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1.
The present study assesses the forecast skill of the Madden–Julian Oscillation (MJO) observed during the period of DYNAMO (Dynamics of the MJO)/CINDY (Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011) field campaign in the GFS (NCEP Global Forecast System), CFSv2 (NCEP Climate Forecast System version 2) and UH (University of Hawaii) models, and revealed their strength and weakness in forecasting initiation and propagation of the MJO. Overall, the models forecast better the successive MJO which follows the preceding event than that with no preceding event (primary MJO). The common modeling problems include too slow eastward propagation, the Maritime Continent barrier and weak intensity. The forecasting skills of MJO major modes reach 13, 25 and 28 days, respectively, in the GFS atmosphere-only model, the CFSv2 and UH coupled models. An equal-weighted multi-model ensemble with the CFSv2 and UH models reaches 36 days. Air–sea coupling plays an important role for initiation and propagation of the MJO and largely accounts for the skill difference between the GFS and CFSv2. A series of forecasting experiments by forcing UH model with persistent, forecasted and observed daily SST further demonstrate that: (1) air–sea coupling extends MJO skill by about 1 week; (2) atmosphere-only forecasts driven by forecasted daily SST have a similar skill as the coupled forecasts, which suggests that if the high-resolution GFS is forced with CFSv2 forecasted daily SST, its forecast skill can be much higher than its current level as forced with persistent SST; (3) atmosphere-only forecasts driven by observed daily SST reaches beyond 40 days. It is also found that the MJO–TC (Tropical Cyclone) interactions have been much better represented in the UH and CFSv2 models than that in the GFS model. Both the CFSv2 and UH coupled models reasonably well capture the development of westerly wind bursts associated with November 2011 MJO and the cyclogenesis of TC05A in the Indian Ocean with a lead time of 2 weeks. However, the high-resolution GFS atmosphere-only model fails to reproduce the November MJO and the genesis of TC05A at 2 weeks’ lead. This result highlights the necessity to get MJO right in order to ensure skillful extended-range TC forecasting.  相似文献   

2.
The Climate Forecast Systems (CFS) datasets provided by National Centers for Environmental Prediction (NCEP), which cover the time from 1981 to 2008, can be used to forecast atmospheric circulation nine months ahead. Compared with the NCEP datasets, CFS datasets successfully simulate many major features of the Asian monsoon circulation systems and exhibit reasonably high skill in simulating and predicting ENSO events. Based on the CFS forecasting results, a downscaling method of Optimal Subset Regression (OSR) and mean generational function model of multiple variables are used to forecast seasonal precipitation in Guangdong. After statistical analysis tests, sea level pressure, wind and geopotential height field are made predictors. Although the results are unstable in some individual seasons, both the OSR and multivariate mean generational function model can provide good forecasting as operational tests score more than sixty points. CFS datasets are available and updated in real time, as compared with the NCEP dataset. The downscaling forecast method based on the CFS datasets can predict three seasons of seasonal precipitation in Guangdong, enriching traditional statistical methods. However, its forecasting stability needs to be improved.  相似文献   

3.
This study investigates the potential use of a regional climate model in forecasting seasonal tropical cyclone (TC) activity. A modified version of Regional Climate Model Version 3 (RegCM3) is used to examine the ability of the model to simulate TC genesis and landfalling TC tracks for the active TC season in the western North Pacific. In the model, a TC is identified as a vortex satisfying several conditions, including local maximum relative vorticity at 850?hPa with a value?≥450?×?10?6?s?1, and the temperature at 300?hPa being 1°C higher than the average temperature within 15° latitude radius from the TC center. Tracks are traced by following these found vortices. Six-month ensemble (8 members each) simulations are performed for each year from 1982 to 2001 so that the climatology of the model can be compared to the Joint Typhoon Warning Center (JTWC) observed best-track dataset. The 20-year ensemble experiments show that the RegCM3 can be used to simulate vortices with a wind structure and temperature profile similar to those of real TCs. The model also reproduces tracks very similar to those observed with features like genesis in the tropics, recurvature at higher latitudes and landfall/decay. The similarity of the 500-hPa geopotential height patterns between RegCM3 and the European Centre for Medium-Range Weather Forecasts 40 Year Re-analysis (ERA-40) shows that the model can simulate the subtropical high to a large extent. The simulated climatological monthly spatial distributions as well as the interannual variability of TC occurrence are also similar to the JTWC data. These results imply the possibility of producing seasonal forecasts of tropical cyclones using real-time global climate model predictions as boundary conditions for the RegCM3.  相似文献   

