共查询到20条相似文献，搜索用时 15 毫秒
1.
A nonlinear ensemble prediction model for typhoon rainstorm has been developed based on particle swarm optimization-neural network (PSO-NN). In this model, PSO algorithm is employed for optimizing the network structure and initial weight of the NN with creating multiple ensemble members. The model input of the ensemble member is the high correlated grid point factors selected from the rainfall forecast field of Japan Meteorological Agency numerical prediction products using the stepwise regression method, and the model output is the future 24 h rainfall forecast of the 89 stations. Results show that the objective prediction model is more accurate than the numerical prediction model which is directly interpolated into the stations, so it can better been implemented for the interpretation and application of numerical prediction products, indicating a potentially better operational weather prediction. 相似文献
2.
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
3.
Geochemical exploration in secondary environments can be viewed as a particular manifestation of indirect geological observation. Geochemical anomalies in complex sample media reflect dispersion signatures, generally much disguised by secondary or higher-order mechanical and physico-chemical processes such as mixing, comminution, dilution, (re)transportation, weathering etc. Such complexities often make a thorough understanding of the origin of any particular sample type difficult ot obtain. The objective of data analysis in this context is to convert the geochemical data into a meaningful “signal”, particularly useful for prospecting, and other, in this case irrelevant, variability or “noise”. The experience of the last decades of practical exploration has clearly shown that statistical as well as geographical geochemical anomaly patterns are multi-element signatures. Using suitable multivariate statistical procedures (in the present case principal components modelling), it is possible to simultaneously define both a background data model and to quantify multivariate geochemical anomalies. This type of data analysis is guided very strongly by geological interaction, in which the emphasis is on modelling the background population(s), coupled with geographic plotting facilities. This outlier-screening facility is critical for many types of geochemical data evaluation. An example of this approach is described below. Another application of indirect multivariate data analysis is represented by PLS (Partial Least Squares) regression, which is a supervised pattern recognition and regression technique. We use it here to predict modal scheelite occurrences from regional stream-sediment data. 相似文献
4.
Ensemble Kalman filtering with shrinkage regression techniques 总被引：1，自引：0，他引：1
The classical ensemble Kalman filter (EnKF) is known to underestimate the prediction uncertainty. This can potentially lead
to low forecast precision and an ensemble collapsing into a single realisation. In this paper, we present alternative EnKF
updating schemes based on shrinkage methods known from multivariate linear regression. These methods reduce the effects caused
by collinear ensemble members and have the same computational properties as the fastest EnKF algorithms previously suggested.
In addition, the importance of model selection and validation for prediction purposes is investigated, and a model selection
scheme based on cross-validation is introduced. The classical EnKF scheme is compared with the suggested procedures on two-toy
examples and one synthetic reservoir case study. Significant improvements are seen, both in terms of forecast precision and
prediction uncertainty estimates. 相似文献
5.
文章利用CESM1.1(公共地球系统模式)模式过去千年集合试验结果,对模拟的过去千年中国东部持续性严重干旱事件的时空特征及发生机制进行了初步分析。模式模拟出过去千年中国东部发生了7次持续性严重干旱事件,分别为883~910年、951~977年、1253~1305年、1327~1346年、1471~1488年、1587~1610年和1688~1699年干旱事件,其中仅1471~1488年干旱事件与中国东部旱涝指数对应较好,表明模式对中国东部干旱事件的模拟能力较低。这7次干旱事件均与模拟的ENSO(厄尔尼诺-南方涛动)负位相状态相对应,揭示ENSO可能对中国东部干旱事件的发生起了非常重要的作用。模拟分析结果显示,1253~1305年干旱事件前期可能主要受火山活动驱动,后期则可能受到太阳活动和自然内部变率的影响。另外,1587~1610年干旱事件后期可能也受到火山活动的影响;883~910年和951~977年干旱事件则完全受自然内部变率的影响。对1327~1346年、1471~1488年和1688~1699年这3次干旱事件,无法分辨外强迫和内部变率ENSO的各自贡献。 相似文献
6.
