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1.
长江流域降水极值时间序列的分布特征 总被引：3，自引：0，他引：3
在1960-2005年长江流域147气象观测站汛期4-9月逐日降水资料基础上,通过计算逐站大于95th强降水及其间隔天数、小于1.27mm/d的持续天数,分析长江流域降水极值时间序列的时空分布特征,并建立概率分布模式.研究发现,长江上游四川盆地附近及中下游鄱阳湖流域东南部是汛期强降水中心,也是长江流域强降水最集中发生的地区.汛期降水强度小于1.27mm/d的天数,在上游干流、岷沱江流域、乌江上游地区为多.但此处干旱持续天数最短,干旱形式并不严重.而在金沙江上、下游,洞庭湖流域,鄱阳湖流域东南部支流及下游干流区干旱持续天数较长.长江流域大于95th强降水的间隔天数与小于1.27mm/d的干旱持续天数服从Weibull-Ⅱ型分布.分布参数变化的模式较准确的反映降水极值时间序列的时空变化特征. 相似文献
2.
青藏高原东部玉树降水中稳定同位素季节变化与水汽输送 总被引：9，自引：0，他引：9
青藏高原东部玉树降水中稳定同位素的季节变化特征与青藏高原南部的西南季风区和北部的内陆地区有显著不同, 降水中δ18O波动幅度大季节变化特征不明显. 降水中稳定同位素变化的差异反映了水汽来源变化的差异. 通过降水中稳定同位素的空间对比以及结合NCAR/NCEP再分析数据研究了形成该地区降水的水汽来源变化与降水中稳定同位素之间的关系. 研究发现青藏高原东部降水的水汽来源受夏季西南季风直接带来的水汽以及北部内陆与局地蒸发水汽的共同影响; 水汽来源以西南季风为主, 但西南季风的输送强度较青藏高原南部地区偏弱, 而北方的大陆水汽输送与局地水汽增强. 其结果导致夏季玉树降水中δ18O波动幅度增加, 而季节变化特征减弱. 相似文献
3.
利用MM5V3区域气候模式单向嵌套ECHAM5全球环流模式,对中国地区1978-2000年及IPCC A1B情景下2038-2070年气候分别进行了水平分辨率为50 km的模拟试验.文章首先检验了模式模拟的当代极端气候结果,在此基础上对6个极端温度指数和6个极端降水指数的未来变化进行了预估.检验结果表明:MM5V3模式对中国地区当代日最高、最低温度及强降水(大雨和暴雨)日数的空间分布和概率特征均具有一定的模拟能力,但模拟的日最高温度在大部分地区偏低,日最低温度在南方地区偏低、西北地区偏高.概率统计结果显示日最高温度向低值频段偏移,日最低温度在0℃的峰值附近明显偏高.模式对大雨和暴雨年平均日数的模拟在东部地区偏多,概率统计结果则为一致偏大.未来中国地区极端气候预估结果表明:极端高温、极端低温和相对高温在全国范围内都将升高,且线性趋势均为上升;霜日日数则为减少,并具有下降趋势;暖日日数和相对低温在青藏高原和新疆部分地区有所减少、其它地区均为增加,且线性趋势暖日日数为上升,相对低温不明显.极端降水指数的变化具有区域特征,其中单日最大降水、连续五日最大降水、最长无雨期、强降水日数、简单降水强度和极端降水总量均在江淮、华南及西南地区有所增多,而在东北及内蒙古地区有所减少,未来中国南方地区降水的极端化趋势将更加显著.极端降水指数的线性趋势除最长无雨期外其它均为上升. 相似文献
4.
