中国植被碳通量与氮沉降通量百年尺度时空变化及其与气候的关系

利用7个地球系统模式的植被净初级生产力(NPP)对中国地区1901～2005年植被碳通量的时空变化进行了研究,并结合气候因子分析了NPP的变化与气温、降水和辐射的关系;文章还进一步研究了中国地区1901～2005年氮沉降通量NH_x、NO_y的时空变化,并分析了NH_x、NO_y的变化与气温、降水和NPP的关系.结果表明:(1)近百年来中国地区NPP呈现上升趋势,模式集合平均的趋势系数为0.88, NPP的分布趋势总体呈现出北低南高,由西北到东南逐渐增加的特征.温度、降水、光照在该梯度方向上均有利于植物生长,其中模式集合平均NPP与气温、降水、长波辐射和短波辐射相关系数分别为0.88、0.73、0.91和0.67.(2)近百年来中国地区NH_x、NO_y呈现上升趋势,其中趋势系数分别为0.98和0.98,且通过了99.9%的信度检验. NH_x和NO_y总体呈现出北低南高,由西北到东南呈阶梯状逐渐增加的特征.(3) NH_x和NO_y与气温之间的相关系数空间分布大体相似,只是数值略有差异,与气温相关系数空间分布从东到西是正相关-负相关-正相关相间的分布; NH_x和NO_y与降水之间的相关系数空间分布也是大体相似,但降水相关系数空间分布相对比较复杂,在季风区从北到南呈正相关-负相关-正相关-负相关-正相关的相间分布,非季风区从东到西呈负相关-正相关-负相关-正相关的相间分布.(4) NH_x和NO_y与NPP之间的相关系数空间分布总体一致,与NPP相关系数空间分布相对比较复杂,其中模式集合平均的分布在东北地区和西南地区为正相关值区,其他地区是正相关与负相关交替分布.     

基于MODIS数据的博斯腾湖流域植被变化及其与气候因子的关系

以博斯腾湖流域为研究区,基于2001-2016年时间序列的MODIS NDVI数据分析了研究区植被的时空变化趋势,并结合流域气象站点的气温、降水、日照时数和相对湿度数据分析了植被生长季累积NDVI和16天NDVI与气候因子之间的响应特征.结果表明:(1)流域植被覆盖变化呈改善趋势,生长季累积NDVI年变化率为0.014 a-1,16天NDVI变化率均为正值,植被改善趋势显著区域主要分布在高山草原湿地和农业灌溉区边缘的新增农田.(2)植被生长季累积NDVI主要受降水和相对湿度影响,植被总体生产力与水分条件关系最密切,生长季逐16天NDVI与同期气温和日照时数在植被生长初期和末期关系显著,而与降水没有显著的相关性,说明植被短期瞬时长势对热量条件更为敏感.(3)在植被生长不同阶段对气候变化具有不同的滞后效应,其中植被生长初期和末期对气温有0.5~1个月的滞后,生长盛期对降水有0.5~3个月的滞后、日照时数有1.5~2.5个月的滞后、相对湿度有0.5~2.5个月的滞后,揭示了植被不同生长阶段水热条件对其生长韵律的控制差异.     

青藏高原植被变化与地表热源及中国降水关系的初步分析

利用设在青藏高原的5个自动气象站（AWS）近地层梯度观测资料、归一化植被指数（GIMMS NDVI）和中国624个台站月降水资料,初步分析了青藏高原植被变化与地表热源及中国降水的关系．结果表明：青藏高原植被与地表热源之间存在明显的正相关关系．高原西部感热与NDVI的正相关关系较高原东部显著,而高原东部地表潜热与NDVI的正相关关系则好于高原西部．植被改善后,各季节地表热源以增加为主,尤其夏季,热源增量最大;冬、春季感热对地表热源增量贡献较大,潜热贡献相对较小;夏、秋季感热与潜热对地表热源增量贡献同等重要．青藏高原植被与中国夏季降水相关系数从南到北,呈“＋-＋”带状分布．植被变化引起的高原地表加热异常可能是影响中国夏季降水的重要因子之一．     

