基于气象数据和遥感影像的太白山气温直减率

基于太白山内2013—2014年气象站点实测数据和DEM分析太白山南北坡不同时间尺度的气温直减率,并利用辐射传输方程法针对Landsat 8影像数据反演地表温度场,通过窗口差分法推导太白山气温直减率场及其特征。研究表明:1实测法计算太白山年均气温直减率北坡为0.515℃/(100 m),南坡为0.505℃/(100 m);10月直减率北坡为0.505℃/(100 m),南坡为0.480℃/(100 m);春、夏季气温直减率较大,北坡大于南坡,而冬季较小,北坡小于南坡。2采用辐射传输方程法针对Landsat 8 TIRS 10反演地表温度具有较高置信度,获取10月北坡气温直减率为0.611℃/(100 m),南坡为0.502℃/(100 m)。3气温直减率在山脊和山谷附近表现出高直减率条带;海拔对太白山气温直减率的影响高于坡向,高、中、低海拔区气温直减率分别为0.913℃/(100 m)、0.471℃/(100m)、0.755℃/(100 m);坡向对气温直减率分布的影响表现为随阳坡至阴坡而逐渐变大,依次为0.515℃/(100m)、0.541℃/(100 m)、0.617℃/(100 m)。     

岷江上游雨季南北坡小气候特征比较

利用岷江上游茂县大沟不同坡向的小气候观测资料,探讨了该地区地雨季的太阳辐射、气温、地表温、水汽压、相对湿度、风速等小气候要素的南北坡特征及其与谷底的差异。通过比较分析得出:在雨季南坡的太阳辐射量大于北坡和谷底;南北坡气温、水汽压、相对湿度在昼间有一定差异;北坡气温略高于南坡;气温垂直递减率南坡(O.71℃/100m)大于北坡(O.61℃/100m)。水汽压为北坡<南坡<谷底;而相对湿度为谷底<北坡<南坡,北坡和谷底的太阳辐射、气温、地表温、水汽压最大值比南坡早出现1h。南北坡风速均大于谷底,而南坡风速又大于北坡。由此可见,岷江上游地区即使在雨季,山地对局地气候仍有一定影响。     

1960-2013年秦岭陕西段南北坡极端气温变化空间差异

作为气候变化研究的重要内容,极端气温研究对生态环境保护和灾害事件预警具有重要意义。根据1960-2013年秦岭32个气象站点的逐日气温资料,采用RClimDex软件、克里格插值法、线性倾向估计法和相关性分析法,研究秦岭山地陕西段（简称秦岭）气温的空间分布特点,以及极端气温的空间变化特征。结果表明：① 1960-2013年秦岭年平均气温、年最高气温和年最低气温分别为10.48 ℃、16.44 ℃和6.18 ℃;秦岭北坡气温在低海拔区高于南坡,在中、高海拔区低于南坡;南北坡的气温差值在低海拔区域最小,中海拔区域最大。② 秦岭极端气温的频率、强度和持续时间均表现为增加趋势,极端气温变化的敏感区域位于南坡的镇安、柞水和北坡的周至、户县。③ 秦岭北坡极端气温频率的变化更明显,秦岭南坡极端气温强度和持续时间的变化更明显;且北坡的增温主要发生在夜间,南坡的增温主要发生在白昼。④ 秦岭极端气温的变暖速率随海拔升高而增大,高海拔区域极端气温频率和强度的变化最明显,中海拔区域极端气温持续时间的变化最明显。     

念青唐古拉山西段高海拔陆-气系统水热特征

利用实测的念青唐古拉山脉南坡海拔4800 m和5333 m,以及北坡5400 m的土壤温、湿度和地表气温一年的数据,对该地区水热特征作了初步分析,结果表明：地、气温差冬季大夏季小,且相对邻近地区偏大。同时地温与气温有良好相关,但随深度增加,相关系数减小。土壤热力梯度的方向低海拔由下而上,高海拔则相反。土壤湿度高海拔略大于低海拔,干季和湿季分别受冻融过程和印度洋季风降水影响。高海拔冻结期比低海拔长3~4个月,其下层土壤湿度在冻融交替期表现一个剧烈的跃变现象。念青唐古拉山南、北坡海拔相近区域相同层位土壤温度差异在0~8℃之间。南坡土壤温度年平均高于北坡3~4℃。南坡冻结比北坡晚而融化比北坡早,上层土壤湿度南坡小于北坡,而下层土壤湿度南坡大于北坡,南北坡水热过程存在明显差异。     

