1971-2004年青藏高原总云量时空变化及其影响因子

With Empirical Orthogonal Function (EOF) and trend analysis method adopted, the spatio-temporal variation of total cloud amount is analyzed for 75 stations on the Qinghai-Tibet Plateau during the period 1971-2004. Analysis indicates that the total cloud amount decreases from the southeast to the northwest of the plateau, and that the annual and seasonal variations in total cloud amount both show an apparent declining tendency over the past decades. Correlation analysis demonstrates that the total cloud amount is negative with sunshine duration and diurnal temperature range (DTR), and is positive with precipitation and the relative humidity, respectively. The negative correlation is consistent with the radiative effect of cloud, while the positive correlation between total cloud amount and precipitation is obscured because of the influence of topographic factors. Discussion implies that the decrease of total cloud amount is possibly due to the variation of atmospheric aerosol content and ozone concentration over the plateau, although it is difficult to quantify the driving force mechanism up to now.     

Cloudiness variations over the Qinghai-Tibet Plateau during 1971–2004

With Empirical Orthogonal Function （EOF） and trend analysis method adopted, the spatio-temporal variation of total cloud amount is analyzed for 75 stations on the Qinghai-Tibet Plateau during the period 1971-2004. Analysis indicates that the total cloud amount decreases from the southeast to the northwest of the plateau, and that the annual and seasonal variations in total cloud amount both show an apparent declining tendency over the past decades. Correlation analysis demonstrates that the total cloud amount is negative with sunshine duration and diurnal temperature range （DTR）, and is positive with precipitation and the relative humidity, respectively. The negative correlation is consistent with the radiative effect of cloud, while the positive correlation between total cloud amount and precipitation is obscured because of the influence of topographic factors. Discussion implies that the decrease of total cloud amount is possibly due to the variation of atmospheric aerosol content and ozone concentration over the plateau, although it is difficult to quantify the driving force mechanism up to now.     

1961-2004年青藏高原夏季降水的时空分布

The summer day-by-day precipitation data of 97 meteorological stations on the Qinghai-Tibet Plateau from 1961 to 2004 were selected to analyze the temporal-spatial distribution through accumulated variance,correlation analysis,regression analysis,empirical orthogonal function,power spectrum function and spatial analysis tools of GIS.The result showed that summer precipitation occupied a relatively high proportion in the area with less annual precipitation on the Plateau and the correlation between summer precipitation and annual precipitation was strong.The altitude of these stations and summer precipitation tendency presented stronger positive correlation below 2000 m,with correlation value up to 0.604（α=0.01）.The subtracting tendency values between 1961-1983 and 1984-2004 at five altitude ranges（2000-2500 m,2500-3000 m,3500-4000 m,4000-4500 m and above 4500 m）were above zero and accounted for 71.4%of the total.Using empirical orthogonal function, summer precipitation could be roughly divided into three precipitation pattern fields：the Southeast Plateau Pattern Field,the Northeast Plateau Pattern field and the Three Rivers＇ Headstream Regions Pattern Field.The former two ones had a reverse value from the north to the south and opposite line was along 35°N.The potential cycles of the three pattern fields were 5.33a,21.33a and 2.17a respectively,tested by the confidence probability of 90%.The station altitudes and summer precipitation potential cycles presented strong negative correlation in the stations above 4500 m,with correlation value of-0.626（α=0.01）.In Three Rivers Headstream Regions summer precipitation cycle decreased as the altitude rose in the stations above 3500 m and increased as the altitude rose in those below 3500 m.The empirical orthogonal function analysis in June precipitation,July precipitation and August precipitation showed that the June precipitation pattern field was similar to the July＇s,in which southern Plateau was positive and northern Plateau negative.But positive     

