江河源区达日县近50年气候变化的多尺度分析

利用墨西哥帽小波对达日县1956~2004年共588个月的气温和降水数据进行多尺度分析,揭示了达日县气候变化多时间尺度的复杂结构,分析了不同时间尺度下降水和气温序列的变化周期和突变点,并确定了各序列中存在的主周期。结果表明:达日县气温和降水的变化趋势与青藏高原以及江河源区气候总体变化基本一致,局部存在较明显的滞后反应,小尺度的变化嵌套在较大尺度的复杂背景之中,不同时间尺度下突变的年份有所差异,小波分析在揭示气候变化的多尺度构型和主周期方面具有明显的优势。     

新疆叶尔羌河流域温度与降水序列的小波分析

利用1961—2006年叶尔羌河流域7个气象站点的气温和降水系列资料,采用Morlet小波函数,分析了不同时间尺度下气温和降水序列变化的周期和突变点,确定了各序列中存在的主周期。结果表明：该流域暖湿化趋势比较明显,气温和降水的变化趋势与西北地区和新疆区的气候变化基本一致;小尺度的变化嵌套在较大尺度的复杂背景之中,不同时间尺度下突变的年份有所差异。     

西畴县近48年来降水及气温小波分析

利用连续小波分析1962～2009年西畴县年降水量和年平均气温序列的小波变化特征,揭示了西畴县降水量与平均气温存在多时间尺度的周期变化特征。其中降水有2个明显的特征时间尺度,分别是4年和8年,平均气温存在以准2～4年为周期的周期振荡。此外,也可以看出近48年来,平均气温存在明显升高的趋势,降水也有减少的趋势,为掌握西畴县的气候变化规律及今后的气象预报服务工作提供了一定的参考价值。     

河西走廊沙尘暴及其影响因子的多尺度研究

沙尘暴活跃期具有周期性,这与影响因子的周期变化有关,尝试利用具有多时间尺度和多分辨率特性的小波分析技术对其进行研究。利用Morlet小波对甘肃河西走廊18个气象站多年平均的沙尘暴日数进行分析,发现沙尘暴变化的时间序列具有多尺度振荡的特点,存在7 a、13 a、以及23 a左右的特征时间尺度（周期变化）。通过对大风日数、干旱指数、降水、气温等沙尘暴的影响因子分析,表明沙尘暴的活跃度与大气环流的年际变化和突变有关,特别是与大风日数在时间尺度和主周期等方面具有明显的一致性,7 a左右的年际变化是它们的主周期;干旱指数、降水和气温具有同步的时间序列,13～25 a的年代际变化是它们的主周期,因此,它们对沙尘暴的影响主要体现在大时间尺度上。     

贵州麦岗水库小流域降水变化特征的小波分析

利用1960-2007年月平均降水和年平均降水数据,采用墨西哥帽小波连续函数,对贵州省紫云县麦岗水库流域近48年来降水时间序列的季节变化和年际变化进行多尺度分析,揭示了麦岗水库流域降水变化多时间尺度的结构特征,并提取各季节和年降水序列的周期变化及突变点。结果表明,不同季节和年降水存在不同时间尺度的变化周期。春季降水的变...     

毛乌素沙地1969—2009年主要气候因子时间序列小波分析

采用Morlet复值小波变换法对毛乌素沙地5个气象站点1969—2009年主要气候要素不同时间尺度下的变化周期和突变点进行了分析,并根据主周期预测了未来气温、降水和相对湿度的变化趋势。结果表明:1969—2009年,毛乌素沙地年平均气温呈现出波动上升的趋势,平均上升0.401℃/10a,年降水量和年平均相对湿度的变化趋势不明显;毛乌素沙地年平均气温、年降水量和年平均相对湿度的年际变化过程中存在着多重时间尺度上的复杂嵌套结构,在不同的尺度周期中,表现出不同的冷暖、干湿振荡规律,总体表现为由小尺度无明显规律的剧烈振荡向大尺度有明显规律的振荡变化;目前气候正处于"暖干"向"暖湿"的过渡阶段,且这种暖湿化主要受气候周期性变化的影响。     

