共查询到19条相似文献，搜索用时 328 毫秒
1.
利用热带降雨计划卫星（TRMM）获得的雷达降雨资料，对南海及其周边区域（简称南海地区）降雨的空间分布和季节特征进行了研究。结果表明：南海地区的降雨在空间上分布很不均匀，同时具有显著的季节变化。除了副高活动、季风潮、冬季冷涌和热带低压活动等天气过程，南海周边广泛分布的山地地形对该地区的降雨分布也产生强烈影响，降雨呈现南部高于北部、东部高于西部的分布特征。与CAMP和台站资料相比，PR观测具有更丰富的空间结构，能够更好地体现降雨随时间和空间变化的特征、反映高大的山地地形对降雨分布的影响。 相似文献
2.
广东省1960～2007年降雨侵蚀力变化趋势分析 总被引：3，自引：0，他引：3
降雨侵蚀力反映由降雨引起的土壤侵蚀的潜在能力.本文利用广东省25个站点48年(1960～2007)的日雨量资料计算了各站的降雨侵蚀力,并用Mann-Kendall(M-K)非参数检验和克里格空间插值法分析了降雨侵蚀力的时空变化规律.结果表明:广东省降雨侵蚀力的空间分布呈沿海向内陆逐渐递减的趋势.全省大部分地区的年降雨侵蚀力呈现不明显上升趋势,且存在较明显的年代际和年际变化.降雨侵蚀力的年内分布特征和降雨量分布类似,呈"双峰型",主要集中在4～9月的雨季.对于季节序列,冬季、春季和夏季大部分地区的降雨侵蚀力有不同程度的上升,秋季全省几乎所有地区呈下降趋势.汛期的降雨侵蚀力变化特征与年降雨侵蚀力相似. 相似文献
3.
日本四国地区分布有大量具有独特地质条件和活动特征的结晶片岩滑坡。长期的实地观测结果表明,季节性的集中降雨是影响此类滑坡活动的主要因素。文章基于对此类滑坡活动观测资料和降雨资料的综合分析,阐述了结晶片岩滑坡的活动特点以及集中降雨对其的影响作用。通过对有效雨量和滑坡位移等反映降雨影响和滑坡活动状况参数的分析,揭示了集中降雨与滑坡活动之间的关系,并且确定了对该地区滑坡活动产生影响的降雨特征,为此类滑坡灾害的防治与管理提供了依据和评价指标。 相似文献
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我国西南山区降雨侵蚀力时空变化趋势研究 总被引：14，自引：0，他引：14
降雨是我国西南山区土壤侵蚀的主要动力因素,降雨侵蚀力反映了降雨对土壤侵蚀的潜在能力,研究降雨侵蚀力的时空变化趋势对我国西南山区土壤侵蚀的监测、评估、预报和治理具有重要意义。利用1960—2009年129个气象站逐日降雨量资料,计算出西南山区各气象站逐年降雨侵蚀力。采用趋势系数、气候倾向率和克吕格插值等方法对西南山区降雨侵蚀力50年来的时空变化趋势进行了探讨。结果表明:西南山区降雨侵蚀力空间分布特征与年降水量的空间分布特征一致;西南山区西北部的青藏高原区域降雨侵蚀力年际变化明显,变差系数Cv一般高于0.40;西南山区大部地区降雨侵蚀力呈上升趋势,说明由降雨侵蚀力引起的土壤侵蚀风险在增加,但在成都平原附近降雨侵蚀力在明显下降;降雨侵蚀力变化趋势系数随海拔高度升高而不断增加,在海拔2 500 m以上地区尤为明显,西南山区西北部的高海拔地区海拔高度对降雨侵蚀力增加具有放大效应。 相似文献
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分析了1949～2008年间120个对宁波市造成影响热带气旋的年内分布情况,及其移动路径、强度变化对宁波市降雨分布的影响。结果表明:热带气旋的不同行进路径、不同登陆地点以及不同影响时间,直接影响宁波市降雨的时空分布及降雨的强度,分析的结果可以作为今后防台工作中相似预报的参考。 相似文献
8.