气候变化和人类活动对黄土高原植被覆盖变化的影响

利用GIMMS和SPOT VGT两种归一化植被指数(NDVI)数据对黄土高原地区1981~2006年期间植被覆盖的时空变化进行了研究, 并从气候变化和人类活动的角度分析了植被覆盖变化的原因. 黄土高原地区植被覆盖经历了以下4个阶段: ① 1981~1989年植被覆盖持续增加时期; ② 1990~1998年以小幅波动为特征的相对稳定时期; ③ 1999~2001年植被覆盖迅速下降时期; ④ 2002~2006年植被覆盖进入迅速上升时期. 黄土高原地区植被覆盖变化存在显著的空间差异, 内蒙古和宁夏沿黄农业灌溉区和鄂尔多斯退耕还林还草生态恢复区的植被覆盖明显提高, 而黄土丘陵沟壑区和六盘山、秦岭北坡等山地森林区的植被覆盖明显退化. 从不同的植被类型来看, 沙地、草地和耕地的NDVI上升趋势显著, 而森林植被的NDVI呈明显的下降趋势. 研究表明: 植被覆盖变化是气候变化和人类活动共同作用的结果. 黄土高原地区气候变暖在加剧土壤干燥化抑制夏季植被生长的同时, 提高了春、秋季节植被生长活性, 延长了植被生长期. 黄土高原地区植被覆盖和降水关系密切, 降水变化是植被覆盖变化的重要原因. 农业生产水平的提高致使农业区NDVI在不断上升, 同时, 正在黄土高原大规模进行的退耕还林还草工程建设, 其生态效应也正在呈现.     

鄱阳湖湿地典型植被群落地下水—土壤—植被—大气系统界面水分通量及水源组成

地下水-土壤-植被-大气系统(GSPAC)界面水分传输是湿地生态水文过程研究的关键.本文选取鄱阳湖湿地高位滩地的2种典型植被群落:茵陈蒿(Artemisia capillaris)和芦苇(Phragmites australis)群落为研究对象,运用HYDRUS-1D垂向一维数值模拟,量化了湿地GSPAC系统界面水分通量,阐明了典型丰水年(2012年)和枯水年(2013年)鄱阳湖湿地植被群落的蒸腾用水规律和水源组成.结果表明:(1)茵陈蒿和芦苇群落土壤-大气界面的年降水入渗量为1570~1600 mm,主要集中在雨季4-6月,占年总量的60%;植物-大气界面的年蒸腾总量分别为346~470 mm和926~1057 mm,其中7-8月植被生长旺季最大,占年总量的40%~46%;地下水-根区土壤界面的向上补给水量受不同水文年水位变化的影响显著,地下水年补给量分别为15~513 mm和277~616 mm,主要发生在蒸散发作用强烈和地下水埋深较浅的时段.(2)植被蒸腾用水分为生长初期(4-6月)和生长旺季(7-10月)2个阶段,丰水年植被的整个生长期蒸腾用水充足,枯水年植被生长旺季的蒸腾用水受到严重水分胁迫,实际蒸腾量仅为潜在蒸腾量的一半左右.(3)不同水文年湿地植被生长旺季的水源贡献不同:丰水年茵陈蒿群落以地下水补给为主,芦苇群落以湖水和地下水补给为主;枯水年茵陈蒿群落以降水和前期土壤水储量为主,芦苇群落以地下水补给为主.本研究结果有助于揭示湿地植被的水分利用策略,为阐明湖泊水情变化与植被演替的作用机理提供参考依据.     

应用MODIS数据监测千岛湖流域植被覆盖动态(2001-2013年)

流域植被覆盖状况对于水源地生态环境保护具有重要的指示作用.当前的水质目标管理不仅要着眼于湖库水质参数控制,更应该从整个流域的角度维系生态平衡.在此背景下,依托长时间序列MODIS遥感数据对千岛湖流域2001-2013年植被覆盖状况进行监测,采用最小二乘法趋势分析和Mann-Kendall显著性检验方法分析了千岛湖流域植被的空间分布特征、时间变化特征与长期变化趋势.研究表明该方法能够有效地监测流域植被覆盖的时空动态变化:1)从空间分布上来看,千岛湖流域植被覆盖状况整体较好,但同时也发现受人为干扰较大的地域如河、湖附近的城镇建设用地、农业用地以及园地,其NDVI值明显低于自然林地;2)从时间变化特征上看,2001-2013年千岛湖流域植被年际NDVI在0.69~0.73之间波动,且近年来有增长趋势,年内季节性NDVI动态分析表明高时间分辨率的MODIS数据能够用来区分常绿植被与落叶植被的物候特征,以分析不同植被类型对流域氮、磷流失的风险差异;3)从变化趋势上看,2001-2013年植被覆盖状况改善的区域远大于退化的区域,其中改善区域约占流域面积的55.90%,呈现出一定退化状态的区域约占29.60%(严重退化区域仅占3.97%),而相对稳定不变区域约占14.51%.经与气温与降水等气候因子进行相关性分析表明,植被NDVI与气温呈显著正相关,而降水则不敏感,说明气温是研究区植被生长的主导气候因子.同时发现,人类活动对局部植被变化影响较大.研究结果可为流域水资源与生态环境保护提供空间数据支撑.     

