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1.
Aiming at reducing losses from flood disaster, risk assessment of flood disaster and forewarning model is studied. The model is built upon risk indices in flood disaster system, proceeding from the whole structure and its parts at different spatial-temporal scales. In this study, on the one hand, it mainly establishes the long-term forewarning model for the surface area with three levels of prediction, evaluation, and forewarning. The method of structure-adaptive back-propagation neural network on peak identification is used to simulate indices in prediction sub-model. Set pair analysis is employed to calculate the connection degrees of a single index, comprehensive index, and systematic risk through the multivariate connection number, and the comprehensive assessment is made by assessment matrixes in evaluation sub-model. The comparison judging method is adopted to divide warning degree of flood disaster on risk assessment comprehensive index with forewarning standards in forewarning sub-model and then the long-term local conditions for proposing planning schemes. On the other hand, it mainly sets up the real-time forewarning model for the spot, which introduces the real-time correction technique of Kalman filter based on hydrological model with forewarning index, and then the real-time local conditions for presenting an emergency plan. This study takes Tunxi area, Huangshan City of China, as an example. After risk assessment and forewarning model establishment and application for flood disaster at different spatial-temporal scales between the actual and simulated data from 1989 to 2008, forewarning results show that the development trend for flood disaster risk remains a decline on the whole from 2009 to 2013, despite the rise in 2011. At the macroscopic level, project and non-project measures are advanced, while at the microcosmic level, the time, place, and method are listed. It suggests that the proposed model is feasible with theory and application, thus offering a way for assessing and forewarning flood disaster risk. 相似文献
2.
基于动力降尺度预测系统,中国科学院大气物理研究所竺可桢-南森国际研究中心对2018年夏季我国极端降水日数及滑坡泥石流灾害的发生风险进行了超前4个月的实时预测试验。与实测结果相比,该系统对2018年夏季我国极端降水日数空间分布的预测与实况基本相符,但大部分地区存在明显低估;滑坡泥石流的预测结果与目前统计的由于降水引发的滑坡泥石流灾害事件的分布基本吻合。此次预测试验表明,中国科学院大气物理研究所竺可桢-南森国际研究中心发展的动力降尺度预测系统对我国夏季极端降水和滑坡泥石流灾害具有一定的预测能力,具有实时预测价值。 相似文献
3.
热带大气低频振荡 (MJO) 和北半球夏季季节内振荡 (BSISO) 对全球范围天气气候事件有重要影响,是次季节-季节 (S2S) 预报最主要的可预报性来源之一。国家气候中心 (BCC) 基于我国完全自主的T639全球分析场数据、风云三号气象卫星射出长波辐射 (OLR) 资料以及BCC第2代大气环流模式系统的实时预报,发展了MJO实时监测预测一体化业务技术,建立了ISV/MJO监测预测业务系统 (IMPRESS1.0),已投入实时业务运行,在全国气象业务系统得到应用。该文着重介绍该系统提供的MJO和BSISO指数监测预测数据和图形产品,并描述了这些业务产品在2015年对MJO典型个例的实时监测预测应用情况。监测分析和预报检验表明,基于我国自主资料的监测结果能够较为准确地表征MJO和BSISO指数的振荡和演变过程,该系统对MJO和BSISO事件分别至少具备16 d和10 d左右的预报技巧。因此,基于IMPRESS1.0的MJO/BSISO监测预测一体化业务产品可为制作延伸期预报提供重要的参考依据。 相似文献
4.
1999年中国夏季气候的预测和检验 总被引：35，自引：6，他引：29
利用改进的中国科学院大气物理研究所短期气候预测系统（IAPPSSCA）,结合IAPENSO预测系统所预测的1999年热带太平洋地区的海温异常,对1999年中国夏季气候进行了适时集合预测。预测结果表明：IAPPSSCA较好地预测出了1999年夏季北半球大尺度环流场的异常情况,并较好地预测出1999年中国南涝北旱的大范围降水形势。IAPPSSCA对长江下游的强降水中心、中国南方大部夏季多雨的特征以及中国北方大部的干旱少雨形势的预测,与实测较相符。但IAPPSSCA预测的南方大范围雨带的北界比实测的略为偏北,北方的小范围的降水正距平区域也没有能预报出来。另外,对于月平均降水距平的预测亦存在较大的不确定性。这说明我们的预测系统还有待于进一步的改进和完善。 相似文献
5.
