Statistical Postprocessing of NWP Model Outputs Applied to Maximum and Minimum Temperature Forecasts     

Karel Dejmal 《Studia Geophysica et Geodaetica》2000,44(1):73-83

Statistical postprocessing of NWP model outputs is applied to maximum and minimum temperature forecasts. Two approaches to its application are effected to local short-range weather forecasts of minimum and maximum temperatures: Model Output Statistics and modified Perfect Prognosis. The modified Perfect Prognosis method is restricted to the first step of PP because of the significant difference between the horizontal resolution of the available objective analyses and the NWP model outputs. The modified Perfect Prognosis method uses actual data from the objective analysis related to the forecast period instead of the NWP forecast. The results are compared with a simple statistical prognostic model, which does not utilize the NWP model outputs, and with simple reference methods. The forecast is verified using ground station measurements from stations providing SYNOP reports. The results show that the predictive accuracy of the Model Output Statistics method is not very different from that of the modified Perfect Prognosis method, and both are significantly more accurate than the direct predictions of the NWP model. The results have confirmed that statistical postprocessing is able to make localized predictions even if lowresolution data are used.  相似文献   

MOS based forecast of 6-hourly area precipitation     

Z. Sokol 《Studia Geophysica et Geodaetica》2006,50(1):105-120

A statistical post-processing methodology for application to numerical weather prediction (NWP) model outputs for precipitation forecast is proposed. The post-processing is based on the model output statistics approach. The statistical relationships are described by the multiple linear regression model, which is complemented by an iteration procedure to further correct the regression outputs. Prognostic fields of the ALADIN/LACE (Aire Limitée Adaptation Dynamique Développement InterNational/Limited Area Modelling in Central Europe) NWP model are used for the forecast of 6-hourly areal precipitation amounts at 15 river basins. The NWP model integration starts at 00UTC and forecasts are calculated for lead times of +12, +18, +24 and +30 hours. The post-processing models are developed separately for each lead time and for separate warm (April to September) and cool (October to March) seasons. The forecasts are focused on large precipitation amounts. Using all the combinations, data from four years (1999–2002) are divided into calibration data (3 years), where the models are developed, and verification data. The models are evaluated by examining the root-mean-square error (RMSE), bias, and correlation coefficient (CC) on the verification data samples. The results show that the additional iteration procedure increases the forecast accuracy for a given range of precipitation amounts and simultaneously does not deteriorate the bias, a situation which can arise when negative regression outputs are set to zero. The post-processing method improves the forecast of the NWP model in terms of RMSE and CC. For large precipitation amounts during the summer season, the decrease of RMSE reaches 10% to 20% depending upon the applied method of verification. For the cool season, the decrease is somewhat smaller (7% to 15%).  相似文献   

Integrating hydrometeorological information for rainfall‐runoff modelling by artificial neural networks     

Yen‐Ming Chiang  Fi‐John Chang 《水文研究》2009,23(11):1650-1659

The major purpose of this study is to effectively construct artificial neural networks‐based multistep ahead flood forecasting by using hydrometeorological and numerical weather prediction (NWP) information. To achieve this goal, we first compare three mean areal precipitation forecasts: radar/NWP multisource‐derived forecasts (P_r), NWP precipitation forecasts (P_n), and improved precipitation forecasts (P_m) by merging P_r and P_n. The analysis shows that the accuracy of P_m is higher than that of P_r and P_n. The analysis also indicates that the NWP precipitation forecasts do provide relative effectiveness to the merging procedure, particularly for forecast lead time of 4–6 h. In sum, the merged products performed well and captured the main tendency of rainfall pattern. Subsequently, a recurrent neural network (RNN)‐based multistep ahead flood forecasting techniques is produced by feeding in the merged precipitation. The evaluation of 1–6‐h flood forecasting schemes strongly shows that the proposed hydrological model provides accurate and stable flood forecasts in comparison with a conventional case, and significantly improves the peak flow forecasts and the time‐lag problem. An important finding is the hydrologic model responses which do not seem to be sensitive to precipitation predictions in lead times of 1–3 h, whereas the runoff forecasts are highly dependent on predicted precipitation information for longer lead times (4–6 h). Overall, the results demonstrate that accurate and consistent multistep ahead flood forecasting can be obtained by integrating predicted precipitation information into ANNs modelling. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

