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1.
Vassiliki Kotroni Evangelos Floros Konstantinos Lagouvardos Goran Pejanovic Luka Ilic Momcilo Zivkovic 《Earth Science Informatics》2010,3(4):209-218
Weather forecasting is based on the use of numerical weather prediction (NWP) models that are able to perform the necessary
calculations that describe/predict the major atmospheric processes. One common problem in weather forecasting derives from
the uncertainty related to the chaotic behaviour of the atmosphere. A solution to that problem is to perform in addition to
“deterministic” forecasts, “stochastic” forecasts that provide an estimate of the prediction skill. A computationally feasible
approach towards this aim is to perform “ensemble forecasts”. Indeed, in the frame of SEE-GRID-SCI EU funded project a Regional
scale Multi-model, Multi-analysis ensemble forecasting system (REFS) was built and ported on the Grid infrastructure. REFS
is based on the use of four limited area models (namely BOLAM, MM5, ETA, and NMM) that are run using a multitude of initial
and boundary conditions over the Mediterranean. This paper presents the tools and procedures followed for developing this
application at a production level. 相似文献
2.
V S PRASAD SAJI MOHANDAS SURYA KANTI DUTTA M DAS GUPTA G R IYENGAR E N RAJAGOPAL SWATI BASU 《Journal of Earth System Science》2014,123(2):247-258
Medium range weather forecasts are being generated in real time using Global Data Assimilation Forecasting System (GDAFS) at NCMRWF since 1994. The system has been continuously upgraded in terms of data usage, assimilation and forecasting system. Recently this system was upgraded to a horizontal resolution of T574 (about 22 km) with 64 levels in vertical. The assimilation scheme of this upgraded system is based on the latest Grid Statistical Interpolation (GSI) scheme and it has the provision to use most of available meteorological and oceanographic satellite datasets besides conventional meteorological observations. The new system has an improved procedure for relocating tropical cyclone to its observed position with the correct intensity. All these modifications have resulted in improvement of skill of medium range forecasts by about 1 day. 相似文献
3.
Progress in Researches on Ensemble Forecasting of Extreme Weather Based on Numerical Models 总被引：1，自引：1，他引：0
Under the background of climate change, extreme weather events (e.g., heavy rainfall, heat wave, and cold damage) in China have been occurring more frequently with an increasing trend of induced meteorological disasters. Therefore, it is of great importance to carry out research on forecasting of extreme weather. This paper systematically reviewed the primary methodology of extreme weather forecast, current status in development of ensemble weather forecasting based on numerical models and their applications to forecast of extreme weather, as well as progress in approaches for correcting ensemble probabilistic forecast. Nowadays, the forecasting of extreme weather has been generally dominated by methodology using dynamical models. That is to say, the dynamical forecasting methods based on ensemble probabilistic forecast information have become prevailing in current operational extreme weather forecast worldwide. It can be clearly found that the current major directions of research and development in this field are the application of ensemble forecasts based on numerical models to forecasting of extreme weather, and its improvement through bias correction of ensemble probabilistic forecast. Based on a relatively comprehensive review in this paper, some suggestions with respect to development of extreme weather forecast in future were further given in terms of the issues of how to propose effective approaches on improving level of identification and forecasting of extreme events. 相似文献
4.
Antti Pulkkinen Michael Hesse Shahid Habib Luke Van der Zel Ben Damsky Fritz Policelli David Fugate William Jacobs Elizabeth Creamer 《Natural Hazards》2010,53(2):333-345
In this paper, central elements of the Solar Shield project, launched to design and establish an experimental system capable
of forecasting the space weather effects on high-voltage power transmission system, are described. It will be shown how Sun–Earth
system data and models hosted at the Community Coordinated Modeling Center (CCMC) are used to generate two-level magnetohydrodynamics-based
forecasts providing 1–2 day and 30–60 min lead-times. The Electric Power Research Institute (EPRI) represents the end-user,
the power transmission industry, in the project. EPRI integrates the forecast products to an online display tool providing
information about space weather conditions to the member power utilities. EPRI also evaluates the economic impacts of severe
storms on power transmission systems. The economic analysis will quantify the economic value of the generated forecasting
system. The first version of the two-level forecasting system is currently running in real-time at CCMC. An initial analysis
of the system’s capabilities has been completed, and further analysis is being carried out to optimize the performance of
the system. Although the initial results are encouraging, definite conclusions about system’s performance can be given only
after more extensive analysis, and implementation of an automatic evaluation process using forecasted and observed geomagnetically
induced currents from different nodes of the North American power transmission system. The final output of the Solar Shield
will be a recommendation for an optimal forecasting system that may be transitioned into space weather operations. 相似文献
5.