利用热带降雨观测计划(TRMM)卫星雷达降雨数据驱动分布式陆面水文模型,研究流域尺度陆面水文过程,评估该数据在水文模拟与预报等研究领域的性能。通过与实测雨量资料比较,验证TRMM卫星雷达降雨数据的质量。分别将TRMM卫星雷达降雨与观测降雨作为耦合模型的气象输入,模拟和研究淮河流域1998~2003年的陆面水文过程时空变化。结果表明,TRMM卫星雷达降雨数据能够很好地描述降雨的时空分布,利用TRMM降雨模拟的结果与利用观测降雨模拟的结果精度相当;模拟流量与实测资料基本吻合。卫星雷达降雨数据在陆面水文过程研究中具有广泛的应用前景。 相似文献
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亚马逊流域降雨径流时空变化分析 总被引：2，自引：0，他引：2
基于全球降雨气候中心(GPCC)和全球径流数据中心(GRDC)的降雨径流资料,选择亚马逊流域16个测站,利用三次样条、Mann-Kendall法、Yamamoto检验、最大熵谱法和小波分析法,分析了各子流域的年降水量和年径流量的趋势性、周期性、突变性,并对降水、径流的时间变化和空间分布进行分析。结果表明:整个流域降水量和径流量随时间变化呈增加趋势;其降雨分布不均,南多北少;年降水倾向率有明显空间差异,近50年,流域上、下游径流增加,中游径流减少,整体则有微弱增长。 相似文献
11.
Some characteristics of very heavy rainfall over Orissa during summer monsoon season 总被引：1，自引：0，他引：1
Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very
heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features
of very heavy rainfall (24 hours rainfall ≥125 mm) over Orissa during summer monsoon season (June–September) by analysing
20 years (1980–1999) daily rainfall data of different stations in Orissa. The principal objective of this study is to find
out the role of synoptic scale monsoon disturbances in spatial and temporal variability of very heavy rainfall over Orissa.
Most of the very heavy rainfall events occur in July and August. The region, extending from central part of coastal Orissa
in the southeast towards Sambalpur district in the northwest, experiences higher frequency and higher intensity of very heavy
rainfall with less interannual variability. It is due to the fact that most of the causative synoptic disturbances like low
pressure systems (LPS) develop over northwest (NW) Bay of Bengal with minimum interannual variation and the monsoon trough
extends in west-northwesterly direction from the centre of the system. The very heavy rainfall occurs more frequently with
less interannual variability on the western side of Eastern Ghat during all the months and the season except September. It
occurs more frequently with less interannual variability on the eastern side of Eastern Ghat during September. The NW Bay
followed by Gangetic West Bengal/Orissa is the most favourable region of LPS to cause very heavy rainfall over different parts
of Orissa except eastern side of Eastern Ghat. The NW Bay and west central (WC) Bay are equally favourable regions of LPS
to cause very heavy rainfall over eastern side of Eastern Ghat. The frequency of very heavy rainfall does not show any significant
trend in recent years over Orissa except some places in north-east Orissa which exhibit significant rising trend in all the
monsoon months and the season as a whole. 相似文献
12.
