首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献,搜索用时 156 毫秒
1.
Using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) implemented at the Korea Meteorological Administration (KMA), the effect of doubling the ensemble size on the performance of ensemble prediction in the warm season was evaluated. Because a finite ensemble size causes sampling error in the full forecast probability distribution function (PDF), ensemble size is closely related to the efficiency of the ensemble prediction system. Prediction capability according to doubling the ensemble size was evaluated by increasing the number of ensembles from 24 to 48 in MOGREPS implemented at the KMA. The initial analysis perturbations generated by the Ensemble Transform Kalman Filter (ETKF) were integrated for 10 days from 22 May to 23 June 2009. Several statistical verification scores were used to measure the accuracy, reliability, and resolution of ensemble probabilistic forecasts for 24 and 48 ensemble member forecasts. Even though the results were not significant, the accuracy of ensemble prediction improved slightly as ensemble size increased, especially for longer forecast times in the Northern Hemisphere. While increasing the number of ensemble members resulted in a slight improvement in resolution as forecast time increased, inconsistent results were obtained for the scores assessing the reliability of ensemble prediction. The overall performance of ensemble prediction in terms of accuracy, resolution, and reliability increased slightly with ensemble size, especially for longer forecast times.  相似文献   

2.
Selecting proper parameterization scheme combinations for a particular application is of great interest to the Weather Research and Forecasting(WRF) model users. This study aims to develop an objective method for identifying a set of scheme combinations to form a multi-physics ensemble suitable for short-range precipitation forecasting in the Greater Beijing area. The ensemble is created by using statistical techniques and some heuristics. An initial sample of 90 scheme combinations was first generated by using Latin hypercube sampling(LHS). Then, after several rounds of screening, a final ensemble of 40 combinations were chosen. The ensemble forecasts generated for both the training and verification cases using these combinations were evaluated based on several verification metrics, including threat score(TS), Brier score(BS), relative operating characteristics(ROC), and ranked probability score(RPS). The results show that TS of the final ensemble improved by 9%–33% over that of the initial ensemble. The reliability was improved for rain ≤ 10 mm day1-, but decreased slightly for rain 10 mm day-1 due to insufficient samples. The resolution remained about the same. The final ensemble forecasts were better than that generated from randomly sampled scheme combinations. These results suggest that the proposed approach is an effective way to select a multi-physics ensemble for generating accurate and reliable forecasts.  相似文献   

3.
Based on a simple coupled Lorenz model, we investigate how to assess a suitable initial perturbation scheme for ensemble forecasting in a multiscale system involving slow dynamics and fast dynamics. Four initial perturbation approaches are used in the ensemble forecasting experiments: the random perturbation(RP), the bred vector(BV), the ensemble transform Kalman filter(ETKF), and the nonlinear local Lyapunov vector(NLLV) methods. Results show that,regardless of the method used, the ensemble ave...  相似文献   

4.
The skill of probability density function (PDF) prediction of summer rainfall over East China using optimal ensemble schemes is evaluated based on the precipitation data from ˉve coupled atmosphere-ocean general circulation models that participate in the ENSEMBLES project. The optimal ensemble scheme in each region is the scheme with the highest skill among the four commonly-used ones: the equally-weighted ensemble (EE), EE for calibrated model-simulations (Cali-EE), the ensemble scheme based on multiple linear regression analysis (MLR), and the Bayesian ensemble scheme (Bayes). The results show that the optimal ensemble scheme is the Bayes in the southern part of East China; the Cali-EE in the Yangtze River valley, the Yangtze-Huaihe River basin, and the central part of northern China; and the MLR in the eastern part of northern China. Their PDF predictions are well calibrated, and are sharper than or have approximately equal interval-width to the climatology prediction. In all regions, these optimal ensemble schemes outperform the climatology prediction, indicating that current commonly-used multi-model ensemble schemes are able to produce skillful PDF prediction of summer rainfall over East China, even though more information for other model variables is not derived.  相似文献   

