Under the background of global change， the cryosphere and atmosphere over the Tibetan Plateau （TP） are changing rapidly， which seriously affects the ecological environment of “Asian Water Tower” and “the Third Pole”. This paper reviews some issues in the research on climate change over the TP in recent years， including the change of extreme climate events over the TP and its relationship with the atmospheric circulation， the amplified warming and the physical mechanism of elevation dependent warming， applicability of modern reanalysis data， the bias and inaccuracy of climate models in the areas with scarce data over the TP， and the projection and risk study of climate change over the TP under the different warming threshold. Finally， some important issues and associated scientific challenges in the study of climate change over the TP are identified and their prospects are discussed. Addressing these will support the implementation of the Belt and Road Initiative.

在全球变化的背景下，青藏高原冰冻圈和大气圈正在发生快速变化，对“亚洲水塔”和“第三极”的生态环境带来深刻影响。研究并梳理了近年来青藏高原气候变化的若干前沿科学问题的研究进展，如高原极端气候事件变化及其与大气环流的关系；高原变暖放大效应及海拔依赖型变暖的物理机制；再分析资料在高原气候变化应用的适用性；气候模式在高原资料稀缺地区的模拟偏差特征及不确定性；以及不同升温阈值下高原气候变化的预估及其风险等。同时展望了高原气候变化研究的前沿问题和科学难点。认清高原气候变化研究的前沿科学问题，可为“一带一路”倡议顺利实施提供科学依据。

As a part of the supply of ecosystem services, land and water resources are an important factor restricting economic development in mountainous areas. Taking the Hengduan Mountains Area as a case study, we evaluated the degree of matching between land and water resources and economic development using the Gini coefficient method. Furthermore, the sensitivity of economic growth to land-water factors was analyzed by establishing an extended Cobb-Douglas function based on the individual stochastic effect model. In addition, the growth drag model was introduced to measure the restriction of land-water resources on economic development in the study area quantitatively. The research produced several important results: (1) From 2006 to 2015, the fluctuation ranges of the Gini coefficient between land and water resources and gross domestic product (GDP) in the study area were 0.265-0.298 and 0.389-0.424, respectively. The satisfaction by water resources in different industries was relatively reasonable, but the utilization of land resources for economic development was not satisfactory, especially in the secondary and tertiary industries. (2) The sensitivity analysis results showed that the elasticity of land resources in the region was about twice that of water resources. The cumulative contribution rate of land resources was significantly higher than that of water resources, and the contribution of land resources to economic growth was greater than that of water resources. (3) The average growth drag values of land and water resources were 0.012 and 0.022, respectively, indicating that both land and water resources had obvious restraining effects on the economic development, which was greatly restricted by land resources. The research showed that effective development of mountainous areas in China should focus on the sufficient land-water resources demanded by economic growth. Utilizing the potential of land-water resources and increasing their supply can reduce restriction on economic growth and promote sustainable development.

水土资源不仅是山区生态系统服务供给的一部分,同时也是山区经济发展的重要投入要素。本文以横断山区为研究对象,利用基尼系数法评估水土资源和经济发展之间的匹配状况,同时基于个体随机效应模型建立拓展的Cobb-Douglas生产函数模型实现了经济增长对水土要素的敏感性分析,引入经济增长阻尼模型定量测算了水土资源对横断山区经济发展的制约程度。结果表明：① 2006—2015年横断山区水资源、土地资源与GDP的区域基尼系数波动范围分别为0.260~0.298和0.389~0.424,水资源对不同产业的满足程度相对合理,而对土地资源的利用与经济发展较不匹配,尤其是第二、三产业;② 敏感性分析结果表明,横断山区土地资源的产出弹性是水资源2倍左右,土地资源的累计贡献率明显高于水资源,土地资源要素对经济增长贡献大于水资源要素。③ 水土资源增长阻尼平均水平分别为0.012和0.022,说明水资源和土地资源对横断山区经济发展均产生明显的约束作用,且受土地资源的限制较大。研究表明中国山区发展需要更加重视水土资源开发利用与经济增长需求的匹配,充分挖掘水土资源的利用潜力提高供给可以降低其对经济增长的制约程度。

