共查询到20条相似文献，搜索用时 15 毫秒
1.
A computational method for the determination of rainfall distribution for applications in short term rainfall prediction is presented here. The method is strongly influenced by the experience gained from the observation and analysis of data gathered on a heavy rainfall event in 1986 that occurred during the Baiu Season in Japan. The method is based on the concept that rainfall occurs as an interaction between an instability field, appropriately modeled, and a field of water vapor under the influence of topography. The results from this computational method showed good agreement with the temporal variation in the rainband that moved across the observation field in 1986. Towards determination of the parameters in the computational model, another method for the determination of the rainfield is also developed. This second method determines the rainfall distribution from estimation of the conversion rate of water vapor to liquid water through use of data from a three dimensional scanning radar. The results are consistent with those obtained from the first method. 相似文献
2.
利用昭通中心站YRY-4钻孔应变仪前兆观测数据资料,提取降雨对该仪器观测数据的干扰事件,采用降雨总量、瞬间最大值降雨量两类降雨分类统计方法,定量分析降雨对观测数据产生的影响。结果表明:当降雨总量达到40 mm、瞬间最大值降雨量大于0.4 mm时,YRY-4钻孔应变仪观测数据受降雨干扰明显;当降雨总量大于40 mm时,降雨总量与观测数据应变量呈线性关系,瞬间最大值降雨量与降雨总量之间无显著的对应关系。分析认为,降雨干扰影响主要来自降雨渗透和台站周边地质抗水体荷载量大小两个方面。定量分析降雨干扰,有利于区分异常与干扰,积累经验,以便于及时对有效异常进行判定,为地震研究服务。 相似文献
3.
Short‐term flood inundation prediction using hydrologic‐hydraulic models forced with downscaled rainfall from global NWP 
下载免费PDF全文
下载免费PDF全文 A short‐term flood inundation prediction model has been formulated based on the combination of the super‐tank model, forced with downscaled rainfall from a global numerical weather prediction model, and a one‐dimensional (1D) hydraulic model. Different statistical methods for downscaled rainfall have been explored, taking into account the availability of historical data. It has been found that the full implementation of a statistical downscaling model considering physically‐based corrections to the numerical weather prediction model output for rainfall prediction performs better compared with an altitudinal correction method. The integration of the super‐tank model into the 1D hydraulic model demonstrates a minimal requirement for the calibration of rainfall–runoff and flood propagation models. Updating the model with antecedent rainfall and regular forecast renewal has enhanced the model's capabilities as a result of the data assimilation processes of the runoff and numerical weather prediction models. The results show that the predicted water levels demonstrate acceptable agreement with those measured by stream gauges and comparable to those reproduced using the actual rainfall. Moreover, the predicted flood inundation depth and extent exhibit reasonably similar tendencies to those observed in the field. However, large uncertainties are observed in the prediction results in lower, flat portions of the river basin where the hydraulic conditions are not properly analysed by the 1D flood propagation model. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
4.
采用分层神经网络（LNN）分析地下水的氡浓度,试图给出氡浓度和环境参数之间的函数关系。由于环境（例如：降雨量）对水氡浓度的影响可能是非线性的,与目前时间脉冲响应线性计算方法相比,该方法能够较准确的估计环境参数造成的氡浓度变化。 相似文献
5.
首先根据2000年环北京实际的精细下垫面布局资料（500m分辨率）,按美国USGS陆面资料分类标准（25类）对其提供的全球30 s经纬分辨率（≈1 km）下垫面分类资料进行了更新设计.进而针对一个北京夏季暴雨过程,利用10:3.3km双向双重嵌套的MM5V3.6-Noah LSM陆气耦合模式进行24h数值对比试验,研究了北京精细下垫面信息引入对暴雨的影响.分析表明：新设计的陆面资料更真实地反映了环北京区域的下垫面结构,尤其针对北京城区面积迅增特征;同时还修正了原资料将亚洲中纬度区域落叶阔叶林下垫面类型归属为热带(或亚热带)稀疏大草原类型的问题.其在数值天气模式中的引入会对短期暴雨过程的发生发展产生重要影响.对此次暴雨主要降水中心的模拟,12h差值分布范围远达30km以上,中心值相对差异可达30%.研究发现在城市下垫面和大气相互间存在一个重要的相互影响机制,即由于城区面积的扩大会导致自然植被减少,进而会减少地表蒸发及相应局地大气水分供应、加深边界层高度并增强大气水汽混合,这不利于降水的发生发展. 相似文献
6.