Mountain range specific analog weather forecast model is developed utilizing surface weather observations of reference stations
in each mountain range in northwest Himalaya (NW-Himalaya). The model searches past similar cases from historical dataset
of reference observatory in each mountain range based on current situation. The searched past similar cases of each mountain
range are used to draw weather forecast for that mountain range in operational weather forecasting mode, three days in advance.
The developed analog weather forecast model is tested with the independent dataset of more than 717 days (542 days for Pir
Panjal range in HP) of the past 4 winters (2003–2004 to 2006–2007). Independent test results are reasonably good and suggest
that there is some possibility of forecasting weather in operational weather forecasting mode employing analog method over
different mountain ranges in NW-Himalaya. Significant difference in overall accuracy of the model is found for prediction
of snow day and no-snow day over different mountain ranges, when weather is predicted under snow day and no-snow day weather
forecast categories respectively. In the same mountain range, significant difference is also found in overall accuracy of
the model for prediction of snow day and no-snow day for different areas. This can be attributed to their geographical position
and topographical differences. The analog weather forecast model performs better than persistence and climatological forecast
for day-1 predictions for all the mountain ranges except Karakoram range in NW-Himalaya. The developed analog weather forecast
model may help as a guidance tool for forecasting weather in operational weather forecasting mode in different mountain ranges
in NW-Himalaya. 相似文献
6.
利用最小二乘支持向量机(LS-SVM)方法,建立了基于天气预报的参考作物腾发量(ET0)的预测模型.对广利灌区1997~2006年逐日气象信息中的天气类型和风速等级进行量化后,以不同天气预报信息作为输入量,建立10种验证方案,对2007年的逐日ET0进行预测.经验证,方案1~方案7精度均令人满意,其中方案1精度最高.方案1的输入量为气温、天气类型、风速等级3项的预测值,该方案的模型预测值与计算值的统计参数分别为:均方根偏差ERMS为0.5182 mm,相对偏差ER为0.1878,决定系数R2为0.864 8,认同系数IA为0.966 9,回归系数RC为0.9867;方案7精度亦较好,且以上指标统计参数依次为0.6576 mm、0.2332、0.986 6、0.774 7及0.986 6,该方案输入量只有气温项,实用性很强. 相似文献
7.
In this study, the Florida State University Global Spectral Model (FSUGSM), in association with a high-resolution nested regional
spectral model (FSUNRSM), is used for short-range weather forecasts over the Indian domain. Three-day forecasts for each day
of August 1998 were performed using different versions of the FSUGSM and FSUNRSM and were compared with the observed fields
(analysis) obtained from the European Center for Medium Range Weather Forecasts (ECMWF). The impact of physical initialization
(a procedure that assimilates observed rain rates into the model atmosphere through a set of reverse algorithms) on rainfall
forecasts was examined in detail. A very high nowcasting skill for precipitation is obtained through the use of high-resolution
physical initialization applied at the regional model level. Higher skills in wind and precipitation forecasts over the Indian
summer monsoon region are achieved using this version of the regional model with physical initialization.
A relatively new concept, called the ‘multimodel/multianalysis superensemble’ is described in this paper and is applied for
the wind and precipitation forecasts over the Indian subcontinent. Large improvement in forecast skills of wind at 850 hPa
level over the Indian subcontinent is shown possible through the use of the multimodel superensemble. The multianalysis superensemble
approach that uses the latest satellite data from the Tropical Rainfall Measuring Mission (TRMM) and the Defense Meteorological
Satellite Program (DMSP) has shown significant improvement in the skills of precipitation forecasts over the Indian monsoon
region. 相似文献
8.
Persistent extreme weather is of high disaster causing capability, represents a great threat to the safety of both people and property and results in substantial economic losses. However, the underlying mechanism of such high impact weather remains unclear, and related forecasting methods are quite under studied currently. Based on the comprehensive reviews of the relevant studies about persistent extreme weather, the prediction of such events within the period during 1～2 weeks in advance is believed to be a significant scientific issue. For this scientific problem, the studies of atmospheric low frequency process, the interaction between multi scale systems, the forcing of complicated underlying surface and sea land atmosphere interactions are necessary to be performed. These multi perspective studies will favor the final establishment of the corresponding forecasting theory and method based on the combination of dynamical prediction and statistical predication. It is hoped that the deficiencies in systematic studies about persistent extreme weather may be made up through pertinent studies, which will prolong the time length of forecasting and increase the prediction precision of such high impact events. 相似文献
9.