曲靖市降水量和低云量的时空变化特征研究

利用曲靖市城市和郊区1974～2011年38年的降水量、低云量等气象资料,对资料进行分析后得出其日变化、月变化、年变化规律,并对城市和郊区进行对比分析,同时对曲靖市降水量和低云量的影响因子进行了灰色关联度分析。结果表明:城市一天中夜晚城市降水量比白天多,14时低云量在一天中最大,降水量和低云量月变化都是夏秋季节多冬春季节少,降水量总体呈下降趋势,低云量的年变化趋势总体上升趋势。城市和郊区对比分析发现降水量的日变化是白天城市多,夜晚郊区多,年降水量城市和郊区差别越来越小,最近8年市区降水量超过郊区;城市和郊区低云量对比分析发现日变化是08时和20时前后都是城市少于郊区,而14时前后城市多于郊区,低云量的年变化是,前20年是城市少于郊区,近18年是城市反而多于郊区。对降水量和低云量影响最大的自然因子是年平均风速,人为因子是非农业人口,且人为因子比自然因子的影响更大。     

京津冀地区AOD时空变化及影响因子的地理探测

基于MODIS 3 km AOD遥感数据,利用空间自相关模型及地理探测器对2010—2016年京津冀地区AOD的时空变化特征及其影响因子进行探测。结果表明:(1) 2010—2016年京津冀地区年平均AOD值为0.83,其中天津市年均AOD值为研究区最高,河北省次之,北京市最低。研究区及各分区AOD的7 a变化趋势大体一致,呈现先下降后上升再小幅波动的状态。(2)空间自相关分析表明京津冀地区AOD空间分布呈现显著正相关。局部高高聚集区主要集中在北京市东南部、天津市南部及河北省的中南部,低低聚集区集中分布在西北部山区。研究区高低聚集区面积均呈减小趋势,不显著区呈扩大态势。(3)地理探测器结果表明不同区域的主导影响因子不同,北京市首要影响因子为NDVI,其次为人口密度,且二者交互作用明显。天津市主导因子为风速,人口密度、第二产业生产总值等人为因子的作用力也较大,风速与其交互作用较强。河北省主导因子为人口密度,GDP与第二产业生产总值等的作用力次之,整体交互作用偏弱。通过地理探测器解析京津冀地区AOD空间分异的影响机理,其结果对我国大气污染治理具有重要意义。     

青藏高原夏季夜雨率空间分布及其变化特征

选取了1961-2007年青藏高原海拔2000m以上76个气象站夏季(6-9月)逐日地面降水观测资料,分析了青藏高原夏季夜雨率的时空特征,结果表明:1.青藏高原夜雨率具有显著的区域差异性,在西藏中西部夜雨率呈“纬向型”分布,而西藏东部、川西高原至滇北夜雨率则表现为“西北-东南”走向;夜雨率高值中心出现在雅鲁藏布江中段(日喀则地区东北部至拉萨市一带),达到75％以上,同时喜马拉雅山脉南麓可能是夜雨率＞70％的另一个高值区域;夜雨率最低值在青海省西北部,仅为33％;2.高原夜雨率具有明显的海拔效应,夜雨率与海拔呈显著的反相关,即海拔越高夜雨率越低,反之亦然;3.高原夜雨率随夏季日期推后呈增大趋势,而年际变化上则表现为明显的下降趋势,20世纪80年代初存在明显的突变现象;4.高原夜雨率与日降水量之间存在一定的关联:当日降水量＜1 mm时夜雨率仅为48.8％,此后夜雨率随着日降水量增加而明显增大,特别是降水量在20 mm以下时,夜雨率上升速度最快,上升幅度超过20％;当日降水量为23～40 mm时,夜雨率稳定在70％～76％间,随后又略有波动下降;当日降水量为33 mm时,夜雨率达到极大值,为75.1％.青藏高原夜雨率的空间变化可能受大地形的影响.高原夜雨对农牧业生产有利的同时,也可能会带来诸多自然灾害.因此,深入探讨夜雨率是制定有效防御气象灾害对策的重要依据.     