河西走廊近50年来地表水资源时间序列的小波分析

小波分析（wavelet Analysis）是时间-频率分析领域近年来迅速发展的一种新技术,具有多时间尺度、多层次和多分辨的特性。应用小波分析原理对甘肃河西走廊近50a来的径流、降水、气温等影响地表水资源时间序列的因素进行了分析,结果表明,水资源具有多尺度振荡的特点,具有2～4a,5～9a,12～15a,以及20a左右的周期变化。径流与降水和气温具有同步的时间序列,但是它们的主要周期尺度不同。小波分析的应用对河西走廊水资源趋势和预测研究提供了一个新的方法和思路。     

地方气候、小气候与应用气候

P426 .616 2003010047降水t时间序列变化的小波特征二Wavelet characteristicsofthe change in precipitation time series楠彤,王文圣…//长江流域资源与环境一2002,11(5)一466一470 利用小波变换对降水量时间序列的多时间尺度变化及突变特征进行了探讨.以新安江流域黄山地区主汛期(5一7月)和年降水量为例,计算表明,其年际及年代际时间尺度在时域中分布不均匀,具有明显的局部化特征;同时分析出 7主汛期降水具有8年、19年左右的周期,年降水存在6年、19年左右的周期.还表明,主汛期降水的时间尺度变化比较接近.图5参7(宋金叶)HNP463 .3 2003…     

盘龙河上游山洪径流多时间尺度特征分析

采用小波变换方法,对盘龙河龙潭寨水文站51年(1951～2001年)的山洪径流序列进行小波分析,揭示了盘龙河上游山洪径流多时间尺度的变化特征,分析了不同时间尺度下的径流序列变化周期和丰枯突变点.研究结果表明,径流序列变化具有26a以上,17～25a,7～15a和9a左右的时间尺度特征.通过小波方差检验,得出盘龙河上游山洪径流变化的主周期均为21年,其次为15,11,7和4年,以21年主周期来看,盘龙河上游地区山洪径流变化具有同步性.     

花园口站年最大洪峰流量时间序列的HHT分析

Hilbert-Huang变换能够定量描述非线性、非平稳复杂时间序列的时频特性,较传统分析方法更具优势。通过对时间序列进行EMD分解,得到变化过程的内在模态函数和趋势项函数,而后对各内在模态函数进行Hilbert-Huang变换,从而揭示出时间序列的多时间尺度特征。以黄河花园口站1952-2009年的年最大洪峰流量时间序列为例,对其进行多时间尺度分析,得到不同波动周期的振荡分量及趋势分量,具体分析了各分量的变化特征。结果表明,花园口年最大洪峰流量变化过程中存在准3.2a、准6.4a、准11.8a和准31.0a周期的波动,其中准3.2a和准6.4a的周期波动是引起原序列波动的主要原因,近60年来花园口年最大洪峰流量变化呈递减趋势,由此揭示了年最大洪峰流量变化过程的多时间尺度特征。在此基础上,探讨了各波动分量变化的影响因素,其变化与大气低频振荡、ENSO、太阳活动及气候变迁等因素有关。     

塔里木盆地南缘于田绿洲近50a来气候变化特征分析

基于于田气象站48 a(1960—2007年)逐月平均气温和降水量数据,借助小波分析、人工神经网络等方法研究了塔里木盆地南缘于田绿洲近50 a来在全球气候变暖的背景下气候变化的特征和总体趋势。结果表明,二维小波系数图可以清楚地显示出气候变化在不同时间尺度上的演变特征,并能对未来的气候演变趋势做出定性估计。小波方差图显示于田绿洲逐月平均气温存在4 a为主的短周期和以11~13 a为主的长周期;逐月降水存在以7 a为主的短周期和以准12 a、27 a左右为主的长周期。RBFN(Radial Basis Function Network)模型预测的结果显示,该区2008—2012年降水量的变化处于相对高值期,气温变化处于相对低值期。近50 a于田绿洲气候总体趋于暖湿。     