青藏高原植被物候对不同强度极端温度和降水的差异化响应

量化气候因素如何影响植被物候对于理解全球变化背景下气候-植被相互作用以及碳水循环至关重要.然而,不同强度的极端气候事件对青藏高原植被物候的影响尚不明确.利用长期日光诱导叶绿素荧光遥感,研究了2000～2018年青藏高原植被物候对不同强度极端温度和降水事件的响应.研究发现,随着温度梯度的增加,最高温度暴露天数(Maximum temperature exposure days, TxED)和最低温度暴露天数(Minimum temperature exposure days,T_nED)均导致春季物候(Start of the growing season, SOS)由延迟转为提前.然而, T_xED和T_nED对秋季物候(end of the growing season, EOS)的影响随着温度梯度的增加由提前转为延迟,直到达到温度阈值.超过该温度阈值将会对植被生长产生不利影响,引起EOS提前结束.具体而言,对应的最高和最低温度阈值分别为10.12℃和2.54℃.对于累积降水(Cumulative precipitation...     

横断山地区气候-植被区划

横断山地区是中国今后生态保护、清洁能源生产、川藏和滇藏铁路等重大基础设施工程建设的重要布局区.这里高山峡谷纵横,气候和植被分布区域性与垂直地带性显著,孕灾环境复杂,亟待开展横断山地区气候-植被区划,以便有效服务于农业生产与生态建设、山地灾害风险防范和重大工程建设等国家需求.为此,本文基于横断山地区最新划界成果,采用横断山地区及其周边122个气象站点1990～2019年气温、降水量、气压、日照时数、风速、相对湿度等地面观测数据和高精度土地覆被类型遥感反演数据,制定了适用于横断山地区高山峡谷复杂大地貌格局、气象站点稀少、气候和植被分异显著等综合自然地理特征的气候-植被区划方案,并将横断山地区划分为5个温度带、20个干湿区、55个植被小区.该气候-植被区划方案分别以日平均气温稳定通过10℃日数、年干燥度指数、主要植被类型作为划分温度带、干湿区、植被小区的主要指标,且以≥10℃积温、最冷月气温、最暖月气温等为辅助指标.与之前区划方案相比,本方案遴选并优化了适用于横断山地区复杂地形的薄盘光滑样条气候空间插值模型;结合地理探测器,科学厘定了存在争议的气候带(区)间区划指标阈值;提出逐步降尺度窗格划...     

末次冰盛期中国气候要素定量重建

古气候定量化是古全球变化研究的核心目标之一.重建末次冰盛期时段((18±2)ka14C)气候变化特征,对理解冰期-间冰期地球气候演化规律具有重要的意义.以往古气候要素定量重建,主要基于现代气候条件下孢粉-气候的统计学方法,因难以有效区分过去气候季节性变化和大气CO2浓度降低对植物生长的影响,导致重建结果可能存在不确定性.本研究基于植物生理过程、新一代古气候定量重建的植被反演方法,考虑上述环境因子对植物生长的影响,利用新完善的中国第四纪孢粉数据库,重建了古气候的空间格局.结果表明,在末次冰盛期,大气CO2浓度降低对中国古气候要素重建结果影响不显著;全国年均温比现在低约(5.6±0.8)℃,最冷月温度和最热月温度分别降低约(11.0±1.6)℃和(2.6±0.9)℃,且中国南方降温幅度达到约(5.5±0.5)℃,接近平均值的水平,年均温变化主要归因于冬季温度的降低;全国年降水量比现在低约(46.3±17.8)mm,其中北方降水减少约(51.2±21.4)mm,年降水变化主要源于夏季降水的减少.与古气候模拟结果的对比揭示,虽然现有模式能较好模拟年均气候模态,但是在季节性变化上与重建结果还有较大的差距,指示未来在提高古气候重建精度的同时需进一步加强古气候模式的季节性气候模拟能力.     

