As one of the most important plant traits of crops, crop phenology reflects the characteristics of crop growth and development; its variation also affects crop production. Therefore, crop phenology is a reliable and comprehensive biological indicator reflecting global climate change. Global climate change, marked by rising temperatures, has exerted significant impacts on crop phenology. Under the background of global climate change, revealing the mechanism of global climate change impacts on crop phenology and growth as well as the formation of crop yield is of theoretical and practical significance. At present, crop phenology shifts and their influencing factors have become a hot research topic and an important international issue, thus a large number of studies have been carried out, and achieved rich and effective results. In this paper, we mainly focus on the research progress of crop phenological changes under the background of climate change, including the driving factors and their influencing mechanisms of crop phenological changes as well as methods of research on crop phenology, and the key scientific issues which need to be solved in future study are also discussed. The conclusions of this research could provide a theoretical basis for understanding the impacts and mechanisms of global climate change on crop phenology and for guiding regional agricultural production practices.

To limit global mean warming to below 2.0 ℃ in accordance with the Paris Agreement, countries submitted their Intended Nationally Determined Contributions (INDC) for emission reductions. Those emissions will be the key determinant to the future climate change impacts. However, it remains unclear what the resulting changes in the regional precipitation and its extremes would be under the INDC pledges. Here, we analyze the response of precipitation in Central Asia to emission scenarios under warming resulting from the INDC pledges (as of May 2019), based on an ensemble of comprehensive Earth System Models from the Coupled Climate Model Intercomparison Project Phase 5 (CMIP5). Our results show an increase in the mean precipitation in Central Asia by the end of the 21st century by 10.6% (4.6%-13.3%) for INDC-pledge scenario. However, spatial heterogeneity of precipitation changes reflects the complexity of precipitation responses in future climate projections. Furthermore, heavy precipitation events will strengthen with the enhanced warming, but the trend of dry spell events increases or decreases in different regions. Considering the impacts of precipitation-related extremes, we find that the projected population exposure to heavy rainfall and dry spell events will significantly increase in most Central Asian regions. Limiting warming to lower levels (such as 2.0 ℃ or 1.5 ℃) would reduce the population exposure to heavy rainfall, thereby avoiding impacts associated with more intense precipitation extremes. These results contribute to an improved understanding of future risk from climate extremes, which is paramount for mitigation and adaptation activities for Central Asia, an ecologically fragile area.

The precipitation distribution has obvious intraseasonal variation characteristics in the Haihe River Basin (HRB) during summer. In this paper, intraseasonal evolution of the key areas of precipitation in the HRB and its associated atmospheric circulation pattern have been investigated, and the relative contributions of different atmospheric circulation factors to precipitation in the key areas are quantitatively calculated, by using daily precipitation data of 148 meteorological stations over the HRB and NCEP/NCAR reanalysis data. The results present a prominent intraseasonal variation of the key areas of summer precipitation in the HRB. The key areas move clockwise around the lower reaches of the Luanhe River and Beisan River located in the northeastern HRB, which are the maximum contribution areas of station precipitation to the HRB total amount, from early summer (June) to midsummer (July and August). The key areas are distributed in northeast HRB, east and south HRB, east and central HRB along with the movement. During early summer, the activities of the Northeast Cold Vortex (NECV) play a dominant role (relative contribution is 69.6%) in precipitation in the key areas; in July, the anomalous precipitation in the key areas is mainly affected by the ridge line of the Western Pacific Subtropical High (WPSH), with a relative contribution of more than 60%; in August, the ridge line of the WPSH and the East Asian summer monsoon index (EASMI) has an equivalent contribution to precipitation in the key areas. In addition, the monthly significant correlation areas relating to these atmospheric circulation factors for precipitation, are found at the same location as the key areas of precipitation in the HRB, and their intraseasonal changing paths are both accordant with the position changes of the associated atmospheric circulation systems in summer.

