西南地区植被变化与气温及降水关系的初步分析

利用卫星遥感植被归一化指数(NDVI)资料和西南地区96个实测台站的月平均气温以及降水资料,初步分析了西南地区植被变化与气温及降水的关系。结果表明:近20年来西南地区植被覆盖状况较好,其中夏季植被覆盖最好,冬季植被分布空间差异最大;西南地区植被整体呈增加趋势,同时也存在较明显的季节和区域差异:春季西南大部分地区植被以增加为主,夏季、秋季全区以减少为主,冬季则以增加为主且存在明显的东西反向特征,东部减少西部增加。时滞互相关分析表明:西南地区11~2月份的植被对超前其1~2个月的气温以及夏季的植被对春季气温的敏感性比较大,3~4月的植被生长对上年夏季的降水敏感性比较大;同期时,1~3月植被和气温为正相关关系,6~9月的植被生长和降水为明显的负相关关系;在植被超前气候的条件下,1~2月的植被和滞后1~2个月的气温呈正相关关系,与滞后1个月的降水有明显的负相关关系。      

青藏高原冬、春季植被特征及其对西南地区夏季降水的影响

本文利用西南地区96个气象台站1982-2001年夏季(6-8月)月平均降水资料和归一化植被指数(GIMMS NDVI)资料,分析了青藏高原冬、春季植被特征及其对西南地区夏季降水的影响,得到以下几点认识:青藏高原冬、春季植被呈现东南部覆盖较好,逐渐向西北部减少的特征.近20 a来,高原冬、春季植被总体呈增加趋势,其高原中西部、南部、北部增加明显,而南部侧边界和中东部呈减少趋势.相关分析和奇异值分解表明:高原冬、春季植被对西南地区夏季降水有较明显影响,且这种影响也存在一定的区域差异.高原前期植被变化可以作为西南地区夏季降水长期预报综合考虑的一个参考因子.     

我国东部地区NDVI与气温、降水的关系研究

利用东部地区的1982—2001年归一化植被指数(NDVI)资料以及131个标准气象台站的气温、降水资料,用相关分析、奇异值分析(SVD)方法研究了该地区的植被与气温、降水的相互作用,得到以下几点认识：NDVI的最大值滞后于气温最高值的时间尺度在一个月左右。前期气温与后期NDVI的相关系数在春夏为负值,在秋冬却以正值为主。前期植被与后期气温的相关系数以负值为主。NDVI最大值滞后于降水最大值的时间尺度在两个月左右,同期NDVI与降水的相关系数为负值,而无论降水超前于NDVI或者NDVI超前于降水的时间尺度大于1个月时,二者的相关系数转为正值。由SVD方法得到东部地区7月份的NDVI与8月份的气温、降水有较好的相关关系。河南西南部及东北部区域NDVI与大部分地区的气温为正相关;长江流域NDVI与32 °N以南地区的降水有较好的负相关。因此,前期植被的变化特征可以作为后期气温、降水的预报的一种参考因子。     

中国东部前冬、春土壤湿度与夏季气候的关系

利用中国东部(100°E以东)139个站的1951~1999年逐月反演的土壤湿度资料以及160个气象台站的气温、降水资料,分析了我国东部不同区域前冬、春土壤湿度异常与夏季气候的关系。研究结果表明,黄河以南地区上年冬季土壤湿度与夏季降水存在正的相关关系,但这种滞后相关存在明显的地域差异。其中云贵高原和华中地区夏季气候对上年冬季土壤湿度响应最显著。黄河以北的华北和内蒙地区上年冬季土壤湿度与夏季降水有弱的负相关关系。除了云贵高原地区外,多数地区上年冬季土壤湿度与夏季温度存在负相关关系,其中负相关最显著的是华北地区。春季土壤湿度除与云贵高原的夏季气候关系密切外,与其他地区夏季气候的关系不显著。土壤湿度与气候的滞后相关表明土壤湿度在年际尺度上对后期气候有一定的影响。     