Water vapor plays a crucial role in atmospheric processes that act over a wide range of temporal and spatial scales, from global climate to micrometeorology. The determination of water vapor distribution in the atmosphere and its changing pattern is very important. Although atmospheric scientists have developed a variety of means to measure precipitable water vapor(PWV) using remote sensing data that have been widely used, there are some limitations in using one kind satellite measurements for PWV retrieval over land. In this paper, a new algorithm is proposed for retrieving PWV over land by combining different kinds of remote sensing data and it would work well under the cloud weather conditions. The PWV retrieval algorithm based on near infrared data is more suitable to clear sky conditions with high precision. The 23.5 GHz microwave remote sensing data is sensitive to water vapor and powerful in cloud-covered areas because of its longer wavelengths that permit viewing into and through the atmosphere. Therefore, the PWV retrieval results from near infrared data and the indices combined by microwave bands remote sensing data which are sensitive to water vapor will be regressed to generate the equation for PWV retrieval under cloud covered areas. The algorithm developed in this paper has the potential to detect PWV under all weather conditions and makes an excellent complement to PWV retrieved by near infrared data. Different types of surface exert different depolarization effects on surface emissions, which would increase the complexity of the algorithm. In this paper, MODIS surface classification data was used to consider this influence. Compared with the GPS results, the root mean square error of our algorithm is 8 mm for cloud covered area. Regional consistency was found between the results from MODIS and our algorithm. Our algorithm can yield reasonable results on the surfaces covered by cloud where MODIS cannot be used to retrieve PWV. 相似文献
7.
在地震地下流体研究中,地下水补给及循环过程是重要的研究内容之一,氢氧同位素示踪技术是目前研究该过程的常用手段。南昌地震台流体观测井自2013年8月22日投入观测以来,其基础数据未进行有效分析,通过对南昌井水样数据进行氢氧同位素及水化学实验分析,结果表明：井水主要补给源为直接大气降雨,补给前经历了一定蒸发作用;水—岩反应不充分,属于未成熟水;水样中无明显优势阳离子,Ca2+、Na+占主体,优势阴离子为HCO3－,表明井水属重碳酸型水;水源补给高程约582 m。南昌地震台流体观测井总体受大气降水影响较大。 相似文献
8.
GPS数据用于改正InSAR中大气延迟误差的方法受GPS站点密度的限制,只利用有限的几个站点所观测到的大气数据来生成干涉图的大气改正图,往往达不到很好的效果.本文研究利用GPS与MODIS数据的联合使用来生成大气改正图,首先用GPS数据对MODIS水汽产品进行分块校准,并且对MODIS水汽数据进行了空间结构函数分析,得到研究区域内水汽场的空间分布规律.然后把这种区域水汽场的空间分布信息结合到Kriging内插法中生成更为合理的水汽图.通过上海地区ENVISAT ASAR数据的实验发现,这种加以改正的GPS和MODIS数据联合改正法不仅可以对长波大气信号有明显的消弱,还能消弱一些短波的大气信号,特别是一些幅度较强的短波信号;经过GPS+MODIS算法改正后,短波信号占优和长波信号占优的两幅差分大气延迟图的整体RMS分别降低了32.74%和38.82%,去除幅度较大.与GPS+ATM(大气传输模型)算法比较,我们发现,在上海地区有限的数据条件下（即研究区域内只有6个GPS点）,GPS+MODIS法在大气去除效果或者说大气信号重现能力方面优于GPS+ATM算法.GPS+MODIS算法在捕获短波大气信号方面要比GPS+ATM更有优势,因此也可以改正短波大气误差. 相似文献
9.