Seasonal Prediction of Summer Temperature over Northeast China Using a Year-to-Year Incremental Approach 总被引：4，自引：0，他引：4 
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下载免费PDF全文 We present a model for predicting summertime surface air temperature in Northeast China (NESSAT) using a year-to-year incremental approach. The predicted value for each year's increase or decrease of NESSAT is added to the observed value within a particular year to yield the net forecast NESSAT. The seasonal forecast model for the year-to-year increments of NESSAT is constructed based on data from 1975-2007. Five predictors are used: an index for sea ice cover over the East Siberian Sea, an index for central Pacific tropical sea surface temperature, two high latitude circulation indices, as well as a North American pressure index. All predictors are available by no later than March, which allows for compilation of a seasonal forecast with a two-month lead time. The prediction model accurately captures the interannual variations of NESSAT during 1977-2007 with a correlation coefficient between the predicted and observed NESSAT of 0.87 (accounting for 76% of total variance) and a mean absolute error (MAE) of 0.3℃. A cross-validation test during 1977 2008 demonstrates that the model has good predictive skill, with MAE of 0.4℃ and a correlation coefficient between the predicted and observed NESSAT of 0.76. 相似文献
6.
An Effective Approach for Improving the Real-Time Prediction of Summer Rainfall over China 总被引：1，自引：0，他引：1 下载免费PDF全文
下载免费PDF全文 LANG Xian-Mei 《大气和海洋科学快报》2011,4(2):75-80
This paper has two purposes. One is to evaluate the ability of an atmospheric general circulation model (IAP9L-AGCM) to predict summer rainfall over China one season in advance. The other is to propose a new approach to improve the predictions made by the model. First, a set of hindcast experiments for summer climate over China during 1982-2010 are performed from the perspective of real-time prediction with the IAP9L-AGCM model and the IAP ENSO prediction system. Then a new approach that effectively combines the hind-cast with its correction is proposed to further improve the model’s predictive ability. A systematic evaluation reveals that the model’s real-time predictions for 41 stations across China show significant improvement using this new approach, especially in the lower reaches between the Yellow River and Yangtze River valleys. 相似文献
7.
利用耦合有起电和放电物理过程的中尺度起电放电模式WRF-Electric,开展了华北地区连续3年（2015—2017年）的闪电活动预报试验。结合全国地闪定位观测资料,针对不同影响范围雷暴类型和预报时间,对数值预报结果开展点对点的定量检验,评估模式对闪电活动的预报能力及特点。结果表明:WRF-Electric中尺度模式具备一定的区域闪电活动预报能力,在起报后的6~12 h对闪电活动区域具有较好的预报效果。雷暴落区预报的点对点定量检验中,模式和业务预报在华北主汛期（6—8月）的预报临界成功指数（CSI）均为0.1,模式对于活动范围较小的局地性雷暴过程的预报更具参考价值。模式预报的闪电活动范围相对集中,闪电活动密度偏高,预报的主要问题存在于放电参数化方案的设计。应当考虑到模式空间分辨率对云内电场强度的影响,合理降低闪电参数化中的放电阈值以扩大预报的闪电活动范围。模式在闪电密度的定量预报上还有较大改进空间,单次放电中和电荷量应当更符合观测事实。 相似文献
8.
Summary A completely new nonhydrostatic model system known as the Advanced Regional Prediction System (ARPS) has been developed in
recent years at the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma. The ARPS is designed
from the beginning to serve as an effective tool for basic and applied research and as a system suitable for explicit prediction
of convective storms as well as weather systems at other scales. The ARPS includes its own data ingest, quality control and
objective analysis packages, a data assimilation system which includes single-Doppler velocity and thermodynamic retrieval
algorithms, the forward prediction component, and a self-contained post-processing, diagnostic and verification package.
The forward prediction component of the ARPS is a three-dimensional, nonhydrostatic compressible model formulated in generalized
terrain-following coordinates. Minimum approximations are made to the original governing equations. The split-explicit scheme
is used to integrate the sound-wave containing equations, which allows the horizontal domain-decomposition strategy to be
efficiently implemented for distributed-memory massively parallel computers. The model performs equally well on conventional
shared-memory scalar and vector processors. The model employs advanced numerical techniques, including monotonic advection
schemes for scalar transport and variance-conserving fourth-order advection for other variables. The model also includes state-of-the-art
physics parameterization schemes that are important for explicit prediction of convective storms as well as the prediction
of flows at larger scales.
Unique to this system are the consistent code styling maintained for the entire model system and thorough internal documentation.
Modern software engineering practices are employed to ensure that the system is modular, extensible and easy to use.
The system has been undergoing real-time prediction tests at the synoptic through storm scales in the past several years over
the continental United States as well as in part of Asia, some of which included retrieved Doppler radar data and hydrometeor
types in the initial condition.