Water and land resources are the foundation for human wellbeing. The coupling of water-land elements in mountainous areas is closely related to the functionality of production-living-ecology space, whose coupling process and features are closely related to ecosystem services and sustainable socio-economic development in mountainous areas. Through constructing a more scientific coupling index of water-land elements (CIWL), the present study conducted a large-scale and long-term analysis of the coupling characteristics of the Taihang Mountains, Hengduan Mountains and Guizhou-Guangxi karst mountains. The influencing factors of the coupling index in each period were analyzed by employing geodetector method. The results show that: (1) The three mountainous areas are significantly different in spatial differences of coupling index of water-land elements. The Taihang Mountains are dominated by water deficiency, while the Hengduan Mountains are by the balanced area. The Guizhou-Guangxi mountainous areas are dominated by water deficiency and the abundant areas. (2) In terms of the vertical differentiation, the coupling of water-land elements of the three major mountainous areas varies at 1300 m, 1800-3400 m and 500-1500 m, respectively, with the coupling index of water-land elements in ecological functional sub-regions indicating that the forest ecological sub-region > forest grass ecological sub-region > agro-ecological sub-region. (3) Natural factors and human factors are responsible for spatial differentiation of coupling index, among which, the climate is a dominant driving factor, the topography and land use type are secondary, and the human factors are superimposed on the natural factors, jointly causing the complexity and variation of the coupling of water-land elements. The coupling index of water and land elements established in this paper has deepened the study of spatial-temporal processes of water and land interaction in mountainous areas, thereby providing a decision-making reference for coping with the sustainable development of mountainous areas in a changing environment.

水土资源是人类生存的基础,山地水土要素耦合性与“三生空间”的功能性密切相关,其耦合的时空过程及规律关乎山区的生态服务与经济社会可持续发展。通过构建更加科学的水土要素耦合指数对太行山地、横断山地、黔桂喀斯特山地水土要素耦合特征进行大尺度、长时序的分析,并采用地理探测器方法分析了各时期水土耦合的影响因素。结果表明：① 三大山地水土要素耦合空间差异十分显著。太行山地以缺水区为主,横断山地以平衡区为主,黔桂喀斯特山地平衡区和充沛区兼有。② 垂直分异上,三大山地水土要素耦合指数分别在1300 m、1800~3400 m、500~1500 m处发生变异。各山地水土要素耦合指数在生态功能亚区表现为,林地生态亚区>林草复合生态亚区>农业生态亚区。③ 三大山地水土要素耦合的空间异质性是自然要素和人文要素综合作用的结果。其中,气候要素为主导驱动,地形地貌和土地利用居次,人为作用叠加在自然作用之上,加剧了水土要素耦合的时空复杂性和变异性。本文构建的水土要素耦合指数,加深了山地水土要素相互作用的时空过程研究,可为促进变化环境下的山区可持续发展提供决策依据。

Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we show the ability of Sentinel-1 to map snow depth in the Northern Hemisphere mountains at 1 km² resolution using an empirical change detection approach. An evaluation with measurements from ~4000 sites and reanalysis data demonstrates that the Sentinel-1 retrievals capture the spatial variability between and within mountain ranges, as well as their inter-annual differences. This is showcased with the contrasting snow depths between 2017 and 2018 in the US Sierra Nevada and European Alps. With Sentinel-1 continuity ensured until 2030 and likely beyond, these findings lay a foundation for quantifying the long-term vulnerability of mountain snow-water resources to climate change.

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.

基于秦岭南北70个气象站点观测资料,辅以极点对称模态分解方法（ESMD）,对秦岭南北近期气温时空变化特征进行分析,进而以日平均温≥ 10 ℃积温天数为主要指标,以1月0 ℃等温线变化为辅助指标,探讨秦岭山脉的气候分界意义。结果表明：① 1970-2015年秦岭南北气温变化具有同步性,呈现出“非平稳、非线性、阶梯状”的增暖过程,变化阶段可分为：1970-1993年为低位波动期、1994-2002年为快速上升期、2003-2015年为增温停滞期;② ESMD信息分解结果表明,秦岭南北气温变化以年际波动为主导,并未呈现出明显的线性增暖趋势;③ 在空间上,秦岭南北气温趋势呈现“同步增温,南北分异”的响应特征,即秦岭以北地区空间增温具有一致性,秦岭以南地区则呈现“西乡—安康盆地交界”、“商丹盆地”两个低值中心;④ 在气候变暖背景下,秦岭作为气候分界线的作用依然明显,但是南北响应方式存在差异。其中,秦岭以南,北亚热带北界沿山地“垂直上升”,汉江谷地热量资源逐年增加;秦岭以北,尽管以城市带为中心的增温区不断延展,但是冷月气温偏低的格局并未改变。

Groundwater (GW) overexploitation is a critical issue in North China with large GW level declines resulting in urban water scarcity, unsustainable agricultural production, and adverse ecological impacts. One approach to addressing GW depletion was to transport water from the humid south. However, impacts of water diversion on GW remained largely unknown. Here, we show impacts of the central South-to-North Water Diversion on GW storage recovery in Beijing within the context of climate variability and other policies. Water diverted to Beijing reduces cumulative GW depletion by ~3.6 km, accounting for 40% of total GW storage recovery during 2006-2018. Increased precipitation contributes similar volumes to GW storage recovery of ~2.7 km (30%) along with policies on reduced irrigation (~2.8 km, 30%). This recovery is projected to continue in the coming decade. Engineering approaches, such as water diversions, will increasingly be required to move towards sustainable water management.

