A Model Output Machine Learning Method for Grid Temperature Forecasts in the Beijing Area     

Haochen LI  Chen YU  Jiangjiang XIA  Yingchun WANG  Jiang ZHU  Pingwen ZHANG 《大气科学进展》2019,36(10):1156-1170

In this paper, the model output machine learning (MOML) method is proposed for simulating weather consultation, which can improve the forecast results of numerical weather prediction (NWP). During weather consultation, the forecasters obtain the final results by combining the observations with the NWP results and giving opinions based on their experience. It is obvious that using a suitable post-processing algorithm for simulating weather consultation is an interesting and important topic. MOML is a post-processing method based on machine learning, which matches NWP forecasts against observations through a regression function. By adopting different feature engineering of datasets and training periods, the observational and model data can be processed into the corresponding training set and test set. The MOML regression function uses an existing machine learning algorithm with the processed dataset to revise the output of NWP models combined with the observations, so as to improve the results of weather forecasts. To test the new approach for grid temperature forecasts, the 2-m surface air temperature in the Beijing area from the ECMWF model is used. MOML with different feature engineering is compared against the ECMWF model and modified model output statistics (MOS) method. MOML shows a better numerical performance than the ECMWF model and MOS, especially for winter. The results of MOML with a linear algorithm, running training period, and dataset using spatial interpolation ideas, are better than others when the forecast time is within a few days. The results of MOML with the Random Forest algorithm, year-round training period, and dataset containing surrounding gridpoint information, are better when the forecast time is longer.  相似文献   

一种新的集合预报权重平均方法   总被引：6，自引：0，他引：6       下载免费PDF全文

段明铿  王盘兴 《应用气象学报》2006,17(4):488-493

提出了一种新的考虑权重的集合预报成员平均方法。使用气候等概率区间来对集合成员进行分组, 并根据气候等概率区间的大小及其中的成员数, 对集合成员的权重进行调整, 得到了一种改进的集合平均预报结果。检验表明, 它可以进一步提高集合平均预报的效果。相对于提高模式分辨率或发展庞大的集合预报系统, 这种方法的效果是显著的。  相似文献   

Wave measurement and modeling in Chesapeake Bay   总被引：4，自引：0，他引：4  

Weiqi Lin  Lawrence P. Sanford  Steven E. Suttles 《Continental Shelf Research》2002,22(18-19)

Three recently measured wind and wave data sets in the northern part of Chesapeake Bay (CB) are presented. Two of the three data sets were collected in late 1995. The third one was collected in July of 1998. The analyzed wind and wave data show that waves were dominated by locally generated, fetch limited young wind seas. Significant wave heights were highly correlated to the local driving wind speeds and the response time of the waves to the winds was about 1 h. We also tested two very different numerical wave models, Simulation of WAves Nearshore (SWAN) and Great Lakes Environmental Research Laboratory (GLERL), to hind-cast the wave conditions against the data sets. Time series model–data comparisons made using SWAN and GLERL showed that both models behaved well in response to a suddenly changing wind. In general, both SWAN and GLERL over-predicted significant wave height; SWAN over-predicted more than GLERL did. SWAN had a larger scatter index and a smaller correlation coefficient for wave height than GLERL had. In addition, both models slightly under-predicted the peak period with a fairly large scatter and low correlation coefficient. SWAN predicted mean wave direction better than GLERL did. Directional wave spectral comparisons between SWAN predictions and the data support these statistical comparisons. The GLERL model was much more computationally efficient for wind wave forecasts in CB. SWAN and GLERL predicted different wave height field distributions for the same winds in deeper water areas of the Bay where data were not available, however. These differences are as yet unresolved.  相似文献   

北京地区夏季降水概率预报业务应用研究   总被引：8，自引：2，他引：8  

周兵  陆晨  周小平 《气象》1996,22(1):3-6

作者分析了降水概率预报的基本特征，在北京中尺度数值预报模式（ＢＭＮＦＭ）的基础上应用事件概率回归估计（ＲＥＥＰ）方法，建立北京地区夏季两个量级（≥０．１ｍｍ和≥１０．０ｍｍ）的降水概率预报方程，并结合最新天气观测资料和预报员知识订正客观预报结果。应用Ｂ评分，Ｂｓ评分和Ｂｉａｓ方法对主观降水概率预报和客观降水概率预报进行评估。  相似文献   

NUMERICAL ANALYSIS OF THE DIFFERENCES IN DIFFUSION BETWEEN p－SURFACE AND σ－SURFACE     

阎敬华  薛纪善 《热带气象学报(英文版)》1995,1(1):98-110

Dimensional analysis and reduction are done to two existing schemes of 4th-order linear horizontal diffusion, and detailed control experiments between them are made using a topographyincluded mesoscale model. Horizontal diffusion is calculated on the or surface in one (known as Scheme A afterwards ), and on the p-surface in another (Scheme B). Experiments show that differences are small in smooth-terrain areas and very large in steep mountain areas, with the 24h rainfall prediction deviating by 50 mm between forecasts of the two sChemes. The reason may be that temperature and humidity are falsely diffused in Scheme A, which causes abnormal temperature and humidity, and results in the anomalies of the unstable layer and convective processes. In addition, Scheme A could also bring about circulation anomalies which assumingly have direct link to the convective anomalies in the scheme. Furthermore, perturbation may also affect surrounding areas by wave-like propagation such that precipitation anomalies may occur in the area. The analysis indicate that Scheme B is necessary and feasible for it minimizes diffusion-involved forecast abnormality in steep mountains and areas around.  相似文献   