5.
Based on 20 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6), this article explored possible reasons for differences in simulation biases and projected changes in precipitation in northern China among the allmodel ensemble(AMME), “highest-ranked” model ensemble(BMME), and “lowest-ranked” model ensemble(WMME),from the perspective of atmospheric circulations and moisture budgets. The results show that the BMME and AMME reproduce the East Asian winter circulations better than...  相似文献   

6.
郑飞  朱江  王慧 《大气科学进展》2009,26(2):359-372
Based on an intermediate coupled model (ICM), a probabilistic ensemble prediction system (EPS) has been developed. The ensemble Kalman filter (EnKF) data assimilation approach is used for generating the initial ensemble conditions, and a linear, first-order Markov-Chain SST anomaly error model is embedded into the EPS to provide model-error perturbations. In this study, we perform ENSO retrospective forecasts over the 120 year period 1886–2005 using the EPS with 100 ensemble members and with initial conditi...  相似文献   

7.
Two important questions are addressed in this paper using the Global Ensemble Forecast System(GEFS) from the National Centers for Environmental Prediction(NCEP):(1) How many ensemble members are needed to better represent forecast uncertainties with limited computational resources?(2) What is the relative impact on forecast skill of increasing model resolution and ensemble size? Two-month experiments at T126L28 resolution were used to test the impact of varying the ensemble size from 5 to 80 members at the 500hPa geopotential height.Results indicate that increasing the ensemble size leads to significant improvements in the performance for all forecast ranges when measured by probabilistic metrics,but these improvements are not significant beyond 20 members for long forecast ranges when measured by deterministic metrics.An ensemble of 20 to 30 members is the most effective configuration of ensemble sizes by quantifying the tradeoff between ensemble performance and the cost of computational resources.Two representative configurations of the GEFS-the T126L28 model with 70 members and the T190L28 model with 20 members,which have equivalent computing costs-were compared.Results confirm that,for the NCEP GEFS,increasing the model resolution is more(less) beneficial than increasing the ensemble size for a short(long) forecast range.  相似文献   

8.
Early and effective flood warning is essential for reducing loss of life and economic damage.Three global ensemble weather prediction systems of the China Meteorological Administration (CMA),the Europe...  相似文献   

9.
Four sets of climate change simulations at grid spacing of 50 km were conducted over East Asia with two regional climate models driven at the lateral boundaries by two global models for the period 1981–2050. The focus of the study was on the ensemble projection of climate change in the mid-21 st century(2031–50) over China. Validation of each simulation and the ensemble average showed good performances of the models overall, as well as advantages of the ensemble in reproducing present day(1981–2000) December–February(DJF), June–August(JJA), and annual(ANN) mean temperature and precipitation. Significant warming was projected for the mid-21 st century, with larger values of temperature increase found in the northern part of China and in the cold seasons. The ensemble average changes of precipitation in DJF, JJA, and ANN were determined, and the uncertainties of the projected changes analyzed based on the consistencies of the simulations. It was concluded that the largest uncertainties in precipitation projection are in eastern China during the summer season(monsoon precipitation).  相似文献   

10.
The initial ensemble perturbations for an ensemble data assimilation system are expected to reasonably sample model uncertainty at the time of analysis to further reduce analysis uncertainty. Therefore, the careful choice of an initial ensemble perturbation method that dynamically cycles ensemble perturbations is required for the optimal performance of the system. Based on the multivariate empirical orthogonal function (MEOF) method, a new ensemble initialization scheme is developed to generate balanced initial perturbations for the ensemble Kalman filter (EnKF) data assimilation, with a reasonable consideration of the physical relationships between different model variables. The scheme is applied in assimilation experiments with a global spectral atmospheric model and with real observations. The proposed perturbation method is compared to the commonly used method of spatially-correlated random perturbations. The comparisons show that the model uncertainties prior to the first analysis time, which are forecasted from the balanced ensemble initial fields, maintain a much more reasonable spread and a more accurate forecast error covariance than those from the randomly perturbed initial fields. The analysis results are further improved by the balanced ensemble initialization scheme due to more accurate background information. Also, a 20-day continuous assimilation experiment shows that the ensemble spreads for each model variable are still retained in reasonable ranges without considering additional perturbations or inflations during the assimilation cycles, while the ensemble spreads from the randomly perturbed initialization scheme decrease and collapse rapidly.  相似文献   