：Climatic characteristics of snowfall, snow days, snow belt north of 25°N in China is analyzed using the daily snow observation data. The following results have been obtained in the analysis.1) Snow season length and snow days have the feature of latitudinal distribution in the east, with the Da Hinggan Mountains recording the longest (>210 d) snow season, and no snow or only occasional snow all year round in the south of the Yangtze River. In the west, Qinghai Province has the longest (>300 d) snow season, followed by the junction areas of Yunnan, Sichuan and the Tibet. Snow season length in northern Xinjiang is close to the north of Northeast China. The least snowfall occurs in the southeast, and Northeast and northern Northwest record the higher snowfall more (>30 mm),and Qinghai and Tibet are characterized by the highest snowfall(>60 mm). Maximum snowfall intensity is in the Yangtze-Huaihe region. 2) Snow belts are divided based on snowfall frequency: the Northeast and eastern Inner Mongolia, Northern Xinjiang, the Qinghai-Tibet Plateau, and the Qinling Mountains are snow-frequent belts. Southern Yunnan, Sichuan Basin, coastal areas of Jiangsu and Zhejiang and other areas are permanent snow-free belts.The other areas are snow-ordinary belts and snow-occasional belts. 3) The percentage of snowstorm days to total snow days is generally low in all of the regions. The highest percentage is seen for light snow days to total snow days. In view of the ratio of snowfall of all categories to total snowfall, the proportion of snowstorm witnesses the lowest value, followed by heavy snow, and light snow has the highest value in the north of Northeast, North, Northwest, Xinjiang and eastern Tibet Plateau. However, Southeast China is characterized by lowest value of the ratios for light snow, and the highest value for snowstorm. 4) The double-peak distribution of snowfall within the year is seen in northern Northeast, Northwest, Xinjiang and eastern Tibet Plateau, and the Yellow-Huai River basins and Southeast have a single-peak distribution of snowfall. 5) The total snow days, heavy snow days, medium snow days and light snow days generally increase with increasing latitude in the East of China, meanwhile with increasing altitude in the West; with increasing latitude, the total snowfall intensity has a decreasing trend in both the East and the West, also the small snow intensity in the West.

利用逐日地面降雪观测资料,分析中国25ºN以北范围内降雪量、降雪日数、雪带分布和各强度降雪的气候学特征,得到以下结论：① 雪季长度与年降雪日数在东部呈纬向分布,大兴安岭北部最长（>210 d）,长江以南最短（常年无雪或偶尔降雪）;在西部青海省南部和西藏自治区北部最长（>300 d）,滇、川、藏交界处及新疆自治区北部较长,南疆较短（<60 d）。年降雪量东南部最少,东北和西北北部较多（>30 mm）,青海和西藏降雪量最多（>60 mm）。平均降雪强度江淮一带最大。② 根据雪季降雪频次划分中国的雪带,东北大部、内蒙自治区东部、新疆北部、青藏高原大部、秦岭等地区为常年多雪带;长江以南的滇南、四川盆地、江浙沿海等地区为永久无雪带;其余地区为常年降雪带和偶尔降雪带。③ 不同区域各级降雪日数占总降雪日数的比例都是暴雪日数最少,大雪日数其次,小雪日数最多;但中雪降雪量占总降雪量的比例在东北北部、华北、西北、新疆、东南、青藏高原东部等区域仅高于小雪降雪量,而在黄-淮地区仅次于暴雪降雪量。④ 降雪年内分配在东北北部、西北、新疆、青藏高原东部等地区都呈双峰型,最多雪时节在早冬和晚冬、早春,隆冬时节并不是降雪最多时间,黄-淮和东南地区呈单峰型,东南地区峰值更陡。⑤ 总降雪日数和除暴雪外的各等级降雪日数与地理位置关系较明显,在中国东部主要随着纬度升高增加,在中国西部随海拔高度增加而增加;随着纬度升高,东部和西部的总降雪强度都减小,西部的小雪强度也减小。