过去50年中国西部气候和径流变化的区域差异 总被引：12，自引：0，他引：12
通过对过去50年中国西部降水和主要河流径流变化的对比分析, 研究降水和径流的区域变化差异, 结果表明, 黄河上游径流和降水与新疆北部和青藏高原南部雅鲁藏布江流域径流、降水呈显著的反相关关系. 中国西部降水变化大体上以青藏高原唐古拉山和天山为界, 表现出南北一致, 中部(西部的喀喇昆仑山除外)相反, 即从南到北呈现出干-湿-干或湿-干-湿的区域变化差异; 在河流径流上表现为北部伊犁河流域和南部雅鲁藏布江流域径流变化的一致性, 而与黄河上游径流变化呈反位相变化; 同时, 新疆和黄河径流的反位相变化表现在年代际上, 而黄河和雅鲁藏布江径流变化表现在年际变化上. 黄河上游径流的变化与西北太平洋季风指数的变化比较一致, 这表明黄河上游径流变化受到较强的东亚季风的影响; 新疆总径流分别与西北太平洋季风指数和西风指数存在显著的正负相关关系, 寻找不同地区径流变化异同对于认识和预测径流未来变化具有重要的指导意义. 相似文献
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6.
利用NASA的MERRA再分析数据、台站降水资料、热带气旋最佳路径数据集和雷达资料初步对比探讨了2014年两次路径相似台风（"威马逊"和"海鸥"）的降水特征及其成因.结果表明，两者台站过程降水和最大日降水强度差异明显；在华南产生的过程降水和日降水均表现出明显的非对称性，最强均在海南岛；在海南岛产生的过程降水、日降水和最大小时降水最强均在海南岛西部和北部.与"海鸥"相比，在强降水时段，"威马逊"产生更大台站日降水的原因之一是其自身更强的强度和偏慢的移动速度，而且还与高层更强的南亚高压主体、中层偏弱偏东的副热带高压和低层强的低空急流密切相关.在强降水阶段，两者所处的环境风垂直切变均指向西南偏西-西南偏南方向，而强的对流均主要在环境风垂直切变的左侧或前侧.两者强降水主要在海南岛西部和北部的关键原因是五指山山脉和台风路径的相对位置配置类似，强降水区恰好处于向岸风面或五指山的迎风面. 相似文献
7.
本文通过对青藏高原降水季节演变特征的分析，选取日降水量和降水频率两个特征量来定义青藏高原各站点及全区的雨季，揭示了1961—2019年青藏高原雨季开始时间、结束时间、雨季长度和总雨量等的气候和变化特征.分析发现，青藏高原雨季的开始自东向西推进，而结束西早东晚，雨季持续时间自东向西缩短，雨季雨量东多西少.就青藏高原整体而言，雨季开始的平均日期在5月4日，结束的平均日期在10月15日，雨季平均持续163天，雨季雨量平均为413.2 mm.近60年，青藏高原雨季发生了显著变化，表现为开始时间提前、结束时间推迟、雨季延长、雨量增多.青藏高原各站点雨季的变化具有一定的区域性差异，主要表现为：高原雨季的开始整体提前，但是，高原东部边缘雨季开始提前的变化幅度相对较小；高原雨季的结束时间在南部和北部提前而在中部和东部推后；高原大部地区雨季雨量增多，但南部边缘等部分地区雨季雨量有所减少. 相似文献
8.
利用一套新的遥感信息反演的叶面积指数(LAI)数据和生物气候数据,建立了全球尺度的LAI与降水及温度的总体相关和距平相关,用以揭示全球尺度的植被季节和年际的变化对气候变化的响应特征.结果发现,全球尺度植被与气候因子的季节和年际变化随不同的生态系统差异明显.植被LAI与温度的总体正相关的最大值出现在北半球的中高纬度地区;LAI与降水的总体正相关高值(＞0.8)出现在亚洲东部、北美洲北部腹地和热带非洲北部的Sahel地区;最大的LAI与温度的正距平相关(0.4-0.6)出现在东南亚南部、非洲Sahel地区的南部和巴西东部等热带地区;而从LAI与降水的距平相关来看,最明显的特征是出现在西伯利亚、亚洲北部和北美西北部的强的负距平相关.本文进一步阐明了出现相关特征差异的陆-气过程物理机制. 相似文献
9.
