series. The sensitivities of the streamflow to climatic parameters are assessed at the watershed scale, especially considering the Three Gorges Dam's (TGD) effect on changing runoff. The results of the study indicate that the annual precipitation of 29 out of 34 series indicate homogeneity, while 31 out of 34 annual mean temperature series show heterogeneity, with jump points around 1997 in the mean temperature of 20 sites. Detectable changes in precipitation were not observed during 1951–2020; however, the temperature increased significantly in the whole basin on annual and seasonal scales, except for several stations in the eastern part. The magnitude of increase in air temperature in high altitudes (Tibet Plateau) is higher than that in low altitudes (Sichuan Plain) over the last seven decades, and future temperatures continue to sharply increase in high altitudes. The TGD plays an important role in explaining the seasonal variations in streamflow at Yichang station, with streamflow experiencing a sharp increase in winter and spring (dry season) and a decrease in summer and autumn (rainy season) compared to the pre-TGD period. The streamflow variation at an annual scale is mainly regulated by climate fluctuation (variation in precipitation). During the last seven decades, increasing air temperature and decreases in rainfall and runoff signify reduced water resources availability, and the climate tends to be warmer and drier over the basin. The sensitivity of the streamflow to watershed precipitation is higher than that to temperature, with variation in annual rainfall explaining 71% of annual runoff variability. [ABSTRACT FROM AUTHOR]

A number of previous studies have contributed to a better understanding of the thermal impacts of dam-related reservoirs on stream temperature, but very few studies have focused on air temperature, especially at the catchment scale. In addition, due to the lack of quantitative analysis, the identification of the effects of water impoundment on regional air temperature is still lacking. We investigated the impacts of reservoirs on the regional air temperature changes before and after two large dam constructions in the lower Jinsha River located in southwest China, by using a 40 year record of reanalysis data at 90 m resolutions. Furthermore, the long short-term memory (LSTM) model was also employed to construct an impoundment effect on the temperature (IET) index. Research results indicate that compared to the pre-impoundment period (1980–2012), the variations in the air temperature at the catchment scale were reduced during the post-impoundment period (2013–2019). The annual maximum air temperature decreased by 0.4 °C relative to the natural regimes. In contrast, the cumulative effects of dam-related reservoirs increased the annual mean and minimum air temperature by 0.1 °C and 1.0 °C, respectively. Warming effects prevailed during the dry season and in the regions with high elevations, while cooling effects dominated within a 4 km buffer of the reservoirs. Therefore, this study offers important insights about the impacts of anthropogenic impoundments on air temperature changes, which could be useful for policymakers to have a more informed and profound understanding of local climate changes in dammed areas. [ABSTRACT FROM AUTHOR]

Evaluation of changes in dry-wet climate is crucial in the context of global climate change to ensure regional water resources, ecosystem stability, and socio-economic development. Long-term daily meteorological data, including temperature, precipitation, relative humidity, wind speed, sunshine duration, and air pressure data from 1680 stations across mainland China from 1971 to 2019, were collected to investigate the temporal and spatial variations in aridity index (AI), precipitation (P), reference evapotranspiration (ET0), and the underlying driving climatic factors. Results indicated that the Northwest, Northeast, and Huang-Huai regions were undergoing significant wetting processes, while the Southwest and Southeast China were undergoing significant drying processes. The changing AI was mainly decided by the changing trends of ET0. For most regions, ET0 has undergone significant increases. The average increasing rate over mainland China was 3.76 mm/10a. Stations with decreasing trends were mainly located in the Tibet Plateau, Huang-Huai, and northern Northeast China. Trends in ET0 were negatively affected by the increasing changes in relative humidity and positively affected by the decreasing changes in wind speed and sunshine duration and the increasing changes in air temperature. Wind speed and relative humidity were found to be the main dominant factors driving the changes in ET0, and their contribution varied with regions. Huang-Huai and northern Northeast China showed a significant downward trend in ET0, mainly driven by the decrease in wind speed, while the increase in relative humidity was the primary contributor to the significant upward trends in ET0 across all other regions in China. [ABSTRACT FROM AUTHOR]