A New Integrated Weighted Model in SNOW-V10: Verification of Categorical Variables     

Laura X. Huang  George A. Isaac  Grant Sheng 《Pure and Applied Geophysics》2014,171(1-2):289-302

This paper presents the verification results for nowcasts of seven categorical variables from an integrated weighted model (INTW) and the underlying numerical weather prediction (NWP) models. Nowcasting, or short range forecasting (0–6 h), over complex terrain with sufficient accuracy is highly desirable but a very challenging task. A weighting, evaluation, bias correction and integration system (WEBIS) for generating nowcasts by integrating NWP forecasts and high frequency observations was used during the Vancouver 2010 Olympic and Paralympic Winter Games as part of the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) project. Forecast data from Canadian high-resolution deterministic NWP system with three nested grids (at 15-, 2.5- and 1-km horizontal grid-spacing) were selected as background gridded data for generating the integrated nowcasts. Seven forecast variables of temperature, relative humidity, wind speed, wind gust, visibility, ceiling and precipitation rate are treated as categorical variables for verifying the integrated weighted forecasts. By analyzing the verification of forecasts from INTW and the NWP models among 15 sites, the integrated weighted model was found to produce more accurate forecasts for the 7 selected forecast variables, regardless of location. This is based on the multi-categorical Heidke skill scores for the test period 12 February to 21 March 2010.  相似文献   

Quantitative assessment of short‐term rainfall forecasts from radar nowcasts and MM5 forecasts     

Sara Liguori  Miguel Angel Rico‐Ramirez 《水文研究》2012,26(25):3842-3857

Short‐term Quantitative Precipitation Forecasts (QPFs) can be achieved from numerical weather prediction (NWP) models or radar nowcasting, that is the extrapolation of the precipitation at a future time from consecutive radar scans. Hybrid forecasts obtained by merging rainfall forecasts from radar nowcasting and NWP models are potentially more skilful than either radar nowcasts or NWP rainfall forecasts alone. This paper provides an assessment of deterministic and probabilistic high‐resolution QPFs achieved by implementing the Short‐term Ensemble Prediction System developed by the UK Met Office. Both radar nowcasts and hybrid forecasts have been performed. The results show that the performance of both deterministic nowcasts and deterministic hybrid forecasts decreases with increasing rainfall intensity and spatial resolution. The results also show that the blending with the NWP forecasts improves the performance of the forecasting system. Probabilistic hybrid forecasts have been obtained through the modelling of a stochastic noise component to produce a number of equally likely ensemble members, and the comparative assessment of deterministic and probabilistic hybrid forecasts shows that the probabilistic forecasting system is characterised by a higher discrimination accuracy than the deterministic one. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

Skill of 6HR and 12HR thunderstorm forecasts based on assessment of larger-scale information     

Daniela Řezáčová  Zbyněk Sokol 《Studia Geophysica et Geodaetica》1995,39(1):60-73

Summary The relationship between information, contained in aerological data from the European area, and a thunderstorm occurrence in the area of the Czech Republic was investigated with input data from the period of May–September 1989–1991. SYNOP reports from Czech ground stations were utilized to assess event occurrence. TEMP 00UTC and TEMP 12UTC reports from European stations were used to determine potential diagnostic predictors, and the TEMP00 data served as the input data set for the 12hr mesoscale model forecast to gain prognostic predictors. Each of the two diagnostic data sets from 00UTC and 12UTC and of the prognostic data set comprised about 400 predictors/predictand elements. The categorical forecast of thunderstorm occurrence, based on the application of linear regression and a simple version of pattern recognition, is discussed. The critical success index was determined for every type of forecast and used to assess forecast skill.  相似文献   