赤道太平洋对流活动异常对我国夏季降水和气温的影响

利用月平均ＯＬＲ、降水和气温资料,研究了ＥＮＳＯ期间赤道太平洋对流活动与我国夏季降水和气温的关系。结果表明：春季、夏季中、西太平洋对流活动异常与我国夏季江淮地区的降水有密切关系;春季和前一年冬季西太平洋对流活动异常与东北地区夏季降水有显著相关。前一年冬季中、西太平洋对流活动异常与我国降水的显著相关区是不同的,前者为华南、西南地区,后者为东北至内蒙古一带。气温与同期中、西太平洋对流活动的相关不显著。     

青藏高原冬季NDVI与西南地区夏季气温的滞后关系

该文利用EOF分解得到的1982—2001年西南地区夏季平均、最高和最低气温的时空特征显示, 西南地区夏季平均、最高气温的时空变化具有很好的一致性, 尤其是川渝地区20世纪80年代为气温负距平, 90年代开始有明显升温。利用GIMMS NDVI和西南4省市96个台站的气温资料进行了相关分析、合成分析以及SVD分析, 得到前期冬季青藏高原植被影响该区夏季气温的滞后关系以及影响较大的区域。结果表明:西南地区夏季平均气温、最高气温对青藏高原冬季植被变化较敏感, 其中青藏高原西部NDVI与西南地区夏季气温的相关强于东部; 青藏高原NDVI异常偏高对应西南地区夏季气温偏高, 其中最高气温升高较明显, 增温最大值出现在7月, 位于西南地区北部; 青藏高原冬季植被变化与西南地区平均气温、最高气温和最低气温的最佳耦合模态中影响程度及关键区域略有差异, 青藏高原冬季NDVI与夏季平均气温关系最密切, 其中青藏高原东北大部分地区和南部 (包括拉萨及林芝东部地区) 的影响最大, 气温对前期青藏高原NDVI变化反应的敏感区主要位于四川盆地及其附近地区。     

赤道太平洋对流活动异常对我国夏季降水和气温的影响

利用月平均ＯＬＲ、降水和气温资料,研究了ＥＮＳＯ期间赤道太平洋对流活动与我国夏季降水和气温的关系。结果表明：春季、夏季中、西太平洋对流活动异常与我国夏季江淮地区的降水有密切关系;春季和前一年冬季西太平洋对流活动异常与东北地区夏季降水有显著相关。前一年冬季中、西太平洋对流活动异常与我国降水的显著相关区是不同的,前者为华南、西南地区,后者为东北至内蒙古一带。气温与同期中、西太平洋对流活动的相关不显著。     

青藏高原冬、春植被归一化指数变化特征及其与高原夏季降水的联系

青藏高原气候独特,影响高原夏季降水的原因是十分复杂的和多方面的。文中利用1982—2001年的卫星遥感植被归一化指数(NDVI)资料和青藏高原55个实测台站降水资料,应用经验正交分解(EOF)、奇异值分解(SVD)等方法分析了青藏高原冬、春植被变化特征及其与高原夏季降水的联系,得到以下几点初步认识:青藏高原冬、春季植被分布基本呈现东南地区植被覆盖较好,逐渐向西北地区减少的特征。其中高原东南部地区和高原南侧边界地区NDVI值最大,而西北地区和北侧边界地区NDVI较小。EOF分析表明,20年来冬、春季高原植被的变化趋势是总体呈阶段性增加,其中尤以高原北部、西北部(昆仑山、阿尔金山和祁连山沿线)和南部的雅鲁藏布江流域植被增加明显。由SVD方法得到的高原前期NDVI与后期降水的相关性是较稳定的。青藏高原多数区域冬、春植被与夏季降水存在较好的正相关,且这种滞后相关存在明显的区域差异。高原南部和北部区域的NDVI在冬春两季都与夏季降水有明显的正相关,即冬春季植被对夏季降水的影响较显著。而冬季高原中东部玉树地区附近区域的NDVI与夏季降水也存在较明显的负相关,即冬季中东部区域的植被变化对夏季降水的影响也较显著。由此可见,高原前期NDVI的变化特征,可以作为高原降水长期预报综合考虑的一个重要参考因子。     