Linking sinuosity, a fairly recently developed metric, with high temperature extremes (HTEs) can be both useful and insightful to better understand the physical mechanisms behind HTEs. However, it is not clear whether there exists a relationship between the sinuosity changes and HTE changes in present and future climate conditions over southeastern China. In this paper, the anomalous characteristics of the atmospheric circulation are quantified by sinuosity. Three sinuosity metrics are used in this study: individual sinuosity (SIN), aggregate sinuosity (ASIN), and comprehensive sinuosity (CSIN). Furthermore, we examine the relationship between sinuosity changes and HTE changes in present and future climate conditions. ASIN is strongly correlated with surface air temperature (SAT). We find that the influence of individual sinuosity (SIN) at different latitudes on the SAT of southeastern China is different. The SIN of low (middle) latitude isohypses has significant positive (negative) correlations with the SAT of southeastern China. The SIN of high-latitude isohypses is rather limited and can therefore be ignored. The projected relationship between the sinuosity changes and HTE changes in the late 21st century suggests similar results. The change in SAT is related to the changes in climate variables over southeastern China in the future, and these changes increase with the increase in Z500 or V850 and the decrease in U500. Moreover, the frequencies of large (small) comprehensive sinuosity (CSIN) values at low (mid) latitudes will increase. At the end of the 21st century, Z500 isohypses at different latitudes will have an obvious poleward shift. Our results indicate that measuring the aggregate waviness of the midtropospheric flow (via sinuosity) can provide insight regarding HTEs, and the climate model output can be used to examine the future likelihood of increased HTE. [ABSTRACT FROM AUTHOR]

It is of great importance to study the changes in reference evapotranspiration (ET0) and the factors that influence it to ensure sustainable and efficient water resource utilization. Daily ET0 data calculated using the Penman–Monteith method from 37 meteorological stations located within Guangdong Province in the humid zone of southern China from 1960 to 2020 were analyzed. The trend analysis and Mann–Kendall test were used to analyze the time series changes in ET0 and major climatic factors (air temperature (T), relative humidity (RH), sunshine duration (SD), and wind speed (u2)) for over 61 years. Sensitivity and contribution analyses were used to evaluate the driving factors of ET0. The main findings of the study are as follows: (1) the trend in average annual ET0 time series in Guangdong slightly increased at a trend rate of 1.61 mm/10a over the past 61 years, with most stations experiencing an increase in ET0. During the same period, air temperature significantly increased, while RH and SD decreased; u2 also decreased. (2) Sensitivity analysis showed that ET0 was more sensitive to RH and T than SD and u2, with ET0 being most sensitive to RH in spring and winter and T in summer and autumn. (3) The contribution analysis showed that T was the dominant factor for ET0 variation in Guangdong, followed by SD. SD was found to be the dominant factor in ET0 changes in areas where the "evaporation paradox" occurred, as well as in spring and summer. The study concludes that the climate in Guangdong became warmer and drier over the past 61 years, and if the current global warming trend continues, it will lead to higher evapotranspiration and drought occurrence in the future. [ABSTRACT FROM AUTHOR]

Satellite-derived Land Surface Temperature (LST) dynamics have been increasingly used to study various geophysical processes. This review provides an extensive overview of the applications of LST in the context of global change. By filtering a selection of relevant keywords, a total of 164 articles from 14 international journals published during the last two decades were analyzed based on study location, research topic, applied sensor, spatio-temporal resolution and scale and employed analysis methods. It was revealed that China and the USA were the most studied countries and those that had the most first author affiliations. The most prominent research topic was the Surface Urban Heat Island (SUHI), while the research topics related to climate change were underrepresented. MODIS was by far the most used sensor system, followed by Landsat. A relatively small number of studies analyzed LST dynamics on a global or continental scale. The extensive use of MODIS highly determined the study periods: A majority of the studies started around the year 2000 and thus had a study period shorter than 25 years. The following suggestions were made to increase the utilization of LST time series in climate research: The prolongation of the time series by, e.g., using AVHRR LST, the better representation of LST under clouds, the comparison of LST to traditional climate change measures, such as air temperature and reanalysis variables, and the extension of the validation to heterogenous sites. [ABSTRACT FROM AUTHOR]