城市化进程对北京地区冬季降水分布的影响 总被引：8，自引：0，他引：8
根据北京地区城市化程度将城市化进程分成两个时期: 即以1980年为分界点, 将1961~1980年划分为城市化慢速期, 1981~2000年为城市化快速期. 利用北京地区14个标准气象站40 a的降水量资料. 研究了城市化进程对北京地区降水分布的影响. 结果表明: 北京地区冬季降水分布发生了显著的、系统性的变化; 城市化缓慢期, 北京地区南部为降水相对较多地区, 北部为降水相对偏少地区; 城市化快速期, 相对降水量的分布正相反, 南部地区变为降水相对较少地区, 而北部变为降水相对偏多地区. 随着城市规模的扩大, 北京冬季“城市热岛”和“城市干岛”效应增强, 加速了云下降水物的蒸发过程, 使城区及南部地区的降水相对减少. 这可能是造成北京冬季降水分布变化的重要原因之一. 相似文献
10.
基于TRMM/TMI的亚洲夏季降水研究 总被引：4，自引：0，他引：4
利用热带测雨卫星(TRMM)微波成像仪(TMI)的长期观测资料, 对亚洲夏季降水的水平分布特征进行了统计分析, 指出了孟加拉湾北部沿岸, 中国南海南部, 赤道西太平洋暖池三个稳定的强降水中心. 并借助全球降水气候计划(GPCP)地表降水资料, 对亚洲范围内洋面, 陆面及6个典型区域的TMI降水准确性进行了评估, 结果表明利用TMI和GPCP资料对亚洲夏季降水的强弱降水中心及雨带位置的指示基本一致, TMI对陆面降水仍存在普遍的低估, 最大相对偏差在25%左右. 差异水平分布显示出极强的地域性特征, 出现最大差异(>3 mm/d)的区域位于陆地上青藏高原周边(正偏差), 及孟加拉湾北部地区(负偏差). 对产生偏差原因的分析表明, TMI陆面算法强烈依赖于降水云系统上层冰粒子含量的特性是构成其系统性偏低和局部地区对降水高估的主要因素, 而进一步的分析也显示GPCP雨量计极不均匀的分布对差异的产生也有所贡献, 尤其是在雨量计稀少的高原周边地区. 相似文献
11.
The response of the flood peak to the spatial distribution of rainfall has been reported in basins with nonuniform characteristics. However, prioritization of the influences of these characteristics is still poorly understood. This study evaluated the variability in the flood peak with the spatial distribution of rainfall at Sukhothai (city) in the Yom River basin, Thailand, and investigated the influence of the basin characteristics on the flood peak. For each of the 2-, 5- and 10-y rainfalls with durations of 24, 48 and 72 h, 1000 simulated rainfall events with various spatial distributions were generated according to the observed data by using a Monte Carlo analysis and Cholesky randomization. The floods from these rainfalls were then simulated, and the peak discharges were evaluated. The flood peaks from 24-h rainfalls were usually small but highly variable and could be extremely large when the rainfalls were concentrated over the mountainous region. The flood peaks from 48 to 72-h rainfalls were consistently large and correlated with the rainfalls over the joint area between the mountainous region and plain area. The basin characteristics that influenced the response of the flood peak to the spatial distribution of the rainfall appeared to depend on the rainfall duration and magnitude. For short-duration rainfalls, the response was mainly influenced by the surface storage when the rainfall was small and by the terrain steepness when the rainfall was large. For long-duration rainfalls, the response was mainly influenced by the soil percolation rate. 相似文献
12.