《中国科学:地球科学(英文版)》2015,(10)
A statistical downscaling model is built for the late-winter rainfall over Southwest China(SWC).A partial-correlation method is used for selecting factors.The results show that the selected factors for late-winter rainfall in SWC are sea level pressure in Western Europe(SNAO)and sea surface temperature in Western Pacific(WPT).SNAO is related to the southern pole of North Atlantic Oscillation(NAO)and excites Southern Eurasian teleconnection,which influences the development of the southern branch trough and the water vapor transport to SWC.WPT indicates the variability of ENSO in the tropical Western Pacific.WPT excites Pacific-East Asia teleconnection and an anticyclone(cyclone)is formed in the southern part of China and suppresses(enhances)rainfall over SWC.A regression statistical downscaling model using SNAO and WPT shows good performance in fitting the variability of late-winter rainfall in the whole SWC region and every observation station,and the model also shows strong robustness in the independent validation.The statistical model can be used for downscaling output from seasonal forecast numerical models and improve the SWC late winter rainfall prediction in the future. 相似文献
10.
利用1962～2006年NCEP/NCAR再分析资料,采用对历史个例进行合成分析的方法,研究了异常降水中心分别位于长江以南区域的江南型和长江-淮河流域的江淮型低频雨型的季节内水汽输送特征.研究表明,江南型的总水汽输送主要来源于孟加拉湾,并经中南半岛和南海输入江南区域;江淮型的总水汽输送主要直接来源于南海,但水汽源地主要为印度季风区.对于水汽输送异常,江南型和江淮型具有明显不同的特征.江南型的水汽输送异常主要来源于热带西太平洋-南海,中纬度西风带和中高纬度南下的水汽输送异常的贡献次之;而江淮型的水汽输送异常主要来源于热带和副热带西太平洋,中纬度西风带水汽输送异常的贡献次之.另外,水汽输送异常对江南型的区域总水汽收支的贡献约为50%,而对江淮型的区域总水汽收支的贡献高达70%左右.因此,虽然总水汽输送主要取决于气候平均水汽输送,但是,水汽输送异常与气候平均水汽输送对江南型和江淮型的水汽供应具有相同甚至更为重要的贡献.特别是对于江淮型,区域总水汽收支主要取决于水汽输送异常的贡献,而水汽输送异常的变化较平均水汽输送更为复杂,这有可能是江淮流域汛期降水预报较为困难的原因之一. 相似文献
11.
Michael J. Crozier 《地球表面变化过程与地形》1999,24(9):825-833
A rainfall-based landslide-triggering model, developed from previous landslide episodes in Wellington City, New Zealand, is tested for its ability to provide a 24-hour forecast of landslide occurrence. The model, referred to as the Antecedent Water Status Model, calculates an index of soil water, by running a daily water balance and applying a soil drainage factor to excess precipitation, over the preceding ten days. Together with the daily rainfall input, the soil water status has been used empirically to identify a threshold condition for landslide triggering. The prediction process provides a daily update of the soil water status and thereby the amount of rainfall required on the following day to equal or exceed the triggering threshold. The probability that this triggering rainfall will occur is then determined from the frequency/magnitude distribution of the local rainfall record. The model produces a satisfactory level of prediction, particularly for periods of concentrated landslide activity. Copyright © 1999 John Wiley & Sons, Ltd. 相似文献
12.
13.
D. -J. Seo J. A. Smith 《Stochastic Environmental Research and Risk Assessment (SERRA)》1991,5(1):17-29
Procedures for estimating rainfall from radar and raingage observations are constructed in a Bayesian framework. Given that the number of raingage measurements is typically very small, mean and variance of gage rainfall are treated as uncertain parameters. Under the assumption that log gage rainfall and log radar rainfall are jointly multivariate normal, the estimation problem is equivalent to lognormal co-kriging with uncertain mean and variance of the gage rainfall field.The posterior distribution is obtained under the assumption that the prior for the mean and inverse of the variance of log gage rainfall is normal-gamma 2. Estimate and estimation variance do not have closed-form expressions, but can be easily evaluated by numerically integrating two single integrals. To reduce computational burden associated with evaluating sufficient statistics for the likelihood function, an approximate form of parameter updating is given. Also, as a further approximation, the parameters are updated using raingage measurements only, yielding closed-form expressions for estimate and estimation variance in the Gaussian domain.With a reduction in the number of radar rainfall data in constructing covariance matrices, computational requirements for the estimation procedures are not significantly greater than those for simple co-kriging. Given their generality, the estimation procedures constructed in this work are considered to be applicable in various estimation problems involving an undersampled main variable and a densely sampled auxiliary variable. 相似文献
14.