The increased frequency of climate extremes associated with ongoing climate change has the potential for significant impacts on maize grain yield in maize-producing regions worldwide. In this study, we used a modeling approach to investigate the effects of different types of climatic extremes on maize grain yield in Northeast China. We combined annual mean air temperature and accumulated precipitation data and divided the climate years into 9 categories, using the 10th and 90th percentiles as extreme thresholds. The climate data were represented by 1 normal climate type, 4 individual climate extremes, and 4 combined climate extremes. Changes in the frequencies of climate extremes and their impacts on maize grain yields were analyzed for two 30-year periods (period I: 1960–1989; period II: 1990–2019) using the Agricultural Production Systems sIMulator (APSIM-Maize). Compared with period I, the occurrences of the normal climate and all 3 cold-related climate extremes (i.e., cold-normal, cold-humid, and cold-dry) decreased during period II, while occurrences of the other climate extremes increased. Moreover, according to the APSIM-Maize model, the estimated yield in the years with a normal climate decreased by 4.01%; the 3 cold-related climate extremes increased yields by 26.56%, 12.10%, and 6.68%, respectively; the 2 warm-related climate extremes (warm-normal and warm-dry) and normal-humid years decreased estimated yields by 6.39%, 24.12%, and 5.10%, respectively. The increase in the occurrence of warm-humid years increased the estimated yield by 11.69%. This work confirms the adverse effects of warmer temperatures in the absence of excess rainfall on grain yield and highlights the importance of extremely dry or wet conditions under normal temperature conditions. [ABSTRACT FROM AUTHOR]

Soil moisture is closely related to the hydrosphere, atmosphere, and biosphere, which makes it one of the most significant climate variables. Using data from the National Environmental Forecasting Center (NCEP), this paper analyzes the temporal and spatial characteristics of soil moisture at a depth of 0–10 cm in China for the period of 1948 to 2014. In addition, the soil moisture's possible interaction with air temperature is explored. Mainly using statistical analysis, the results showed that annual soil moisture decreased significantly (p < 0.01) in most areas. The tendency of decreasing soil moisture was relatively higher in spring and autumn than that in summer and winter. As to the national annual average soil moisture, there was a sudden change in the 1970s. The soil moisture had a relatively high value with a larger deviation before the abrupt change, but after that, the soil moisture was at a relatively low level with a smaller deviation. It was also found that the soil moisture at 0–10 cm showed a negative correlation with the 2-m air temperature above ground in the northern part of China, where the speed of the temperature rise was higher. The results are expected to help improve the understanding of the link between regional soil moisture variation and climate change. [ABSTRACT FROM AUTHOR]

Vegetation phenology is a sensitive indicator of climate change, and can help understand the response of vegetation cycles to climate, which is important for understanding the impact of global climate change on terrestrial ecosystems. In this study, based on the enhanced vegetation index (EVI) time-series data, derived from the moderate-resolution imaging spectroradiometer (MODIS) data, the climate parameters were extracted using the Savitzky–Golay (S–G) filtering method to explore the spatial and temporal variation characteristics of the vegetation phenology in an agro-pasture ecotone in China, from 2000 to 2020. In addition, the response characteristics of the vegetation phenology to the climate elements (temperature and precipitation) were also analyzed. The results showed the following: (1) The start of the growing season (SOS) was widely advanced, and that was caused by climate change. The end of the growing season (EOS) was delayed, and the length of the growing season (LOS) was gradually extended with a large interannual fluctuation in the SOS and the LOS in the region; (2) the SOS showed significant negative correlations with the air temperature and precipitation. Precipitation was mainly positively correlated with the EOS, but there was no significant difference in the correlation between temperature and the EOS. In general, pre-season precipitation is the main driver of the vegetation phenology, while the influence of temperature on the phenology is less obvious; (3) in the semi-arid area and arid area, the phenology was mainly influenced by precipitation. The response of the vegetation phenology to the temperatures in different temperature zones was found to be regular, showing high spatial differences. In general, the higher the cumulus temperature, the lower the negative effect of the temperature on both the SOS and EOS. These results may provide new reference to study the non-systematic changes of the vegetation phenology in response to climate change. [ABSTRACT FROM AUTHOR]