Nowcasting with INCA During SNOW-V10     

T. Haiden  A. Kann  G. Pistotnik 《Pure and Applied Geophysics》2014,171(1-2):231-242

A Central-European nowcasting system which has been developed for use in mountainous terrain is tested in the Whistler/Vancouver area as part of the SNOW-V10 experiment. The integrated nowcasting through comprehensive analysis system provides hourly updated gridded forecasts of temperature, humidity, and wind, as well as precipitation forecasts which are updated every 15 min. It is based on numerical weather prediction (NWP) output and real-time surface weather station and radar data. Verification of temperature, relative humidity, and wind against surface stations shows that forecast errors are significantly reduced in the nowcasting range compared to those of the driving NWP model. The main contribution to the improvement comes from the implicit bias correction due to use of the latest observations. Relative humidity shows the longest lasting effect, with >50 % reduction of mean absolute error up to +4 h. For temperature and wind speed this percentage is reached after +2 and +3 h, respectively. Two cases of precipitation nowcasting are discussed and verified qualitatively.  相似文献   

A New Integrated Weighted Model in SNOW-V10: Verification of Continuous Variables     

Laura X. Huang  George A. Isaac  Grant Sheng 《Pure and Applied Geophysics》2014,171(1-2):277-287

This paper presents the verification results of nowcasts of four continuous variables generated from an integrated weighted model and underlying Numerical Weather Prediction (NWP) models. Real-time monitoring of fast changing weather conditions and the provision of short term forecasts, or nowcasts, in complex terrain within coastal regions is challenging to do with sufficient accuracy. A recently developed weighting, evaluation, bias correction and integration system was used in the Science of Nowcasting Olympic Weather for Vancouver 2010 project to generate integrated weighted forecasts (INTW) out to 6 h. INTW forecasts were generated with in situ observation data and background gridded forecasting data from Canadian high-resolution deterministic NWP system with three nested grids at 15-, 2.5- and 1-km horizontal grid-spacing configurations. In this paper, the four variables of temperature, relative humidity, wind speed and wind gust are treated as continuous variables for verifying the INTW forecasts. Fifteen sites were selected for the comparison of the model performances. The results of the study show that integrating surface observation data with the NWP forecasts produce better statistical scores than using either the NWP forecasts or an objective analysis of observed data alone. Overall, integrated observation and NWP forecasts improved forecast accuracy for the four continuous variables. The mean absolute errors from the INTW forecasts for the entire test period (12 February to 21 March 2010) are smaller than those from NWP forecasts with three configurations. The INTW is the best and most consistent performer among all models regardless of location and variable analyzed.  相似文献   

Bayesian analyses of seasonal runoff forecasts     

R. Krzysztofowicz  S. Reese 《Stochastic Environmental Research and Risk Assessment (SERRA)》1991,5(4):295-322

Forecasts of seasonal snowmelt runoff volume provide indispensable information for rational decision making by water project operators, irrigation district managers, and farmers in the western United States. Bayesian statistical models and communication frames have been researched in order to enhance the forecast information disseminated to the users, and to characterize forecast skill from the decision maker's point of view. Four products are presented: (i) a Bayesian Processor of Forecasts, which provides a statistical filter for calibrating the forecasts, and a procedure for estimating the posterior probability distribution of the seasonal runoff; (ii) the Bayesian Correlation Score, a new measure of forecast skill, which is related monotonically to theex ante economic value of forecasts for decision making; (iii) a statistical predictor of monthly cumulative runoffs within the snowmelt season, conditional on the total seasonal runoff forecast; and (iv) a framing of the forecast message that conveys the uncertainty associated with the forecast estimates to the users. All analyses are illustrated with numerical examples of forecasts for six gauging stations from the period 1971–1988.  相似文献   