The plausible long‐term trend of precipitation in China and its association with El Niño–southern oscillation (ENSO) are investigated by using non‐parametric techniques. It is concluded that a greater number of decreasing trends are observed than are expected to occur by chance. Geographically, the decreasing trend was concentrated in most parts of China, including the Songliao River, Hai River, Huai River, Yellow River, Zhujiang River, and southern part of the Yangtze River basins, whereas an increasing trend appeared primarily in the western and middle parts of China, mainly including the Inland River basin, and the northern part of the Yangtze River basins. Monthly mean precipitation for the summer and early autumn months generally decreased, with the greatest decrease occurring in August. The precipitation in spring from January to April and later autumn, including September and October, tended to increase. The teleconnection between precipitation and ENSO has been investigated by using the non‐parametric Kendall's τ. The correlation coefficients between the southern oscillation index (SOI) and precipitation show the areas with positive or negative associations. Approximately 20% of the stations exhibit statistically significant correlations between SOI and precipitation, of which 70% show a negative correlation, with most of them appearing in southeast China and several appearing in northwest and northeast China. Similar regional patterns are also observed when the precipitation records are further subdivided into El Niño, La Niña, and neutral periods. Statistical tests for the three kinds of time series were carried out using the non‐parametric Wilcoxon rank‐sum test, and it is noted that the stations with significant differences in precipitation averages are mainly marked in the Yellow River basin and south China. The frequencies of below‐ and above‐average precipitation that occurred during the El Niño, La Niña, and neutral periods are estimated as well. The result shows that greater precipitation may be associated with El Niño episodes in south China, but drought may easily occur during El Niño episodes in the Yellow River basin. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
13.
江淮流域是我国暴雨频发的地区之一，而乌拉尔山阻塞高压和西太平洋副热带高压是北半球两个主要的大气环流系统.本文统计分析了1971~2003年期间乌山阻塞高压和西太平洋副高的逐日强度变化特征，研究了乌山阻塞高压和西太平洋副高对江淮流域强暴雨过程的响应关系.结果表明，江淮流域多数强暴雨过程发生在乌山阻高的减弱期，在乌山阻高的建立和加强期较少有持续性暴雨发生.乌山阻高的突然减弱是江淮流域强暴雨过程发生的强信号之一.同时，西太平洋副热带高压的加强西伸登陆是江淮流域强暴雨过程发生的必要条件之一. 相似文献
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本文以数字高程(DEM)地貌特征分析为基础,采用磷灰石裂变径迹测试和温度-时间反演模拟研究,分析江西相山铀矿田铀成矿后剥蚀程度的差异性,结合已知矿床的成矿特征,探讨地貌剥蚀程度与矿体保存之间的关系,为区域找矿提供指导.通过DEM合成图像和水系分布特征,表明相山铀矿田是一个遭受中等侵蚀的地貌区,相山主峰南北和东西侧地貌侵蚀差异特征明显.统计分析表明,已经发现的铀矿床、点的分布与次级火山机构关系密切,相山南部的次火山机构剥蚀较深,西部次火山机构剥蚀相对弱,而北部和西北部则处于中等剥蚀程度.磷灰石裂变径迹测试结果表明,相山铀矿田的南部和东部开始剥蚀的时间早于西部,但晚于相山主峰的剥蚀.利用磷灰石的裂变径迹长度和温度参数,进一步开展了温度-时间的反演模拟研究,结果显示相山西部快速隆升发生于40~60 Ma之间,相山南部和东部的快速隆升发生于60~75 Ma之间,相山主峰的快速隆升发生于75~100 Ma之间,表明相山主峰、相山东部及南部较西部经历了较长时间的剥蚀.结合现今区域地质体出露特征及铀矿化蚀变类型的空间展布规律、成矿深度的估算等,推测相山铀矿田东部和南部剥蚀程度较深,早期可能形成的中低温铀矿体被剥蚀殆尽;北部剥蚀程度中等,地表出露了形成深度稍深的碱交代蚀变矿床;而西部剥蚀程度较低,地表发育浅部低温成矿的酸交代蚀变铀矿床.据此推断,相山铀矿田的西部深部具有很好的找矿潜力. 相似文献
15.