High-resolution gridded 2 m air temperature datasets are important input data for global and regional climate change studies, agrohydrologic model simulations and numerical weather predictions, etc. In this study, the digital elevation model (DEM) is used to correct temperature forecasts produced by ECMWF. The multi-grid variation formulation method is then used to fuse the data from corrected temperature forecasts and ground automatic station observations. The fused dataset covers the area over (0–60°N, 70–140°S), where different underlying surfaces exist, such as plains, basins, plateaus, and mountains. The spatial and temporal resolutions are 1 km and 1 h, respectively. The comparison of the fusion data with the verification observations, including 2400 weather stations, indicates that the accuracy of the gridded temperature is superior to European Centre for Medium-Range Weather Forecasts (ECMWF) data. This is because a more significant number of stations and high-resolution terrain data are used to generate the fusion data than are utilized in the ECMWF. The obtained dataset can describe the temperature feature of peaks and valleys more precisely. Due to its continuous temporal coverage and consistent quality, the fusion dataset is one of China's most widely used temperature datasets. However, data uncertainty will increase for areas with sparse observations and high mountains, and we must be cautious when using data from these areas. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a key component of the hydrological cycle, but traditional monitoring approaches are always based on measurements, which cannot satisfy the requirements of research on a regional scale. Hence, ET estimation by remote sensing is essential. MOD16 is a remote-sensing model based on the P-M equation and has good applicability. However, it describes soil moisture indirectly by RH, etc., which may cause uncertainties in ET estimating, so this study attempts to utilize the NDWI as a supplement to soil moisture information and makes improvements on the MOD16 model (with the resultant new model being named MOD16-sm). Specific work includes two aspects: one is model verification through making comparisons between ET estimates and measurements, and the other is a model application effect test analyzing the spatiotemporal characteristics of ET and exploring how ET responds to climate and land-use changes. Model verification indicated that the accuracy of the improved MOD16-sm model increased, with a higher R2 of 0.71, a lower RMSE 0.9 mm, and a lower MAE 0.91 mm, and that the improved MOD16-sm model was convincing. The application effect test of the MOD16-sm model showed that the average relative change rate of annual ET was 1.7%, showing an upward trend, and areas with growth trends of ET also had high vegetation coverage. As for the impacts of climate and land-use changes on ET, ET was positively correlated with precipitation, whereas it had no relevant correlation with air temperature in most areas, and the ET of all land-use types displayed significant increasing trends resulting from climate change. The application effect test demonstrated that ET estimates by the improved MOD16-sm model were reasonable. [ABSTRACT FROM AUTHOR]

Projecting future changes of streamflow in the Jinsha River Basin (JRB) is important for the planning and management of the west route of South-to-North Water Transfer Project (SNWTP). This paper presented an analysis of the implications of CMIP5 climate models on the future streamflow in the JRB, using SWAT model. Results show that: (1) In the JRB, a 10% precipitation decrease might result in a streamflow increase of 15 to 18% and a 1 °C increase in temperature might results in a 2 to 5% decrease in streamflow; (2) GFDL-ESM2M and NORESM1-M showed considerable skill in representing the observed precipitation and temperature, which can be chosen to analyze the changes in streamflow in the future; (3) The precipitation and temperature were projected to increase by 0.8 to 5.0% and 1.31 to 1.87 °C. The streamflow was projected to decrease by 4.1 to 14.3% in the upper JRB. It was excepted to change by −4.6 to 8.1% in the middle and lower JRB (MLJRB). The changes of low streamflow in the MLJRB were −5.8 to 7.4%. Therefore, the potential impact of climate on streamflow will have little effect on the planning and management of the west route of SNWTP. [ABSTRACT FROM AUTHOR]