H N Bhalme R S Reddy D A Mooley Bh V Ramana Murty 《Journal of Earth System Science》1981,90(3):245-262
The literature on influences of solar activity on the Indian weather and climate is reviewed since the discovery of sunspot cycle. Fluctuations in solar activity are undoubtedly a factor affecting weather and climate. Although the results of some of the studies are conflicting, Indian weather and climate is, in general, inversely related to sunspots. However, the areal extent of floods in India seems to expand and contract in phase with the Hale double sunspot cycle, suggesting that the flood rhythm is in some manner controlled by long-term solar activity related to solar magnetic effects. All the evidences of solar influences on weather and climate may have practical implications in improving long-range forecasting of weather and climate, once the physical coupling mechanisms and their modification by other factors are clearly understood. Some of the promising plausible physical mechanisms for explaining solar effects on weather and climate are also discussed. 相似文献
10.
陕西省地质灾害-气象预报预警系统研制及应用 总被引：5，自引：0，他引：5
为了提高地质灾害-气象预报预警工作的自动化程度和产品的质量,文章从计算机系统制作的角度探讨了地质灾害-气象预报预警的方法,论述了陕西省地质灾害-气象预报预警系统的运行环境、软件功能、空间数据库、模型方法等内容,并介绍了陕西省汛期地质灾害-气象预报预警的应用实例。 相似文献
11.
《Comptes Rendus Geoscience》2005,337(1-2):203-217
Advances in flood forecasting have been constrained by the difficulty of estimating rainfall continuously over space, for catchment-, national- and continental-scale areas. This has had a concomitant impact on the choice of appropriate model formulations for given flood-forecasting applications. Whilst weather radar used in combination with raingauges – and extended to utilise satellite remote-sensing and numerical weather prediction models – have offered the prospect of progress, there have been significant problems to be overcome. These problems have curtailed the development and adoption of more complete distributed model formulations that aim to increase forecast accuracy. Advanced systems for weather radar display and processing, and for flood forecast construction, are now available to ease the task of implementation. Applications requiring complex networks of models to make forecasts at many locations can be undertaken without new code development and be readily revised to take account of changing requirements. These systems make use of forecast-updating procedures that assimilate data from telemetry networks to improve flood forecast performance, at the same time coping with the possibility of data loss. Flood forecasting systems that integrate rainfall monitoring and forecasting with flood forecasting and warning are now operational in many areas. Present practice in flood modelling and forecast updating is outlined from a UK perspective. Challenges for improvement are identified, particularly against a background of greater access to spatial datasets on terrain, soils, geology, land-cover, and weather variables. Representing the effective runoff production and translation processes operating at a given grid or catchment scale may prove key to improved flood simulation, and robust application to ungauged basins through physics-based linkages with these spatial datasets. The need to embrace uncertainty in flood-warning decision-making is seen as a major challenge for the future. To cite this article: R.J. Moore et al., C. R. Geoscience 337 (2005). 相似文献
12.
In recent decades, population growth associated with unplanned urban occupation has increased the vulnerability of the Brazilian population to natural disasters. In susceptible regions, early flood forecasting is essential for risk management. Still, in Brazil, most flood forecast and warning systems are based either on simplified models of flood wave propagation through the drainage network or on stochastic models. This paper presents a methodology for flood forecasting aiming to an operational warning system that proposes to increase the lead time of a warning through the use of an ensemble of meteorological forecasts. The chosen configuration was chosen so it would be feasible for an operational flood forecast and risk management. The methodology was applied to the flood forecast for the Itajaí-Açu River basin, a region which comprises a drainage area of approximately 15,500 km2 in the state of Santa Catarina, Brazil, historically affected by floods. Ensemble weather forecasts were used as input to the MHD-INPE hydrological model, and the performance of the methodology was assessed through statistical indicators. Results suggest that flood warnings can be issued up to 48 h in advance, with a low rate of false warnings. Streamflow forecasting through the use of hydrological ensemble prediction systems is still scarce in Brazil. To the best of our knowledge, this is the first time this methodology aiming to an operational flood risk management system has been tested in Brazil. 相似文献
13.
以福建金溪池潭水库流域为例,采用TIGGE数据中心的ECMWF、UKMO、NCEP等7种模式控制预报产品驱动新安江模型,开展径流集合预报。通过集合挑选、多模式集成前处理以及基于BMA模型的后处理等过程,探讨不同处理方案和初始集合质量对气象水文耦合径流预报精度及不确定性的影响。结果表明,不同的处理方案均能有效提高径流预报的精度和稳定性,同时进行前处理和后处理能从降低误差输入和控制误差输出两方面减小预报误差,相对于其他方案表现更好。初始集合质量对气象水文耦合径流集合预报有一定影响,但前处理或后处理对预报误差的有效控制使得该影响并不显著。总体而言,前处理和后处理过程是提高气象水文耦合径流预报准确性和可靠性必不可少的环节,应予以重视。 相似文献
14.