4.
The real-time forecasting of monsoon activity over India on extended range time scale (about 3 weeks) is analyzed for the monsoon season of 2012 during June to September (JJAS) by using the outputs from latest (CFSv2 [Climate Forecast System version 2]) and previous version (CFSv1 [Climate Forecast System version 1]) of NCEP coupled modeling system. The skill of monsoon rainfall forecast is found to be much better in CFSv2 than CFSv1. For the country as a whole the correlation coefficient (CC) between weekly observed and forecast rainfall departure was found to be statistically significant (99 % level) at least for 2 weeks (up to 18 days) and also having positive CC during week 3 (days 19–25) in CFSv2. The other skill scores like the mean absolute error (MAE) and the root mean square error (RMSE) also had better performance in CFSv2 compared to that of CFSv1. Over the four homogeneous regions of India the forecast skill is found to be better in CFSv2 with almost all four regions with CC significant at 95 % level up to 2 weeks, whereas the CFSv1 forecast had significant CC only over northwest India during week 1 (days 5–11) forecast. The improvement in CFSv2 was very prominent over central India and northwest India compared to other two regions. On the meteorological subdivision level (India is divided into 36 meteorological subdivisions) the percentage of correct category forecast was found to be much higher than the climatology normal forecast in CFSv2 as well as in CFSv1, with CFSv2 being 8–10 % higher in the category of correct to partially correct (one category out) forecast compared to that in CFSv1. Thus, it is concluded that the latest version of CFS coupled model has higher skill in predicting Indian monsoon rainfall on extended range time scale up to about 25 days.  相似文献   

5.
Recent summers in the United States have been plagued by intense droughts that have caused significant damage to crops and have had a large impact on society. The ability to forecasts such events would allow for preparations that could help reduce the impact on society. Coupled land–atmosphere–ocean models were created to provide such forecasts but there are large uncertainties associated with their predictions. The predictive skill of these models is particularly low during the convective season due to the weaker connections with the oceans and an increase in the land–atmosphere interactions. To better understand the degradation of forecasts skill during the summer months and its connection to the land–atmosphere interactions we analyze National Centers for Environmental Prediction’s Climate Forecast System Version 2 (CFSv2) in terms of its climatological land–atmosphere interactions. To do this we use a recently developed classification of land–atmosphere interactions and other diagnostic variables to compare the reanalysis from the Climate Forecast System (CFSR) with CFSv2 re-forecasts (CFSRR) over the period 1982–2009. Coupling in the CFSRR tends toward the wet coupling regime for most areas east of the Rocky Mountains. Although the specific mechanism driving CFSRR to wet coupling state varies by region, the overall cause is enhanced vegetation rooting depth, originally implemented to address a near-surface warm bias in CFSR. The long-term tendency to wet coupling precludes the forecast model from consistently predicting and maintaining drought over the continental US.  相似文献   

6.
Future changes in tropical cyclone(TC)activity over the western North Pacific(WNP)under the representative concentration pathway RCP4.5 are investigated based on a set of 21 st century climate change simulations over East Asia with the regional climate model RegCM4 driven by five global models.The RegCM4 reproduces the major features of the observed TC activity over the region in the present-day period of 1986-2005,although with the underestimation of the number of TC genesis and intensity.A low number of TCs making landfall over China is also simulated.By the end of the 21st century(2079-98),the annual mean frequency of TC genesis and occurrence is projected to increase over the WNP by16%and 10%,respectively.The increase in frequency of TC occurrence is in good agreement among the simulations,with the largest increase over the ocean surrounding Taiwan Island and to the south of Japan.The TCs tend to be stronger in the future compared to the present-day period of 1986-2005,with a large increase in the frequency of strong TCs.In addition,more TCs landings are projected over most of the China coast,with an increase of~18%over the whole Chinese territory.  相似文献   