Investigating the attributions of evapotranspiration (ET) and gross primary production (GPP) changes is of great importance for regional, sustainable water resources and ecological management in semi-arid regions. Based on the simulation conducted during 2000–2019 by improving water-carbon coupling Distributed Time Variant Gain Model, the trends of ET and GPP were estimated and the driving factors were identified via 10 experimental scenarios in the water source area of the Xiong'an New Area in North China. The results show significant increases both in ET and GPP by 2.4 mm/a and 6.0 gC/m2/a in the region, respectively. At the annual scale, increasing precipitation dominates the ET uptrend. Air temperature, humidity and the interactive effects also contribute to the ET uptrend, and the contributions are 12.8%, 2.0% and 2.3%, respectively, while elevated atmospheric CO2 concentration (eCO2) and solar dimming lead to ET changes of about −7.2% and −12.4%, respectively. For the GPP changes, the increase in GPP is mainly caused by eCO2, increasing precipitation and rising temperature with the contributions of 56.7%, 34.8% and 27.8%, respectively. Solar dimming, humidity and windspeed contribute −6.8%, −4.8% and −3.5% of the GPP changes. Compared to climate change, land use and cover change has smaller effects on both ET and GPP for the few changes in land coverage. At the seasonal scale, ET and GPP increase to a greater extent during the growing season in spring and summer than in autumn and winter. Precipitation, temperature and eCO2 are generally the main causes for ET and GPP changes. Meanwhile, the decreasing humidity and rising temperature are dominant factors for ET and GPP increases, respectively, in winter. Furthermore, solar dimming has strong effects on ET reduction in autumn. The contribution of the interactive effects is much higher on a seasonal scale than annual scale, contributing to considerable decreases in ET and GPP in spring, increases in ET in autumn and winter, and an increase in GPP in winter. This study highlights the importance of considering water-carbon coupling on the attributions of ET and GPP changes and the differentiation of the effects by the abovementioned influential factors at annual and seasonal scales. [ABSTRACT FROM AUTHOR]

The presence of seasonal snow cover in the cold season can significantly affect the thermal conditions of the ground. Understanding the change of the snow–soil interface temperature (TSS) and its environmental impact factors is essential for predicting subnivean species changes and carbon balance in future climatic conditions. An improved Snow Thermal Model (SNTHERM) is employed to quantify TSS in farmland of Northeast China (NEC) in a 39-year period (1979–2018) firstly. This study also explored the variation tendency of TSS and its main influencing factors on grid scale. The result shows that annual average TSS and the difference between TSS and air temperature (TDSSA) increased rapidly between 1979 and 2018 in the farmland of NEC, and we used the Mann–Kendall test to further verify the increasing trends of TSS and TDSSA on aggregated farmland of NEC. The correlation analysis showed that mean snow depth (MSD) is the most pivotal control factor in 95% of pixels and TDSSA increases as MSD increases. Snow depth can better predict the change of TSS in deep–snow regions than average winter temperature (TSA). The results of this study are of great significance for understanding the impact of snow cover on the energy exchange between the ground and the atmosphere in the cold climate. [ABSTRACT FROM AUTHOR]

Global climate change has created a major threat to biodiversity. However, little is known about the habitat and distribution characteristics of Cinnamomum camphora (Linn.) Presl., an evergreen tree growing in tropical and subtropical Asia, as well as the factors influencing its distribution. The present study employed Maxent and a GARP to establish a potential distribution model for the target species based on 182 known occurrence sites and 17 environmental variables. The results indicate that Maxent performed better than GARP. The mean diurnal temperature range, annual precipitation, mean air temperature of driest quarter and sunshine duration in growing season were important environmental factors influencing the distribution of C. camphora and contributed 40.9%, 23.0%, 10.5%, and 7.2% to the variation in the model contribution, respectively. Based on the models, the subtropical and temperate regions of Eastern China, where the species has been recorded, had a high suitability for this species. Under each climate change scenario, the potential geographical distribution shifted farther north and toward a higher elevation. The predicted spatial and temporal distribution patterns of this species can provide guidance for the development strategies for forest management and species protection. [ABSTRACT FROM AUTHOR]

Potential evapotranspiration (ET0) is an essential component of the hydrological cycle, and quantitative estimation of the influence of meteorological factors on ET0 can provide a scientific basis for studying the impact mechanisms of climate change. In the present research, the Penman–Monteith method was used to calculate ET0. The Mann–Kendall statistical test with the inverse distance weighting were used to analyze the spatiotemporal characteristics of the sensitivity coefficients and contribution rates of meteorological factors to ET0 to identify the mechanisms underlying changing ET0 rates. The results showed that the average ET0 for the Yanhe River Basin, China from 1978–2017 was 935.92 mm. Save for a single location (Ganquan), ET0 increased over the study period. Generally, the sensitivity coefficients of air temperature (0.08), wind speed at 2 m (0.19), and solar radiation (0.42) were positive, while that of relative humidity was negative (−0.41), although significant spatiotemporal differences were observed. Increasing air temperature and solar radiation contributed 1.09% and 0.55% of the observed rising ET0 rates, respectively; whereas decreasing wind speed contributed −0.63%, and relative humidity accounted for −0.85%. Therefore, it was concluded that the decrease of relative humidity did not cause the observed ET0 increase in the basin. The predominant factor driving increasing ET0 was rising air temperatures, but this too varied significantly by location and time (intra- and interannually). Decreasing wind speed at Ganquan Station decreased ET0 by −9.16%, and was the primary factor underlying the observed, local "evaporation paradox". Generally, increase in ET0 was driven by air temperature, wind speed and solar radiation, whereas decrease was derived from relative humidity. [ABSTRACT FROM AUTHOR]