Using a total of 37 a high mountain snow observation data from 32 national meteorological stations in the Qinling Mountains in Shaanxi Province from 1980 through 2016， statistical analysis has been done of the regional alpine snow cover processes with 5 or more consecutive days with snow cover more than or equal to 3 days. The regional stable alpine snow cover processes of long-term alpine snow cover process with 5 or more weather stations with continuous snow cover days greater than or equal to 20 days， 5 or more weather stations with continuous snow cover days greater than or equal to 60 days， have been studied also. The results show that in the Qinling Mountains from 1980 through 2016 there were 114 regional alpine snow cover events， including 29 regional long-term alpine snow cover events and 6 regional stable alpine snow cover events. Regional alpine snow cover events occurred from November to April （the cold season）， among them 60% occurring in winter （December to February）. There were 6 regional stable snow cover events with an average of 73.7 days per snow cover event. The longest regional stable snow cover event， totally lasting 81 days， occurred from November 7， 2003 to April 18， 2004. The number of regional alpine snow events was the highest in the 1980—1989 （44 times）， followed by 1990—1999 and 2000—2009 （29 times each）， and the least one in 2010—2016 （12 times）. The average temperature and precipitation in winter had significantly correlated with the atmospheric circulation index， and had significantly negatively correlated with the Tibetan Plateau Index， the Indo-Burma Basin Intensity Index， the Antarctic Oscillation Index and the Western Pacific Subtropical High West Point Index. Beside， they had clearly positively correlated with the Pacific Trade Wind Index and the Asian Polar Vortex Area Index. In the context of climate warming， the regional snow cover events in the Qinling Mountains had showed a significant reduction trend in 1980—2016， with a reduction rate of -0.8 times/10a. The average number of long-term incidents in various epochs was once a year in the 1980s， 0.9 times a year in the 1990s and only 0.4 times per year in the 1910s. After 2004， there was no regional stable mountain snow cover event in the Qinling Mountains. In 1980—2016， there were 161 snow events in Taibai Station， including 58 long-term snow cover events and 37 snow-stabilizing events. At the 37 a， the regional alpine snow cover events at Taibai Station had showed a decreasing trend with a reduction rate of -0.47 times per 10 years.

为了研究秦岭高山积雪事件变化特点，利用秦岭陕西境内32个国家气象站1980—2016年度共37年高山积雪观测记录，统计分析5个或者5个以上气象站连续积雪日数≥3 d的区域性高山积雪事件、5个或者5个以上气象站连续积雪日数≥20 d的区域性长时间高山积雪事件、5个或者5个以上气象站连续积雪日数≥60 d的区域性稳定高山积雪事件，结果表明：秦岭1980—2016年度共出现区域性高山积雪事件114次，其中包含区域性长时间高山积雪事件29次，区域性稳定高山积雪事件6次。区域性高山积雪事件均发生在冷季（11月—次年4月），其中60%的区域性高山积雪事件发生在冬季（12月—次年2月）。6次区域性稳定高山积雪事件都发生在12月—次年3月。区域性高山积雪事件1980—1989年度最多（44次），其次是1990—1999年度和2000—2009年度（各29次），2010—2016年度最少（12次）。1980—2016年度，区域性高山积雪事件呈现明显减少趋势（通过α=0.01的信度检验），减幅为-0.86次?（10a）^-1，区域性高山稳定积雪事件次数与冷季平均气温呈显著的负相关关系（通过α=0.01的信度检验）。

The basic variation characteristics of snow cover in the Mount Hua and its relationship to temperature and precipitation were analyzed by using linear tendency estimate， M-K inspection， correlation analysis and path analysis， based on the snow cover observation data in the Mount Hua weather station from 1953 to 2016 and satellite remote sensing data from 1989 to 2016. The results demonstrated that： （1） Average days of snow cover were 78.5 d. Snow cover mainly occurred from October to the following May. The beginning date of snow cover had delayed； the ending date of snow cover had advanced； the days from the beginning to the ending had decreased； the days of snow cover had decreased significantly with the rates of winter half year and winter from 1953 to 2016； the annual， winter half year and winter snow days had significantly reduced by 8.3 d?（10a）-1， 7.6 d?（10a）-1， 4.7 d?（10a）-1， respectively. There was no significant decreasing trend of annual maximum snow depth and annual accumulated snow depth had decreased significantly with the rate of 88.2 cm?（10a）-1 from 1981 to 2016. Monthly decreasing trend of snow cover days， maximum snow depth and accumulated snow depth were the most significant in March during the 36 years. There was no obvious decrease of snow cover area， light snow cover area and deep snow cover area in the Mount Hua from 1989 to 2016. （2） From 1953 to 2016 average temperature had risen， precipitation had decreased， the days of snow cover had a significant negative correlation with average temperature and a significant positive correlation with precipitation in the Mount Hua. Temperature was the key factor impacting snow cover days in year， winter half year and winter. The annual， winter half year and winter days of snow cover all had changed abruptly in the years close to the year that average temperature changed abruptly. （3） Average temperature and precipitation had significantly correlated with atmospheric circulation index in winter half year and in winter from 1953 to 2016. The snow cover days of winter and winter half year had negatively correlated with atmospheric circulation indexes， such as Tibet Plateau Region index， India-Burma Trough intensity index， Antarctic Oscillation and Western Pacific Sub Tropical High Western Ridge Point index， and had positively correlated with East Pacific 850 hPa Trade Wind index and Asia Polar Vortex area index significantly.