青藏高原年日照时数变化的时空特征

利用青藏高原地区68个测站1973-2007年近35 a的日照时数资料,采用主成分分析、旋转主成分分析、小波分析等方法对年日照时数变化的时空特征进行了分析.结果表明:1.青藏高原年日照时数呈现东南部较少,逐渐向西北地区增加的特征,近35 a青藏高原西部、西藏西南部和青海西南部年日照时数呈增加趋势,其余地区以减少趋势为主.第一载荷向量场反映了全区日照时数较一致的偏多或偏少;第二三载荷向量场分别反映了高原日照时数南北相反变化以及中部与西部、北部相反变化的差异.2.青藏高原年日照时数空间异常区可分为7个,即高原东南区、高原北部区、高原中部区、藏东区、青海北部区、藏西南区和高原西部区.高原北部和中东部年日照时数减少趋势较为显著,高原西部和西南部年日照时数呈增加趋势.3.高原东南区、高原中部区、青海北部区和藏西南区存在显著的16 a周期,其他异常区的显著周期及其年代变化差异较大.     

甘肃省2004-2009年土地沙漠化时空变化分析

基于遥感和GIS技术,选取2004年和2009年的TM和ETM遥感数据,并辅以甘肃省地形图及其他资料,通过野外调查和人机交互解译,采用转移矩阵分析研究甘肃省沙漠化土地面积、程度、类型变化及区域分异,并对其变化因素进行了分析.结果表明,总体上甘肃省沙漠化土地面积在减少,沙漠化程度在减轻,土地沙漠化呈现逆转的态势,但玛曲县沙漠化土地面积有所增加.一方面是由于气候变化和降水减少,导致黄河河道来水量减少,河道滩地裸露,原来的水域变化为固定沙地;另一方面是由于过度放牧,使大面积的非沙漠化土地变为流动、固定、半固定沙地,导致沙漠化进一步加剧.     

1983-2019年黑龙江省春季土壤湿度时空变化特征及影响因素

春季土壤湿度是影响东北粮食产量和品质的重要因素.在气候变暖的背景下,东北春季土壤湿度如何变化,鲜有研究.本文基于1983-2019年黑龙江省22个农业气象站的土壤湿度和气象观测资料,采用方差分析、突变分析及空间分析等方法,分析20世纪80年代以来黑龙江省春季土壤湿度的时空变化特征及其影响因素.结果 表明:1983-20...     

青藏高原冬季积雪时空变化特征及其与北极涛动的关系北大核心CSCDCSSCI

青藏高原积雪不仅是气候变化的敏感指示器,而且对亚洲季风区乃至全球气候具有显著影响。利用2002-2014年MODIS积雪覆盖范围产品及ERA-Interim再分析资料,采用气候统计诊断方法探究了青藏高原冬季积雪的时空变化特征及其与北极涛动(AO)的关系,结果表明:(1)高原冬季积雪空间分布差异明显,高原西部和东南部多雪,中部和北部少雪,东部积雪年际变化大,西部多雪区积雪较为稳定。(2)高原冬季积雪EOF分解第一模态具有东—西反位相变化特征,当高原东部积雪偏多(少)时,西部积雪偏少(多)。(3)该模态与AO密切相关。AO正位相时,东亚大槽减弱,南支槽加深东移,西太平洋副高加强使得更多暖湿气流到达高原,有利于高原东部降雪,而高原西南侧阿拉伯海附近存在反气旋异常,使得阿拉伯海的水汽不易抬升进入高原西部,高原西部盛行干燥的下沉气流异常,造成少雪的环流背景,且地表温度偏高不利于积雪维持,从而导致高原西部积雪的减少;AO负位相时,东亚大槽增强使得冬季风加强,高原东部受来自西北的干冷气流控制,不利于降雪产生,高原西南侧出现气旋异常,促使来自阿拉伯海和孟加拉湾的暖湿气流输送至高原西部,与来自西伯利亚的冷空气相遇,营造多雪的环流背景。     

Cloudiness variations over the Qinghai–Tibet Plateau during 1971–2004

With Empirical Orthogonal Function (EOF) and trend analysis method adopted, the spatio-temporal variation of total cloud amount is analyzed for 75 stations on the Qinghai–Tibet Plateau during the period 1971–2004. Analysis indicates that the total cloud amount decreases from the southeast to the northwest of the plateau, and that the annual and seasonal variations in total cloud amount both show an apparent declining tendency over the past decades. Correlation analysis demonstrates that the total cloud amount is negative with sunshine duration and diurnal temperature range (DTR), and is positive with precipitation and the relative humidity, respectively. The negative correlation is consistent with the radiative effect of cloud, while the positive correlation between total cloud amount and precipitation is obscured because of the influence of topographic factors. Discussion implies that the decrease of total cloud amount is possibly due to the variation of atmospheric aerosol content and ozone concentration over the plateau, although it is difficult to quantify the driving force mechanism up to now.     