Climate changes show asymmetrical warming, and warming is typically greater at night than during the day. To understand how nocturnal warming (NW) affects the performance of maize (Zea mays L.), an open-field experiment with a free air temperature increase (FATI) facility was conducted for three seasons during 2014 to 2016 at Luancheng eco-agro-experimental station on the North China Plain (NCP). Three nocturnal warming scenarios were set up: the entire growing period (T1, from V4 to maturity), only the vegetative stages (T2, from V4 to a week presilking) and the reproductive stages (T3, from a week presilking to R6). The treatment without NW was the control. Maize lodged seriously in 2015 due to heavy rainfall combined with strong winds, and the experiment failed. The results from 2014 and 2016 were analyzed in this study. During the experimental duration, the average nocturnal temperature was increased by approximately 3.6 and 3.3 °C at 150 cm height and 2.0 and 1.7 °C at the soil surface during the vegetative stages. The corresponding increases were 2.1 and 2.5 °C and 0.7 and 1.2 °C at the soil surface during the reproductive stages in 2014 and 2016, respectively, as compared with that of the CK treatment. NW during the whole growth period significantly decreased maize yield for the two seasons. Treatment T2 had a smaller impact on maize yield than T1 and T3. The silking stage was delayed by 2 days in 2014 and 2016 under T1. As a result, presilking duration and VT-R1 interval were prolonged by 1–2 days; and the postsilking duration were shortened by 1–3 days under T1. The soil moisture in the warmed plots was slightly lower than that in the control plots in the 2014 and during the stages before the earlier grain-filling stages in 2016, but NW decreased soil water content greatly at the later grain-filling stages in 2016, which caused the fast green leaf senescence and exacerbated the negative effects of NW on maize yield. NW for the whole growth duration (T1) significantly decreased seed weight and harvest index. NW increased leaf nighttime respiration rate in both seasons. No significant effects of NW on ear leaf net photosynthesis, leaf area, and specific leaf weight at early grain-filling stage were observed, irrespective of the warming stage and season. The results suggested that reproductive stages were more sensitive to NW compared to vegetative stages under the growing conditions of NCP. The negative effects of NW were worsened in dry seasons. The reduction in maize yield with nocturnal warming was driven by the reduction in the aboveground carbon allocation from shoot to grain during postanthesis stage. [ABSTRACT FROM AUTHOR]

Positive degree-day (PDD) indicates the accumulated positive temperature in a given time period; it directly relates to the melting of snow and ice, and it is a key parameter between global warming and cryosphere changes. In this study, we calculated the PDD based on the daily mean temperatures from 1960 to 2018 at meteorological stations, and we used measured and interpolated data to determine spatial and temporal distribution and changes in PDD in western China (WC). Results show that the mean annual, warm season, and cold season PDD values at 209 meteorological stations were 3652.2, 2832.9, and 819.3 °C, respectively. PDD spatial distribution in WC is similar to that of air temperature. In WC, PDD mainly ranged from 0 to 5000, 1000 to 4000, and 0 to 1000 °C year−1, respectively for annual, warm season, and cold season. From 1960 to 2018, the observed mean initial day of PDD moved forward by 8.3 days, and the final day was delayed by 8.2 days, with the duration expanding to 16.6 days; the trend in PDD reversed in the 1980s and the change rate in PDD for annual, warm season and cold season was 6.6, 3.8, and 2.7 °C year−1, respectively. Regionally, PDD increased in almost all areas; the high PDD advanced from south to north, east to west, desert to mountain, and low to high altitudes. The results also showed that the warming rate of PDD was lower in the cold season and in high-altitude areas, which was opposite to the observed temperature patterns, however, the non-linear relationship between PDD and mean temperature over a period of time is the main reason for this phenomenon. This study adds more details for the understanding of climate change in WC, and suggests that more attention should be paid to PDD in the study of cryosphere changes. [ABSTRACT FROM AUTHOR]