<p>Snowfall in China has significant uncertainty and spatial differences, and its response to climate change is complex. Therefore, it is of great scientific significance to analyze the characteristics of snowfall along the north-south transition zone of the Qinling Mountains. Based on the daily meteorological data of 72 stations, we analyzed the type of snowfall (rain, snow, and sleet) along the northern and southern boundaries of the Qinling Mountains in the cold season (occurred from November to the following May) during 1970/1971-2018/2019. The study focuses on the spatiotemporal variation of snowfall, and the response relationship between snowfall, air temperature and wet bulb temperature was analyzed. According to the continuous change characteristics of the sea surface temperature anomaly in summer, autumn and winter Ni&ntilde;o 3.4, we further identified the 4 types ofdifferent development El Ni&ntilde;o-Southern Oscillation (ENSO) events to reveal that the relationships between different developing ENSO events and snowfall anomalies. The results showed that 1) Snowfall in the north and south of the Qinling Mountains showed a fluctuating deceasing trend in winter. Compared with the average snowfall in 1970-2000, there was a trend that in the south slope of the Qinling Mountains (warm temperate zone) decreased by 3.1 mm in recent 29 years, which was basically equal to the snowfall in the Guanzhong Plain (17.1 mm). 2) Considering the isoline of 1000 m as the dividing boundary, the snowfall in the low-altitude valley (<1000 m) did not show an obvious changing trend, while the snowfall in the high-altitude mountain area (>1000 m) showed a significant decrease. 3) As for the response relationship between snowfall and temperature, the air temperature or wet bulb temperature increased by 1.0℃ from November to March of the second year, and the snowfall in alpine area of the Qinling Mountains decreased by 23.1 mm and 24.3 mm respectively. However, the air temperature or wet bulb temperature increases by 1.0℃ from north to south, the snowfall decrease by 3.0 mm and 2.8 mm in zonality, respectively. 4) The analysis showed that from the perspective of disaster-forming factors, the types of ENSO events affecting the snow anomaly to the north and south of the Qinling Mountains are mainly successive El Ni&ntilde;o events. When the successive El Ni&ntilde;o/La Ni&ntilde;a events occurred, anomalously more snowfall in Guanzhong Plain. When the developing La Ni&ntilde;a events occurred, anomalously less snowfall in the Qinling and Dabashan Moutains. When the developing El Ni&ntilde;o events occurred, the below normal snowfall in eastern of region and Guanzhong Plain.</p>

基于72个气象站点逐日观测数据，对1970/1971—2018/2019年秦岭南北冷季（11月~次年5月）降水类型（降雪、降雨和雨夹雪）进行识别；重点关注降雪时空变化特征，探讨降雪与气温、湿球温度的响应关系；依据“夏季-秋季-冬季”Ni&ntilde;o 3.4区海温异常状态，细化4种不同发展过程的厄尔尼诺-南方涛动（ENSO）事件，分析降雪异常与不同ENSO事件的对应关系。结果表明：① 相比气候平均态（1970—2000年），1990—2018年，秦岭南坡（山地暖温带）降雪量下降了3.1 mm，基本与关中平原降雪量（17.1 mm）持平；② 空间趋势上，低海拔河谷地带降雪量以年代波动为主，山地高海拔地区为降雪下降区；③ 秦岭高山地区气温或湿球温度每升高1.0℃，降雪量分别下降23.1 mm和24.3 mm；从地带性角度分析，由北向南气温或湿球温度每升高1.0℃，秦岭南北降雪量分别下降3.0 mm和2.8 mm；④ 当厄尔尼诺/拉尼娜持续型发生时，关中平原降雪异常偏多；当拉尼娜发展型发生时，秦岭山地和大巴山区降雪异常偏少。当厄尔尼诺发展型发生时，秦岭南北降雪异常呈现“东西分异”，秦岭山地东部和关中平原为降雪异常偏少区。