大气科学的世纪进展与未来展望   总被引：11，自引：2，他引：9  

张大林 《气象学报》2005,63(5):812-824

今天的大气科学已从20世纪初经验的阐述转变为既有理论基础又有客观定量化的一门数理学科,其发展步伐在近50年来不断加快。文章回顾了近百年来大气科学在探测、数值天气预报和气候研究3方面所取得的主要成就,并对大气科学在21世纪的潜在发展作一展望。大气探测、计算能力和信息输送方面的技术进步无疑是近代和未来大气科学迅速发展的巨大动力。这些技术进步促使数值模式分辨率在不断提高,越来越多的实测和卫星等遥感资料在通过反演和同化进入模式初始条件和全球气象分析场,模式物理过程和参数化逐步趋向现实,从而使全球和区域数值预报水平持续提高。同时对大量观测资料的统计分析和许多气候子系统耦合模式的若干试验,大大提高了对造成气候变化和影响的物理、动力机制的认识;特别是对全球气温变暖,其中人类活动的影响,以及ENSO的发生、发展和消亡的机制和过程的认识。近期数值天气预报则趋向于模式发展的统一、预报时效的增加和对有足够成员且有代表性的集合预报的日益重视。气候研究将致力于减少各物理和化学过程参数化、分辨率等因素在模式中的不确定性,逐步达到跨月、季节直至年代际气候变化的合理预测。可以预言在不久的将来,地球-空间系统各变量的观测和预报将逐步数字化、自动化,人们可提前3~5 d得知灾害性天气发生时间和地点的概率,人工影响天气等学科在21世纪将会有突破。同时,可以看到世界各国共同协作建立地球-空间综合观测系统,发展能“包罗万象”的地球-空间-减灾的统一模式。然后综合利用大量观测和模式资料,及时掌握地球-空间系统中的各尺度变化规律,以确保人类社会的持续发展。  相似文献   

基于WebGIS和Flex的青岛市海洋气象服务平台的研发     

王会蒙  孙勇  季民  孙正  王杰 《地理信息世界》2015,(3)

为进一步完善和发展青岛海洋气象预报工作,构建了青岛市海洋气象信息预报服务平台。该平台以Flex和Web GIS技术为支撑,依托丰富的气象服务产品,综合运用GIS服务器的空间数据处理能力和GIS的专题地图显示功能,编辑与分析多种与海洋相关的气象产品的时空要素特征。平台实现了多种海洋气象实况要素与地理信息的叠加、近海区域的天气预报与预警信息、海洋生态与船舶信息、台风实况路径查询、卫星和雷达图的动态显示等功能,提高了青岛市海洋气象综合观测、预警服务能力,为促进海洋经济结构的调整和优化提供气象保障。  相似文献   

中央气象台天气预报服务业务的过去、现在和将来     

端义宏 《气象》2010,36(7):5-11

中央气象台成立到今天,已经走过60年的风雨历程。文章回顾中央气象台天气预报业务的发展历程、总结中央气象台天气预报业务的现有成就、展望中央气象台预报业务的未来,使我们更加坚定预报业务发展的信心。  相似文献   

甘肃省黑河干流中游地区泉水动态特征及预报   总被引：3，自引：1，他引：2  

丁宏伟  徐大录  赵玉苹  杨建军 《干旱区地理》2009,32(5)

在简述区域水文地质条件的基础上,依据1986-2007年泉水流量系列观测资料,详细论述了区内下降泉、上升泉的年内和多年动态变化特征,对比分析了1967年、1984年、2006年测区各泉域泉水量和泉水总量的时空分布规律和变化特征。利用已有的潜水二维流水量数学模型,推递并建立了利用泉点周围节点水头(水位)预报泉水流量的数学模型,并对测区泉水总量未来15年的变化趋势进行了预报。结果表明,在现状节水灌溉条件下,由于出山径流量的增加和地下水开采量的减少,未来黑河干流中游地区的泉水资源基本处于稳定状态。  相似文献   

Seasonal drought predictability in Portugal using statistical–dynamical techniques     

《Physics and Chemistry of the Earth》2016

Atmospheric forecasting and predictability are important to promote adaption and mitigation measures in order to minimize drought impacts. This study estimates hybrid (statistical–dynamical) long-range forecasts of the regional drought index SPI (3-months) over homogeneous regions from mainland Portugal, based on forecasts from the UKMO operational forecasting system, with lead-times up to 6 months. ERA-Interim reanalysis data is used for the purpose of building a set of SPI predictors integrating recent past information prior to the forecast launching. Then, the advantage of combining predictors with both dynamical and statistical background in the prediction of drought conditions at different lags is evaluated. A two-step hybridization procedure is performed, in which both forecasted and observed 500 hPa geopotential height fields are subjected to a PCA in order to use forecasted PCs and persistent PCs as predictors. A second hybridization step consists on a statistical/hybrid downscaling to the regional SPI, based on regression techniques, after the pre-selection of the statistically significant predictors. The SPI forecasts and the added value of combining dynamical and statistical methods are evaluated in cross-validation mode, using the R² and binary event scores. Results are obtained for the four seasons and it was found that winter is the most predictable season, and that most of the predictive power is on the large-scale fields from past observations. The hybridization improves the downscaling based on the forecasted PCs, since they provide complementary information (though modest) beyond that of persistent PCs. These findings provide clues about the predictability of the SPI, particularly in Portugal, and may contribute to the predictability of crops yields and to some guidance on users (such as farmers) decision making process.  相似文献