Fire is one of the most widespread and destructive disasters, which causes property losses, casualties, and disruption of the balance of ecosystems. Therefore, it is highly necessary for firefighting to study the variations in fire and its climatic attributions. This study analyzed the characteristics of fire-burned area (BA) and its response to climatic factors in seven subregions of China from 2001 to 2018 using satellite remote sensing BA products. The results show that the BA in China and most of its subregions shows a decreasing trend. In general, it is negatively correlated with precipitation and positively correlated with air temperature and wind speed based on the regression and correlation analyses. Based on Pearson correlation and random forest methods, it is also found that the temperature is commonly an important factor contributing to BA in China, except for R2 (Inner Mongolia region), where wind speed is more important, and R5 (South China), where precipitation is more important, which coexists at annual and seasonal scales. Besides temperature, precipitation in spring and summer is the main driving factor, such as in R1 (Northeast China), R5, R6 (Northwest China) and R7 (Qinghai–Tibet Plateau) in spring and R4 (Central China), R5 and R7 in summer; and wind speed in autumn and winter is the main driving factor, such as in R2 and R4 in autumn and R2, R3, R5, R6 and R7 in winter. Finally, the distributions of BA with respect to each climatic factor were also analyzed to quantify the range of climatic factors with maximum BA occurrence. [ABSTRACT FROM AUTHOR]

The relationship between climate and forest is critical to understanding the influence of future climate change on terrestrial ecosystems. Research on trees at high elevations has uncovered the relationship in the Hengduan Mountains region, a critical biodiversity hotspot area in southwestern China. The relationship for the area at low elevations below 2800 m a.s.l. in the region remains unclear. In this study, we developed tree ring width chronologies of Pinus yunnanensis Franch. at five sites with elevations of 1170–1725 m in this area. Monthly precipitation, relative humidity, maximum/mean/minimum air temperature and the standardized precipitation evapotranspiration index (SPEI), a drought indicator with a multi-timescale, were used to investigate the radial growth-climate relationship. Results show that the growth of P. yunnanensis at different sites has a similar response pattern to climate variation. Relative humidity, precipitation, and air temperature in the dry season, especially in its last month (May), are critical to the radial growth of trees. Supplemental precipitation amounts and reduced mean or maximum air temperature can promote tree growth. The high correlations between chronologies and SPEI indicate that the radial growth of trees at the low elevations of the region is significantly limited by the moisture availability. Precipitation in the last month of the previous wet season determines the drought regime in the following dry seasons. In spite of some differences in the magnitudes of correlations in the low-elevation area of the Hengduan Mountains region, chronologies generally matched well with each other at different elevations, and the differences are not evident with the change in elevation. [ABSTRACT FROM AUTHOR]

The ongoing global warming and changing patterns of precipitation have significant implications for crop yields. Process-based models are the most commonly used method to assess the impacts of projected climate changes on crop yields. In this study, the crop-environment resource synthesis (CERES)-Maize 4.6.7 model was used to project the maize crop yield in the Shaanxi Province of China over future periods. In this context, the downscaled ensemble projections of 17 general circulation models (GCMs) under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) were used as input for the calibrated CERES-Maize model. Results showed a negative correlation between temperature and maize yield in the study area. It is expected that each 1.0 °C rise in seasonal temperature will cause up to a 9% decrease in the yield. However, the influence of CO2 fertilization showed a positive response, as witnessed by the increase in the crop yield. With CO2 fertilization, the average increase in the maize crop yield compared to without CO2 fertilization per three decades was 10.5%, 11.6%, TA7.8%, and 6.5% under the RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios, respectively. An elevated CO2 concentration showed a pronounced positive impact on the rain-fed maize yield compared to the irrigated maize yield. The average water use efficiency (WUE) was better at elevated CO2 concentrations and improved by 7–21% relative to the without CO2 fertilization of the WUE. Therefore, future climate changes with elevated CO2 are expected to be favorable for maize yields in the Shaanxi Province of China, and farmers can expect further benefits in the future from growing maize. [ABSTRACT FROM AUTHOR]