Majid Javari 《Arabian Journal of Geosciences》2017,10(4):78
The main objective of this paper is to analyze the spatial variability of rainfall trends using the spatial variability methods of rainfall trend patterns in Iran. The study represents a method on the effectiveness of spatial variability for predicting rainfall trend patterns variations. In rainfall trend analysis and spatial variability methods, seven techniques were used: Mann–Kendall test, Sen’s slope method, geostatistical tools as a global polynomial interpolation and the spatial autocorrelation (Global Moran’s I), high/low clustering (Getis-Ord General G), precipitation concentration index, generate spatial weights matrix tool, and activation functions of semiliner, sigmoid, bipolar sigmoid, and hyperbolic tangent in the artificial neural network technique .For the spatial variability of monthly rainfall trends, trend tests were used in 140 stations of spatial variability of rainfall trends in the 1975–2014 period. We analyzed the long and short scale spatial variability of rainfall series in Iran. Spatial variability distribution of rainfall series was depicted using geostatistical methods (ordinary kriging). Relative nugget effect (RNE) predicted from variograms which showed weak, moderate, and strong spatial variability for seasonal and annual rainfall series. Moreover, the rainfall trends at each station were examined using the trend tests at a significance level of 0.05. The results show that temporal and spatial trend patterns are different in Iran and the monthly rainfall had a downward (decreasing) trend in most stations, and the trend was statistically significant for most of the series (73.5% of the stations demonstrated a decreasing trend with 0.5 significance level). Rainfall downward trends are generally temporal-spatial patterns in Iran. The monthly variations of rainfall decreased significantly throughout eastern and central Iran, but they increased in the west and north of Iran during the studied interval. The variability patterns of monthly rainfall were statistically significant and spatially random. Activation functions in the artificial neural network models, in annual time scale, had spatially dispersed distribution with other clustering patterns. The results of this study confirm that variability of rainfall revealing diverse patterns over Iran should be controlled mainly by trend patterns in the west and north parts and by random and dispersed patterns in the central, southern, and eastern parts. 相似文献
13.
Temporal distribution of southwest monsoon (June –September) rainfall is very useful for the country’s agriculture and food
grain production. It contributes more than 75% of India’s annual rainfall. In view of this, an attempt has been made here
to understand the performance of the monthly rainfall for June, July, August and September when the seasonal rainfall is reported
as excess, deficient or normal. To know the dependence of seasonal rainfall on monthly rainfall, the probabilities of occurrence
of excess, deficient and normal monsoon when June, July, August and also June + July and August + September rainfall is reported
to be excess or deficient, are worked out using the long homogenous series of 124 years (1871-–1994) data of monthly and seasonal
rainfall of 29 meteorological sub-divisions of the plain regions of India.
In excess monsoon years, the average percentage contribution of each monsoon month to the long term mean (1871–1994) seasonal
rainfall (June –September) is more than that of the normal while in the deficient years it is less than normal. This is noticed
in all 29 meteorological sub-divisions. From the probability analysis, it is seen that there is a rare possibility of occurrence
of seasonal rainfall to be excess/deficient when the monthly rainfall of any month is deficient/excess. 相似文献
14.
反映流域整体降水情势的面雨量一直是水文模型的重要输入参数之一,在泰森多边形雨量法的基础上考虑地理空间要素对降雨空间分布的影响,采用面向对象的遥感信息聚类方法提取出雅砻江流域2项形状因子(周长、面积)和5项地形因子(平均高程、平均坡度、平均坡向、高程差周长比和高程差面积比)。降雨—径流相关性分析结果表明:地形因子雨量法在月尺度上的降雨估算精度高于年尺度,且在月尺度上能更好地反映流域不同区段的降雨空间分布特征;在月、年际降雨变化趋势分析方面,年尺度上的降雨与径流一阶差分后平均相关系数为0. 903,高于月尺度的0. 629,主要由于水电站调蓄过程对流域径流异质性的影响,且影响度随着时间尺度缩小而放大。 相似文献
15.
Spatio-temporal variability of summer monsoon rainfall over Orissa in relation to low pressure systems 总被引：2，自引：0，他引：2
The summer monsoon rainfall over Orissa occurs mostly due to low pressure systems (LPS) developing over the Bay of Bengal
and moving along the monsoon trough. A study is hence undertaken to find out characteristic features of the relationship between
LPS over different regions and rain-fall over Orissa during the summer monsoon season (June-September). For this purpose,
rainfall and rainy days over 31 selected stations in Orissa and LPS days over Orissa and adjoining land and sea regions during
different monsoon months and the season as a whole over a period of 20 years (1980-1999) are analysed. The principal objective
of this study is to find out the role of LPS on spatial and temporal variability of summer monsoon rainfall over Orissa.