As a huge mountain range in the North-South boundary of China, the Qinling-Daba Mountains are characterized by prominent mass elevation effect (MEE) and play an important role in the azonality pattern of climate and ecology in central China. The essence of the MEE is the warming effect of mountains, as huge mountain and plateau absorbs more solar radiation compared with the free atmosphere of the same altitude and then releases in the form of long-wave radiation external heat, making the internal mountain temperature higher than the external in the same altitude of free atmosphere. Therefore, the temperature difference between the mountain interior and the periphery has been suggested as an appropriate indicator to quantify the MEE. To analyze MEE of the Qinling-Daba Mountains, MODIS land surface temperature (LST) data, STRM-1 DEM data and observation data from 118 meteorological stations were combined to estimate monthly mean air temperature by ordinary linear regression (OLS) and geographical weighted regression (GWR) methods in the Qinling-Daba Mountains. Air temperature at an altitude of 1500 m (the average elevation of the Qinling-Daba Mountains) in the interior of the Qinling-Daba Mountains was calculated by a fixed lapse rate and compared with that in the periphery. The results show that: (1) Compared with OLS method, the GWR method has higher accuracy with R 2 > 0.89 and the root mean squared error (RMSE) = 0.68-0.98 ℃. (2) The monthly mean temperature at the altitude of 1500 m estimated by GWR presents a gradual upward trend from east to west. In the western Qinling Mountains, the annual average temperature and temperature in July at the altitude of 1500 m increase about 6 ℃ and 4.5 ℃ compared with the eastern flank, while in the Daba Mountains, they are about 8°C and 5 ℃ higher in the west than in the east. (3) From south to north, with the Hanjiang River as the boundary, the monthly mean temperature at the altitude of 1500 m tends to rise from the rim of the mountains to the ridge. (4) Compared with the lower valleys in Hanzhong and western Henan, the monthly mean temperatures at the altitude of 1500 m are approximately 3.85-9.28 ℃, 1.49-3.34 ℃ and 0.43-3.05 ℃ higher those in the great undulating high mountains in the western Qinling-Daba Mountains, the great undulating middle-high mountains in the Qinling Mountains and the great undulating middle mountains in the Daba Mountains, respectively, and the average temperature difference is about 3.50 ℃. This shows that the MEE of the Qinling-Daba Mountains is obvious and its impact on the distribution patterns of mountain climate and ecology needs to be further studied.

秦巴山地作为横亘在中国南北过渡带的巨大山脉,其山体效应对中国中部植被和气候的非地带性分布产生了重要的影响,山体内外同海拔的温差是表征山体效应大小较为理想的指标。本研究结合MODIS地表温度（LST）数据、STRM-1 DEM数据和秦巴山地的118个气象站点的观测数据,分别采用普通线性回归（OLS）和地理加权回归（GWR）两种分析方法对秦巴山地的气温进行估算,在此基础上将秦巴山地各月气温转换为同海拔（1500 m,秦巴山地平均海拔）气温,对比分析秦巴山地的山体效应。结果表明：① 相比OLS分析,GWR分析方法的精度更高,各月回归模型的R ²均在0.89以上,均方根误差（RMSE）在0.68~0.98 ℃之间。② 利用GWR估算得到的同海拔气温,从东向西随海拔升高呈现了明显的升高的趋势,秦岭西部山地比东段升高约6 ℃和4.5 ℃;大巴山西部山地年均和7月份同海拔的气温较东段升高约8 ℃和5 ℃。③ 从南向北,以汉江为分界,秦岭与大巴山的同海拔的气温均呈现出由山体边缘向内部升高的趋势。④ 秦巴山地西部大起伏高山,秦岭大起伏高中山和大巴山大起伏中山,相比豫西汉中中山谷地,各月均同海拔气温分别升高了约3.85~9.28 ℃、1.49~3.34 ℃和0.43~3.05 ℃,平均温差约为3.50 ℃,说明秦巴山地大起伏中高山的山体效应十分明显。

秦巴山地垂直带谱结构的空间分异对于揭示秦巴山地地域结构复杂性和过渡性、探索中国复杂的生态地理格局具有重要的意义。本文从文献中搜集了秦巴山地33个山地垂直带谱,建立了秦巴山地数字垂直带谱体系,从纬向、经向和坡向3个维度分析了山地垂直带谱的结构、特征、数量、高度以及分布模式。结果表明：① 纬向上从南向北基带由亚热带常绿阔叶林带逐渐转变为暖温带落叶阔叶林带;垂直带结构由复杂逐渐变得简单;优势带由山地针阔混交林和山地常绿落叶阔叶混交林转变为山地落叶阔叶林带;② 经向上山地垂直带结构呈现复杂—简单—复杂的特征;常绿落叶阔叶混交林带和山地落叶阔叶林带的海拔呈现了二次曲线分布模式;山地针阔混交林带的海拔则呈现显著的线性降低趋势;③ 坡向方面,秦岭北坡和南坡基带均为暖温带落叶阔叶林带,但南坡含有常绿成分;大巴山北坡为亚热带常绿落叶阔叶混交林带,大巴山南坡为亚热带常绿阔叶林带;秦岭和大巴山北坡优势带类似,均为山地针阔混交林带或山地落叶阔叶林带,但大巴山南坡具有独特的山地常绿落叶阔叶混交林优势带,这表明了大巴山比秦岭更适合作为暖温带和北亚热带的分界线,但是未来还需使用土壤和气候指标进行系统的分析。