秦岭陕西段南北坡植被对干湿变化响应敏感性及空间差异

秦岭位于暖温带与亚热带交界处,也是中国南北地理分界线,秦岭南北坡植被对干湿变化响应敏感性,可以折射出暖温带、亚热带地区主要植被类型对干湿变化的响应规律和机制特征,对深入理解不同气候带植被变化规律具有重要意义。本文利用秦岭山地32个气象站点的气象数据和MODIS NDVI时间序列数据集,探讨了2000—2018年秦岭南北坡NDVI和SPEI时空变化特征,揭示了南北坡植被对干湿变化响应敏感性及其空间差异。结果表明：① 2000—2018年秦岭植被覆盖情况整体显著改善,但秦岭南坡NDVI上升幅度和面积占比均高于北坡,南坡植被比北坡改善情况好。秦岭湿润化趋势不显著,但秦岭北坡湿润化速率和面积占比均大于南坡。② 秦岭北坡植被比南坡植被更易受干湿变化影响,秦岭北坡植被对3—6月总体干湿变化最为敏感,南坡植被对3—5月（春季）干湿变化最为敏感。秦岭南北坡植被主要受3~7个月尺度干湿变化影响,对11~12个月尺度的干湿变化响应较弱。③ 秦岭有90.34%的区域NDVI与SPEI呈正相关,大部分地区春季湿润化能促进全年植被生长;随海拔上升,植被对干湿变化响应敏感性先上升再下降,海拔800~1200 m是植被响应最敏感的海拔段,海拔1200~3000 m随海拔上升植被响应敏感性下降;南北坡草丛均是对干湿变化响应最为敏感的植被类型,但秦岭北坡多数植被类型对干湿变化响应比南坡敏感。     

黄河源区多年冻土温度及厚度研究新进展

利用新布设的冻土孔及原有冻土资料,分析黄河源区冻土温度和厚度的空间分布。源区实测多年冻土年均地温最低为-1.81℃,冻土最厚74 m,均位于巴颜喀拉山北坡的查拉坪。214国道(K445-K604段)沿线多为高温多年冻土(年均地温>-1℃),但巴山北坡海拔4 520 m、布青山海拔4 300 m以上,年均地温低于-0.5℃。巴山北坡海拔4 610 m、布青山海拔4 420 m以上,年均地温低于-1℃。巴山北坡海拔每升高100 m,年均地温减少0.47~0.75℃,冻土厚度增加16~25 m;纬度向北增加1°,年均地温减少0.85℃,冻土厚度增加20~30 m。     

豫西山地植被NDVI及其气候响应的多维变化

豫西山地是秦岭山系在河南境内的余脉,处于亚热带向暖温带的过渡区域,是气候变化的敏感区。利用S-G滤波算法重构2000-2013年MODIS-NDVI时序影像,结合DEM、气温和降水数据,运用趋势分析、相关性分析等方法探讨豫西山地NDVI及其气候响应的多维变化。结果表明:(1)14年来豫西山地NDVI呈增长态势,增速为0.041/10a。NDVI值随山地海拔升高先增后降,随坡度增加而增大,在各坡向的分布相差不大。(2)植被在1100 m海拔区恢复概率最高,在1700 m区域退化概率最高;在10°~20°坡度区域恢复概率最高,在0°~5°区域退化概率最高;坡向对植被变化的分异作用不明显。(3)不同海拔、坡度、坡向上的植被所受影响因素不同,高海拔区植被动态主要受降水控制;不同坡度上的植被NDVI与气温的相关性均大于与降水的;在不同坡向上差异不明显。(4)崤山、熊耳山、伏牛山三大山脉北坡NDVI增速均大于南坡;北坡植被对降水变化较敏感,而南坡植被对气温变化较敏感。这些都是在全球变化背景下该区生态环境响应的重要信号,反映了过渡带生态响应因子对山地生态系统的重要性。     