Characterized by increasing surface air temperature, global warming has altered the hydrological cycle at global and regional scales. In order to adapt water resources management under the context of global warming, attribution analysis on regional differentiation of water resources in the Yangtze River basin (YRB) was conducted in this study. Meteoro-hydrological variations across the basin were examined for the period 1960–2013, and then a statistic-based method was applied in quantifying the contributions of climate variability and human activities on annual runoff variations in different tributary sub-basins in the YRB. Our observation indicates that both the annual increasing rate and the inter-annual fluctuations of temperature in China and in the YRB were higher than that of the global average since the turn of the century. Climate change analysis indicates that the YRB experienced a hot-wet period during 1994–2002 and a hot-dry period during 2003–2013, since the step change of temperature in 1993. Contributions of climate change and human activities on runoff variations varied spatially in the basin. With reference to the baseline period of 1960–1993, the contribution of climate change played a dominant role in most regions of the basin, especially in those upstream sub-basins. The effect of human activities in the basin was quite complicated, not only its regional differentiation, but also its contribution were opposite during the hot-wet period and the hot-dry period in some sub-basins. The result of this study is helpful in understanding the impacts of climate change and human activities on water resources variation in both temporal and spatial scales. [ABSTRACT FROM AUTHOR]

Understanding historical trends in temperature, precipitation, and runoff is important but incomplete for developing adaptive measures to climate change to sustain fragile ecosystems in cold and arid regions, including the Balagaer River watershed on the Mongolian Plateau of northeast China. The objective of this study was to detect such trends in this watershed from 1959 to 2017. The detection was accomplished using a Mann-Kendall sudden change approach at annual and seasonal time scales. The results indicated that the abrupt changes in temperature preceded that in either runoff or precipitation; these abrupt changes occurred between 1970 and 2004. Significant (α = 0.05) warming trends were found at the minimum temperatures in spring (0.041 °C a−1), summer (0.037 °C a−1), fall (0.027 °C a−1), and winter (0.031 °C a−1). In contrast, significant decreasing trends were found in the precipitation (−1.27 mm a−1) and runoff (−0.069 mm a−1) in the summer. Marginally increasing trends were found in the precipitation in spring (0.18 mm a−1) and fall (0.032 mm a−1), whereas an insignificant decreasing trend was found in the runoffs in these two seasons. Both precipitation and runoff in the wet season exhibited a significant decreasing trend, whereas in the dry season, they exhibited a marginally increasing trend. Sudden changes in spring runoff and sudden rises in temperature are the main causes of sudden changes in basin rainfall. [ABSTRACT FROM AUTHOR]

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) is the most commonly grown afforestation species in subtropical China. It is essential that we understand the response of radial tree growth to climate factors, yet most experiments have been conducted based on total annual growth and not on monthly dynamics, which alone can detail the influence of climatic factors. In this study, we aimed to: (i) construct a monthly growth model and compare the growth rate of different social statuses of trees, and (ii) determine the response of radial increments of different social statuses to climate factors. The radial growth was monitored monthly during four years using manual band dendrometers (MBD). The data were fitted using the Gompertz function. Within-stand differences in the social status of Chinese firs resulted in growing period and growth rate length variations. The radial growth began in March, and suppressed trees—especially groups of AS1 and BS1 (suppressed trees of classes I in sites A and B)—stopped in September, whereas dominant and intermediate trees were delayed and stopped in November. The periodic monthly increment curve showed double peaks, and the maximum growth rate occurred in April and August. The peak values were affected by social status, which showed that dominant trees had the greatest radial growth rates. S-shaped Gompertz meant that monthly increment models were successfully fitted to our data, which explained more than 98% of the variation in increment data and passed the uncertainty test. Temperature and precipitation had a significant influence on radial growth, and the correlation between radial growth and air temperature was the highest. Our results also revealed that temperatures explain the double-peak features of Chinese fir. The limiting factors of radial growth changed with the seasons and were mainly affected by temperature and precipitation, which should be considered in predicting the response of tree growth to climate change. [ABSTRACT FROM AUTHOR]