As the first of a two-part paper series, we describe herein the dynamic and numerical framework of the model, together with
the subgrid-scale turbulence and the PBL parameterization. The model dynamic and numerical framework is then verified using
idealized and realistic mountain flow cases and an idealized density current. Other physics parameterization schemes will
be described in Part II, which is followed by verification against observational data of the coupled soil-vegetation model,
surface layer fluxes and the PBL parameterization. Applications of the model to the simulation of an observed supercell storm
and to the prediction of a real case are also found in Part II. In the latter case, a long-lasting squall line developed and
propagated across the eastern part of the United States following a historical number of tornado outbreak in the state of
Arkansas.
Received April 14, 2000 Revised July 17, 2000 相似文献
9.
热带大气季节内振荡(MJO)实时监测预测业务 总被引：8，自引：2，他引：6
参考目前国际上普遍认可的Wheeler和Hendon设计的MJO监测指标,设计了适合开展实时业务监测的MJO计算方法,初步在国家气候中心建立了逐日的MJO实时监测业务,通过与国外同类监测结果的比较分析表明,监测指标可以很好地描述MJO的强度和传播特征,与国外同类监测产品有很好的一致性。另外,引入了两种统计方法进行了针对MJO指数的实时预测,对预测结果的检验表明,对MJO在两周内有较好的预测技巧,其中利用滞后线性回归方法（PCL）的预测技巧要高于自回归模型（ARM）。 相似文献
10.
11.
Emilia K. Jin James L. Kinter III B. Wang C.-K. Park I.-S. Kang B. P. Kirtman J.-S. Kug A. Kumar J.-J. Luo J. Schemm J. Shukla T. Yamagata 《Climate Dynamics》2008,31(6):647-664
The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO. 相似文献
12.
利用DEMETER多模式集合研究计划中Météo France模式的预报资料集,在分析其对冬季北半球中高纬度地区 (20°~90°N)500 hPa高度场预报效果的基础上,针对模式预测较差的模态分别运用最优子集回归修正方案和回归-相似相结合的修正方案对其进行订正。结果表明:数值模式对观测模态的预测能力并非随模态数的增加而递减,方差贡献较小的模态的预报效果可能好于方差贡献较大的模态;基于最优子集的回归订正方法未能改进原模式预报技巧;在最优子集回归基础上再经相似订正的方法 (DAP-OSR) 能够改进预测效果,独立试报的距平相关系数平均每年提高0.1。 相似文献
13.
An integrated approach to real-time prediction of point rainfall is presented. This is based on the assumption that hourly rainfall at a station can be predicted by a Multivariate AutoRegressive Integrated Moving Average (MARIMA) process. The real-time calibration of the multivariate model is performed by combining radar maps and data from rain gages. Accordingly, radar maps provide the basic information for a storm tracking procedure which enables to detect the direction and the speed of storm movement. Storm tracking is used to select those stations which are characterized by the highest Lagrangian cross-correlation of observed precipitation, and which are therefore best suitable for application of the multivariate model. The parameters of the multivariate model are finally estimated using only observed rainfall at the selected stations throughout the current event. Preliminary results of an application to some events which occurred in northern Italy show that the combined use of radar and rain gages allows for an increased efficiency of the MARIMA model performances, as compared with empirical selection of stations to be considered by the multivariate model. The multivariate approach performs better also when it is compared with simple nowcasting procedures based on rain gage data or on radar data used separately. Finally, some considerations are issued in view of a systematic use of this technique to nowcast rainfall intensity in small urban or natural catchments, with a response time of less than 1 or 2 h. 相似文献
14.
Probabilistic Flood Prediction in the Upper Huaihe Catchment Using TIGGE Data 总被引：1，自引：0，他引：1 下载免费PDF全文
下载免费PDF全文 ZHAO Linn QI Dan TIAN Fuyou WU Hao DI Jingyue WANG Zhi LI Aihua 《Acta Meteorologica Sinica》2012,26(1):62-71
Based on the precipitation and temperature data obtained from THORPEX (The Observing System Research and Predictability Experiment) Interactive Grand Global Ensemble (TIGGE)-China Meteorological Administration (CMA) archiving center and the raingauge data,the three-layer variable infiltration capacity (VIC-3L) land surface model was employed to carry out probabilistic hydrological forecast experiments over the upper Huaihe River catchment from 20 July to 3 August 2008.The results show that the performance of the ensemble probabilistic prediction from each ensemble prediction system (EPS) is better than that of the deterministic prediction.Especially,the 72-h prediction has been improved obviously.The ensemble spread goes widely with increasing lead time and more observed discharge is bracketed in the 5th-99th quantile.The accuracy of river discharge prediction driven by the European Centre (EC)-EPS is higher than that driven by the CMA-EPS and the US National Centers for Environmental Prediction (NCEP)-EPS,and the grand-ensemble prediction is the best for hydrological prediction using the VIC model.With regard to Wangjiaba station,all predictions made with a single EPS are close to the observation between the 25th and 75th quantile.The onset of the flood ascending and the river discharge thresholds are predicted well,and so is the second rising limb.Nevertheless,the flood recession is not well predicted. 相似文献
15.