陕西年降水量变化特征及周期分析

以1959-2009年陕西省各气象站逐旬降水资料为基础,采用墨西哥帽小波函数,线性趋势分析以及Mann-Kendall检验法,对陕西省51 a降水的时空分布特征及趋势进行分析,揭示了陕西省降水变化的多时间尺度的复杂结构,分析了不同时间尺度下降水序列变化的周期和突变点,并确定了主要周期。结果表明：（1）陕西省年降水量年际变化大且时空分布极不均匀,降水量从北部向南部递增,呈南多北少特征,大致上为纬向分布。陕北、关中、陕南年降水量多年平均值依次为279 mm、563 mm、840 mm。三大区域年均降水变化相对较为平稳,近51 a来,研究区内年均降水总体呈北部和南部略微下降,中部微弱上升的变化格局,线性倾向率分别为-5.110 mm/10 a、-3.758 mm/10 a、1.908 mm/10 a;（2）陕西省年均降水量有3～7 a,10～17 a,17～30 a周期,以中时间尺度10～17 a的少-多交替最为明显。在微观尺度上,陕北、关中、陕南地区的周期均表现得零乱且不显著。中观尺度,关中和陕南的降水周期比较显著,为10～17 a,陕北的降水周期表现得不十分规律。宏观尺度,陕北的降水周期为23～30 a,关中和陕南较为相似,为18～25 a;（3）Mann-Kendall检验发现1993年是陕西省年均降水量增加的一个显著突变点,2009年以后陕西省将处于多雨期。     

近60年昆明市气候变化特征分析

利用线性倾向率、Mann-Kendall非参数检验、滑动T检验(MTT法)和小波分析等数理统计分析方法,分析昆明市近60 a气候变化趋势和气候突变特征。结果显示:近60 a昆明市气候变化呈气温升高、降水量略微减少的暖干化趋势;气温上升率0.24℃/10 a,降水量下降率3.89 mm/10 a;干季增温强于雨季,而雨季降雨量下降趋势明显;2001~2010年是近60 a来昆明气温最高、降水量最少的10 a;昆明市气温变化包含5~10、10~15 a左右周期,其降水量变化有10~15 a左右的周期变化特征。     

Comparisons on seasonal and annual variations of δ18O in precipitation

The spatial and temporal variations of stable oxygen isotope in precipitation on different time scales are analyzed according to the data from the IAEA/WMO stations with long survey series in the Northern Hemisphere. Temperature effect is mainly distributed in mid-high latitudes on seasonal scale except for Bamako and Addisababa stations. The δ18O/temperature slope displays the positive correlation against altitude for most of the statistical stations. Amount effect appears primarily in the region south of 30oN and coastal areas. The δ18O/precipitation slope is indirectly proportional to precipitation amount. For some of the sampling stations at mid-high latitudes where their seasonal distribution of precipitation is contrary to that of temperature, coupled with temperature effect, the amount effect appears synchronistically. Either the temperature effect or the amount effect on seasonal scale, there are positive correlations to a certain extent between the annual weighted mean δ18O and the annual mean temperature for almost all the stations. The correlation between composite δ18O and temperature on spatial scale is much more marked, compared with that of individual station. There is a good agreement between 10-year moving average temperature curves I and II, with the values of the former all markedly smaller than corresponding ones of the latter, calculated by the monthly mean series group I and the annual mean series group II, respectively. However, two calculated dδ18O/dT curves display the distinct difference: the variation amplitude of slope series II is larger than that of slope series I. Both curves had similar ascending trend from the 1960s to the 1970s, and then, their variations display the anti-phase. Moreover, the analyses show that there is negative correlation between slope series II and temperature series II. However, the status is different for slope series I and temperature series I. Both series have contrary trend from the 1960s to the 1970s, whereas the same trend since the 1980s.     