基于EVI的中国最近10 a植被覆盖变化特征分析

通过对2000—2009年增强型植被指数(EVI)数据的分析发现:在过去的10 a里,中国的植被覆盖度明显增加,植被活动在增强。植被覆盖的年变化和季节变化特征如下:(1)10 a来植被覆盖地区的面积呈增加趋势,植被稀少地区的面积呈减少趋势;(2)无论是植被覆盖区还是全国平均,单位面积EVI年平均值都呈增加趋势;(3)在生长季节(夏季、春季)植被活动增加更明显,EVI增加速率按季节排列如下:夏季春季秋季冬季。植被覆盖的空间变化特征显示,尽管总体上中国植被覆盖呈增加趋势,但存在空间异质性。结合同期的温度、降水和森林资源清查数据,从两个方面初步解释了植被覆盖度增加的原因,即:温度的上升和春季降水量的增加;近年来中国开展的大型林业生态建设工程。     

春季格陵兰海冰与夏季中国气温和降水的关系

采用英国Hadley中心的GISST海冰面积资料、NCEP/NCAR再分析资料以及中国160站气温和降水资料,分析了春季格陵兰海冰面积与夏季中国区域气温和降水的关系.初步研究表明,春季格陵兰海冰面积变化和随后夏季我国黄河长江中下游之间地区气温以及8月份华北和西南地区降水呈明显正相关,而和6月黄河中上游地区降水则具有明显的负相关.同时,春季格陵兰海冰异常时期对应着北半球大气环流的明显变化,表明海冰与我国气温及降水之间的联系具有一定的环流背景.     

Assessment of vegetation dynamics and their response to variations in precipitation and temperature in the Tibetan Plateau

The Tibetan Plateau is a region sensitive to climate change, due to its high altitude and large terrain. This sensitivity can be measured through the response of vegetation patterns to climate variability in this region. Time series analysis of Normalized Difference Vegetation Index (NDVI) imagery and correlation analyses are effective tools to study land cover changes and their response to climatic variations. This is especially important for regions like the Tibetan Plateau, which has a complex ecosystem but lacks a lot of detailed in-situ observation data due to its remoteness, vastness and the severity of its climatic conditions. In this research a time series of 315 SPOT VEGETATION scenes, covering the period between 1998 and 2006, has been processed with the Harmonic ANalysis of Time Series (HANTS) algorithm in order to reveal the governing spatiotemporal pattern of variability. Results show that the spatial distribution of NDVI values is in agreement with the general climate pattern in the Tibetan Plateau. The seasonal variation is greatly influenced by the Asian monsoon. Interannual analysis shows that vegetation density (recorded here by the NDVI values) in the entire Tibetan Plateau has generally increased. Using a 1 km resolution land cover map from GLC2000, seven meteorological stations, presenting monthly data on near surface air temperature and precipitation, were selected for correlation analysis between NDVI and climate conditions in this research. A time lag response has also been found between NDVI and climate variables. Except in desert grassland (Shiquanhe station), the NDVI of all selected sites showed strong correlation with air temperature and precipitation, with variations in correlation according to the different land cover types at different locations. The strongest relationship was found in alpine and subalpine plain grass, the weakest in desert grassland.     

黄河源区植被变化趋势及其对气候变化的响应过程研究

利用1982～2001年NOAA/AVHRR(美国大气海洋局卫星/甚高分辨率辐射计)NDVI(归一化植被指数)资料、2000～2008年EOS/MODIS(地球观测系统卫星/中等分辨率成像光谱仪)NDVI资料以及1982～2008年黄河源区的玛多、玛曲和兴海气象台站逐月气温和降水资料,分析了黄河源区玛多、玛曲和兴海地区...     