The evolution and structure of rainstorms associated with a flash‐flood event are simulated by the Advanced Weather Research and Forecasting (WRF‐ARW) model of the National Center for Atmospheric Research and the Gridpoint Statistical Interpolation (GSI) data assimilation (DA) system of the National Oceanic and Atmospheric Administration (NOAA) of the United States. The event is based on a flash flood that occurred in the central Guangdong Province of south‐east China during 20–21 June 2005. Compared to an hourly mixed rain‐gauge and satellite‐retrieved precipitation data, the model shows the capability to reproduce the intensity and location of rainfall; however, the simulation depends on three conditions to a large extent: model resolution, physical processes schemes and initial condition. In this case, the Eta Ferrier microphysics scheme and the initialization with satellite radiance DA with a fine 4‐km grid spacing nested grid and coarse 12‐km grid spacing outer grid are the best options. The model‐predicted rain rates, however, are slightly overestimated, and the activities of the storms do not precisely correspond with those observed, although peak values are obtained. Abundant moisture brought by the south‐westerly winds with a mesoscale low‐level jet from the South China Sea or Bay of Bengal and trapped within the XingfengJiang region encompassed by northern Jiulian, southern Lianhua and eastern small mountains are apparently the primary elements responsible for the flood event. All simulated rainstorms were initiated over the southern slopes of the Jiulian Mountain and moved south or north‐eastward within the Xingfengjiang region. Meanwhile, the Skew‐T/Log‐P diagrams show that there is a fairly high convective available potential energy (CAPE) over the active areas of the rainstorms. The higher CAPE provides a beneficial thermodynamic condition for the development of rainstorms, but the higher convective inhibition near the northern, eastern and southern mountains prohibits the storms from moving out of the region and causes heavy rainfall that is trapped within the area. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
16.
Sensitivity analysis of the hydrological behaviour of basins has mainly focused on the correlation between streamflow and climate, ignoring the uncertainty of future climate and not utilizing complex hydrological models. However, groundwater storage is affected by climatic change and human activities. The streamflow of many basins is primarily sourced from the natural discharge of aquifers in upstream regions. The correlation between streamflow and groundwater storage has not been thoroughly discussed. In this study, the storage–discharge sensitivity of 22 basins in Taiwan was investigated by means of daily streamflow and rainfall data obtained over more than 30 years. The relationship between storage and discharge variance was evaluated using low‐flow recession analysis and a water balance equation that ignores the influence of rainfall and evapotranspiration. Based on the obtained storage–discharge sensitivity, this study explored whether the water storage and discharge behaviour of the studied basins is susceptible to climate change or human activities and discusses the regional differences in storage–discharge sensitivity. The results showed that the average storage–discharge sensitivities were 0.056 and 0.162 mm?1 in the northern and southern regions of Taiwan, respectively. In the central and eastern regions, the values were both 0.020 mm?1. The storage–discharge sensitivity was very high in the southern region. The regional differences in storage–discharge sensitivity with similar climate conditions are primarily due to differences in aquifer properties. Based on the recession curve, other factors responsible for these differences include land utilization, land coverage, and rainfall patterns during dry and wet seasons. These factors lead to differences in groundwater recharge and thus to regional differences in storage–discharge sensitivity. 相似文献
17.
本文分析处理了华北及其邻近地区以及日本三个地磁台1960——1977年的水平分量(H)、垂直分量(Z)和总强度(F)的观测资料。结果表明,华北地区Z的逐年变化在1974————1976年呈现一个由下降到上升的转折,但华北南部和北部的转折时间和速率存在着局部性差异,同时,等变线在空间上亦有由南向北的移动现象。H和F同样具有类似的区域性特征。 华北地区的上述差异,曾被一些作者认为是唐山地震的磁效应。他们提出:北京、昌黎地区地震前出现约数伽马至十几伽马的负异常。从本文的分析可以看出,这种负异常并非局部性的,它只不过是长期变化大尺度区域性特征的一种表现而已。 相似文献
18.