为了考虑预见期内降水预报的不确定性对洪水预报的影响,采用中国气象局、美国环境预测中心和欧洲中期天气预报中心的TIGGE(THORPEX Interactive Grand Global Ensemble)降水预报数据驱动GR4J水文模型,开展三峡入库洪水集合概率预报,分析比较BMA、Copula-BMA、EMOS、M-BMA 4种统计后处理方法的有效性。结果表明:4种统计后处理方法均能提供一个合理可靠的预报置信区间;其期望值预报精度相较于确定性预报有所提高,尤其是水量误差显著减小;M-BMA方法概率预报效果最佳,它能够考虑预报分布的异方差性,不需要进行正态变换,结构简单,应用灵活。 相似文献
7.
随着煤层气勘探的不断深入,对煤层含气量预测精度提出了更高的要求。基于煤层含气量测井响应特征,分析测井参数与含气量的相关性,提出MIV（Mean Impact Value）技术与LSSVM（Least Squares Support Vector Machine）结合的测井参数优选策略,优选最优测井参数作为网络建模的输入自变量组合,通过粒子群算法优化LSSVM网络核心参数,最后构建一套适用于煤层含气量预测的MIV-PSO-LSSVM模型。在此基础上,分别对比分析LSSVM、PSO-LSSVM、MIV-LSSVM和MIV-PSO-LSSVM模型对煤层含气量的预测性能,并与传统多元回归方法进行了对比,利用拟合优度和均方根误差对此5类模型进行评价。结果表明:PSO优化下的LSSVM模型预测精度得到有效提升,结合MIV方法优选测井参数可大幅度改善神经网络建模性能,MIV-PSO-LSSVM模型可实现煤层含气量高精度预测,为煤层气勘探及其储层评价提供新的技术支撑,且本研究的建模策略及思想可广泛应用于其他机器学习建模研究领域。 相似文献
8.
以云南阳宗海1020 cm长的湖泊沉积物岩芯为研究对象,由7个木屑和树叶残体样的AMS14C测年建立岩芯年代框架,以18~19 cm间隔获取52个样品作花粉/炭屑分析,重建了阳宗海流域过去13000年的植被、气候以及森林火灾历史。研究结果表明,过去13000年植被演替、气候变化和森林火灾可分为5个阶段:1)13200~11000 cal.a B.P.,植被以常绿、落叶阔叶混交林为主,气候温凉湿润,森林火灾多发,后期(12300~11000 cal.a B.P.)随着温度和湿度的降低,森林火灾发生愈加频繁;2)11000~8000 cal.a B.P.,松林扩张,阔叶林缩小,气候较上阶段温暖偏干,森林火灾发生次数明显降低;3)8000~5000 cal.a B.P.,松林和常绿阔叶林占优势,且出现暖热性的枫香林,流域内气温升至13000 cal.a B.P.以来的最高值,湿度进一步降低,但森林火灾发生频率低;4)5000~800 cal.a B.P.,松林扩张至最盛,常绿阔叶林收缩,落叶阔叶林成分增加,气温和湿度均明显下降,森林火灾发生频率有所增加;5)800 cal.a B.P.至今,松林和常绿阔叶林收缩,落叶阔叶成分增加,草本植物中禾本科迅速上升,可能与人类活动有关,森林火灾发生频率低。阳宗海花粉/炭屑记录重建的植被、气候和森林火灾史表明,在滇中地区,落叶阔叶成分易引起森林火灾,冷气候导致多发的森林火灾,冷干气候是宜森林火灾发生的气候条件。 相似文献
9.