11.
北半球中纬度地区地面气温的超级集合预报   总被引:25,自引:7,他引:18       下载免费PDF全文
基于TIGGE资料中的ECMWF、JMA、NCEP和UKMO四个中心2007年6月1日-8月31日北半球中纬度地区地面气温24~168 h集合预报资料,分别利用固定训练期超级集合(SUP, Superensemble)和滑动训练期超级集合(R-SUP, Running Training Period Superensemble )对2007年8月8-31日预报期24 d进行超级集合预报试验.采用均方根误差对预报结果进行检验评估,比较了两种超级集合方法与最好的单个中心模式预报、多模式集合平均的预报效果.结果表明,SUP预报有效降低了预报误差,24~144 h的预报效果优于多模式集合平均(EMN, Ensemble Mean)和最好的单个中心预报,168 h的预报效果略差于EMN.R-SUP预报进一步改善了预报效果.对于24~168 h的预报,R-SUP预报效果都要优于EMN.尤其对于168 h的预报,R-SUP改进了预报效果,优于EMN.  相似文献   

12.
基于TIGGE资料的地面气温多模式超级集合预报   总被引:13,自引:3,他引:10       下载免费PDF全文
基于TIGGE资料, 采用均方根误差分别对欧洲中期天气预报中心、日本气象厅、美国国家环境预报中心和英国气象局4个中心集合预报的地面气温场集合平均结果进行检验评估, 比较各中心地面气温的预报效果。并利用超级集合、多模式集合平均和消除偏差集合平均3种方法对4个中心的地面气温预报进行集成, 同时对预报结果进行分析。结果表明: 2007年夏季日本气象厅与欧洲中期天气预报中心在北半球大部分地区预报效果最好, 各中心在不同地区预报效果不同。超级集合与消除偏差集合平均降低了预报误差, 预报效果优于最好的单个中心预报和多模式集合平均。对于较长的预报时效, 消除偏差集合平均表现出了更好的预报性能。  相似文献   

13.
Summary ?We evaluate United Kingdom Meteorological Office (UKMO) one-month ensemble forecasts of mean sea-level pressure (MSLP) in the southern hemisphere (SH) to 60° S, with a special focus on their utility near New Zealand (NZ). There are 105 9-member ensembles, at approximately two-week intervals, between 1995 and 1999. Each forecast is averaged over two successive 15-day periods and verified against the NCEP/NCAR reanalysis data set. Compared to climatology, the skill of the ensemble mean is slightly positive in days 1–15, and slightly negative in days 16–30. Skill near NZ is slightly lower than the SH averages. For SH-scale circulation patterns (as seen in the first few principal components), skill is greater than for most individual grid points, but is still negligible or negative in days 16–30. Moderate skill-spread correlations (ρ ≈−0.5) were found for some skill scores. The way that skill varies with season and the Southern Oscillation Index is consistent with other research but not statistically significant for this small data set. Probabilistic forecasts of low and high pressures have skill similar to that of the ensemble mean. The ensemble spread is generally too small, in that the analysis lies within the ensemble less often than the theoretically optimum value of 80% of the time. Measured as a fraction of the natural variability, the spread increases substantially with time and latitude: it is less than 0.5 near the equator in days 1–15, and takes values near 1 only at higher latitudes during days 16–30. The initial sequential structure of the ensembles (a consequence of the use of time lags in their genesis) is still apparent in days 1–15 but has disappeared by days 16–30. Three potential alternatives to the ensemble mean were all found to have less skill than it. Received June 17, 2001; revised July 4, 2002; accepted November 22, 2002 Published online March 17, 2003  相似文献   