巴颜喀拉山青康公路沿线多年冻土和活动层分布特征及影响因素

巴颜喀拉山是较典型的高海拔多年冻土区。南、北坡迥异的气候、土壤及地表景观控制和影响其多年冻土空间分布。2008~2012年冻土调查及测温资料表明,该山以高温冻土(>-1℃)为主。海拔是冻土主要影响因素。年均地温随海拔升高而降低的高程递减率在北坡6℃/km,南坡4℃/km。北坡查拉坪及巴颜喀拉山口一带,活动层厚度约1 m,活动层随海拔降低而增厚;南坡活动层厚度受局地因素影响较大,与海拔无明显相关。     

秦岭山地气候变化的地形效应

研究不同地形下的山地气候变化对于植被生长、不同动物种群的生存习性及对气候的应激性有重要意义。本文基于陕西秦岭地区1959—2016年32个国家站的日气温和降水资料,采用Anusplin插值法、标准化降水蒸散指数(SPEI)、稳健回归和Theil-sen回归法等方法分析了山区地形对气候变化的影响。结论如下:(1)58年来秦岭四个坡向上年均温度随着海拔的升高呈现显著下降趋势,年降水随着海拔的升高呈现不同程度的上升趋势。温度随坡度的增加表现出下降趋势;除秦岭南坡西段外,降水随着坡度的增加呈现出上升趋势,但均不显著。(2)年尺度上,秦岭山地南坡和南坡东段的气温呈显著增温趋势,南坡西段和北坡呈不显著增温趋势;四个方向上的降水均呈显著下降趋势。秦岭山地四个方向上的干湿等级为正常,北坡和南坡西段的干湿状况一致,58年年均SPEI均为0.07,南坡东段较暖湿(0.08),南坡较暖干(0.05)。(3)季节尺度上,秦岭山地四个方向上除了夏季外,其他季节的气温均表现出不同程度的升温趋势,降水均呈下降趋势。秦岭四个方向上四季干湿变化属于正常等级。秦岭北坡出现春季干暖化趋势;南坡秋季较暖湿;南坡东段和西段的冬季呈暖湿化特征;南坡西段夏季呈现暖干化特征。     

豫西山地植被NDVI及其气候响应的多维变化北大核心CSCDCSSCI

豫西山地是秦岭山系在河南境内的余脉,处于亚热带向暖温带的过渡区域,是气候变化的敏感区。利用S-G滤波算法重构2000-2013年MODIS-NDVI时序影像,结合DEM、气温和降水数据,运用趋势分析、相关性分析等方法探讨豫西山地NDVI及其气候响应的多维变化。结果表明:(1)14年来豫西山地NDVI呈增长态势,增速为0.041/10a。NDVI值随山地海拔升高先增后降,随坡度增加而增大,在各坡向的分布相差不大。(2)植被在<1100 m海拔区恢复概率最高,在>1700 m区域退化概率最高;在10°~20°坡度区域恢复概率最高,在0°~5°区域退化概率最高;坡向对植被变化的分异作用不明显。(3)不同海拔、坡度、坡向上的植被所受影响因素不同,高海拔区植被动态主要受降水控制;不同坡度上的植被NDVI与气温的相关性均大于与降水的;在不同坡向上差异不明显。(4)崤山、熊耳山、伏牛山三大山脉北坡NDVI增速均大于南坡;北坡植被对降水变化较敏感,而南坡植被对气温变化较敏感。这些都是在全球变化背景下该区生态环境响应的重要信号,反映了过渡带生态响应因子对山地生态系统的重要性。     