The length and magnitude of vegetation growing season are important factors affecting the change of vegetation productivity during the growth process. Under the context of global warming, vegetation growing season at the middle and high latitudes of the Northern Hemisphere has prolonged significantly and caused positive feedback on vegetation productivity. However, the change of vegetation growth magnitude and its impact on vegetation productivity are still unclear. Northeast China is located in the mid-latitude temperate zone with high vegetation coverage and various vegetation types. Exploring the change of vegetation growth season length and magnitude and their influence on productivity is meaningful for understanding and coping with ecosystem changes in the study area. Based on the long-term GIMMS NDVI3g remote sensing data (1982-2015), the curvature derivation method was used to extract the key vegetation phenological parameters such as start of season (SOS), end of season (EOS), growth season length (LOS) and growth magnitude (GM). Then the relative importance (RI) method was employed to detect the relative contribution of LOS and GM to vegetation productivity (expressed as mean NDVI value in growing season, MGS) in growing season. The results showed that: (1) The overall vegetation productivity and growth magnitude in the study area showed an increasing trend, while the LOS showed a decreasing trend, which led to the GM becoming the main factor controlling the change trend of productivity (RI = 70%); (2) In different vegetation coverage areas, the impact of growth season length and magnitude on productivity showed significant spatial discrepancy. Vegetation productivity in the western grassland region was most significantly controlled by GM (RI = 93%), followed by coniferous forest and broad-leaved forest (RI = 66%, 62%) and crop area was least affected by GM (RI = 56%). The impact of LOS on vegetation productivity is most significant in croplands (RI = 40%) and affects about 27%-35% in other areas. GM was positively correlated with productivity in all vegetation cover areas, while LOS was negatively correlated with productivity; (3) Both climate factors (precipitation, temperature) and phenological changes affect the main contributing factor GM. In detail, the change of SOS has the most significant effect on the GM in a large spatial range. The main manifestation is that delayed SOS can promote GM. Based on remote sensing technique, this study found that vegetation in Northeast China is generally growing more vigorously, but vegetation growth activities are mainly affected by growth magnitude. This study can provide direct evidence for the study of vegetation phenological changes and productivity response under the background of global change.

The climate-sensitive region is an important direction of climate change research, however most previous studies paid more attention to research on single index, instead of that on comprehensive indicators. Based on the spatial distribution and temporal variation of climate types defined by the K?ppen climate classification, this research presents a new definition method to classify the Chinese climate-sensitive regions, where climate types varied frequently. Here we selected Community Earth System Model (CESM) under the intermediate carbon emission scenario (RCP4.5) to simulate the change of climate types during 2006-2013, the 2040s and the 2090s, and predicted the variation of climate-sensitive regions in the next 30 to 80 years. The results indicate that the climate change sensitive regions were consistent with the precipitation sensitive regions. The most sensitive regions in China are located near the Heihe-Tengchong Line, the Qinling-Huaihe region, the western Qinghai-Tibet Plateau and the north of the Tianshan Mountains, while the most stable regions are distributed in the east-central Qinghai-Tibet Plateau, the Kunlun Mountains, the north of Qilian Mountains, the south of the Tianshan Mountains, the west of Helan Mountains and the Da Hinggan Mountains region. In the next 30 to 80 years, the climate change sensitive regions in the western part of China (the west of Helan Mountains and Hengduan Mountains) will be stable, while in the eastern they are shifting northward significantly. This study provides a new perspective for the research of climate change sensitivity and regional responses to climate change, and it is conducive to a timely and effective decision-making in tackling climate change.

Research on extreme temperature is of great significance to ecological and environmental protection and disaster warning in the context of climate change. Based on the daily temperature data observed from 32 meteorological stations from 1960 to 2013, we studied the spatial distributions of air temperature and extreme temperature in the Shaanxi section in Qinling Mountains by integrating the methods of Kriging interpolation, linearity estimation and correlation analysis and the RClimDex software. The results showed that: (1) The annual average temperature, maximum temperature and minimum temperature in the study area were 10.48℃, 16.44℃ and 6.18℃ during the last 54 years, respectively. The temperature on the southern slope of Qinling Mountains was higher than that on the northern slope in the middle-altitude area and high-altitude area, and lower than that in northern slope in the low-altitude area. The difference in air temperature between the northern and southern slopes was lower in the low-altitude area and greater in the middle-altitude area. (2) The frequency, intensity and duration of extreme temperature all tended to increase in the Qinling Mountains. The zones sensitive to extreme temperature change were Zhenan and Zhashui located on the southern slope as well as Zhouzhi and Huxian on the northern slope. (3) The variety of the extreme temperature change was more obvious in frequency on the northern slope while in intensity and duration on the southern slope. Moreover, warming occurred mainly in the night on the northern slope but in the daytime on the southern slope. (4) The warming rate of extreme temperature in the study area increased with the increase of altitude. The change of frequency and intensity of extreme temperature was more obvious in the high-altitude area, and the duration of extreme temperature more obvious in the middle-altitude area.