14.
Summary Climatological statistics of extreme temperature events over Kenya are established from the analysis of daily and monthly maximum temperatures for a representative station (Nairobi Dagoretti Corner) over the period 1956–1997. The months of June to August were shown to be the coldest with a mean monthly maximum temperature of less than 22 °C. Seasonal (June to August) mean maximum temperature was 21.5 °C. Using this seasonal mean temperature for the period 1967–1997 delineated 1968 as the coldest year in this series and 1983 as the warmest year. Spectral analysis of the seasonal data, for both the coldest and the warmest years, revealed that the major periods were the quasi-biweekly (10 days) and the Intraseasonal Oscillations (23 days). Secondary peaks occurred at periods of 4–6 and 2.5–3.5 days. A temperature threshold of 16.7 °C during July was used to define cold air outbreaks over Nairobi. This threshold temperature of 16.7 °C was obtained from the mean July maximum temperature (20.9 °C) minus two standard deviations. Notable trends include a decrease in the frequency of station-days, between 1956 and 1997, with temperatures less than 16.7 °C during July. Surface pressure patterns indicate that the origin of the cold air is near latitude 25° S and to the east of mainland South Africa. The cold air near 25° S is advected northwards ahead of the surface pressure ridge. Received July 19, 1999 Revised January 11, 2000  相似文献   

15.
Different multimodel ensemble methods are used to forecast precipitations in China, 1998, and their forecast skills are compared with those of individual models. Datasets were obtained from monthly simulations of eight models during the period of January 1979 to December 1998 from the “Climate of the 20th Century Experiment” (20C3M) for the Fourth IPCC Assessment Report. Climate Research Unit (CRU) data were chosen for the observation analysis field. Root mean square (RMS) error and correlation coeffi-cients (R) are used to measure the forecast skills. In addition, superensemble forecasts based on different input data and weights are analyzed. Results show that for original data, superensemble forecasting based on multiple linear regression (MLR) performs best. However, for bias-corrected data, the superensemble based on singular value decomposition (SVD) produces a lower RMS error and a higher R than in the MLR superensemble. It is an interesting result that the SVD superensemble based on bias-corrected data performs better than the MLR superensemble, but that the SVD superensemble based on original data is inferior to the corresponding MLR superensemble. In addition, weights calculated by different data formats are shown to affect the forecast skills of the superensembles. In comparison with the MLR superensemble, a slightly significant effect is present in the SVD superensemble. However, both the SVD and MLR superensembles based on different weight formats outperform the ensemble mean of bias-corrected data.  相似文献   

16.
    
The approach of getting useful information of monthly dynamical prediction from ensemble forecasts is studied. The extended range ensemble forecasts (8 members, the initial perturbations of the lagged average forecast (LAF)(0000, 0600, 1200 and 1800 GMT in two consecutive days) of the 500 hPa height field with the global spectral model (T63L16) from January to May 1997 are provided by the National Climate Center of China. The relationship between the spread of ensemble measured by root–mean–square deviation of ensemble member from ensemble mean and forecast skill (the anomaly correlation or the root–mean–square distance between the ensemble mean forecast and the observation) is significant. The spread of ensemble can evaluate the useful forecast days N for the best estimate of 30 days mean. Thus, a weighted mean approach based on ensemble spread is put forward for monthly dynamical prediction. The anomaly correlation of the weighted monthly mean by the ensemble spread is higher than that of both the arithmetic mean and the linear weighted mean. Better results of the monthly mean circulation and anomaly are obtained from the ensemble spread weighted mean. Supported by the Excellent National State Key Laboratory Project (49823002), the National Key Project ‘Study on Chinese Short-Term Climate Forecast System’ (96-908-02) and IAP Innovation Foundation (8-1308). The data were provided through the National Climate Center of China. The authors wish to thank Ms. Chen Lijuan for her assistance.  相似文献   