7.
The Dynamical-Statistical-Analog Ensemble Forecast model for landfalling tropical cyclones (TCs) precipitation (DSAEF_LTP) utilises an operational numerical weather prediction (NWP) model for the forecast track, while the precipitation forecast is obtained by finding analog cyclones, and making a precipitation forecast from an ensemble of the analogs. This study addresses TCs that occurred from 2004 to 2019 in Southeast China with 47 TCs as training samples and 18 TCs for independent forecast experiments. Experiments use four model versions. The control experiment DSAEF_LTP_1 includes three factors including TC track, landfall season, and TC intensity to determine analogs. Versions DSAEF_LTP_2, DSAEF_LTP_3, and DSAEF_LTP_4 respectively integrate improved similarity region, improved ensemble method, and improvements in both parameters. Results show that the DSAEF_LTP model with new values of similarity region and ensemble method (DSAEF_LTP_4) performs best in the simulation experiment, while the DSAEF_LTP model with new values only of ensemble method (DSAEF_LTP_3) performs best in the forecast experiment. The reason for the difference between simulation (training sample) and forecast (independent sample) may be that the proportion of TC with typical tracks (southeast to northwest movement or landfall over Southeast China) has changed significantly between samples. Forecast performance is compared with that of three global dynamical models (ECMWF, GRAPES, and GFS) and a regional dynamical model (SMS-WARMS). The DSAEF_LTP model performs better than the dynamical models and tends to produce more false alarms in accumulated forecast precipitation above 250 mm and 100 mm. Compared with TCs without heavy precipitation or typical tracks, TCs with these characteristics are better forecasted by the DSAEF_LTP model.  相似文献   

8.
Lagged ensembles from the operational Climate Forecast System version 2 (CFSv2) seasonal hindcast dataset are used to assess skill in forecasting interannual variability of the December–February Arctic Oscillation (AO). We find that a small but statistically significant portion of the interannual variance (>20 %) of the wintertime AO can be predicted at leads up to 2 months using lagged ensemble averages. As far as we are aware, this is the first study to demonstrate that an operational model has discernible skill in predicting AO variability on seasonal timescales. We find that the CFS forecast skill is slightly higher when a weighted ensemble is used that rewards forecast runs with the most accurate representations of October Eurasian snow cover extent (SCE), hinting that a stratospheric pathway linking October Eurasian SCE with the AO may be responsible for the model skill. However, further analysis reveals that the CFS is unable to capture many important aspects of this stratospheric mechanism. Model deficiencies identified include: (1) the CFS significantly underestimates the observed variance in October Eurasian SCE, (2) the CFS fails to translate surface pressure anomalies associated with SCE anomalies into vertically propagating waves, and (3) stratospheric AO patterns in the CFS fail to propagate downward through the tropopause to the surface. Thus, alternate boundary forcings are likely contributing to model skill. Improving model deficiencies identified in this study may lead to even more skillful predictions of wintertime AO variability in future versions of the CFS.  相似文献   