Strongly impacted by climate change, glacier and snow, as major parts of solid reservoirs in mountains, can regulate the local water sources. This study uses glacier and snow datasets to analyze the variations of glaciers, snow, water storage, and runoff in the Tianshan Mountains, and selects three typical river basins (Aksu River, Kaidu River, and Urumqi River) to interpret the impact of glacier and snow changes on regional water resources in this region. Results indicate that: (1) the functional relationship between glaciers retreat and glaciers area is f(x) = -0.53×x^-0.15 (R² = 0.42, RMSE = 0.086), and small glacier retreat is more sensitive under climate change. Meanwhile, glacier retreat rate at the low-middle elevation bands is faster than that of the high elevation band; (2) the decreasing rate of regional average total water storage (TWS) is -0.7±1.53 cm/a in the study area during 2003-2015. The maximum of TWS deficit region was mainly observed in the central part of the mountains, which is closely related with accelerated glacier retreats; (3) during the past half century, the increased melting of glacier and snow melt led to a runoff increase in the three typical river basins, especially in the Aksu river basin (0.4×10⁸ m³/a). The area decreasing, thinning, and rising equilibrium line altitude (ELV) of glaciers are the major factor contributing to the decreasing trend of runoff in the three river basins since the mid-1990s. Therefore, results revealed that the mechanism of influence of solid water reserves reduction in mountains on regional water resources under climate change, and also provided references for water resources management in the mountainous river basin.

Due to the increasing effects of climate change, drought induced economic losses of agricultural production should no longer be ignored. It has become vital to better understand the causes of agricultural drought. This will help to ensure the security of agricultural production, especially in the major grain production regions of China. Few previous studies have focused on multi-year agricultural drought risk in the grain production of Northeast China. The three provinces are crucial to grain production in China. Increased understanding of drought in this agricultural region would benefit the management of agricultural production. This study focuses on the investigation of possible risks that contribute to agricultural drought in the region, based on the natural disaster system theory. A risk assessment model is developed, based on the region, to investigate the spatiotemporal features of agricultural drought and regionalize the potential risks at county and city levels. The contributing factors for agricultural drought potential risk are exposure, vulnerability, resistance capacity, and agricultural drought composite risk, and these factors have been explored separately. Results indicated two important ideas. First, at the province level, the risk of agricultural drought was the highest for Heilongjiang and the lowest for Liaoning, with Jilin falling in between. The disaster risk changed during the year when the fluctuation of exposure was comparatively stable. Drought vulnerability was gradually rising while agricultural drought resistance capacity remained stable from 2010 to 2014. Second, looking at the entire region, the risk of agricultural drought gradually increased from south to north. The severity level, which is the percentage of county and municipal agricultural drought composite risk within each province, was Heilongjiang (75.81%), Jilin (41.30%) and Liaoning (0%). The highest agricultural drought risks were concentrated in the Sanjiang Plain and Songnen Plain.

Delayed response is one of important characteristics of self-adjustment in fluvial processes. Based on the mechanism of delayed response in fluvial processes, a delayed response model, considering the effects of water-sediment regime and the base level (Tongguan elevation), was developed to simulate the sedimentation processes in wet and dry seasons. The measured data in the period of 1960-2001 was used to estimate the parameters, and the measured data in the period of 2002-2015 was used to validate this model. Results showed that the proposed model could reasonably simulate the sedimentation processes in wet and dry seasons in the Xiaobeiganliu reach. This model performed better for cumulative sediment storage than single sediment storage in wet and dry seasons. Besides, this model also performed better for cumulative and single sediment storage in wet season than in dry season. Since the closure of Sanmenxia Dam, the sedimentation processes in wet and dry seasons in the Xiaobeiganliu has changed obviously in different periods during 1960-2015. Using this model, the contributions of water-sediment regime and the Tongguan elevation on sedimentation in different periods were analyzed. The sedimentation process was mainly affected by the Tongguan elevation in the period of 1960-1970(wet season) and 1960-1968(dry season). However, it was dominated by water- sediment regime after 1970(wet season) and 1968(dry season).