近35 年青藏高原雨量和雨日的变化特征

利用青藏高原1971-2005 年49 个气象台站逐日雨量和雨日资料, 分析了青藏高原年、 季雨量和雨日变化趋势。结果表明, 近35 年西藏大部分地区年雨量、雨日呈现显著增加趋 势, 而青海省大部分地区雨量、雨日却呈减少趋势。夏半年, 高原上雨日减少, 雨量增加, 说明降水越来越集中, 降水强度在增加。冬半年, 高原上雨日、雨量均在增加。高原夏半年小雨(0.1~4.9 mm) 雨日减少, 雨量增加; 小雨(5.0~9.9 mm) 和中雨的雨日和雨量均呈增加趋 势, 大雨以上的雨日和雨量均减少。冬半年, 青藏高原小雪、中雪、大雪不同量级日数和雪 日的平均雪量均呈增加趋势; 暴雪日和雪量变化均不明显。     

PATMOS-x、ISCCP云量产品及地面观测在中国区域的对比分析

利用1986~2006年PATMOS-x 、ISCCP总云量和低云量产品与中国区域地面台站观测的总云量、低云量资料进行对比分析,对比不同来源、不同观测方法造成的云量数据在时间、空间上的差异,为资料使用者提供参考。结果表明,与台站观测资料相比,无论PATMOS-x还是ISCCP其总云量数据的空间分布、与站点观测数据的格点相关性均好于低云量数据;PATMOS-x总云量、低云量多年平均的空间分布较ISCCP更接近站点观测;中国区域平均低云量的线性趋势PATMOS-x与站点观测一致,表现为显著的上升趋势,而ISCCP低云量数据则呈现微弱的下降趋势。     

夏半年青藏高原“湿池”的水汽分布及水汽输送特征

采用1948-2007年共计60年的NCEP/NCAR再分析资料.计算了夏半年(4-9月)青藏高原大气中的可降水量、水汽输送通量和水汽输送通量散度,分析了夏半年青藏高原可降水量的分布和变化特征,青藏高原及其附近的水汽输送.结果表明:在对流层中层的青藏高原上空,夏季是一个明显的大气水汽含量高中心,"湿池"特征非常显著,湿池主要有三个大的可降水量中心,即高原的西南部、东南部和高原南侧.4-9月,高原上的可降水量变化很大,高原的增湿的速度小于减湿的速度.水汽进人高原主要通过三条水汽通道,即西风带水汽输送通道、印度洋-孟别拉湾水汽通道和南海-孟加托湾水汽通道.水汽主要在高原西南侧、喜马拉雅山中段和高原东南侧进入高原.     

青藏高原地气温差变化分析

利用青藏高原及其临近区域的99个气象站1960~2000年地表温度和气温资料, 利用主成分分析和功率谱分析方法, 分析了青藏高原地气温差的空间分布及时间演变特征。结果表明：青藏高原地气温差6月份最大,12月份最小。青藏高原冷、暖季和年均的地气温差空间分布前三个载荷向量场大致可表现三种分布型：西北-东南反向变化型、地形海拔反映型、冻土分布反映型;载荷所对应的时间演变型：单调上升、单调下降型、基本平稳型和具有极小值的下凹抛物线型。高原地气温差的周期振荡在不同区域的显著性不同,普遍出现的是2年左右的周期。依据温差冷季第三主分量载荷的空间分布型,可将高原划分为两大区,即多年冻土影响气温区和季节冻土影响气温区。     

