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1.
德令哈降水中δ18O年际变化与水汽输送 总被引：1，自引：0，他引：1
根据德令哈地区1992—2001年的降水中δ18O数据及降水时刻所记录的相关气象参数,并对比中国气象局气象资料和NCEP/NCAR格点气象数据,利用相关、回归等分析方法分别对该地区降水中δ18O与温度、降水量以及水汽通量之间的关系进行分析,并讨论了降水量与大气环流的变化关系,揭示了影响该地区降水中δ18O变化的气象因素,特别是与水汽来源之间的关系。研究结果表明,德令哈降水中δ18O年际变化表现出一定程度的“温度效应”,但与温度的相关性要低于季节尺度。不同类型汽团的水汽输送是影响降水中δ18O年际变化的另一个重要原因。 相似文献
2.
模糊均生函数残差模型在地下水数值模拟降水量预报中的应用 总被引：4，自引：2，他引：2
地下水主要补给来源为大气降水的入渗和地表水体的渗漏.在地下水模拟预报模型中需要预先知道降水量.迄今为止,年降水量的预测仍然是一个不易解决的难题.在模糊均生函数模型(FAFM)基础上,利用其残差数据序列对FAFM进行校正,提出了模糊均生函数残差模型(REMFAF),给出了模型预报精度的检验方法.实例研究表明,REMFAF模型应用于吉林省西部地区地下水数值模拟中的降水量预报,比FAFM的预报精度更高,取得了较为理想的结果. 相似文献
3.
本文根据郴州市气象站三十四年的大气降水量资料和该市供水水文地质勘察工作取得的大量数据,用相关分析和有限差分法对海泉地下水资源及水位动态进行了预测和预报。论述了合理开发利用海泉地下水资源的前景。 相似文献
4.
影响大气降水入渗补给量的因素较为复杂,主要有土地利用类型、降水量、包气带厚度及岩性等。随着遥感影像解译技术的发展,人们能更精确地识别空间土地利用类型,从而更精确地计算大气降水入渗补给量,并了解其空间分布。综合考虑这些影响因素,本文提出了一种基于土地利用类型,并结合地理信息系统(GIS)和VBA(visual basic for applications)编程技术的大气降水入渗补给量计算方法(PIRCL)。以广州市广花盆地为例,利用PIRCL法计算得到该地多年平均大气降水入渗补给量为14 369万m3,该结果与水量平衡法计算得到的大气降水入渗补给量结果相近,相对误差约为2.4%;并且,计算得到的大气降水入渗补给量空间分布基本合理。与水量平衡法相比,PIRCL法计算大气降水入渗补给量只需区域遥感数据、区域降水量数据、对应时段地下水位动态变化及区域水文地质参数,不需要计算地下水其他的补给、排泄项,可以省略大量的工作量,且方便编程实现。 相似文献
5.
基于TIGGE数据的五个单中心集合预报结果(CMA、CMC、ECMWF、NCEP、UKMO)构成的多中心超级集合预报系统的降水量预报,以及相应时段的实测降水量值,应用贝叶斯模式平均法(Bayesian Model Averaging,BMA)建立大渡河流域的BMA概率预报模型。通过CRPS、MAE、BS三种评价指标,对大渡河流域的BMA降水概率预报模型进行评价与检验,三种指标均显示BMA降水概率预报比原始集合预报具有更高的准确性,其中BMA模型的CRPS和MAE指标均值分别相比原始集合预报减少了31.6%和23.9%;分析模型权重参数,得出ECMWF对大渡河流域BMA降水预报贡献最大,即ECMWF对研究区域降水预报效果最好;模型对大渡河流域极端降水预报效果较差,常低估极端降水量。 相似文献
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TRMM遥感降水数据在伊洛瓦底江流域的精度检验和校正方法研究 总被引：1，自引：0，他引：1
在伊洛瓦底江流域利用13个雨量站数据对TRMM日降水数据进行了精度检验,提出了一种基于水量平衡的TRMM数据校正方法。该方法首先以SWAT模型为基础,以不同子流域内的水量平衡为目标,计算各个子流域的TRMM数据校正系数;其次以子流域内的坡度值为自变量,校正系数为因变量,对二者进行回归分析,在没有水文控制站的子流域根据坡度求得对应的校正系数,对各个子流域的降水数据分别进行校正。结果显示,校正前TRMM年降水量和月降水量与实测值有较高相关性,但偏差较大;校正后年降水量与实测值基本一致;月降水量与实测曲线吻合较好;日降水量的预报等级从中等提高到了良好,校正前2个站预报等级差,7个良好,4个中等,校正后6个良好,2个中等,5个优秀。结果表明此方法在伊江流域能在不同时间尺度上显著提高TRMM数据的精度,为流域水文水资源分析提供数据支持。 相似文献
7.