30年来呼伦贝尔地区草地植被对气候变化的响应(英文)

Global warming has led to significant vegetation changes especially in the past 20 years. Hulun Buir Grassland in Inner Mongolia, one of the world’s three prairies, is undergoing a process of prominent warming and drying. It is essential to investigate the effects of climatic change (temperature and precipitation) on vegetation dynamics for a better understanding of climatic change. NDVI (Normalized Difference Vegetation Index), reflecting characteristics of plant growth, vegetation coverage and biomass, is used as an indicator to monitor vegetation changes. GIMMS NDVI from 1981 to 2006 and MODIS NDVI from 2000 to 2009 were adopted and integrated in this study to extract the time series characteristics of vegetation changes in Hulun Buir Grassland. The responses of vegetation coverage to climatic change on the yearly, seasonal and monthly scales were analyzed combined with temperature and precipitation data of seven meteorological sites. In the past 30 years, vegetation coverage was more correlated with climatic factors, and the correlations were dependent on the time scales. On an inter-annual scale, vegetation change was better correlated with precipitation, suggesting that rainfall was the main factor for driving vegetation changes. On a seasonal-interannual scale, correlations between vegetation coverage change and climatic factors showed that the sensitivity of vegetation growth to the aqueous and thermal condition changes was different in different seasons. The sensitivity of vegetation growth to temperature in summers was higher than in the other seasons, while its sensitivity to rainfall in both summers and autumns was higher, especially in summers. On a monthly-interannual scale, correlations between vegetation coverage change and climatic factors during growth seasons showed that the response of vegetation changes to temperature in both April and May was stronger. This indicates that the temperature effect occurs in the early stage of vegetation growth. Correlations between vegetation growth and precipitation of the month before the current month, were better from May to August, showing a hysteresis response of vegetation growth to rainfall. Grasses get green and begin to grow in April, and the impacts of temperature on grass growth are obvious. The increase of NDVI in April may be due to climatic warming that leads to an advanced growth season. In summary, relationships between monthly-interannual variations of vegetation coverage and climatic factors represent the temporal rhythm controls of temperature and precipitation on grass growth largely.     

Comparisons on seasonal and annual variations of δ<Superscript>18</Superscript>O in precipitation

The spatial and temporal variations of stable oxygen isotope in precipitation on different time scales are analyzed according to the data from the IAEA/WMO stations with long survey series in the Northern Hemisphere. Temperature effect is mainly distributed in mid-high latitudes on seasonal scale except for Bamako and Addisababa stations. The δ¹⁸O/temperature slope displays the positive correlation against altitude for most of the statistical stations. Amount effect appears primarily in the region south of 30°N and coastal areas. The δ¹⁸O/precipitation slope is indirectly proportional to precipitation amount. For some of the sampling stations at mid-high latitudes where their seasonal distribution of precipitation is contrary to that of temperature, coupled with temperature effect, the amount effect appears synchronistically. Either the temperature effect or the amount effect on seasonal scale, there are positive correlations to a certain extent between the annual weighted mean δ¹⁸O and the annual mean temperature for almost all the stations. The correlation between composite δ¹⁸O and temperature on spatial scale is much more marked, compared with that of individual station. There is a good agreement between 10-year moving average temperature curves I and II, with the values of the former all markedly smaller than corresponding ones of the latter, calculated by the monthly mean series group I and the annual mean series group II, respectively. However, two calculated dδ¹⁸O/dT curves display the distinct difference: the variation amplitude of slope series II is larger than that of slope series I. Both curves had similar ascending trend from the 1960s to the 1970s, and then, their variations display the anti-phase. Moreover, the analyses show that there is negative correlation between slope series FI and temperature series II. However, the status is different for slope series I and temperature series I. Both series have contrary trend from the 1960s to the 1970s, whereas the same trend since the 1980s.     

30年来呼伦贝尔地区草地植被对气候变化的响应(英文)

Global warming has led to significant vegetation changes especially in the past 20 years. Hulun Buir Grassland in Inner Mongolia, one of the world’s three prairies, is undergoing a process of prominent warming and drying. It is essential to investigate the effects of climatic change (temperature and precipitation) on vegetation dynamics for a better understanding of climatic change. NDVI (Normalized Difference Vegetation Index), reflecting characteristics of plant growth, vegetation coverage and biomass, is...