Mountain altitudinal belts are the miniature of horizontal differentiation and succession of climatic and vegetational zonation. However, altitudinal belts' vertical range, transition model, inner structure and combining pattern vary from place to place. In Mt. Taibai of the central section of China's north-south transitional zone, we have found an altitudinal belt with the largest range in the world, namely, the montane deciduous broad-leaved forest, which extends continuously from the mountain base to about 2800 m, including basal oak belt, typical oak belt of two sub-belts and cold-tolerant pioneer birch belt of two sub-belts, which could otherwise develop independently. Characterized by a "three layers and five sub-belts" structure, this "super altitudinal belt" is much vertically broader than the threshold of 1000 m for normal altitudinal belts. Its formation is closely related with its transitional geographic location, integral spectrum of altitudinal belts in central Qinling Mountains, rich and diverse species of deciduous woody plants, and their strong competitiveness. The finding of the super altitudinal belt has multiple significance: Its existence is another significant physio-geographic feature of China's north-south transitional zone; it shows that an altitudinal belt may have rather complex inner structure and broad vertical range in some special mountain environment. This broadens our understanding of altitudinal belt structures and their mechanisms, and is of great significance for developing structural theory for montane altitudinal belts. This finding also demonstrates that there are many big questions for us to explore and study in the north-south transitional zone, and it is expected that our finding could trigger in-depth study of local climate and biodiversity responsible for the formation of this super belt, and of the complex structure and ecological effect of China's north-south transitional zone.

山地垂直带谱是气候和植被水平地带变化和更替的缩影,垂直带的带幅、带间过渡方式、带内结构和垂直带组合方式都表现出高度的异质性和复杂性。本文发现在中国南北过渡带中部太白山发育了世界上最宽的山地垂直带&#x02014;&#x02014;山地落叶阔叶林垂直带。该垂直带从基带到典型垂直带再到先锋性垂直带皆为山地落叶阔叶林,3种本来可以独立存在的垂直带,连续分布形成了包含3个栎林亚带、2个桦林亚带的&#x0201c;三层五亚带&#x0201d;超级垂直带,远远超过正常情况下山地垂直带1000 m的阈值,且其上限达到了海拔2800 m。它的形成与秦岭所处的过渡性地理位置、秦岭中部垂直带谱的完整性、丰富的落叶木本植物种群及其形成的强大群落竞争优势等因素紧密相关。超级垂直带的发现有多方面的意义：它是中国南北过渡带又一重要的标志性自然地理特征;它表明山地垂直带在特殊的山地环境中可以具有非常复杂的内部结构和宽大带幅,这扩展了我们对山地垂直带谱结构及机理认识的广度,对于创建山地垂直带谱结构理论具有十分重要的意义;超级垂直带的发现,也说明中国南北过渡带还有很多科学内容有待我们去探索和发现,希望本文能起到抛砖引玉的作用,引起学界对超级垂直带形成的气候和生物多样性因素、地理过渡带的结构和生态效应等重大问题进行深入研究。

A clear understanding of the precipitation variation patterns at high altitudes of the Qinling Mountains is a prerequisite for an in-depth understanding of the characteristics of this mountain range as China's north-south transitional zone and its important role of water resources in the Middle Route of South-North Water Transfer Project. However, understanding the precipitation changes in the mountainous areas of the Qinling Mountains has been hindered by limited effective precipitation observation data in these mountainous areas. An analysis of precipitation data measured from June 1, 2018, to May 31, 2019, at an altitude of 3760 m at the Mount Taibai of the Qinling Mountains revealed that the annual precipitation at this altitude can reach 1300 mm, which is much more than the 600-800 mm annual precipitation recorded in the Hanjiang Basin and the Guanzhong Plain. On this basis, the persistence of annual and seasonal precipitation patterns in the Qinling Mountains was examined by kriging, inverse distance weighted interpolation, and ANUSPLIN methods, as well as GPM-corrected data (GPM-cal) and ERA5 reanalysis data. Accurate high-altitude precipitation values could not be obtained using kriging and IDW. However, GPM-cal, ANUSPLIN, and ERA5 data could more accurately portray the variation of annual precipitation with topography in the Qinling Mountains. An analysis of water vapor fluxes showed that the Mount Taibai has significant blocking, forcing, and intercepting effects on southward moist airflow below the 600 hPa height owing to its high terrains, making its southern slope a regional center of high precipitation values. Combining high mountain precipitation observations, ANUSPLIN, multi-source grid point information, and data correction methods is an effective way to understand precipitation formation and variation in the Qinling Mountains.