9.
A hybrid seasonal forecasting approach was generated by the National Centers for Environmental Prediction operational Climate Forecast System (CFS) and its nesting Climate extension of Weather Research and Forecasting (CWRF) model to improve forecasting skill over the United States. Skills for the three summers of 2011–2013 were evaluated regarding location, timing, magnitude, and frequency. Higher spatial pattern correlation coefficients showed that the hybrid approach substantially improved summer mean precipitation and 2-m temperature geographical distributions compared with the results of the CFS and CWRF models. The area mean temporal correlation coefficients demonstrated that the hybrid approach also consistently improved the timing prediction skills for both variables. In general, the smaller root mean square errors indicated that the hybrid approach reduced the magnitude of the biases for both precipitation and temperature. The greatest improvements were achieved when the individual models had similar skills. The comparison with a North American multi-model ensemble further proved the feasibility of improving real-time seasonal forecast skill by using the hybrid approach, especially for heavy rain forecasting. Based on the complementary advantages of CFS the global model and CWRF the nesting regional model, the hybrid approach showed a substantial enhancement over CFS real-time forecasts during the summer. Future works are needed for further improving the quality of the hybrid approach through CWRF’s optimized physics ensemble, which has been proven to be feasible and reliable.  相似文献   

10.
利用美国环境预报中心的第二代气候预报系统(NCEP CFSv2)提供的1982~2010年历史回报资料和2015年6~8月预报产品、NCEP CFSR再分析资料及中国地面观测降水资料,评估了NCEP CFSv2对2015年(厄尔尼诺发展年)中国夏季月降水和环流形势的预报能力,并分析了影响模式预报技巧高低的可能因子。结果表明:1)模式对降水的预报技巧较低且表现出明显的月变化(7月最高,8月次之,6月最低),但总体水平都不高。预报技巧明显依赖于提前时间的长短。2)CFSv2对影响我国夏季降水的500h Pa关键区环流异常空间模态表现出较高的预报技巧。对全东亚区域,模式基本都可提前5~9天(7月9天,6月6天,8月5天)较为准确的预报出未来一个月高度异常空间模态。3)通过对比分析发现,CFSv2环流预报中选取12个集合成员(滑动3天)可以得到较稳定的预报结果。4)在2015年夏季月尺度环流异常模态预报中,东亚全区的环流预报水平很大程度上取决于中高纬地区的预报。CFSv2对中高纬环流月预报技巧(6~8月都能从提前4天开始就基本稳定维持在较高水平)比热带地区更高更稳定。   相似文献   

11.
This study aimed to develop the seasonal forecast models of Korean dust days over South Korea in the springtime. Forecast mode was a ternary forecast (below normal, normal, above normal) which was classified based on the mean and the standard deviation of Korean dust days for a period of 30 years (1981-2010). In this study, we used three kinds of monthly data: the Korean dust days observed in South Korea, the National Center for Environmental Prediction in National Center for Atmospheric Research (NCEP/NCAR) reanalysis data for meteorological factors over source regions of Asian dust, and the large-scale climate indices offered from the Climate Diagnostic Center and Climate Prediction Center in NOAA. Forecast guidance consisted of two components; ordinal logistic regression model to generate trinomial distributions, and conversion algorithm to generate ternary forecast by two thresholds. Forecast guidance was proposed for each month separately and its predictability was evaluated based on skill scores.  相似文献   

12.
NCEP/CFS模式对东亚夏季延伸预报的检验评估   总被引:1,自引:0,他引:1       下载免费PDF全文
利用NCEP的气候预报系统(Climate Forecast System, CFS)所提供的1981—2004年历史回报试验结果,检验和评估了该系统对夏季东亚地区大气环流的预报技巧和系统误差;在此基础上通过提取模式预报和观测的10~20 d及30~60 d低频振荡分量,重点对我国南方3次典型持续性暴雨过程的预报技巧进行检验和诊断分析。结果表明:CFS系统对东亚整体大气环流逐日预报的可靠时效为5 d左右,60°N以北的对流层中高层高度场预报系统性偏低,而在40°~60°N则为系统性偏高。系统性误差随预报时间的延长而增加,但10 d以上预报的系统性误差大小和空间分布逐渐趋于稳定;CFS系统对低频分量的延伸期预报技巧好于对其整体大气环流的预报技巧,并且在典型持续性暴雨过程中,CFS系统对影响强降水过程的主要环流系统低频振荡特征有一定预报能力。  相似文献   