The rainfall has been significantly less than normal over most parts of Orissa except the eastern side of Eastern Ghats during
July and hence during the season as a whole due to a significantly less number of LPS days over northwest Bay in July over
the period of 1980-1999. The seasonal rainfall shows higher interannual variation (increase in coefficient of variation by
about 5%) during 1980-1999 than that during 1901-1990 over most parts of Orissa except northeast Orissa. Most parts of Orissa,
especially the region extending from central part of coastal Orissa to western Orissa (central zone) and western side of the
Eastern Ghats get more seasonal monsoon rainfall with the development and persistence of LPS over northwest Bay and their
subsequent movement and persistence over Orissa. The north Orissa adjoining central zone also gets more seasonal rainfall
with development and persistence of LPS over northwest Bay. While the seasonal rainfall over the western side of the Eastern
Ghats is adversely affected due to increase in LPS days over west central Bay, Jharkhand and Bangladesh, that over the eastern
side of the Eastern Ghats is adversely affected due to increase in LPS days over all the regions to the north of Orissa. There
are significant decreasing trends in rainfall and number of rainy days over some parts of southwest Orissa during June and
decreasing trends in rainy days over some parts of north interior Orissa and central part of coastal Orissa during July over
the period of 1980-1999 相似文献
16.
The summer monsoon rainfall over Orissa, a state on the eastern coast of India, is more significantly related than Indian
summer monsoon rainfall (ISMR) to the cyclonic disturbances developing over the Bay of Bengal. Orissa experiences floods and
droughts very often due to variation in the characteristics of these disturbances. Hence, an attempt was made to find out
the inter-annual variability in the rainfall over Orissa and the frequencies of different categories of cyclonic disturbances
affecting Orissa during monsoon season (June–September). For this purpose, different statistical characteristics, such as
mean, coefficient of variation, trends and periodicities in the rainfall and the frequencies of different categories of cyclonic
disturbances affecting Orissa, were analysed from 100 years (1901–2000) of data. The basic objective of the study was to find
out the contribution of inter-annual variability in the frequency of cyclonic disturbances to the inter-annual variability
of monsoon rainfall over Orissa.
The relationship between summer monsoon rainfall over Orissa and the frequency of cyclonic disturbances affecting Orissa shows
temporal variation. The correlation between them has significantly decreased since the 1950s. The variation in their relationship
is mainly due to the variation in the frequency of cyclonic disturbances affecting Orissa. The variability of both rainfall
and total cyclonic disturbances has been above normal since the 1960s, leading to more floods and droughts over Orissa during
recent years. The inter-annual variability of seasonal rainfall over Orissa and the frequency of cyclonic disturbances affecting
Orissa during monsoon season show a quasi-biennial oscillation period of 2–2.8 years. There is least impact of El Nino southern
oscillation (ENSO) on inter-annual variability of both the seasonal rainfall over Orissa and the frequencies of monsoon depressions/total
cyclonic disturbances affecting Orissa. 相似文献
17.
Abdelkader Elouissi Mohammed Habi Boumedienne Benaricha Sid Ahmed Boualem 《Arabian Journal of Geosciences》2017,10(22):496
This work describes the climate change impact study on rainfall patterns in Macta watershed, located in the northwest of Algeria. The monthly rainfall data collection, verification and validation have built a database with 42 stations, each with 42 years of observations from 1970 to 2011. The study of annual total rainfall has identified a downward trend and quantifies the deficits that are within the observation time series. The division of the annual rainfall series into four periods allowed to highlighting the increase in inter-year temporal variability with the coefficient of variation increases from 17 to 27%. The study shows an annual rainfall deficit increment from 13 to 25%. The standard deviation values decrease significantly for the last two periods showing a spatial variability. Multivariate statistical study by the hierarchical clustering method resulted in the formation of station groups indicating the unification of monthly rainfall patterns. 相似文献
18.