Terrestrial hydrological process is an essential and very weak link in the global/regional climate models. In this paper, the development of research on the coupled atmosphere-hydrology simulations was analyzed, also the research trends and hotspots were identified by scientific literature analysis, and the challenges and opportunities in the coupled atmosphere-hydrology simulations are reviewed and summarized. The land surface processes in most of the existing climate models are mainly designed by the one-dimensional vertical structure, which lacks a detailed description of the two-dimensional hydrologic processes over specific basins, especially the parameterization of human activities on the underlying surface. In order to overcome the poor simulation on watershed hydrological processes derived by climate models, numerous studies were performed to investigate the feedbacks between hydrological processes and atmospheric processes, through coupling hydrological models with regional climate models. At present, improving the representation of hydrologic processes in land surface models and the development of global hydrological models have been the fundamental of investigating the feedbacks between terrestrial hydrology and atmosphere. Furthermore, the research on the coupling between hydrology and atmosphere has developed from the one-way coupling to the two-way coupling (also called fully coupled atmosphere-hydrology simulations). However, these studies on the fully coupled atmosphere-hydrology simulations were still immature and the fully coupled model needed further improvements, including further research on the matching methods of model coupling and system stability, research on effective scale transfer schemes, improvements on parameterization schemes and evaluation on parameter uncertainties, research on effective parameter transfer methods and improvements on regional applicability, as well as the coupled simulation of large-scale terrestrial hydrology and atmosphere at hyper-resolution with acceptable accuracy, and etc.

Based on the long-term phenology observation data of 114 agro-meteorological stations in the maize growing areas of China, the temporal and spatial differentiation characteristics of 8 consecutive phenology periods and the corresponding phenological stages length were quantitatively analyzed. The results showed that the average temperature and GDD (Growing degree days) during the growing seasons from 1981-2010 showed an increasing trend, and the precipitation and sunshine duration showed a decreasing trend in national scale. The maize phenology has changed significantly under the climate change background：Spring maize phenology was mainly advanced, especially in Northwest inland and Southwest mountain hills maize zone. While summer maize and spring-summer maize phenology were all delayed, and the delay trend of summer maize in the Northwest inland changed more than that in the Huanghuai plain. The variations of maize phenology changed the corresponding phenological stages length, the length of vegetative growth period (days from sowing date to tasseling date) of spring/summer/spring-summer maize all showed a trend of shorten in different degrees, and the corresponding reproductive growth period (days from tasseling date to mature date) showed a trend of extension. The whole growth period (days from sowing date to mature date) of spring maize were prolonged, but the whole growth period of summer/spring-summer maize shortened.

Based on the data of phenological observation and daily meteorological records during 1964-2015, we studied the relationship between plant phenology variation and climate change in the Qinling Mountains region by using correlation and Partial Least Squares (PLS) regression analysis. The results showed that: (1) In the past 52 years, the climate of the study region presented a warming-drying trend at the start and the end of plant phenophase, and the warming trend at the start of phenophase is more significant than that at the end of phenophase, especially after the phenophase abrupt change around 1985. (2) The responses of the start and the end of phenophase to the change of climatic factors such as temperature, precipitation and sunshine varied differently. Before the period of phenophase abrupt change, the responses of phenophases were not significant to all the climatic factors except for the daily mean temperature. However, after the period of phenophase abrupt change, the response of phenophases was significant to all the climatic factors. The start of phenophase advanced by 3 d and the end of phenophase delayed by 12 d with the increase of the daily mean temperature by 1℃. The start of phenophase advanced by 1.3 d with the decrease of the accumulated precipitation by 1 mm, and the end of phenophase delayed by 1 d with the increase of the accumulated precipitation by 1 mm. The start of phenophase advanced by 4.3 d and the end of phenophase delayed by 18.3 d with the increase of daily mean sunshine hours by 1 h, respectively. (3) There is a lag effect for the responses of the start and the end of phenophase to climate change. The time-lag was about 1-2 months for air temperature and about 1-3 months for the pre-period accumulated precipitation at the start of phenophase, respectively. No lag effect on the start of phenophase was observed for the sunshine hours. As related to the end of phenophase, the time-lag was about 1-3 months for the air temperature and about 1-2 months for the sunshine hours, respectively. No lag effect on the end of phenophase was found for the precipitation. (4) Both the start and the end of phenophase were jointly affected by the climatic factors, in which the air temperature was the predominant factor. Especially, the rise of the daily mean temperature plays a dominant role in advancing the start of phenophase and delaying the end of phenology.