1971-2011年青藏高原干湿气候区界线的年代际变化

气候变化是沙漠化的重要影响因素,了解青藏高原的气候背景变化是探讨高原沙漠化的基础。利用1971-2011年青藏高原81个站点逐日气温、降水等多种气象要素资料,采用面积权重方法研究了近41a高原干湿气候变化的年代际波动特征。结果表明：近年来高原气温持续升高,降水显著增加,于20世纪90年代中后期变得更暖更湿;平均风速由显著下降趋势转变为平稳变化;相对湿度由上升趋势转为下降趋势,且下降幅度明显;日照时数自80年代开始显著下降,进入21世纪转为上升趋势。在这5个因子共同作用下潜在蒸发量于90年代中后期发生明显转折,由下降趋势转为上升趋势。20世纪90年代中后期是高原气候变化的重要节点。高原干湿界线年代际波动明显,不同干湿气候区的面积存在年代际差异,整体表现为各界线均向西北方向移动,极端干旱区、干旱区面积有所减小,半干旱区、半湿润区及湿润区面积有所增大。干湿指数0.5线与高原沙漠化界线重合,干湿界线波动变化在一定程度可反映高原沙漠化变化情况。     

1971-2010年三江源地区干湿状况变化的空间特征

 依据1971-2010年地面观测气象数据,计算了三江源地区湿润指数。利用经验正交函数分解（EOF）和偏相关系数,对近40 a三江源地区干湿状况变化的时空特征及其影响因素进行了分析。结果表明:三江源地区干湿状况的变化在其北部与南部、东部与西部间存在明显反相位变化特征。北部和东部的部分区域分别在20世纪90年代和21世纪后表现出气候湿润化趋势,其余大部地区的持续干旱化趋势始于20世纪80年代初,其中南部与西部变干趋势显著,其湿润指数线性趋势率达到-8%/10 a。虽然三江源地区干湿状况主要决定于降水量和相对湿度的变化,但20世纪90年代中期后气温的显著上升,使得气温也成为关键的影响因子之一,即使在降水明显增加的背景下,也引起三江源主体区域湿润指数的明显下降。气候变暖情景下,北部和东部地区在近十几年暖湿化趋势明显,其余大部地区表现为不同程度的暖干化趋势。     

Characterizing the Spatio-temporal Dynamics and Variability in Climate Extremes over the Tibetan Plateau during 1960-2012

Extreme climate events play an important role in studies of long-term climate change. As the Earth’s Third Pole, the Tibetan Plateau (TP) is sensitive to climate change and variation. In this study on the TP, the spatiotemporal changes in climate extreme indices (CEIs) are analyzed based on daily maximum and minimum surface air temperatures and precipitation at 98 meteorological stations, most with elevations of at least 4000 m above sea level, during 1960-2012. Fifteen temperature extreme indices (TEIs) and eight precipitation extreme indices (PEIs) were calculated. Then, their long-term change patterns, from spatial and temporal perspectives, were determined at regional, eco-regional and station levels. The entire TP region exhibits a significant warming trend, as reflected by the TEIs. The regional cold days and nights show decreasing trends at rates of -8.9 d (10 yr)^-1 (days per decade) and -17.3 d (10 yr)^-1, respectively. The corresponding warm days and nights have increased by 7.6 d (10 yr)^-1 and 12.5 d (10 yr)^-1, respectively. At the station level, the majority of stations indicate statistically significant trends for all TEIs, but they show spatial heterogeneity. The eco-regional TEIs show patterns that are consistent with the entire TP. The growing season has become longer at a rate of 5.3 d (10 yr)^-1. The abrupt change points for CEIs were examined, and they were mainly distributed during the 1980s and 1990s. The PEIs on the TP exhibit clear fluctuations and increasing trends with small magnitudes. The annual total precipitation has increased by 2.8 mm (10 yr)^-1 (not statistically significant). Most of the CEIs will maintain a persistent trend, as indicated by their Hurst exponents. The developing trends of the CEIs do not show a corresponding change with increasing altitude. In general, the warming trends demonstrate an asymmetric pattern reflected by the rapid increase in the warming trends of the cold TEIs, which are of greater magnitudes than those of the warm TEIs. This finding indicates a positive shift in the distribution of the daily minimum temperatures throughout the TP. Most of the PEIs show weak increasing trends, which are not statistically significant. This work aims to delineate a comprehensive picture of the extreme climate conditions over the TP that can enhance our understanding of its changing climate.