陕西省现代大气降水氢氧同位素组成特征研究 总被引：9，自引：1，他引：9
陕西地处我国东部湿润气候与西部干冷气候的过渡地区,气候偏冷,偏旱,降水偏少,蒸发量远大于降水量。全境呈南北狭长状,分属三个不同气候带。本文根据自然地理分区(陕北、关中、陕南)的大气降水氢氧同位素组成的逐月变化,求得陕西地区大气降水的雨水线公式:δD=8.36δ~(?)O 14.5。又根据气象要素——温度(t)、降水量(L)、蒸发量(1)对降水的氢氧同位素组成的影响,通过回归分析得出,影响δ值变化的主要因素是降水量,且为负相关,其次是温度和蒸发量。大气降水δ值与综合气象要素的回归方程式为:δD=-46.382 2.0438t-0.3084L-0.05451,δ~(18)O=-7.8436 0.2677t-0.0335L-0.00611。进而根据全省大气降水和由降水补给的地下水氢氧同位素组成之间的关系,通过相关计算,求得地下水δ值与大气降水δ值的相关关系式:δD_(地下水)=0.3062δD_(降水)-51.00,δ~(?)O_(地下水)=0.1411δ~(18)O_(降水)-8.14。 相似文献
8.
以吉林省九台市气象站1977-2009年的逐月降水量资料为基础,利用滑动平均法、线性倾向估计法和M-K秩次相关法,分析了九台市近33年降水量变化趋势和突变特点。通过均值-标准差建立降水序列的分级标准,采用规范化的各自相关系数确定权重,利用滑动平均马尔可夫链模型,通过转移概率矩阵预测降水量。研究表明,九台市降水年内分配不均,主要集中夏季;降水量有减小的趋势;年降水量存在突变;滑动平均马尔可夫链模型预测精度较高,为降水量预报提供了一种方法。 相似文献
9.
中国地质灾害气象预警初步研究 总被引：50，自引：3，他引：50
根据致灾地质环境条件和气候因素，将中国划分为7个大区、28个预警区。根据对历史时期所发生的地质灾害点和灾害发生之前15日内实际降水量及降水过程的统计分析，创建了地质灾害气象预警等级判据模式图，初步制作了各预警区的预报预警判据图；根据检索到的研究资料建立了部分预警区的判据校正图。据此，在每天收到中国国家气象中心发来的全国降雨预报数据和图像半小时内，对所预报的次日降雨过程是否诱发地质灾害和诱发灾害的空间范围、危害强度进行预报预警。2003年的试验运行表明，地质灾害气象预警在技术上是可行的，能够为主动减灾做出贡献。 相似文献
10.
可降水量是估算可能最大降水(PMP)的一个重要中间量。为验证不同方法推求可降水量的准确性,利用1998~2010年东南沿海五省(自治区)及香港地区共13个探空站和地面露点资料,分别采用3种不同方法(探空法、经验公式法和假绝热法)计算各站的大气可降水量,并对三种估算方法的结果进行比较。结果表明:经验公式法求得可降水量最小,探空法次之,假绝热法求得结果最大,偏差随着纬度变化。纬度越低,假绝热法推求的可降水量相对误差越大,且在有降水日时的偏差更为明显;经验公式法和假绝热法得到的结果均与探空法的可降水量相关性较强;三种求算方法得到的大气可降水量年内变化基本一致。建议在PMP估算中,利用地面最大12 h持续露点温度通过假绝热法推求可降水量时,应考虑纬度校正。 相似文献
11.
Flood forecasts based on multi-model ensemble precipitation forecasting using a coupled atmospheric-hydrological modeling system 总被引：1，自引：0，他引：1
The recent improvement of numerical weather prediction (NWP) models has a strong potential for extending the lead time of precipitation and subsequent flooding. However, uncertainties inherent in precipitation outputs from NWP models are propagated into hydrological forecasts and can also be magnified by the scaling process, contributing considerable uncertainties to flood forecasts. In order to address uncertainties in flood forecasting based on single-model precipitation forecasting, a coupled atmospheric-hydrological modeling system based on multi-model ensemble precipitation forecasting is implemented in a configuration for two episodes of intense precipitation affecting the Wangjiaba sub-region in Huaihe River Basin, China. The present study aimed at comparing high-resolution limited-area meteorological model Canadian regional mesoscale compressible community model (MC2) with the multiple linear regression integrated forecast (MLRF), covering short and medium range. The former is a single-model approach; while the latter one is based on NWP models [(MC2, global environmental multiscale model (GEM), T213L31 global spectral model (T213)] integrating by a multiple linear regression method. Both MC2 and MLRF are coupled with Chinese National Flood Forecasting System (NFFS), MC2-NFFS and MLRF-NFFS, to simulate the discharge of the Wangjiaba sub-basin. The evaluation of the flood forecasts is performed both from a meteorological perspective and in terms of discharge prediction. The encouraging results obtained in this study demonstrate that the coupled system based on multi-model ensemble precipitation forecasting has a promising potential of increasing discharge accuracy and modeling stability in terms of precipitation amount and timing, along with reducing uncertainties in flood forecasts and models. Moreover, the precipitation distribution of MC2 is more problematic in finer temporal and spatial scales, even for the high resolution simulation, which requests further research on storm-scale data assimilation, sub-grid-scale parameterization of clouds and other small-scale atmospheric dynamics. 相似文献
12.