大别山库区降水预报性能评估及应用对策   总被引：1，自引：0，他引：1  

叶金印  张锦堂  黄勇  安晶晶  叶正阳 《湖泊科学》2017,29(6):1528-1537

对降水预报进行性能评估及应用对策研究可以更好地发挥降水预报在水库调度中的决策支持作用.基于大别山库区近10 a汛期(2007—2016年5月1日—9月30日)24~168 h共7个预见期降水预报和地面降水观测资料,采用正确率、TS评分、概率统计、ROC曲线以及CTS等方法评估大别山库区降水预报性能,并以响洪甸水库为重点研究区域分析降水预报在水库调度中的应用对策.结果表明:1)大别山库区各量级的降水预报都有正预报技巧;24~72 h预见期降水预报的TS评分较高且空报率、漏报率也较低,具有较高的预报性能;但96 h及以上预见期降水预报性能明显下降,中雨以上量级空报率、漏报率较大,特别是对大暴雨及其以上量级的降水预报性能显著下降.2)大别山库区预报降水量级与实况降水量级基本符合,预报降水量级大于等于实况降水量级的概率超过75%;虽然降水预报量级上呈现出过度预报的现象,但降水过程预报对水库调度仍有较好的应用价值,应用时要考虑到降水预报量级可能存在偏差.3)转折性天气预报96 h及以上预见期CTS评分较低,但72 h以内预见期的性能明显改进,尤其是24 h预见期CTS评分也提高到了38.2%;水库调度可从长预见期的降水预报获取降水过程及其可能发生转折的信息,根据短预见期的降水预报进行调度方案调整.  相似文献   

An Objective Approach for Prediction of Daily Summer Monsoon Rainfall over Orissa (India) due to Interaction of Mesoscale and Large-scale Synoptic Systems     

M. Mohapatra  U. C. Mohanty 《Pure and Applied Geophysics》2007,164(8-9):1683-1698

Orissa State, a meteorological subdivision of India, lies on the east coast of India close to north Bay of Bengal and to the south of the normal position of the monsoon trough. The monsoon disturbances such as depressions and cyclonic storms mostly develop to the north of 15° N over the Bay of Bengal and move along the monsoon trough. As Orissa lies in the southwest sector of such disturbances, it experiences very heavy rainfall due to the interaction of these systems with mesoscale convection sometimes leading to flood. The orography due to the Eastern Ghat and other hill peaks in Orissa and environs play a significant role in this interaction. The objective of this study is to develop an objective statistical model to predict the occurrence and quantity of precipitation during the next 24 hours over specific locations of Orissa, due to monsoon disturbances over north Bay and adjoining west central Bay of Bengal based on observations to up 0300 UTC of the day. A probability of precipitation (PoP) model has been developed by applying forward stepwise regression with available surface and upper air meteorological parameters observed in and around Orissa in association with monsoon disturbances during the summer monsoon season (June-September). The PoP forecast has been converted into the deterministic occurrence/non-occurrence of precipitation forecast using the critical value of PoP. The parameters selected through stepwise regression have been considered to develop quantitative precipitation forecast (QPF) model using multiple discriminant analysis (MDA) for categorical prediction of precipitation in different ranges such as 0.1–10, 11–25, 26–50, 51–100 and >100 mm if the occurrence of precipitation is predicted by PoP model. All the above models have been developed based on data of summer monsoon seasons of 1980–1994, and data during 1995–1998 have been used for testing the skill of the models. Considering six representative stations for six homogeneous regions in Orissa, the PoP model performs very well with percentages of correct forecast for occurrence/non-occurrence of precipitation being about 96% and 88%, respectively for developmental and independent data. The skill of the QPF model, though relatively less, is reasonable for lower ranges of precipitation. The skill of the model is limited for higher ranges of precipitation. accepted September 2006  相似文献   

Comparing quantitative precipitation forecast methods for prediction of sewer flows in a small urban area     

Alma Schellart  Sara Liguori  Stefan Krämer  Adrian Saul  Miguel A. Rico-Ramirez 《水文科学杂志》2014,59(7):1418-1436

Abstract

Due to the relatively small spatial scale, as well as rapid response, of urban drainage systems, the use of quantitative rainfall forecasts for providing quantitative flow and depth predictions is a challenging task. Such predictions are important when consideration is given to urban pluvial flooding and receiving water quality, and it is worthwhile to investigate the potential for improved forecasting. In this study, three quantitative precipitation forecast methods of increasing complexity were compared and used to create quantitative forecasts of sewer flows 0–3 h ahead in the centre of a small town in the north of England. The HyRaTrac radar nowcast model was employed, as well as two different versions of the more complex STEPS model. The STEPS model was used as a deterministic nowcasting system, and was also blended with the Numerical Weather Prediction (NWP) model MM5 to investigate the potential of increasing forecast lead-times (LTs) using high-resolution NWP. Predictive LTs between 15 and 90 min gave acceptable results, but were a function of the event type. It was concluded that higher resolution rainfall estimation as well as nowcasts are needed for prediction of both local pluvial flooding and combined sewer overflow spill events.