2000—2009年锡林郭勒典型草原植被对气象因子的响应

应用MODIS数据对2000—2009年植被变化情况及其与气温、降水量进行相关分析。2007年年均气温最高,降水最少,NDVI最大值和生长季平均值最低;在降水量最大的2003年NDVI最大值和生长季平均值最高。全生长季中气温和降水量与NDVI值具有显著或极显著相关,相对于气温、降水量对NDVI值影响更大;前一个月的气温和降水量对NDVI值的影响最大,植被对气象因子的响应具有时滞性。     

Spatial patterns of vegetation phenology metrics and related climatic controls of eight contrasting forest types in India – analysis from remote sensing datasets

Summary Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between the biosphere, the climate and the atmosphere. In this study, we characterized the spatial patterns in phenological variations in eight contrasting forest types in an Indian region using coarse resolution NOAA AVHRR satellite data. The onset, offset and growing season length for different forest types has been estimated using normalized difference vegetation index (NDVI). Further, the relationship between NDVI and climatic parameters has been assessed to determine which climatic variable (temperature or precipitation) best explain variation in NDVI. In addition, we also assessed how quickly and over what time periods does NDVI respond to different precipitation events. Our results suggested strong spatial variability in NDVI metrics for different forest types. Among the eight forest types, tropical dry deciduous forests showed lowest values for summed NDVI (SNDVI), averaged NDVI (ANDVI) and integrated NDVI (I-NDVI), while the tropical wet evergreen forests of Arunachal Pradesh had highest values. Within the different evergreen forest types, SNDVI, ANDVI and INDVI were highest for tropical wet evergreen forests, followed by tropical evergreen forests, tropical semi-evergreen forests and were least for tropical dry evergreen forests. Differences in the amplitude of NDVI were quite distinct for evergreen forests compared to deciduous ones and mixed deciduous forests. Although, all the evergreen forests studied had a similar growing season length of 270 days, the onset and offset dates were quite different. Response of vegetative greenness to climatic variability appeared to vary with vegetation characteristics and forest types. Linear correlations between mean monthly NDVI and temperature were found to yield negative relationships in contrast to precipitation, which showed a significant positive response to vegetation greenness. The correlations improved much for different forest types when the log of cumulative rainfall was correlated against mean monthly NDVI. Of the eight forest types, the NDVI for six forest types was positively correlated with the logarithm of cumulative rainfall that was summed for 3–4 months. Overall, this study identifies precipitation as a major control for vegetation greenness in tropical forests, more so than temperature.     

陆川年雷暴日数变化特征与相关气象因子关系的分析

利用1961～2010年,50a陆川县常规地面气象观测资料,对陆川县雷暴日数的变化特征和演变规律进行分析,并就月平均雷暴日数与年月平均气温、年月降水总量、年月平均气压的关系进行了分析。结果表明：陆川年雷暴日数随着年平均气温的增高,呈下降趋势,月平均雷暴日数与月平均温度的高低成正比;随年降水总量的减少,呈下降趋势,月平均...     

Interannual variability and correlation of vegetation cover and precipitation in Eastern China

Based on the SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) data and daily precipitation data of 357 meteorological stations, the spatial and temporal variability of vegetation cover, measured by NDVI, and precipitation as well as their relationships are investigated in Eastern China, which is portioned into three subregions (regions I, II, and III), for the period 1998–2010. The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China.     

The Impact of Agricultural Practices in China on Land-Atmosphere Interactions

Human-induced land use changes and the resulting alterations in vegetation features are major but poorly recognized drivers of regional climatic patterns.In order to investigate the impacts of anthropogenically-induced seasonal vegetation cover changes on regional climate in China,harmonic analysis is applied to 1982-2000 National Oceanic and Atmospheric Administration(NOAA) Advanced Very High Resolution Radiometer(AVVHRR)-derived normalized difference vegetation index(NDVI) time series(ten day interval data).For two climatic divisions of South China,it is shown that the first harmonic term is in phase with air temperature,while the second and third harmonics are in phase with agricultural cultivation.The Penman-Monteith Equation and the Complementary Relationship Areal Evapotranspiration(CRAE) model suggest that monthly mean evapotranspiration is out of phase with temperature and precipitation in regions with signiffcant second or third harmonics.Finally,seasonal vegetation cover changes associated with agricultural cultivation are identiffed:for cropped areas,the temperature and precipitation time series have a single maximum value,while the monthly evapotranspiration time series has a bimodal distribution.It is hypothesized that multi-cropping causes the land surface albedo to sharply increase during harvesting,thereby altering the energy distribution ratio and contributing to observed seasonal vegetation cover changes.