A mathematical optimal control method is developed to identify a hydraulic conductivity distribution in a density dependent flow field. Using a variational method, the adjoint partial differential equations are obtained for the density- dependent state equations used for the saline aquifer water flow. The adjoint equations are numerically solved in through a finite difference method. The developed method is applied to identify the hydraulic conductivity distribution through the numerical solution of an optimal control problem. To demonstrate the effectiveness of the optimal control method, three numerical experiments are conducted with artificial observation data. The results indicate that the developed method has the potential to accurately identify the hydraulic conductivity distribution in a saline water aquifer flow system. 相似文献
15.
应用地基GPS沿倾斜路径方向遥测大气水汽总量,是获得测站周围水汽三维空间分布信息(水汽层析)的基础.本文介绍了地基GPS沿倾斜路径方向遥感大气水汽总量的原理和方法;首先用湿梯度、后处理残差联合计算接收机上空不同方位上大气水汽各向异性成分,在此基础上重构倾斜路径水汽总量.为验证GPS观测结果精度,用微波辐射计（WVR）与GPS一起进行了联合观测,不同观测地点和时间的对比结果表明,二者root mean square (RMS)误差小于4mm,证明应用此种方法地基GPS可较精确地反演出倾斜路径方向大气水汽总量,而且这种反演方法适合于近实时大气遥感探测.地基GPS测量具有全天候可连续观测等优点,可以弥补常规观测的不足,为气候研究提供高精度且连续的水汽数据资料;组网观测可以为数值天气预报提供好的初始场,提高模式预报精度. 相似文献
16.
The overall objective of this study is to improve the forecasting accuracy of the precipitation in the Singapore region by means of both rainfall forecasting and nowcasting. Numerical Weather Predication (NWP) and radar‐based rainfall nowcasting are two important sources for quantitative precipitation forecast. In this paper, an attempt to combine rainfall prediction from a high‐resolution mesoscale weather model and a radar‐based rainfall model was performed. Two rainfall forecasting methods were selected and examined: (i) the weather research and forecasting model (WRF); and (ii) a translation model (TM). The WRF model, at a high spatial resolution, was run over the domain of interest using the Global Forecast System data as initializing fields. Some heavy rainfall events were selected from data record and used to test the forecast capability of WRF and TM. Results obtained from TM and WRF were then combined together to form an ensemble rainfall forecasting model, by assigning weights of 0.7 and 0.3 weights to TM and WRF, respectively. This paper presented results from WRF and TM, and the resulting ensemble rainfall forecasting; comparisons with station data were conducted as well. It was shown that results from WRF are very useful as advisory of anticipated heavy rainfall events, whereas those from TM, which used information of rain cells already appearing on the radar screen, were more accurate for rainfall nowcasting as expected. The ensemble rainfall forecasting compares reasonably well with the station observation data. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
17.
Forecasting monthly precipitation using sequential modelling 总被引：1，自引：1，他引：0
In the hydrological cycle, rainfall is a major component and plays a vital role in planning and managing water resources. In this study, new generation deep learning models, recurrent neural network (RNN) and long short-term memory (LSTM), were applied for forecasting monthly rainfall, using long sequential raw data for time series analysis. “All-India” monthly average precipitation data for the period 1871–2016 were taken to build the models and they were tested on different homogeneous regions of India to check their robustness. From the results, it is evident that both the trained models (RNN and LSTM) performed well for different homogeneous regions of India based on the raw data. The study shows that a deep learning network can be applied successfully for time series analysis in the field of hydrology and allied fields to mitigate the risks of climatic extremes. 相似文献
18.