Based on the operational standard indices, the prediction skills of the Western-Pacific Subtropical High (WPSH) and South-Asian High (SAH) using 2019 real-time forecasts derived from the Global Ensemble Prediction System of GRAPES (GRAPES-GEPS) in China Meteorological Administration (CMA) Numerical Prediction Center were evaluated and the effects of different ensemble approaches on the prediction skills of WPSH and SAH indices were further investigated in this study. The results show that for WPSH, the GRAPES-GEPS has its highest prediction skill for the ridge line index, considerably high skill for the intensity and area indices, but relatively low skill for the western boundary index, and for SAH, it has comparatively high skill for the intensity and center latitude indices, but relatively lower skill for the center longitude index. Prediction errors of the GRAPES-GEPS for the WPSH forecasts are featured by the weaker intensity and area and the more eastward center position, compared with the observation, which can be effectively reduced by employing the maximum/minimum approach from ensemble members, relative to the ensemble mean approach. By direct comparison, prediction errors of the GRAPES-GEPS for the SAH forecasts are featured by the weaker intensity and the more southward center position, which tends to be slightly reduced using the ensemble mean approach. Finally, for the extreme forecast, the maximum approach provides superior performance for both WPSH and SAH than the ensemble mean approach, which can be validated in terms of the two extreme cases. These results clearly indicate that the maximum approach could better improve the GRAPES-GEPS performance for the extreme forecasting of the two primary circulation patterns than the traditional ensemble mean approach. 相似文献
10.
基于新疆深390 cm的SCZ17黄土剖面的黑碳(BC)记录以及总有机碳含量(TOC)和磁化率结果,并与巴里坤湖孢粉记录的温度数据对比,重建了该区末次冰消期(16~12 ka,对应剖面深度202~274 cm)的火灾历史并探讨了其控制因素。结果表明:1)在末次冰消期期间黑碳通量与TOC变化具有较好的一致性,均呈上升趋势,说明随着植被量的增加,生物质燃烧活动增加;2)BC通量与湿度和温度数据的EEMD结果显示:①在13~16 ka期间,剖面的黑碳通量指示的区域生物质燃烧变化与温度变化存在着近乎同步的关系,而在12~13 ka期间可能由于湿度的影响二者的同步关系不太明确;②χfd%所指示的湿度变化和黑碳通量的对比结果显示,湿度峰值/谷值分别对应着黑碳通量的谷值/峰值,即当气候湿润时,火灾活动频率低;气候干旱时,火灾活动频率高。因此,认为研究区火灾活动倾向于发生在暖干的气候条件下,且可燃生物量可能控制着区域火灾变化的长期趋势,而由温度和湿度变化所造成的火灾活动的次一级波动叠加在这一长期趋势上。 相似文献
11.
Due to the limitations of model performances, the predictive skills of current climate models for the Asian-Australian summer monsoon precipitation are still poor. The prediction based on the combination of statistical and dynamic approaches is an effective way to improve the predictive skills. We used such method to identify the predictable modes of the Asian-Australian summer monsoon precipitation with clear physical interpretation from the historical observational data. Then we combined the principal components time series of these modes predicted by the coupled models, which is derived from the seasonal prediction experiments in the ENSEMBLES project, and the corresponding spatial patterns derived from the above observational analysis to reconstruct the precipitation field. These formed a statistical-dynamic seasonal prediction model for the Asian-Australian summer monsoon precipitation. We analyzed the predictive skills of the model at 1-, 4-and 7-month leads. The result shows that the forecast skills of the statistical-dynamic prediction model are higher than those of the simple dynamic predictions. In addition, the predictive skills of the Multi-Model Ensemble (MME) mean are superior to those of any individual models. Therefore, it is very necessary to implement multi-model ensemble prediction for the monsoon precipitation. 相似文献
12.