在划分气象风险等级时,传统地质灾害气象风险预警方法忽略了承灾体脆弱性因素,且气象风险预报等级整体偏高,导致高等级风险区空报率较高。基于此,提出基于机器学习的滑坡、崩塌灾害气象风险预警方法。利用信息量法,分析气象因素影响程度。选取坐标点、降雨量、易发生等级,将其作为机器学习人工神经网络的输入节点,判断是否发生崩塌、滑坡灾害;针对地质灾害区域,根据影响程度计算气象引发因子指数,结合滑坡、崩塌灾害潜势度G和承灾体脆弱性M,确定气象风险预警指数R,划分预警级别,完成滑坡、崩塌灾害气象风险预警。实验结果表明,设计方法有效降低了三级预报和四级预警空报率,提升了预警精细化程度。 相似文献
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14.
卫星气象产品、气候模式预测数据通常与地面观测数据存在偏差,为保证数据的可靠性和合理性,需要对其进行偏差校正,但偏差校正过程往往受具体区域气象特征、方法本身假定等因素的影响,导致修正效果不佳。为此,本文提出一种广义联合偏差修正方法,相较于现有研究最常用的单变量QM修正方法以及固定多变量修正顺序的JBC修正方法,该方法充分考虑到流域尺度降水和气温双变量的时空相关性,并结合其对径流的主导作用对变量修正顺序进行动态调整,实现了QM法和JBC法的优势互补。在澜沧江-湄公河流域的应用表明：考虑降水、气温相关性可显著改善降水和温度极值的修正效果,尤其是5、6月份,修正后气象与实测数据的纳什系数提升了0.5以上;考虑气象要素的修正次序显著降低了修正后的降水和温度频率分布及均值偏差;利用修正后的气象数据驱动分布式水文模型时,部分月份的径流模拟精度提升了54.3%。 相似文献
15.
In consideration of large uncertainties in severe convective weather forecast, ensemble forecasting is a dynamic method developed to quantitatively estimate forecast uncertainty. Based on ensemble output, joint probability is a post-processing method to delineate key areas where weather event may actually occur by taking account of the uncertainty of several important physical parameters. An investigation of the environments of little rainfall convection and strong rainfall convection from April to September (warm season) during 2009-2015 was presented using daily disastrous weather data, precipitation data of 80 stations in Anhui province and NCEP Final Analysis (FNL) data. Through ingredients-based forecasting methodology and statistical analysis,four convective parameters characterizing two types of convection were obtained, respectively, which were used to establish joint probability forecasting together with their corresponding thresholds. Using the ECMWF ensemble forecast and observations from April to September during 2016-2017, systematic verification mainly based on ROC and case study of different weather processes were conducted. The results demonstrate that joint probability method is capable of discriminating little rainfall convection and non-convection with comparable performance for different lead times, which is more favorable to identifying the occurrence of strong rainfall convection. The joint probability of little rainfall convection is a good indication for the occurrence of regional or local convection, but may produce some false alarms. The joint probability of strong rainfall convection is good at indicating regional concentrated short-term heavy precipitation as well as local heavy rainfall. There are also individual missing reports in this method, and in practice, 10% can be roughly used as joint probability threshold to achieve relative high TS score. Overall, ensemble-based joint probability method can provide practical short-term probabilistic guidance for severe convective weather. 相似文献
16.
Musa Ataṣ Ahmet Emre Tekeli Senayi Dönmez Hesham Fouli 《Arabian Journal of Geosciences》2016,9(2):150
Basins located in Eastern Turkey are largely fed by snowmelt runoff during spring and early summer seasons. This study investigates the efficiency of artificial neural networks (ANNs) in snowmelt runoff generation. Although ANNs have been used for streamflow simulating/forecasting in the last two decades, using satellite-based snow-covered area (SCA) maps and meteorological observations as inputs to ANN provides a novel basis for estimating streamflow. The proposed methodology is implemented over Upper Euphrates River Basin in Eastern Turkey. SCA data was acquired from Interactive Multisensor Snow and Ice Mapping System (IMS) for an 8-year period from February 2004 to September 2011. Meteorological observations including daily cumulative precipitation and daily average air temperatures were obtained from Turkish State Meteorological Services. The simulation results are promising with coefficient of correlation varying from 0.67 to 0.98 among proposed models. Past days discharge was found to substantially improve the forecast accuracy. The paper presents the expected basin discharge for 2011 water year based on meteorological observations and SCA input. 相似文献
17.