17.
Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km2) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.  相似文献   

18.
2009年夏季西太平洋台风路径和强度的多模式集成预报   总被引:6,自引:3,他引:3  
周文友  智协飞 《气象科学》2012,32(5):492-499
基于TIGGE资料中的中国气象局、欧洲中期天气预报中心、日本气象厅和英国气象局等四个中心的2009年5月1日-8月31日台风预报资料,利用多模式集合平均、消除偏差集合平均和加权消除偏差集合平均等方法,对2009年8月1-31日预报期的西太平洋的台风路径和强度(中心气压)进行24~ 72 h预报时效的多模式集成预报,并对0907号台风“天鹅”和0908号台风“莫拉克”进行个例分析.结果表明:各中心对于不同时效的预报,预报技巧有明显差异.消除偏差集合平均与加权消除偏差集合平均显著地减小了预报误差,预报效果优于最好的单个中心预报和多模式集合平均.对于24 ~ 72 h预报,加权消除偏差集合平均方法始终表现出最好的预报性能.  相似文献   

19.
Karachi is the largest city of Pakistan. The temperature change in Karachi is studied in this research by analyzing the time series data of mean maximum temperature (MMxT), mean minimum temperature (MMiT) and mean annual temperature (MAT) from 1947 to 2005 (59 years). Data is analyzed in three parts by running linear regression and by taking anomalies of all time periods: (a) whole period from 1947–2005; (b) phase one 1947–1975 and (c) phase two 1976–2005. During 1947 to 2005 MMxT has increased about 4.6°C, MMiT has no change and MAT has increased 2.25°C. During 1947–1975, MMxT increased 1.9°C, in this period there is − 1.3°C decrease in MMiT and MAT has raised upto 0.3°C. During 1976–2005, the MMxT, MMiT and MAT increased 2.7°C, 1.2°C and 1.95°C, respectively. The analysis shows significantly the role of extreme vulnerability of MMxT in rising the temperature of Karachi than the MMiT.  相似文献   

20.
Summary Climate variations in the Caribbean, largely manifest in rainfall activity, have important consequences for the large-scale water budget, natural vegetation, and land use in the region. The wet and dry seasons will be defined, and the important roles played by the El Ni?o-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) in modulating the rainfall during these seasons will be discussed. The seasonal climate forecasts in this paper are made by 13 state of the art coupled atmosphere-ocean general circulation models (CGCMs) and by the Florida State University Synthetic Superensemble (FSUSSE), whose forecasts are obtained by a weighted combination of the individual CGCM forecasts based on a training period. The success of the models in simulating the observed 1989–2001 climatology of the various forecast parameters will be examined and linked to the models’ success in predicting the seasonal climate for individual years. Seasonal forecasts will be examined for precipitation, sea-surface temperature (SST), 2-meter air temperature, and 850 hPa u- and v-wind components during the period 1989–2001. Evaluation metrics include root mean square (RMS) error and Brier skill score. It will be shown that the FSUSSE is superior to the individual CGCMs and their ensemble mean both in simulating the 1989–2001 climatology for the various parameters and in predicting the seasonal climate of the various parameters for individual years. The seasonal climate forecasts of the FSUSSE and of the ensemble mean of the 13 state of the art CGCMs will be evaluated for years (during the period 1989–2001) that have particular ENSO and NAO signals that are known to influence Caribbean weather, particularly the rainfall. It will be shown that the FSUSSE provides superior forecasts of rainfall, SST, 2-meter air temperature, and 850 hPa u- and v-wind components during dry summers that are modulated by negative SOI and/or positive NAO indices. Such summers have become a feature of a twenty-year pattern of drought in the Caribbean region. The results presented in this paper will show that the FSUSSE is a valuable tool for forecasting rainfall and other atmospheric and oceanic variables during such periods of drought.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号