降水作为全球水循环的重要组成,与人们的生产生活密切相关.有效的降水预测对于防灾减灾,以及经济的可持续发展至关重要.然而,由于影响降水过程的复杂性,当前降水预测还存在诸多挑战.针对我国东部夏季降水,我们提出年际增量结合经验正交分解的新统计预测方法.首先计算降水年际增量的主模态,然后针对主模态时间序列构建预测模型,用预测的... 相似文献
16.
Harun A. Rashid Harry H. Hendon Matthew C. Wheeler Oscar Alves 《Climate Dynamics》2011,36(3-4):649-661
Predictions of the Madden?CJulian oscillation (MJO) are assessed using a 10-member ensemble of hindcasts from POAMA, the Australian Bureau of Meteorology coupled ocean?Catmosphere seasonal prediction system. The ensemble of hindcasts was initialised from observed atmosphere and ocean initial conditions on the first of each month during 1980?C2006. The MJO is diagnosed using the Wheeler-Hendon Real-time Multivariate MJO (RMM) index, which involves projection of daily data onto the leading pair of eigenmodes from an analysis of zonal winds at 200 and 850?hPa and outgoing longwave radiation (OLR) averaged about the equator. Forecasts of the two component (RMM1 and RMM2) index are quantitatively compared with observed behaviour derived from NCEP reanalyses and satellite OLR using the bivariate correlation skill, root-mean-square error (RMSE), and measures of the MJO amplitude and phase error. Comparison is also made with a simple vector autoregressive (VAR) prediction model of RMM as a benchmark. Using the full hindcast set, we find that the MJO can be predicted with the POAMA ensemble out to about 21?days as measured by the bivariate correlation exceeding 0.5 and the bivariate RMSE remaining below ~1.4 (which is the value for a climatological forecast). The VAR model, by comparison, drops to a correlation of 0.5 by about 12?days. The prediction limit from POAMA increases by less than 2?days for times when the MJO has large initial amplitude, and has little sensitivity to the initial phase of the MJO. The VAR model, on the other hand, shows a somewhat larger increase in skill for times of strong MJO variability and has greater sensitivity to initial phase, with lower skill for times when MJO convection is developing in the Indian Ocean. The sensitivity to season is, however, greater for POAMA, with maximum skill occurring in the December?CJanuary?CFebruary season and minimum skill in June?CJuly?CAugust. Examination of the MJO amplitudes shows that individual POAMA members have slightly above observed amplitude after a spin-up of about 10?days, whereas examination of the MJO phase error reveals that the model has a consistent tendency to propagate the MJO slightly slower than observed. Finally, an estimate of potential predictability of the MJO in POAMA hindcasts suggests that actual MJO prediction skill may be further improved through continued development of the dynamical prediction system. 相似文献
17.
The meridional propagation of the 30- to 60-day intraseasonal variability (ISV) of precipitation in the East Asian subtropical summer monsoon (EASSM) region and its monitoring and prediction are investigated in the current study. Based on a multivariate empirical orthogonal function (MV-EOF) analysis of precipitation and relative vorticity at 700?hPa in East Asia, a bivariate index referred to as the EASSM-ISV index is designed using the two leading MV-EOF modes, with the objective of real-time monitoring of the 30- to 60-day variability of precipitation in the EASSM region. It is found that this index, with its eight phases, can explain the meridional propagation of the 30- to 60-day ISV in precipitation and circulation in the EASSM region. Based on a singular value decomposition technique, a statistical forecast model is developed in which the EASSM-ISV indices from the preceding five pentads are used to predict the indices in five pentads in the future. Meanwhile, the indices are used to predict the meridional propagation of the 30- to 60-day precipitation anomaly in the EASSM region. This model thus provides a useful tool for intraseasonal prediction of precipitation during the rainy season in China. 相似文献
18.
M. L. Kaplan J. J. Charney K. T. WaightIII K. M. Lux J. D. Cetola A. W. Huffman A. J. Riordan S. D. Slusser M. T. Kiefer P. S. Suffern Y.-L. Lin 《Meteorology and Atmospheric Physics》2006,94(1-4):235-270
Summary In this paper, we will focus on the real-time prediction of environments that are predisposed to producing moderate-severe
(hazardous) aviation turbulence. We will describe the numerical model and its postprocessing system that is designed for said
prediction of environments predisposed to severe aviation turbulence as well as presenting numerous examples of its utility.