Impact of additional surface observation network on short range weather forecast during summer monsoon 2008 over Indian subcontinent 总被引：1，自引：0，他引：1
The three dimensional variational data assimilation scheme (3D-Var) is employed in the recently developed Weather Research
and Forecasting (WRF) model. Assimilation experiments have been conducted to assess the impact of Indian Space Research Organisation’s
(ISRO) Automatic Weather Stations (AWS) surface observations (temperature and moisture) on the short range forecast over the
Indian region. In this study, two experiments, CNT (without AWS observations) and EXP (with AWS observations) were made for
24-h forecast starting daily at 0000 UTC during July 2008. The impact of assimilation of AWS surface observations were assessed
in comparison to the CNT experiment. The spatial distribution of the improvement parameter for temperature, relative humidity
and wind speed from one month assimilation experiments demonstrated that for 24-h forecast, AWS observations provide valuable
information. Assimilation of AWS observed temperature and relative humidity improved the analysis as well as 24-h forecast.
The rainfall prediction has been improved due to the assimilation of AWS data, with the largest improvement seen over the
Western Ghat and eastern India. 相似文献
13.
The prediction of climate change in the future 10~30 year is a hot research area of the international community of the climate science, which has been listed as a core content of the Coupled Model Intercomparison Project (CMIP) and some other important international scientific projects. The forecast object of the decadal climate prediction has been extended from averaged state over the future 10~30 years to temporal evolutions in future 1~10 or 30 years. Recently, the World Meteorological Organization (WMO) has been preparing to issue climate states in the near future based on decadal climate prediction systems. Focusing on the cut-edging and challenging scientific questions of the decadal climate prediction, we reviewed the theoretic basis of the predictability of the decadal climate and recent progresses of the practical decadal prediction experiments by international modelling centers in the paper. Finally, we summarized the core scientific questions to be solved in the area and discuss ed possible pathways to improve the skills of the decadal climate prediction. 相似文献
14.
Experimental real-time multi-model ensemble (MME) prediction of rainfall during monsoon 2008: Large-scale medium-range aspects 总被引：1，自引：0，他引：1
A K MITRA G R IYENGAR V R DURAI J SANJAY T N KRISHNAMURTI A MISHRA D R SIKKA 《Journal of Earth System Science》2011,120(1):27-52
Realistic simulation/prediction of the Asian summer monsoon rainfall on various space–time scales is a challenging scientific
task. Compared to mid-latitudes, a proportional skill improvement in the prediction of monsoon rainfall in the medium range
has not happened in recent years. Global models and data assimilation techniques are being improved for monsoon/tropics. However,
multi-model ensemble (MME) forecasting is gaining popularity, as it has the potential to provide more information for practical
forecasting in terms of making a consensus forecast and handling model uncertainties. As major centers are exchanging model
output in near real-time, MME is a viable inexpensive way of enhancing the forecasting skill and information content. During
monsoon 2008, on an experimental basis, an MME forecasting of large-scale monsoon precipitation in the medium range was carried
out in real-time at National Centre for Medium Range Weather Forecasting (NCMRWF), India. Simple ensemble mean (EMN) giving
equal weight to member models, bias-corrected ensemble mean (BCEMn) and MME forecast, where different weights are given to
member models, are the products of the algorithm tested here. In general, the aforementioned products from the multi-model
ensemble forecast system have a higher skill than individual model forecasts. The skill score for the Indian domain and other
sub-regions indicates that the BCEMn produces the best result, compared to EMN and MME. Giving weights to different models
to obtain an MME product helps to improve individual member models only marginally. It is noted that for higher rainfall values,
the skill of the global model rainfall forecast decreases rapidly beyond day-3, and hence for day-4 and day-5, the MME products
could not bring much improvement over member models. However, up to day-3, the MME products were always better than individual
member models. 相似文献
15.
Lin Li 《中国地质大学学报(英文版)》2011,(5)
Partial least squares(PLS) regression was applied to the Lunar Soil Characterization Consortium(LSCC) dataset for spectral estimation of TiO2.The LSCC dataset was split into a number of subsets including the low-Ti,high-Ti,total mare soils,total highland,Apollo 16,and Apollo 14 soils to investigate the effects of interfering minerals and nonlinearity on the PLS performance.The PLS weight loading vectors were analyzed through stepwise multiple regression analysis(SMRA) to identify mineral species driving and... 相似文献
16.