Precipitation forecasting using classification and regression trees (CART) model: a comparative study of different approaches 总被引：2，自引：0，他引：2
Bahram Choubin Gholamreza Zehtabian Ali Azareh Elham Rafiei-Sardooi Farzaneh Sajedi-Hosseini Özgür Kişi 《Environmental Earth Sciences》2018,77(8):314
Interest in semiarid climate forecasting has prominently grown due to risks associated with above average levels of precipitation amount. Longer-lead forecasts in semiarid watersheds are difficult to make due to short-term extremes and data scarcity. The current research is a new application of classification and regression trees (CART) model, which is rule-based algorithm, for prediction of the precipitation over a highly complex semiarid climate system using climate signals. We also aimed to compare the accuracy of the CART model with two most commonly applied models including time series modeling (ARIMA), and adaptive neuro-fuzzy inference system (ANFIS) for prediction of the precipitation. Various combinations of large-scale climate signals were considered as inputs. The results indicated that the CART model had a better results (with Nash–Sutcliffe efficiency, NSE?>?0.75) compared to the ANFIS and ARIMA in forecasting precipitation. Also, the results demonstrated that the ANFIS method can predict the precipitation values more accurately than the time series model based on various performance criteria. Further, fall forecasts ranked “very good” for the CART method, while the ANFIS and the time series model approximately indicated “satisfactory” and “unsatisfactory” performances for all stations, respectively. The forecasts from the CART approach can be helpful and critical for decision makers when precipitation forecast heralds a prolonged drought or flash flood. 相似文献
18.
为估算松花江干流哈尔滨至同江段相距660 km的河冰厚度分布,用松花江干流短期实测水文和气象资料,在静态水域斯蒂芬冰厚计算公式基础上,引入水流流速的动能效应。假设河流内水流量相等,建立流速同河流宽度的简单关系,估算了一些调查断面的冰下平均流速;用地表温度资料,对干流域内缺少气象资料的调查断面,在证明结冰期间属于同一天气系统的前提下,用距离平方反比法进行空间插值。最后获得松花江干流河冰厚度统计关系式。用计算的哈尔滨至同江河冰厚度与有限的实测数据比较,发现该方法能够体现人为调节流速对冰生长速率的影响,对计算长距离河冰厚度具有一定精度。 相似文献
19.
为解决全球气候模式模拟降雨与实测降雨存在较大偏差的问题,提出了一种基于分段三伽玛分布的偏差纠正方法。该方法将降雨序列按其分位点分为极小值、常规值和极大值3部分,分别对3部分降雨序列的累积概率分布曲线进行偏差纠正;基于分位数偏差累积思想提出了一种综合性评价指标C,对分段三伽玛方法的偏差纠正效果进行综合评估。应用该方法对CMIP5下18个GCMs在雅鲁藏布江附近17个气象站点的模拟降雨进行偏差纠正,并与单伽玛方法和双伽玛方法进行对比分析。结果表明:分段三伽玛方法可以很好地消除GCMs模拟降雨与实测降雨的偏差,率定期和验证期的偏差纠正效果大多在0.85以上;相比单伽玛和双伽玛方法,分段三伽玛方法在验证期的偏差纠正效果更好,表现更稳健。 相似文献
20.
With the principal aim of identifying and comparing suitable evaluation and forecasting models of perennial yield, detailed hydrogeological research was conducted on the cold phreatic aquifer located in the volcanites of Mount Amiata, southern Tuscany's most important water reservoir. The study was based on spring discharge, precipitation, and temperature data. It permitted the identification of the following models: (1) ratios between discharge values measured at the springs, (2) depletion urve analysis of the springs, (3) multiple regression with climatic data, and (4) water balance, coefficients of potential infiltration and runoff coefficients derived on a physiographic basis. Analysis of the results obtained using these models shows their excellent ability to forecast in the medium and long term; for short-term (yearly) forecasts, highly satisfactory results have been obtained for most of the methods used. With regard to Mt. Amiata's average perennial yield, it is estimated at 55×106 m3/yr (the maximum deviation among the various evaluations performed varies from 4 to 8 percent), and it presents a decreasing trend, which is proportional to the reduction of local precipitation. 相似文献