Lake ice phenology is considered a sensitive indicator of regional climate change. We utilized time series information of this kind extracted from a series of multi-source remote sensing (RS) datasets including the MOD09GQ surface reflectance product, Landsat TM/ETM+ images, and meteorological records to analyze spatiotemporal variations of ice phenology of Qinghai Lake between 2000 and 2016 by applying both RS and GIS technology. We also identified the climatic factors that have influenced lake ice phenology over time and draw some conclusions. First, data show that freeze-up start (FUS), freeze-up end (FUE), break-up start (BUS), and break-up end (BUE) on Qinghai Lake usually occurred in mid-December, early January, mid-to-late March, and early April, respectively. The average freezing duration (FD, between FUE and BUE), complete freezing duration (CFD, between FUE and BUS), ice coverage duration (ICD, between FUS and BUE), and ablation duration (AD, between BUS and BUE) were 88 days, 77 days, 108 days and 10 days, respectively. Second, while the results of this analysis reveal considerable differences in ice phenology on Qinghai Lake between 2000 and 2016, there has been relatively little variation in FUS times. Data show that FUE dates had also tended to fluctuate over time, initially advancing and then being delayed, while the opposite was the case for BUS dates as these advanced between 2012 and 2016. Overall, there was a shortening trend of Qinghai Lake's FD in two periods, 2000-2005 and 2010-2016, which was shorter than those seen on other lakes within the hinterland of the Tibetan Plateau. Third, Qinghai Lake can be characterized by similar spatial patterns in both freeze-up (FU) and break-up (BU) processes, as parts of the surface which freeze earlier also start to melt first, distinctly different from some other lakes on the Tibetan Plateau. A further feature of Qinghai Lake ice phenology is that FU duration (between 18 days and 31 days) is about 10 days longer than BU duration (between 7 days and 20 days). Fourth, data show that negative temperature accumulated during the winter half year (between October and the following April) also plays a dominant role in ice phenology variations of Qinghai Lake. Precipitation and wind speed both also exert direct influences on the formation and melting of lake ice cover and also cannot be neglected.

Based on normalized difference vegetation index (NDVI), vegetation type, and meteorological data, this study revealed the seasonal variations of the day- and nighttime warming in growing seasons using unitary linear regression analysis. It examined different effects of asymmetric seasonal warming on vegetation activities in China's temperate zone using the two-order partial correlation analysis method. The results are as follows. (1) The day- and nighttime warming trends from 1982 to 2015 in growing seasons were extremely significant. The day- and nighttime warming rates were featured by asymmetry; daytime warming was slightly faster than nighttime warming in spring and summer. Contrarily, in autumn, nighttime warming was faster than daytime warming. (2) The effects of the day- and nighttime warming on vegetation activity were obviously different; daytime warming had significantly greater and more extensive effects on vegetation than nighttime warming did, and the areas impacted by diurnal warming were broader in spring than in summer and autumn. (3) Different vegetation types responded differently to the seasonal asymmetry in day- and nighttime warming, and the degree of responses showed distinct variations by season.