Identification of best predictors for forecasting seasonal rainfall and runoff in Australia 总被引：2，自引：0，他引：2
The first step towards developing a reliable seasonal runoff forecast is identifying the key predictors that drive rainfall and runoff. This paper investigates the lag relationships between rainfall across Australia and runoff across southeast Australia versus 12 atmospheric‐oceanic predictors, and how the relationships change over time. The analysis of rainfall data indicates that the relationship is greatest in spring and summer in northeast Australia and in spring in southeast Australia. The best predictors for spring rainfall in eastern Australia are NINO4 [sea surface temperature (SST) in western Pacific] and thermocline (20 °C isotherm of the Pacific) and those for summer rainfall in northeast Australia are NINO4 and Southern Oscillation Index (SOI) (pressure difference between Tahiti and Darwin). The relationship in northern Australia is greatest in spring and autumn with NINO4 being the best predictor. In western Australia, the relationship is significant in summer, where SST2 (SST over the Indian Ocean) and II (SST over the Indonesian region) is the best predictor in the southwest and northwest, respectively. The analysis of runoff across southeast Australia indicates that the runoff predictability in the southern parts is greatest in winter and spring, with antecedent runoff being the best predictor. The relationship between spring runoff and NINO4, thermocline and SOI is also relatively high and can be used together with antecedent runoff to forecast spring runoff. In the northern parts of southeast Australia, the atmospheric‐oceanic variables are better predictors of runoff than antecedent runoff, and have significant correlation with winter, spring and summer runoff. For longer lead times, the runoff serial correlation is reduced, especially over the northern parts, and the atmospheric‐oceanic variables are likely to be better predictors for forecasting runoff. The correlations between runoff versus the predictors vary with time, and this has implications for the development of forecast relationship that assumes stationarity in the historical data. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
19.
Satyaban Bishoyi Ratna 《Pure and Applied Geophysics》2012,169(1-2):259-273
This paper presents the results of an analysis of the daily rainfall of 329 rain gauge stations data over Maharashtra, a state in India, during the summer monsoon season, June to September, for the 11?year period from 1998 to 2008. Mesoscale analysis of the daily rainfall data is performed by converting the station rainfall data into gridded format with 15?km resolution. Various statistics have been carried out over 35 districts of four meteorological subdivisions of the Maharashtra state to understand the spatio-temporal variability of rainfall. Variation of monthly mean rainfall for the four monsoon months and a season as whole is analyzed for different rainfall statistics such as mean rainfall, rainfall variability, rainy days, maximum daily rainfall and classification of rainy days. Seasonal rainfall is maximum over the Konkan region followed by the eastern Vidharbha region whereas Madhya Maharashtra as a rain shadow region receives less rainfall. The rainfall is highly variable over all of Maharashtra with the coefficient of variability of the daily rainfall varying between 100 and 300%. Seasonal distribution of the number of rainy days shows 90–100 over southern Konkan, 80–90 over northern Konkan, 50–60 over eastern Vidharbha, and the southeast Madhya Maharashtra has the lowest number of about 15–20 rainy days. The highest values of maximum daily rainfall are located over the Sindhudurg, Ratnagiri, Raigadh, Mumbai and Thane districts of the Konkan region followed by that over eastern Vidharbha. The rainfall data have been divided into three categories (moderate rainfall, heavy rainfall and extreme heavy rainfall) based upon seven categories used by the India Meteorological Department. Heavy rainfall zones lie over the southern Konkan region, whereas extreme heavy rainfalls occur over northern latitudes. The data used in this study is having high resolution and district wise analysis over Maharashtra state is extremely beneficial. 相似文献