2010年国内外3种数值预报在东北地区的预报检验   总被引：4，自引：0，他引：4       下载免费PDF全文

张宁娜  黄阁  吴曼丽  梁寒  盛永  刘桂英 《气象与环境学报》2012,28(2):28-34

对中国国家气象中心T639数值预报、德国降水预报和欧洲中心（ECMWF）数值预报中对中国东北地区的降水、温度和环流模式的预报结果,分别进行检验。结果表明：降水预报中,德国降水预报对中国东北地区的晴雨预报、一般性降水预报效果较好,但T639数值预报的漏报率明显低于德国降水预报,而T639数值预报中24-120 h暴雨预报的TS评分明显高于德国降水预报。温度预报中,T639数值预报对中国东北地区温度预报72 h内基本可用;欧洲中心（ECMWF）数值预报在96 h内效果较好。对于24 h的温度预报准确率,T639数值预报稍高于ECMWF数值预报结果。环流模式方面：48h内T639预报效果好于ECMWF,72 h以后ECMWF预报效果好于T639。  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   

Skill Assessment of Copernicus Climate Change Service Seasonal Ensemble Precipitation Forecasts over Iran     

Masoud NOBAKHT  Bahram SAGHAFIAN  Saleh AMINYAVARI 《大气科学进展》2021,38(3):504-521

Medium to long-term precipitation forecasting plays a pivotal role in water resource management and development of warning systems.Recently,the Copernicus Climate Change Service(C3S)database has been releasing monthly forecasts for lead times of up to three months for public use.This study evaluated the ensemble forecasts of three C3S models over the period 1993-2017 in Iran’s eight classified precipitation clusters for one-to three-month lead times.Probabilistic and non-probabilistic criteria were used for evaluation.Furthermore,the skill of selected models was analyzed in dry and wet periods in different precipitation clusters.The results indicated that the models performed best in western precipitation clusters,while in the northern humid cluster the models had negative skill scores.All models were better at forecasting upper-tercile events in dry seasons and lower-tercile events in wet seasons.Moreover,with increasing lead time,the forecast skill of the models worsened.In terms of forecasting in dry and wet years,the forecasts of the models were generally close to observations,albeit they underestimated several severe dry periods and overestimated a few wet periods.Moreover,the multi-model forecasts generated via multivariate regression of the forecasts of the three models yielded better results compared with those of individual models.In general,the ECMWF and UKMO models were found to be appropriate for one-month-ahead precipitation forecasting in most clusters of Iran.For the clusters considered in Iran and for the long-range system versions considered,the Météo France model had lower skill than the other models.  相似文献   

Satellite-based Observational Study of the Tibetan Plateau Vortex:Features of Deep Convective Cloud Tops     

Yi-Xuan SHOU  Feng LU  Hui LIU  Peng CUI  Shaowen SHOU  Jian LIU 《大气科学进展》2019,36(2):189-205

In this study, an east-moving Tibetan Plateau vortex (TPV) is analyzed by using the ERA-5 reanalysis and multi-source satellite data, including FengYun-2E, Aqua/MODIS and CALIPSO. The objective is to demonstrate: (i) the usefulness of multi-spectral satellite observations in understanding the evolution of a TPV and the associated rainfall, and (ii) the potential significance of cloud-top quantitative information in improving Southwest China weather forecasts. Results in this study show that the heavy rainfall is caused by the coupling of an east-moving TPV and some low-level weather systems [a Plateau shear line and a Southwest Vortex (SWV)], wherein the TPV is a key component. During the TPV's life cycle, the rainfall and vortex intensity maintain a significant positive correlation with the convective cloud-top fraction and height within a 2.5° radius away from its center. Moreover, its growth is found to be quite sensitive to the cloud phases and particle sizes. In the mature stage when the TPV is coupled with an SWV, an increase of small ice crystal particles and appearance of ring- and U/V-shaped cold cloud-top structures can be seen as the signature of a stronger convection and rainfall enhancement within the TPV. A tropopause folding caused by ageostrophic flows at the upper level may be a key factor in the formation of ring-shaped and U/V-shaped cloud-top structures. Based on these results, we believe that the supplementary quantitative information of an east-moving TPV cloud top collected by multi-spectral satellite observations could help to improve Southwest China short-range/nowcasting weather forecasts.  相似文献   

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   

A Spatiotemporal Interactive Processing Bias Correction Method for Operational Ocean Wave Forecasts     

AI Bo  YU Mengchao  GUO Jingtian  ZHANG Wei  JIANG Tao  LIU Aichao  WEN Lianjie  LI Wenbo 《中国海洋大学学报(英文版)》2022,21(2):277-290