Precipitation extremes are expected to become more frequent and intense under global warming in the coming decades. Risk analysis of precipitation extremes has become a hot issue in academic circles and governments. In this paper, we use the data recorded at 756 meteorological stations from 1951 to 2011. Data were first processed to generate a coherent set of precipitation datasets. Pearson-III frequency analysis method was used to define the thresholds of different rainfall return periods. We chose total extreme precipitation amount and extreme precipitation frequency as indices, and scenarios with return periods of 5, 10, 50 and 100 years were designed to analyze precipitation extremes. The vulnerability of economy and population to precipitation extremes was analyzed. Precipitation extremes and the associated vulnerability were evaluated using the risk assessment model of ISDR to assess the risk pattern of precipitation extremes in China, mapping the risk distribution of precipitation extremes under different return periods in China during the past 60 years (1951-2011). Results show that: (1) the magnitude of extreme precipitation decreases from the southeastern coastal areas to the northwestern inlands. The high-risk areas of extreme precipitation in the 5-year scenario are mainly located in southeastern coastal China. The boundary between high-risk and low-risk areas nearly coincides with the isohyet of 400 mm; (2) China's extreme precipitation is mainly observed in densely populated and economically developed eastern coastal metropolitan areas, especially in Yangtze River Delta urban agglomeration, Pearl River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration and several large cities in the western region of China. The western region of the country, which is resource-scarce and economically less developed, is associated with lower-risk precipitation extremes; (3) under each return period, the extreme precipitation risk level decreases from southeastern coastal areas to northwestern inland areas. The high-risk level areas are distributed in South China, southeastern coastal China, middle and lower reaches of the Yangtze River, Huang-Huai-Hai Plain, Bohai Rim and Sichuan Basin. The areas with high risk are mainly distributed to the east of the Heihe-Tengchong Line (Hu Line), and the medium and low risk areas are located to the west of the Hu Line, which is roughly consistent with the Hu Line of population density distribution in China. This research presents a novel approach to evaluating national-scale precipitation extremes and the associated socio-economic risks. Findings obtained herein can be used as scientific references for governments at all levels in disaster prevention and reduction of extreme precipitation in China.

Examining the CO₂ emissions by country in the future whether the mitigation plans are implemented or not, as well as their comparison with INDCs, is important to promote the ambition and cooperation on global long-term goal of climate change. A dynamic model of CO₂ emissions from fuel combustion is established based on statistical analysis between economy and energy development using the latest data from the World Bank and International Energy Agency. Extending and planning scenarios are designed according to whether there exist additional and explicit efforts to mitigate climate change. Then annual CO₂ emissions during 2016-2060 for the European Union, the United States, China and India are simulated and compared with INDCs respectively, from which three main conclusions are derived. (1) In planning scenario China will achieve its INDCs. For detail, the CO₂ emissions per unit of GDP in China will be 63.6% lower than the level of 2005 and the share of non-fossil fuels in primary energy consumption will increase to 24.7%. Besides, China will reach the emission peak 11277±643 Mt CO₂ in 2030, which is 10 years earlier and almost 3000 Mt CO₂ lower than the peak of extending scenario. (2) In planning scenario, the CO₂ emissions of EU and US will significantly decrease and the growth rate of India will slow down, which makes EU and India achieve their INDCs likely but US still has a gap around 300 Mt CO₂. (3) INDCs are ambitious for all countries, especially for China and US. However, making further efforts on global warming mitigation to control the temperature rise below 2 ℃ or even 1.5 ℃, which requires the developed countries to play an important role on policy, technique and finance, including promoting carbon capture and storage technique, achieving negative growth of CO₂ emissions, and providing support for developing countries.