The purpose of this paper is to demonstrate that simple hydrostatic precursor circulations organize regions of preferred wave
breaking and turbulence at the nonhydrostatic scales of motion. This will be demonstrated with a hydrostatic numerical modeling
system, which can be run in real time on a very inexpensive university computer workstation employing simple forecast indices.
The forecast system is designed to efficiently support forecasters who are directing research aircraft to measure the environment
immediately surrounding turbulence.
The numerical model is MASS version 5.13, which is integrated over three different grid matrices in real-time on a university
workstation in support of NASA-Langley’s B-757 turbulence research flight missions. The model horizontal resolutions are 60,
30, and 15 km and the grids are centered over the region of operational NASA-Langley B-757 turbulence flight missions.
The postprocessing system includes several turbulence-related products including four turbulence forecasting indices, winds,
streamlines, turbulence kinetic energy, and Richardson numbers. Additionally there are convective products including precipitation,
cloud height, cloud mass fluxes, lifted index, and K-index. Furthermore, soundings, sounding parameters, and Froude number
plots are also provided. The horizontal cross section plot products are provided from 16,000–46,000 feet in 2,000 feet intervals.
Products are available every three hours at the 60 and 30 km grid interval and every 1.5 hours at the 15 km grid interval.
The model is initialized from the NWS ETA analyses and integrated two times a day. 相似文献
19.
Dong-Kyou Lee Dae-Yong Eom Joo-Wan Kim Jae-Bok Lee 《Asia-Pacific Journal of Atmospheric Sciences》2010,46(3):341-353
The WRF-based real-time forecast system (http://jhwc.snu.ac.kr/weather) of the Joint Center for High-impact Weather and Climate Research (JHWC) has been in operation since November 2006; this system has three nested model domains using GFS (Global Forecast System) data for its initial and boundary conditions. In this study, we evaluate the improvement in daily and hourly weather prediction, particularly the prediction of summer rainfall over the Korean Peninsula, in the JHWC WRF (Weather Research and Forecasting) model system by 3DVAR (three-Dimensional Variational) data assimilation using the data obtained from KEOP (Korea Enhanced Observation Program). KEOP was conducted during the period June 15 to July 15, 2007, and the data obtained included GTS (Global Telecommunication System) upper-air sounding, AWS (Automatic Weather System), wind profiler, and radar observation data. Rainfall prediction and its characteristics should be verified by using the precipitation observation and the difference field of each experiment. High-resolution (3 km in domain 3) summer rainfall prediction over the Korean peninsula is substantially influenced by improved synoptic-scale prediction in domains 1 (27 km) and 2 (9 km), in particular by data assimilation using the sounding and wind profiler data. The rainfall prediction in domain 3 was further improved by radar and AWS data assimilation in domain 3. The equitable threat score and bias score of the rainfall predicted in domain 3 indicated improvement for the threshold values of 0.1, 1, and 2.5 mm with data assimilation. For cases of occurrence of heavy rainfall (7 days), the equitable threat score and bias score improved considerably at all threshold values as compared to the entire period of KEOP. Radar and AWS data assimilation improved the temporal and spatial distributions of diurnal rainfall over southern Korea, and AWS data assimilation increased the predicted rainfall amount by approximately 0.3 mm 3hr?1. 相似文献
20.
A three-level model system for the prediction of local flows in mountainous terrain is described. The system is based upon
an operational weather prediction model with a horizontal grid spacing of about 10 km. The large-scale flow is transformed
to a more detailed terrain, first by a mesoscale model with grid spacing of about 1 km, and then by a local-scale model with
a grid spacing of about 0.2 km. The weather prediction model is hydrostatic, while the two other models are non-hydrostatic.
As a case study the model system has been applied to estimate wind and turbulence over Várnes airport, Norway, where data
on turbulent flight conditions were provided near the runway. The actual case was chosen due to previous experiences, which
indicate that south-easterly winds may cause severe turbulence in a region close to the airport. Local terrain induced turbulence
seems to be the main reason for these effects. The predicted local flow in the actual region is characterized by narrow secondary
vortices along the flow, and large turbulent intensity associated with these vortices. A similar pattern is indicated by the
sparse observations, although there seems to be a difference in mean wind direction between data and predictions. Due to fairly
coarse data for sea surface temperature, errors could be induced in the turbulence damping via the Richardson number. An adjustment
for this data problem improved the predictions. 相似文献