Vertical differentiation of land cover in the central Himalayas

Characterized by obvious altitudinal variation, habitat complexity, and diversity in land cover, the Mt. Qomolangma region within the central Himalayas is one of the most sensitive areas to climate change in the world. At the same time, because the Mt. Qomolangma region possesses the most complete natural vertical spectrum in the world, it is also an ideal place to study the vertical structure of alpine land cover. In this study, land cover data for 2010 along with digital elevation model data were used to define three methods for dividing the northern and southern slopes in the Mt. Qomolangma region, i.e., the ridgeline method, the sample transect method, and the sector method. The altitudinal distributions of different land cover types were then investigated for both the northern and southern slopes of the Mt. Qomolangma region by using the above three division methods along with Arc GIS and MATLAB tools. The results indicate that the land cover in the study region was characterized by obviously vertical zonation with the south-six and north-four pattern of vertical spectrum that reflected both the natural vertical structure of vegetation and the effects of human activities. From low to high elevation, the main land cover types were forests, grasslands, sparse vegetation, bare land, and glacier/snow cover. The compositions and distributions of land cover types differed significantly between the northern and southern slopes; the southern slope exhibited more complex land cover distributions with wider elevation ranges than the northern slope. The area proportion of each land cover type also varied with elevation. Accordingly, the vertical distribution patterns of different land cover types on the southern and northern slopes could be divided into four categories, with glaciers/snow cover, sparse vegetation, and grasslands conforming to unimodal distributions. The distribution of bare land followed a unimodal pattern on the southern slope but a bimodal pattern on the northern slope. Finally, the use of different slope division methods produced similar vertical belt structures on the southern slope but different ones on the northern slope. Among the three division methods, the sector method was better to reflect the natural distribution pattern of land cover.     

南迦巴瓦峰与托木尔峰山地垂直自然带的比较

南迦巴瓦峰地处喜马拉雅山脉东端雅鲁藏布江大拐弯的内侧，托木尔峰地处天山山脉的西端，二者独特的自然地理特征及其高大的山体为山地垂直自然带谱的形成和发展提从了十分有利的自然环境，发育了相当完整的山地垂直系列。比较二者的垂直带谱，可以发现无论在垂直带谱的形成条件，基带，性质和结构类型，还是景观特征，垂直分异影响因素及南北坡差异程度等方面，都存在着较大的差异。南峰垂直带谱为以森林－草原－荒漠土壤系列为特征的季风性湿润，法湿润带谱系统，垂直分异的主导因素为温度；托峰垂直带谱为以荒漠－－草原－荒漠土壤系列为特征的大陆性干旱带谱系统，垂直分异的主导因素为湿度。不同的垂直自然带特征决定了不同的资源开发利用和保护措施。     

喜马拉雅山脉中段土地覆被的垂直分异特征

喜马拉雅山脉中段的珠穆朗玛峰等地,海拔高差巨大、生境复杂多变、土地覆被类型多样且植被垂直带谱完整,是全球范围内研究土地覆被垂直变化的理想场所。本文基于30 m空间分辨率的土地覆被数据（2010年）和DEM数据,在ArcGIS和Matlab平台的支持下,提出并运用脊线法、样带法和扇区法3种山地南北坡划分方法,研究了喜马拉雅山土地覆被垂直分布与结构差异。结果表明：① 山地土地覆被分布具有明确的垂直地带性结构特征,喜马拉雅中部土地覆被垂直带谱为南六北四式,土地覆被垂直带谱中具有人类活动的特点。② 南北坡之间的土地覆被垂直带谱差异明显,南坡土地覆被类型完整多样,北坡相对简单;对同类型土地覆被而言,南坡较北坡分布高程低、幅度宽。③ 依据各类型分布面积比随海拔变化情况,土地覆被类型在南北坡上的垂直分布可分为4种模式：冰川雪被、稀疏植被和草地为单峰分布型,裸地为南单峰北双峰分布型。④ 3种划分方法中,南坡的土地覆被垂直带结构具有相似性,而北坡的土地覆被垂直带结构存在差异,扇区法较好地反映了土地覆被自然分布格局。     