A study on temperature variations in the northern and southern Qinling Mountains is performed using temperature series at 70 meteorological stations for the period 1970-2015. Temporal trends, spatial characteristics, 0 ℃ isotherm displacement and the number of days with active accumulated temperature above 10 ℃ are evaluated, using extreme-point symmetric mode decomposition (ESMD), spatial analysis and other climate diagnosis methods. The significance of climatic boundary line of the Qinling Mountains is explored in the context of global warming. Four new insights have been achieved: (1) The changing trends of temperature in the northern and southern Qinling Mountains over the past 46 years are synchronous, with the warming process shown as a 'non-smooth, nonlinear, and ladder-shaped' pattern. The evolution process can be divided into three periods: the low stationary fluctuation period in 1960-1993, followed by a rapid increase period in 1994-2002, and finally a warming stagnation period in 2003-2015. (2) The ESMD decomposition indicates that the changing trends of temperature over the northern and southern Qinling Mountains are dominated by interannual fluctuation, and have no obvious linear trend. (3) The spatial variation of temperature in the Qinling Mountains is characterized by 'synchronous warming, and differential north-south change'. In the north, the spatial variation of temperature is relatively consistent, while in the south low temperature centers are observed at Xixiang-Ankang basin and Shangdan basin. (4) The Qinling Mountains, as a climatic boundary line, still play a major/obvious role; however, there exists difference in the response of temperature variations to global warming over the north and south of the Qinling Mountains. The northern boundary of north subtropical zone extends upward along the southern Qinling Mountains; while warming zone extends by the form of enclave in the northern Qinling Mountains due to rapid urbanization and mountain blocking.

Based on the daily precipitation data from 75 rainfall gauging stations covering 1960-2015 in the middle and lower reaches of the Yangtze River Basin, we analyzed the temporal and spatial distribution characteristics of dry-wet abrupt alternation (DWAA) events during the summer (from May to August) and its relationship with ENSO by defining the daily scale dry-wet abrupt alternation index (DWAAI) based on the modification of original index. The results showed that: (1) Modified DWAAI, which was defined by taking into account the differences of dry-wet degree between the earlier and later periods as well as how slowly or quickly the process changes from dry to wet in the abrupt alteration period, could be used to identify DWAA events accurately and effectively. (2) On the whole, areas where DWAA events occurred had expanded gradually since 1960. Meanwhile, the frequencies and intensities of such events had gradually increased over time. DWAA events mainly occurred in May-June, and the Hanjiang River watershed sub-basin, the middle reaches of the Yangtze River, the northern Dongting Lake watershed sub-basin and the northwestern Poyang Lake watershed sub-basin were high-incidence areas of such events. (3) There were some relationships between DWAA events and phenomena of continuously low SST in Nino3.4 region before such events occurred. Specifically, La Ni?a early-warning reacted to the occurrence of DWAA events. About 41.04% of such events occurred during decline stages of La Ni?a or within the first 8 months after La Ni?a ended. In terms of intensity, there were significant negative correlations between DWAAI at all the stations and SST anomalies in Nino 3.4 region within 6 months before DWAA events occurred, especially in the Poyang Lake watershed sub-basin and the middle reaches of the Yangtze River. The conclusions indicated that these methods and results were meaningful for the fighting against drought and flood in the Yangtze River Basin.

The study on vegetation phenology is of great importance to understand the relationship between vegetation and climate. In areas where the vegetation is sensitive to climate change, a phenological study is helpful to reveal the response mechanism of vegetation to climate change. Based on Moderate Resolution Imaging Spectro radiometer (MODIS) Enhanced Vegetation Index (EVI) time-series images from 2000 to 2015, we utilized Savitzky-Golay (S-G) filter and dynamic threshold method to extract the phenological parameters of forest vegetation in the Funiu Mountains. Combining temperature and precipitation data, we used Mann-Kendall (M-K) trend test, Theil-Sen estimator, ANUSPLIN interpolation, and correlation analysis methods to analyze phenological changes of vegetation in response to climate factors (temperature/precipitation) in the Funiu Mountains. The results showed that: (1) The start and end of growing season ranged mainly from 105 d to 120 d and from 285 d to 315 d, respectively. The length of the growth season ranged mainly from 165 d to 195 d. There is an evident correlation between forest phenology and altitude. With increasing altitude, the start, end and length of the growing season presented a significantly delayed, advanced and shortened trend, respectively. (2) In terms of the interannual variations, both the start and end of the growing season mainly displayed a delayed trend in 76.57% and 83.81% of the total area, and the length of the growing season exhibited a lengthened trend of 61.21%. The start of forest growing season is mainly affected by the decrease of spring temperature in the region. (3) A significant correlation was found between the start of growing season and mean temperature in March. The negative correlation coefficient indicated that a delayed start of the growing season was primarily due to the temperature decrease in March. The end of growing season was mainly influenced by September precipitation, and their correlation was positive, that is, the increased precipitation in September can delay the end of the growing season. In addition, the length of the growing season was influenced by temperature and precipitation during the whole growing season, for most parts of the region, the mean temperature and precipitation in August were obviously correlated with the length of forest growing season.