Bellie Sivakumar Ashish Sharma 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(4):451-459
High-resolution temporal rainfall data sequences serve as inputs for a range of applications in planning, design and management
of small (especially urban) water resources systems, including continuous flow simulation and evaluation of alternate policies
for environmental impact assessment. However, such data are often not available, since their measurements are costly and time-consuming.
One alternative to obtain high-resolution data is to try to derive them from available low-resolution information through
a disaggregation procedure. This study evaluates a random cascade approach for generation of high-resolution rainfall data
at a point location. The approach is based on the concept of scaling in rainfall, or, relating the properties associated with
the rainfall process at one temporal scale to a finer-resolution scale. The procedure involves two steps: (1) identification
of the presence of scaling behavior in the rainfall process; and (2) generation of synthetic data possessing same/similar
scaling properties of the observed rainfall data. The scaling identification is made using a statistical moment scaling function,
and the log–Poisson distribution is assumed to generate the synthetic rainfall data. The effectiveness of the approach is
tested on the rainfall data observed at the Sydney Observatory Hill, Sydney, Australia. Rainfall data corresponding to four
different successively doubled resolutions (daily, 12, 6, and 3 h) are studied, and disaggregation of data is attempted only
between these successively doubled resolutions. The results indicate the presence of multi-scaling behavior in the rainfall
data. The synthetic data generated using the log–Poisson distribution are found to exhibit scaling behaviors that match very
well with that for the observed data. However, the results also indicate that fitting the scaling function alone does not
necessarily mean reproducing the broader attributes that characterize the data. This observation clearly points out the extreme
caution needed in the application of the existing methods for identification of scaling in rainfall, especially since such
methods are also prevalent in studies of the emerging satellite observations and thus in the broader spectrum of hydrologic
modeling. 相似文献
19.
《中国科学D辑(英文版)》2006,(Z2)
Using data from eddy covariance measurements in a subtropical coniferous forest, a test and evaluation have been made for the model of Carbon Exchange in the Vegetation-Soil-Atmosphere (CEVSA) that simulates energy transfers and water, carbon and nitrogen cycles based on ecophysiological processes. In the present study, improvement was made in the model in calculating LAI, carbon allocation among plant organs, litter fall, decomposition and evapotranspiration. The simulated seasonal variations in carbon and water vapor flux were consistent with the measurements. The model explained 90% and 86% of the measured variations in evapotranspiration and soil water content. However, the modeled evapotranspiration and soil water content were lower than the measured systematically, because the model assumed that water was lost as runoff if it was beyond the soil saturation water content, but the soil at the flux site with abundant rainfall is often above water saturated. The improved model reproduced 79% and 88% of the measured variations in gross primary production (GPP) and ecosystem respiration (Re), but only 31% of the variations in measured net ecosystem exchange (NEP) despite the fact that the modeled annual NEP was close to the observation. The modeled NEP was generally lower in winter and higher in summer than the observations. The simulated responses of photosynthesis and respiration to water vapor deficit at high temperatures were different from measurements. The results suggested that the improved model underestimated ecosystem photosynthesis and respiration in extremely condition. The present study shows that CEVSA can simulate the seasonal pattern and magnitude of CO2 and water vapor fluxes, but further improvement in simulating photosynthesis and respiration at extreme temperatures and water deficit is required. 相似文献
20.
影响因素及埋藏类型是地下水观测数据前兆分析的重要资料.通过海原甘盐池拉分盆地内两口地震水位观测井(GYC 和 GYCN 井)的气压、降雨与水位资料,综合分析水位变化的影响因素,并分别利用阶跃响应函数、频谱分析法、潮汐波群相位超前或滞后法分析地下水埋藏类型.结果表明:(1)气压和降雨是影响海原甘盐池两口地震观测井水位动态变化的主要因素.(2)GYC井地下水埋藏类型为混合水,与该井成井时的判定资料不一致(承压水),可能与其时间较长、长年失修、存在破损现象有关,或受地表水影响较大 ;GYCN 井地下水埋藏类型为承压水.该研究结果为该地区地震水位观测井的准入(退出)机制、今后观测井点的勘选等提供科学依据,对今后异常识别和震情跟踪具有重要意义. 相似文献