全新世初期气候的数值模拟研究

本文尝试用一个完全耦合的大气-海洋-植被模式(Atmosphere-Ocean-Vegetation General Circulation Model, AOVGCM)模拟全新世初期的地球气候.模拟结果表明,耦合模式成功地再现了全新世初期复杂气候条件下的基本特征,为研究这一时期的气候状况提供了重要的模型支持.就全球平均而言,11ka BP冬季地表气温比现代约低1.6 K,夏季比现代低约0.3 K;大气温度从低层到高层有不同的表现,高层反映了太阳辐射的重要作用,而低层气候对下垫面（如冰川、植被和海洋等）的影响比较敏感.从区域分布来看,11 ka BP冬季大部地区比现在偏干,但热带太平洋和南半球少部地区降水偏多;夏季大部地区比现在偏湿,亚洲和非洲季风偏强,主要的季风区降水偏多.     

Preliminary analysis on the relationships between Tibetan Plateau NDVI change and its surface heat source and precipitation of China

Using the automatic weather station data obtained from the Tibetan Plateau (TP), the normalized dif- ference vegetation index and the monthly precipitation data of China and by the methods of correlation and composite analysis, preliminary analytical results are achieved concerning the relationships be- tween TP NDVI change and its surface heat source and precipitation of China. The results of our re- search may lead to the following conclusions: (1) A positive correlation relationship exists between TP NDVI change and its surface heat source, including the sensible heat and the latent heat. As to the correlation of the former, it is more remarkable in western TP than in eastern TP, and as to the correla- tion of the latter, however it turns out contrary. (2) With the improvement of TP vegetation, its surface heat source of every season is also mainly reinforced, especially in summer. As to the contribution of the sensible heat and the latent heat to the increment of the TP surface heat source intensity, the for- mer is comparatively more significant than the latter in winter and spring, while in summer and autumn, the two have almost the same importance. (3) The correlation coefficient between summer NDVI over TP and the corresponding period precipitation of China displays a belt distribution of " ? " from south to north China. (4) Anomalous surface heating field over TP derived from vegetation change is probably an important factor to affect summer precipitation of China.     

The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

Notable shifting in the responses of vegetation activity to climate change in China

The weakening relationship between inter-annual temperature variability and vegetation activity in the Northern Hemisphere over the last three decades has been reported by a recent study. However, how and to what extent vegetation activity responds to climate change in China is still unclear. We applied the Pearson correlation and partial correlation methods with a moving 15-y window to the GIMMS NDVI dataset from NOAA/AVHRR and observed climate data to examine the variation in the relationships between vegetation activity and climate variables. Results showed that there was an expanding negative response of vegetation growth to climate warming and a positive role of precipitation. The change patterns between NDVI and climate variables over vegetation types during the past three decades pointed an expending negative correlation between NDVI and temperature and a positive role of precipitation over most of the vegetation types (meadow, grassland, shrub, desert, cropland, and forest). Specifically, correlation between NDVI and temperature (P_NDVI-T) have shifted from positive to negative in most of the station of temperature-limited areas with evergreen broadleaf forests, whereas precipitation-limited temperate grassland and desert were characterized by a positive P_NDVI-P. This study contributes to ongoing investigations of the effects of climate change on vegetation activity. It is also of great importance for designing forest management strategies to cope with climate change.     

European precipitation connections with large-scale mean sea-level pressure (MSLP) fields

Abstract

To advance understanding of hydroclimatological processes, this paper links spatiotemporal variability in gridded European precipitation and large-scale mean sea-level pressure (MSLP) time series (1957–2002) using monthly concurrent correlation. Strong negative (positive) correlation near Iceland and (the Azores) is apparent for precipitation in northwest Europe, confirming a positive North Atlantic Oscillation (NAO) association. An opposing pattern is found for southwest Europe, and the Mediterranean in winter. In the lee of mountains, MSLP correlation is lower reflecting reduced influence of westerlies on precipitation generation. Importantly, European precipitation is shown to be controlled by physically interpretable climate patterns that change in extent and position from month to month. In spring, MSLP–precipitation correlation patterns move and shrink, reaching a minimum in summer, before expanding in the autumn, and forming an NAO-like dipole in winter. These space–time shifts in correlation regions explain why fixed-point NAO indices have limited ability to resolve precipitation for some European locations and seasons.