Sutapa Chaudhuri Debashree Dutta Sayantika Goswami Anirban Middey 《Natural Hazards》2013,65(1):97-113
The coastal regions of India are profoundly affected by tropical cyclones during both pre- and post-monsoon seasons with enormous loss of life and property leading to natural disasters. The endeavour of the present study is to forecast the intensity of the tropical cyclones that prevail over Arabian Sea and Bay of Bengal of North Indian Ocean (NIO). A multilayer perceptron (MLP) model is developed for the purpose and compared the forecast through MLP model with other neural network and statistical models to assess the forecast skill and performances of MLP model. The central pressure, maximum sustained surface wind speed, pressure drop, total ozone column and sea surface temperature are taken to form the input matrix of the models. The target output is the intensity of the tropical cyclones as per the T??number. The result of the study reveals that the forecast error with MLP model is minimum (4.70?%) whereas the forecast error with radial basis function network (RBFN) is observed to be 14.62?%. The prediction with statistical multiple linear regression and ordinary linear regression are observed to be 9.15 and 9.8?%, respectively. The models provide the forecast beyond 72?h taking care of the change in intensity at every 3-h interval. The performance of MLP model is tested for severe and very severe cyclonic storms like Mala (2006), Sidr (2007), Nargis (2008), Aila (2009), Laila (2010) and Phet (2010). The forecast errors with MLP model for the said cyclones are also observed to be considerably less. Thus, MLP model in forecasting the intensity of tropical cyclones over NIOs may thus be considered to be an alternative of the conventional operational forecast models. 相似文献
17.
Displacement prediction model of landslide based on a modified ensemble empirical mode decomposition and extreme learning machine 总被引：5，自引：1，他引：4
In this paper, an M–EEMD–ELM model (modified ensemble empirical mode decomposition (EEMD)-based extreme learning machine (ELM) ensemble learning paradigm) is proposed for landslide displacement prediction. The nonlinear original surface displacement deformation monitoring time series of landslide is first decomposed into a limited number of intrinsic mode functions (IMFs) and one residual series using EEMD technique for a deep insight into the data structure. Then, these sub-series except the high frequency are forecasted, respectively, by establishing appropriate ELM models. At last, the prediction results of the modeled IMFs and residual series are summed to formulate an ensemble forecast for the original landslide displacement series. A case study of Baishuihe landslide in the Three Gorges reservoir area of China is presented to illustrate the capability and merit of our model. Empirical results reveal that the prediction using M–EEMD–ELM model is consistently better than basic artificial neural networks (ANNs) and unmodified EEMD–ELM in terms of the same measurements. 相似文献
18.
建立红柳沙包沉积纹层年代序列和提取气候环境信息是高分辨率古气候环境变化研究的重要手段。利用策勒达玛沟红柳沙包高度约450 cm沉积纹层红柳落叶的稳定氧同位素数据,结合策勒气象站1960~2011年观测数据,运用移动平均法对稳定氧同位素和气象数据进行平滑处理后,运用相关分析及逐步回归法,定量重建了策勒地区近400年来的4月平均气温和3月降水量序列。研究结果表明:红柳落叶δ^18O平均值为33.96‰,波动范围为27.18‰~44.07‰,波动幅度为16.89‰,δ^18O变化受多个气候要素的综合影响。δ^18O与4月平均气温呈显著负相关,与2月和12月平均气温呈显著正相关;δ^18O与10月、4月、5月、9月、7月以及全年的空气相对湿度呈显著正相关;δ^18O与3月、9月和8月的降水量呈显著正相关,与2月降水量呈显著负相关;δ^18O与2月日照时数呈显著正相关,与9月和10月的日照时数呈显著负相关。策勒地区近400年来气候变化可划分4个阶段:1635~1725年为暖干期,1726~1792年为冷湿期,1793~1897年为暖干期,1898~2009年为冷湿期。 相似文献
19.
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