Sergio H. Franchito V. Brahmananda Rao Ana C. Vasques Clovis M. E. Santo Jorge C. Conforte 《Journal of Earth System Science》2009,118(3):193-207
A comparison between TRMM PR rainfall estimates and rain gauge data from ANEEL and combined gauge/satellite data from GPCP over South America (SA) is made. In general, the annual and seasonal regional characteristics of rainfall over SA are qualitatively well reproduced by TRMM PR and GPCP. It is found that over most of SA GPCP exceeds TRMM PR rainfall. The largest positive differences between GPCP and TRMM PR data occur in the north SA, northwestern and central Amazonia. However, there are regions where GPCP rainfall is lower than TRMM PR, particularly in the Pacific coastal regions and in southern Brazil. We suggest that the cause for the positive differences GPCP minus TRMM PR rainfall are related to the fact that satellite observations based on infrared radiation and outgoing longwave radiance sensors overestimate convective rainfall in GPCP and the cause for the negative differences are due to the random errors in TRMM PR. Rainfall differences in the latter phases of the 1997/98 El Niño and 1998/99 La Niña are analyzed. The results showed that the rainfall anomalies are generally higher in GPCP than in TRMM PR, however, as in the mean annual case, there are regions where the rainfall in GPCP is lower than in TRMM PR. The higher positive (negative) differences between the rainfall anomalies in GPCP and TRMM PR, which occur in the central Amazonia (southern Brazil), are reduced (increased) in the El Niño event. This is due to the fact that during the El Niño episode the rainfall decreases in the central Amazonia and increases in the southern Brazil. Consequently, the overestimation of the convective rainfall by GPCP is reduced and the overestimation of the rainfall by TRMM PR is increased in these two regions, respectively. 相似文献
19.
Y. V. Rama Rao Lyndon Alves Bhaleka Seulall Ziona Mitchell Kelvin Samaroo Garvin Cummings 《Natural Hazards》2012,61(3):1243-1261
In the present study, diagnostic studies were undertaken using station-based rainfall data sets of selected stations of Guyana to understand the variability of rainfall. The multidecadal variation in rainfall of coastal station Georgetown and inland station Timehri has shown that the rainfall variability was less during the May–July (20–30%) of primary wet season compared to the December--January (60–70%) of second wet season. The rainfall analysis of Georgetown based on data series from 1916 to 2007 shows that El Niño/La Niña has direct relation with monthly mean rainfall of Guyana. The impact is more predominant during the second wet season December--January. A high-resolution Weather Research and Forecasting model was made operational to generate real-time forecasts up to 84 h based on 00 UTC global forecast system (GFS), NCEP initial condition. The model real-time rainfall forecast during July 2010 evaluation has shown a reasonable skill of the forecast model in predicting the heavy rainfall events and major circulation features for day-to-day operational forecast guidance. In addition to the operational experimental forecast, as part of model validation, a few sensitivity experiments are also conducted with the combination of two cloud cumulus (Kain--Fritsch (KF) and Betts–Miller–Janjic (BMJ)) and three microphysical schemes (Ferrier et al. WSM-3 simple ice scheme and Lin et al.) for heavy rainfall event occurred during 28–30 May 2010 over coastal Guyana and tropical Hurricane ‘EARL’ formed during 25 August–04 September 2010 over east Caribbean Sea. It was observed that there are major differences in the simulations of heavy rainfall event among the cumulus schemes, in spite of using the same initial and boundary conditions and model configuration. Overall, it was observed that the combination of BMJ and WSM-3 has shown qualitatively close to the observed heavy rainfall event even though the predicted amounts are less. In the case of tropical Hurricane ‘EARL’, the forecast track in all the six experiments based on 00 UTC of 28 August 2010 initial conditions for the forecast up to 84 h has shown that the combination of KF cumulus and Ferrier microphysics scheme has shown less track errors compared to other combinations. The overall average position errors for all the six experiments taken together work out to 103 km in 24, 199 km in 48, 197 km in 72 and 174 km in 84 h. 相似文献