Editor Z.W. Kundzewicz; Associate editor A. Montanari

Citation Lavers, D., Prudhomme, C., and Hannah, D.M., 2013. European precipitation connections with large-scale mean sea-level pressure (MSLP) fields. Hydrological Sciences Journal, 58 (2), 310–327.     

SRES A2情景下中国气候未来变化的多模式集合预测结果

采用政府间气候变化委员会资料中心的模式预测结果,本文分析了SRES A2温室气体和气溶胶排放情景下中国大陆21世纪前30年的10年际气候变化趋势. 研究揭示：大陆冬季和夏季表面温度、表面最高温度和最低温度分别升高0.3～2.3℃、0.1～2.0℃、0.5～2.7℃,增幅大体上呈现东西向带状分布,由南至北升温逐渐加强,且增幅随时间加大. 此外,上述三气候要素冬季升温幅度要大于同期夏季、表面最低温度升幅要强于同期表面最高温度,冬季和夏季表面温度的季节内变化范围减小. 冬季东亚地区海平面气压异常幅度在-1.0hPa至0.4hPa之间变化,呈东西向带状分布,表现为南正北负、随时间推进异常幅度有所加大,正负交界面向南扩展;同时,东北、华北和西部海平面气压负异常较大. 夏季海平面气压异常空间分布与冬季相似. 2001～2030年,青藏高原大部、大陆东南部和河套大部分地区降水量增加0.1～0.8mm/d.     

北大西洋涛动和南半球环状模不同位相配置对我国南方夏季降水的协同影响

利用我国气象台站观测资料和再分析格点数据,诊断研究了前期春季（4-5月份）北大西洋涛动（North Atlantic Oscillation,NAO）和南半球环状模（Southern Annular Mode,SAM）在不同位相配置下对我国南方夏季降水异常变化的协同影响作用.分析结果表明,在剔除ENSO最强信号影响后,我国南方夏季降水异常分布显著地依赖于前期春季两个较为独立的年际变率主模态（NAO和SAM）位相的不同配置,即降水异常型主要表现为两个因子单独作用的叠加效果.当前春SAM正位相偏强而NAO负位相偏强时,二者的影响呈现协同正效应,我国南方夏季（6-7月份）降水表现为全区正异常,特别在长江中下游及其以南附近地区最为显著;反之,当前春SAM呈偏强的负位相而NAO偏强的正位相配置时,二者的影响呈现协同负效应,对应我国夏季长江中下游地区降水表现为显著负异常.对其可能的影响机理研究表明,在SAM与NAO位相相反情况下,二者均会通过海气相互作用过程影响到热带大西洋北部海温的异常变化,进而形成协同作用,增强北大西洋海温三极子模态异常信号,从而通过欧亚大陆的遥相关波列对东亚夏季风和我国南方降水产生显著影响.相比之下,当SAM与NAO同位相时,可能表现为抵消效应,不利于北大西洋海温三极子发展,从而削弱对我国南方夏季降水的影响,此方面还有待进一步研究.

     

Assessing vegetation dynamics and their relationships with climatic variability in northern China

In this study, the vegetation dynamics and their correlations with climate variability in northern China were evaluated based on the normalized difference vegetation index (NDVI) and meteorological datasets from 1982 to 2006. The NDVI showed that vegetation cover had a tiny increasing trend for whole study area in the past 25 years. However, the interannual changes of NDVI were different in each season. The part of spring and autumn NDVI values increased significantly, while the summer NDVI increased no significantly. And the interannual variations of the NDVI showed obvious spatial differentiations. The annual max NDVI increased were mainly distributed in most areas of grassland and farmland, whereas the annual max NDVI decreased were mainly distributed in forest areas. The annual NDVI and temperature had more important relationships. Thus, as compared to precipitation, the correlation between NDVI with temperature was stronger than the precipitation in northern China. NDVI and climatic variables were different in each season. The NDVI trends exhibited a close correspondence to climatological variations in region and season. In Addition, human activities also had profound effect to the NDVI trends in some regions. All these findings will make humans know more about the knowledge of the natural forces that influence vegetation change and supply a scientific basic resource to for the environmental management in northern China.     