太白山北坡成土因素及不同土壤垂直带谱的比较

在系统地考察太白山北坡地质、地貌、气候和植被等成土因素的基础上,总结和回顾了用土壤发生分类和土壤系统分类两种分类体系划定的太白山北坡土壤垂直带谱。根据最新的土壤系统分类,太白山北坡的土壤垂直带谱是:暗瘠寒冻雏形土(3500～3767m)———暗沃寒冻雏形土(3300～3500m)———酸性湿润雏形土(2500～3300m)———简育湿润淋溶土(1400～2500m)———简育干润淋溶土(<1400m)。分析、比较表明:两种体系有密切联系,均以成土因素为依据,建立在土壤发生学理论之上;与土壤地理发生分类相比,土壤系统分类用可以度量的诊断层和诊断特性进行土壤分类,不仅能够反映出山地土壤成土因素的垂直变化趋势,而且避免了太白山北坡土壤类型鉴定上的许多歧义。     

1971-2009 年珠穆朗玛峰地区尼泊尔境内气候变化

利用珠穆朗玛峰南坡尼泊尔境内(科西河流域) 的10 个气象站1971-2009 年月平均气温、月平均最高、最低气温和逐月降水资料, 采用线性趋势、Sen 斜率估计、Mann-Kendall 等方法分析区域气候变化状况及其时空特征, 并与珠穆朗玛峰北坡地区气候进行比较, 分析了珠穆朗玛峰地区气候变化的特征与趋势。结果表明:(1) 1971-2009 年间, 珠穆朗玛峰南坡年平均气温为20.0℃, 线性升温率为0.25℃/10a, 与北坡主要受年平均最低气温影响相反, 增幅主要受年平均最高气温升高的影响, 并且在1974 年及1992 年间出现两次显著增温, 增温特别明显的月份为2 月和9 月;(2) 该地区降水变化的局地性较强, 近40 年间年平均降水量为1729.01 mm, 年平均降水量以每年约4.27 mm的线性增幅有所增加, 但并不显著, 且降水月变化和季变化特征均不明显;(3) 由于珠穆朗玛峰南坡受到季风带来暖湿气流和喜马拉雅山阻挡的双重影响, 珠峰南坡的年平均降水量远高于北坡;(4) 珠穆朗玛峰南坡气温变暖的海拔依赖性并不明显, 且南坡地区的变暖趋势并没有北坡变暖趋势明显。     

Land Cover Status in the Koshi River Basin,Central Himalayas

The Koshi River Basin is in the middle of the Himalayas, a tributary of the Ganges River and a very important cross-border watershed. Across the basin there are large changes in altitude, habitat complexity, ecosystem integrity, land cover diversity and regional difference and this area is sensitive to global climate change. Based on Landsat TM images, vegetation mapping, field investigations and 3S technology, we compiled high-precision land cover data for the Koshi River Basin and analyzed current land cover characteristics. We found that from source to downstream, land cover in the Koshi River Basin in 2010 was composed of water body (glacier), bare land, sparse vegetation, grassland, wetland, shrubland, forest, cropland, water body (river or lake) and built-up areas. Among them, grassland, forest, bare land and cropland are the main types, accounting for 25.83%, 21.19%, 19.31% and 15.09% of the basin’s area respectively. The composition and structure of the Koshi River Basin land cover types are different between southern and northern slopes. The north slope is dominated by grassland, bare land and glacier; forest, bare land and glacier are mainly found on northern slopes. Northern slopes contain nearly seven times more grassland than southern slopes; while 97.13% of forest is located on southern slopes. Grassland area on northern slope is 6.67 times than on southern slope. The vertical distribution of major land cover types has obvious zonal characteristics. Land cover types from low to high altitudes are cropland, forest, Shrubland and mixed cropland, grassland, sparse vegetation, bare land and water bodies. These results provide a scientific basis for the study of land use and cover change in a critical region and will inform ecosystem protection, sustainability and management in this and other alpine transboundary basins.     

Sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics on the northern and southern slopes of the Qinling Mountains in Shaanxi province

The Qinling Mountains, located at the junction of warm temperate and subtropical zones, serve as the boundary between north and south China. Exploring the sensitivity of the response of vegetation there to hydrothermal dynamics elucidates the dynamics and mechanisms of the main vegetation types in the context of changes in temperature and moisture. Importance should be attached to changes in vegetation in different climate zones. To reveal the sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics, the spatio-temporal variation characteristics of the normalized vegetation index(NDVI) and the standardized precipitation evapotranspiration index(SPEI) on the northern and southern slopes of the Qinling Mountains from 2000 to 2018 are explored using the meteorological data of 32 meteorological stations and the MODIS NDVI datasets. The results show that: 1) The overall vegetation coverage of the Qinling Mountains improved significantly from 2000 to 2018. The NDVI rise rate and area ratio on the southern slope were higher than those on the northern slope, and the vegetation on the southern slope improved more than that on the northern slope. The Qinling Mountains showed an insignificant humidification trend. The humidification rate and humidification area of the northern slope were greater than those on the southern slope. 2) Vegetation on the northern slope of the Qinling Mountains was more sensitive to hydrothermal dynamics than that on the southern slope. Vegetation was most sensitive to hydrothermal dynamics from March to June on the northern slope, and from March to May(spring) on the southern slope. The vegetation on the northern and southern slopes was mainly affected by hydrothermal dynamics on a scale of 3–7 months, responding weakly to hydrothermal dynamics on a scale of 11–12 months. 3) Some 90.34% of NDVI and SPEI was positively correlated in the Qinling Mountains. Spring humidification in most parts of the study area promoted the growth of vegetation all the year round. The sensitivity of vegetation responses to hydrothermal dynamics with increasing altitude increased first and then decreased. Elevations of 800 to 1200 m were the most sensitive range for vegetation response to hydrothermal dynamics. The sensitivity of the vegetation response at elevations of 1200–3000 m decreased with increasing altitude. As regards to vegetation type, grass was most sensitive to hydrothermal dynamics on both the northern and southern slopes of the Qinling Mountains; but most other vegetation types on the northern slope were more sensitive to hydrothermal dynamics than those on the southern slope.     

Climate change on the southern slope of Mt. Qomolangma （Everest） Region in Nepal since 1971

Based on monthly mean, maximum, and minimum air temperature and monthly mean precipitation data from 10 meteorological stations on the southern slope of the Mt. Qomolangma region in Nepal between 1971 and 2009, the spatial and temporal characteristics of climatic change in this region were analyzed using climatic linear trend, Sen＇s Slope Estimates and Mann-Kendall Test analysis methods. This paper focuses only on the southern slope and attempts to compare the results with those from the northern slope to clarify the characteristics and trends of climatic change in the Mt. Qomolangma region. The results showed that： （1） between 1971 and 2009, the annual mean temperature in the study area was 20.0℃, the rising rate of annual mean temperature was 0.25℃/10a, and the temperature increases were highly influenced by the maximum temperature in this region. On the other hand, the temperature increases on the northern slope of Mt. Qomolangma region were highly influenced by the minimum temperature. In 1974 and 1992, the temperature rose noticeably in February and September in the southern region when the increment passed 0.9℃. （2） Precipitation had an asymmetric distribution; between 1971 and 2009, the annual precipitation was 1729.01 mm. In this region, precipitation showed an increasing trend of 4.27 mm/a, but this was not statistically significant. In addition, the increase in rainfall was mainly concentrated in the period from April to October, including the entire monsoon period （from June to September） when precipitation accounts for about 78.9% of the annual total. （3） The influence of altitude on climate warming was not clear in the southern region, whereas the trend of climate warming was obvious on the northern slope of Mt. Qomolangma. The annual mean precipitation in the southern region was much higher than that of the northern slope of the Mt. Qomolangma region. This shows the barrier effect of the Himalayas as a whole and Mt. Qomolangma in particular.