Numerical models and correct predictions are important for marine forecasting,but the forecasting results are often unable to satisfy the requirements of operational wave forecasting.Because bias between the predictions of numerical models and the actual sea state has been observed,predictions can only be released after correction by forecasters.This paper proposes a spati-otemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and release of operational ocean wave forecasting products.The proposed method combines the advantages of numerical models and Forecast Discussion;specifically,it integrates subjective and objective information to achieve interactive spatiotemporal correc-tions for numerical prediction.The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judg-ment of forecasters to achieve numerical prediction accuracy.The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis,thereby achieving highly efficient correction for multi-time forecasting fields.In this paper,the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis.Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states.The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently.  相似文献   

东亚地区冬季地面气温延伸期概率预报研究   总被引：5，自引：4，他引：1       下载免费PDF全文

吉璐莹  智协飞  朱寿鹏 《大气科学学报》2017,40(3):346-355

利用TIGGE资料中的ECMWF、NCEP、UKMO三个中心集合预报系统以及由此构成的多中心集合预报系统所提供的地面2 m气温10~15 d延伸期集合预报产品,建立贝叶斯模式平均(Bayesian Model Averaging,BMA)概率预报模型,对东亚地区冬季地面气温进行延伸期概率预报研究。采用距平相关系数、均方根误差、布莱尔评分、等级概率评分等指标分别对BMA确定性结果与概率预报进行评估。结果表明,BMA方法明显地改进了原始集合预报结果,预报技巧优于原始集合预报,且多中心BMA预报优于单中心BMA预报,最佳滑动训练期取35 d。BMA预报为气温的延伸期概率预报提供了更合理的概率分布,定量描述了预报的不确定性。  相似文献   

国家级强对流天气分类预报检验分析   总被引：16，自引：7，他引：9  

唐文苑  周庆亮  刘鑫华  朱文剑  毛旭 《气象》2017,43(1):67-76

预报产品的客观检验是记录、考量各种预报业务质量,促进预报水平提高的重要手段,也是整个天气预报过程中的重要环节。本文采用"点对面"Threat Score(TS)、漏报率、空报率等客观指标首次对2010—2015年4—9月国家级强对流天气预报中雷暴、短时强降雨以及雷暴大风和冰雹等分类预报进行了检验。同时,本文也对强对流天气落区分类预报客观检验存在的问题以及未来发展进行了讨论。检验结果表明:过去6年间,6~24 h时效预报,雷暴TS评分为0.22~0.34,短时强降水为0.18~0.24,雷暴大风和冰雹为0.01~0.07;48、72 h时效预报、雷暴TS评分为0.30~0.40,强对流天气TS评分为0.16~0.23,除雷暴预报TS评分在2012—2013年有所回落外,其他类别的强对流天气预报总体上TS评分呈上升趋势,雷暴大风和冰雹预报评分明显低于其他两个类别。雷暴空报率是漏报率的2~3倍,短时强降水漏报率与空报率接近,雷暴大风和冰雹天气漏报率和空报率都在0.8以上。与美国风暴预报中心(SPC)2000—2010年定期发布的1 d对流展望产品检验结果比较,强天气预报中心雷暴和短时强降水落区预报TS评分较高,雷暴大风和冰雹评分较低。典型个例预报检验结果表明,系统性大范围的风雹天气可预报性较强,评分要显著高于平均预报水平;对于非过程性的、分散的风雹天气,预报难度大,TS评分低。  相似文献   

Simulating the value of El Niño forecasts for the Panama Canal     

Nicholas E. Graham  Konstantine P. Georgakakos  Carlos Vargas  Modesto Echevers 《Advances in water resources》2006

The Panama Canal relies on rain-fed streamflow into Gatun Lake, the canal’s primary storage facility, for operations—principally ship passage and hydropower generation. Precipitation in much of Panama has a strong negative relationship with eastern tropical Pacific sea surface temperature (SST) and this relationship is reflected in Gatun Lake inflows. For example, the correlation coefficient between wet season (July–December) inflow and NINO3 SST is −0.53 over the period 1914–1997. Operational capabilities to predict tropical Pacific SSTs have been demonstrated by several forecast systems during the past decade, and (as we show) such SST forecasts can be used to reduce the uncertainty of estimates of future inflows (compared with climatological expectations). Because substantial reductions in lake inflow negatively impact canal operations, we wondered whether these forecasts of future inflows, coupled with a method for translating that information into effective operational policy, might result in more efficient canal management. A combined simulation/optimization/assessment “virtual” canal system was implemented and exercised using operational El Niño forecasts over the period 1981–1998. The results show the following main points:

(i)

At current demand levels, the canal system is relatively robust (insensitive to flow forecasts) unless flows are substantially reduced (i.e., during El Niño episodes) or forecasts are extremely accurate.  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