1960—2019年鄱阳湖五河流域陆地水储量变化及其对主湖区水量的影响

流域内地表水、土壤水和地下水等水储量组分相互作用和影响,共同构成了陆地水储量(TWS)的动态变化格局。本文以GRACE卫星数据为基准,利用GLDAS数据解析1960-2019年鄱阳湖“五河”流域TWS的时空变化特征及各组分对其变化的贡献,采用相关分析方法分析TWS对降水的滞后响应关系,并进一步采用多元线性回归分析方法探究了“五河”流域TWS及各组分对鄱阳湖主湖区水量的影响。结果表明:“五河”流域年TWS在1960-2011年(P1)以-0.07 mm/a的下降,而在2012-2019年(P2)以3.37 mm/a的速率上升。相较于P1阶段,P2阶段春、夏季TWS盈余增强,秋、冬季TWS亏损减弱。春、夏季流域西部TWS变化逐渐由地表水转变为地下水储量主导,流域东部TWS变化主要由地下水储量主导;秋、冬季流域TWS变化主要为地下水储量主导,且地表水对TWS变化的贡献减弱。流域TWS对降水变化的响应滞时呈现夏、秋季短(1个月)而冬、春季长(3~6个月)的季节模式。地下水储量和土壤水对TWS变化的贡献增加会延长TWS对降水的响应滞时,而地表水对响应滞时起相反的作用。“五河”流域TWS与鄱阳湖主湖区水量具有显著的正相关性,地表水和地下水储量增加对湖区水体的增长具有正向作用,而土壤水增加对湖区水体的增长具有反向作用。本研究解析了近六十年鄱阳湖“五河”流域陆地水储量的变化及其对主湖区水量的影响,可为流域水安全管理提供参考。     

基于MODIS数据的干旱遥感监测研究

干旱是影响社会发展和农业生产的重要因素之一。本文基于EOS/MODIS卫星遥感资料,选取江西省2001-2006年的NDVI时间序列数据,分析了NDVI对干旱的响应规律。计算了NDVI与气温、降水之间的关系。并提取植被状态指数(VCI),分析VCI与气温距平、降水距平的空间分布规律。结果表明:2003年江西夏季旱灾以高温少雨天气为主。这一时期的NDVI数值明显低于其他年份同一时期的NDVI值。气温温度越高,NDVI值越大;日照时数时间越长,NDVI值越大;降水量越高,NDVI值越大;降水距平百分率越高,VCI值越高;平均温度距平越小,VCI值越高。说明气候因素对NDVI指数和VCI指数有很大影响。研究表明,基于MODIS的植被指数可以反映旱灾的时空分布规律。     

Regional sea-surface temperatures explain spatial and temporal variation of summer precipitation in the source region of the Yellow River

ABSTRACT

The summer precipitation (June–September) in the source region of the Yellow River accounts for about 70% of the annual total, playing an important role in water availability. This study divided the source region of the Yellow River into homogeneous zones based on precipitation variability using cluster analysis. Summer precipitation trends and teleconnections with global sea-surface temperatures (SST) and the Southern Oscillation Index (SOI) from 1961 to 2010 were investigated by Mann-Kendall test and Pearson product-moment correlation analysis. The results show that the northwest part (Zone 1) had a non-significantly increasing trend, and the middle and southeast parts (zones 2 and 3) that receive the most precipitation displayed a statistically significant decreasing trend for summer precipitation. The summer precipitation in the whole region showed statistically significant negative correlations with the central Pacific SST for 0–4 month lag and with the Southern Indian and Atlantic oceans SST for 5–8 month lag. Analyses of sub-regions reveal intricate and complex correlations with different SST areas that further explain the summer precipitation variability. The SOI had significant positive correlations, mainly for 0–2 months lag, with summer precipitation in the source region of the Yellow River. It is seen that El Niño Southern Oscillation (ENSO) events have an influence on summer precipitation, and the predominant negative correlations indicate that higher SST in equatorial Pacific areas corresponding to El Niño coincides with less summer precipitation in the source region of the Yellow River.

Editor Z.W. Kundzewicz; Associate editor D. Gerten