Net primary productivity (NPP) is one of the most important indicators of terrestrial ecosystem carbon cycle, and is also the material basis for the survival and development of human society. Therefore it plays an important role in the global environment change and the development and utilization of natural resources. Based on the simulated NPP data from GLOPEM-CEVSA model, air temperature, precipitation and sunshine hours data from 2043 weather stations as well as El Ni?o/La Ni?a events from 1982 to 2011, the spatial and temporal distributions and dynamic changes of NPP in terrestrial ecosystem were analyzed, and the relationships between NPP and climatic factors and ENSO events in China were examined using the GIS spatial analysis and mathematical statistics methods. Results indicated that vegetation NPP increased at a rate of 5.66 gCm^-2 per decade in China during 1982-2011, especially in the 1980s it increased significantly at a linear rate of 50.0 gCm^-2 per decade. Spatially, vegetation NPP increased in western China and the northern and eastern parts of Northeast China, whereas it decreased in the central part of Northeast China, North China Plain, the mid-eastern part of Inner Mongolia, the Yangtze River Delta and the Pearl River Delta in the past 30 years. In the Yangtze-Huaihe river basins, the decrease of vegetation NPP and the reduction of sunshine hours had good corresponding relationships, and in northern China and northern Xinjiang, the increase (decrease) of NPP was relied more on the increase (decrease) of precipitation. In Northeast China, the increase of NPP was associated with the increases in sunshine hours and temperature. For China as a whole, in El Ni?o years, regions with the increase of vegetation NPP were slightly larger than those of NPP decrease, but in La Ni?a years regions with the increase of vegetation NPP was basically equal to those of NPP decrease, and sunshine hours was the main climate factor which leads to the differences of vegetation NPP between El Ni?o years and La Ni?a years. More attentions should be paid to the impacts of radiation, extreme climatic events and anthropogenic air pollution on vegetation NPP in different regions of China in future.

Drought is one of the most catastrophic natural hazards which have severe impacts on human society and yet it is the least understood hazard. Monitoring drought in a reliable way plays a critical role in the early warning as well as the mitigation of drought hazard. Generally, the integrated agro-meteorological drought monitoring is one of the most popular drought monitoring methods and it is the key step to mitigate droughts effectively. However, the originally developed integrated drought monitoring index included nothing about evapotranspiration, and it does perform not well in reflecting impacts of evapotranspiration on occurrence of droughts. In this case, this study attempted to propose an improved version of the multivariate standardized drought index (MSDI) using standardized precipitation evapotranspiration index (SPEI) and standardized soil moisture index (SSI), i.e. modified multivariate standardized drought index (MMSDI). Based on the statistical records of drought-affected crop area in 7 geographical zones across China, this study tests the applicability of MMSDI in drought monitoring across China in 3-month and 6-month time scales, with comparison to the meteorological drought monitored by SPEI, agricultural drought monitored by SSI and integrated agro-meteorological drought monitored by MSDI. The result indicates that MMSDI can monitor meteorological drought and agricultural drought simultaneously. Furthermore, MMSDI has greater superiority than SPEI, SSI and MSDI in the veracity of drought monitoring. Besides, MMSDI can monitor droughts in bad conditions where meteorological drought and agricultural drought monitoring technique cannot be applied. Moreover, MSDI tends to overestimate the drought intensity and the size of drought-affected regions across China. In sum, MMSDI proposed in this study can be used to monitor and detect drought conditions in a more accurate way from perspectives of meteorological drought and agricultural drought. Meanwhile, drought conditions monitored by MMSDI are very close to in-situ observations and to the real-world observations of droughts in terms of drought-affected regions and related losses. In this sense, this study provides a theoretical foundation for large-scale drought monitoring across China, and provides practical regional case studies for related research in other regions of the world.