陆面作为大气运动的下边界,通过动量、热量及物质交换与大气发生复杂的相互作用。陆面过程被认为是影响天气气候的关键过程之一。关于陆面过程对气候的影响已经开展了大量较为深入的研究,相比之下,针对陆面过程对天气的影响研究并没有受到足够的重视。近年来,陆面过程与天气研究也开始受到了越来越多的关注。本文从陆面基本要素、下垫面构成、陆面诱发的局地环流3个方面,回顾了土壤湿度、地形、土地利用、山谷-平原环流等要素和过程对强对流、暴雨、台风、高温热浪等天气事件影响研究的相关进展,以期为今后的研究提供参考。需要指出,尽管此方面的研究已取得了一定进展,但关于陆面过程对天气,尤其是极端(高影响)天气的影响及机制还有待深入研究,进而从陆面过程的角度来理解重要天气形成、发生和发展的机理,从而为数值模式发展和天气预报业务提供更有力的科学支撑。 相似文献
15.
Natural Hazards - The frequency of extreme weather events has increased in recent decades due to climate change, and the demand for both more accurate weather forecasts and early warnings surges in... 相似文献
16.
17.
多普勒雷达图像在地质灾害气象预警中的应用——以湖南省新邵县“2005．05．31”特大地质灾害气象预警为例 总被引：1，自引：0，他引：1
本文介绍了湖南地质灾害概况,通过对暴雨诱发地质灾害的机理分析和多普勒雷达系统监测暴雨的可能性分析,选取地质灾害频发的湖南省作为典型研究区,通过多普勒雷达图像地质灾害气象反演分析和灾害识别研究,精确地预报了湖南省新邵县“2005．05．31”特大地质灾害,论证多普勒雷达是监测突发性地质灾害的有效手段。 相似文献
18.
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
19.
Real-time storm detection and weather forecast activation through data mining and events processing 总被引：1，自引：0，他引：1
Xiang Li Beth Plale Nithya Vijayakumar Rahul Ramachandran Sara Graves Helen Conover 《Earth Science Informatics》2008,1(2):49-57
Each year across the USA, destructive weather events disrupt transportation and commerce, resulting in both loss of lives
and property. Mitigating the impacts of such severe events requires innovative new software tools and cyberinfrastructure
through which scientists can monitor data for specific severe weather events such as thunderstorms and launch focused modeling
computations for prediction and forecasts of these evolving weather events. Bringing about a paradigm shift in meteorology
research and education through advances in cyberinfrastructure is one of the key research objectives of the Linked Environments
for Atmospheric Discovery (LEAD) project, a large-scale, interdisciplinary NSF funded project spanning ten institutions. In
this paper we address the challenges of making cyberinfrastructure frameworks responsive to real-time conditions in the physical
environment driven by the use cases in mesoscale meteorology. The contribution of the research is two-fold: on the cyberinfrastructure
side, we propose a model for bridging between the physical environment and e-Science1 workflow systems, specifically through events processing systems, and provide a proof of concept implementation of that model
in the context of the LEAD cyberinfrastructure. On the algorithmic side, we propose efficient stream mining algorithms that
can be carried out on a continuous basis in real time over large volumes of observational data.
1 e-Science is used to describe computationally intensive science that is typically carried out in highly distributed network 相似文献
20.
The paper intends to present the development of the extended weather research forecasting data assimilation (WRFDA) system in the framework of the non-hydrostatic mesoscale model core of weather research forecasting system (WRF-NMM), as an imperative aspect of numerical modeling studies. Though originally the WRFDA provides improved initial conditions for advanced research WRF, we have successfully developed a unified WRFDA utility that can be used by the WRF-NMM core, as well. After critical evaluation, it has been strategized to develop a code to merge WRFDA framework and WRF-NMM output. In this paper, we have provided a few selected implementations and initial results through single observation test, and background error statistics like eigenvalues, eigenvector and length scale among others, which showcase the successful development of extended WRFDA code for WRF-NMM model. Furthermore, the extended WRFDA system is applied for the forecast of three severe cyclonic storms: Nargis (27 April–3 May 2008), Aila (23–26 May 2009) and Jal (4–8 November 2010) formed over the Bay of Bengal. Model results are compared and contrasted within the analysis fields and later on with high-resolution model forecasts. The mean initial position error is reduced by 33% with WRFDA as compared to GFS analysis. The vector displacement errors in track forecast are reduced by 33, 31, 30 and 20% to 24, 48, 72 and 96 hr forecasts respectively, in data assimilation experiments as compared to control run. The model diagnostics indicates successful implementation of WRFDA within the WRF-NMM system. 相似文献