明确秦岭高海拔山区降水的变化规律,是深入理解秦岭作为中国南北地理过渡带特征、认识秦岭水资源在南水北调中线工程中重要作用的前提。但秦岭高海拔地区长期缺乏有效的降水观测数据,导致对其降水变化缺乏了解。利用2018年6月1日&#x02014;2019年5月31日秦岭太白山海拔3760 m实测降水数据,发现在秦岭海拔3760 m处年降水量可达1300 mm,远高于汉江盆地和关中平原600~800 mm的年降水量。在此基础上,检验了克里金（Kriging）、反距离加权（IDW）和薄盘样条（ANUSPLIN）插值方法,以及GPM修正数据（GPM-cal）和ERA5再分析资料对秦岭中部山地年和季节降水空间模态的再现效果,各方案均能揭示秦岭高山区是降水高值中心,且降水随海拔的升高而增大,但利用克里金、反距离加权插值方案不能得到准确的高海拔降水值,与此相比,GPM-cal数据、薄盘样条插值与ERA5资料能较准确刻画秦岭中部山地年降水量随地形的变化。水汽通量分析显示,秦岭凭借高大地形对600 hPa高度以下的南来湿润气流具有明显的阻挡、强迫和拦截作用,使其南坡成为区域降水高值中心。结合高山区降水观测、薄盘样条插值、多源格点资料和数据修正方法,是认识秦岭山地降水形成和变化的有效途径。

The responses of atmospheric variability to Tibetan Plateau (TP) snow cover (TPSC) at seasonal, interannual and decadal time scales have been extensively investigated. However, the atmospheric response to faster subseasonal variability of TPSC has been largely ignored. Here, we show that the subseasonal variability of TPSC, as revealed by daily data, is closely related to the subsequent East Asian atmospheric circulation at medium-range time scales (approximately 3-8 days later) during wintertime. TPSC acts as an elevated cooling source in the middle troposphere during wintertime and rapidly modulates the land surface thermal conditions over the TP. When TPSC is high, the upper-level geopotential height is lower, and the East Asia upper-level westerly jet stream is stronger. This finding improves our understanding of the influence of TPSC at multiple time scales. Furthermore, our work highlights the need to understand how atmospheric variability is rapidly modulated by fast snow cover changes.

With the advances in research of the Tibetan Plateau (TP) and the deep understanding of multi-disciplinary research, coupled with the progress of geographic big-data, earth observation science and technology, this research systematically discussed the principles, methods and basis for determining the boundaries of the TP. It analyzed the macro landform structures (plateau surface, low basin and deep-cut valley lowland on the edge of the TP) within the TP and the fundamental characteristics of the geographic units' composition in TP's surrounding areas. Based on the high resolution remote sensing images, DEM data and geomorphologic maps etc., the boundary of TP with a 1:1000000 scale is defined through a comparative study of geomorphological features with the support of Arcmap 10.5. The results show that the Tibetan Plateau stretches from the foot of the Himalayas in the south to the foot of the Kunlun Mountains and the Qilian Mountains in the north, with a total length of 1560 km. While it spans about 3360 km from the Hindu Kush Mountains and the Pamir Plateau in the west, to the eastern foot of Hengduan Mountains in the east. The TP, lying between 25°59′26″N-40°1′6″N and 67°40′37″E-104°40′43″E, covers a total area of 3083.44 × 103 km2, with an average altitude of 4320 m. Geographically, the TP is located in Southwest China and eight other countries including India, Pakistan, Tajikistan, Afghanistan, Nepal, Bhutan, Myanmar and Kyrgyzstan. The TP in Chinese section has an area of 2580.90 × 10 3 km2, accounting for around 83.7% of the total area, with an average altitude of 4400 m. In China's part, the TP spans in six provincial-level regions: Tibet Autonomous Region (TAR), Qinghai province, Gansu province, Sichuan province, Yunnan province and Xinjiang Uygur Autonomous Region. Among them, the main parts of TAR and Qinghai are the major section of the TP, which accounted for 60.6% of the total area of the plateau.

伴随青藏高原研究的深入,高原内外多学科研究程度和认识的提高,及地理大数据、地球观测科学和技术的进步,对青藏高原范围提出了新的要求。本研究系统论述了确定青藏高原范围的原则、依据和方法,分析探讨了高原地貌宏观结构（高原面、高原内低盆地与高原边缘河谷低地等）和周围边界各自然地段构成的基本特征。采用ArcMap软件,通过遥感影像和DEM数据及新资料对高原地貌比较研究,实现了1：100万比例尺地图精度的青藏高原范围的界定。研究表明,青藏高原北起西昆仑山-祁连山山脉北麓,南抵喜马拉雅山等山脉南麓,南北最宽达1560 km;西自兴都库什山脉和帕米尔高原西缘,东抵横断山等山脉东缘,东西最长约3360 km;范围为25°59′26″N~40°1′6″N、67°40′37″E~104°40′43″E,总面积为308.34万km²,平均海拔约4320 m。在行政区域上,青藏高原分布于中国、印度、巴基斯坦、塔吉克斯坦、阿富汗、尼泊尔、不丹、缅甸、吉尔吉斯斯坦等9个国家。其中中国境内的青藏高原面积约258.09万km²（占高原总面积的83.7%）,平均海拔约4400 m,分布在西藏、青海、甘肃、四川、云南和新疆等6省区,西藏和青海两省区主体分布在高原范围内（约占高原总面积的60.6%）。