13.
In this study, we have investigated the contribution of El Niño-Southern Oscillation (ENSO) to the North Indian Ocean (NIO) tropical cyclone (TC) activity and seasonal predictability. A statistical seasonal prediction model was developed for the NIO region tropical cyclone genesis, trajectories and landfalls using the Southern Oscillation index (SOI: as a metric of ENSO) as a predictor. The forecast model utilised kernel density estimation (KDE), a generalised additive model (GAM), Euler integration, and a country mask. TCs from the Joint Typhoon Warning Centre were analysed over the 35-year period from 1979 to 2013. KDE was used to model the distribution of cyclone genesis points and the cyclone tracks were estimated using the GAM, with velocities fit as smooth functions of location according to ENSO phase and TC season. The best predictor lead time scales for TC forecast potential were assessed from 1 to 6 months. We found that the SOI (as a proxy for ENSO) is a good predictor of TC behaviour 2-months in advance (70% skill). Two hindcast validation methods were applied to assess the reliability of the model. The model was found to be skillful in hindcasting NIO region TC activity for the pre and post monsoon season. The distribution of TC genesis, movement and landfall probabilities over the study period, as well as the hindcast probabilities of TC landfall during ENSO events, matched well against observations over most of the study domain. Overall, we found that the phase of ENSO has the potential to improve NIO region TC seasonal forecast skill by about 15% over climatological persistence.  相似文献   

14.
热带气旋是气候模拟关注的重要对象,但是,由于当前的气候系统模式分辨率较低,难以合理再现热带气旋分布特征,因此,动力降尺度就成为一种有效的手段。本文使用区域气候模式RegCM3,对中国科学院大气物理研究所气候系统模式FGOALS-g2的模拟结果进行动力降尺度,基于热带气旋路径追踪法,从热带气旋的路径、强度和降水三个方面,检验了动力降尺度在热带气旋模拟能力上的增值。结果表明,动力降尺度结果大幅提升了热带气旋路径频率的模拟,较之全球模式,其与观测的路径频率分布的空间相关系数从0.57提升至0.74;区域模式模拟的热带气旋强度与观测更为一致,全球模式难以模拟40 m s?1以上风速的热带气旋,区域模式能够模拟风速为60 m s?1的热带气旋;在热带气旋降水方面,降尺度后的热带气旋降水贡献率和平均热带气旋降水强度均有所改善,在西北太平洋区域较之全球模式,区域模式将热带气旋降水贡献率和降水强度提高了10%和4.7 mm d?1。动力降尺度后TC(tropical cyclone)的模拟技巧得到提升的区域为西北太平洋区域,但在中国南海区域,技巧提升的不显著甚至有所下降。关于动力降尺度结果在西北太平洋区域的技巧提升,分析表明能够更好体现CISK(Conditional Instability of the Second Kind)机制是主要原因,区域模式模拟的水汽增多、正涡度增强、上升运动增强而垂直风切变减弱都有显著贡献。  相似文献   

15.
古月  陈葆德  董广涛 《气象》2013,39(2):137-145
利用RegCM3区域气候模式,试验研究了15、30、45和60 km 4个分辨率下西北太平洋热带气旋的生成特征.结果表明,RegCM3模式对西北太平洋热带气旋生成的模拟能力受分辨率的影响.分辨率的简单提高,并不一定会使模式的模拟能力有所改善.模式在30 km分辨率下对西北太平洋热带气旋生成频数及频数变化的模拟能力最强,在60 km分辨率下对西北太平洋热带气旋生成频数空间分布的模拟能力最强,在15 km分辨率下对西北太平洋热带气旋生成频数、频数空间分布及频数变化的模拟能力最弱.对比分析不同分辨率下热带气旋的生成过程表明,热带气旋生成前期,β中尺度涡旋没有发生合并,对流层中低层水汽含量不足是导致模式在15 km分辨率下模拟热带气旋生成频数较差的主要原因.  相似文献   

16.
The regional climate model (RegCM3) from the Abdus Salam International Centre for Theoretical Physics has been used to simulate the Indian summer monsoon for three different monsoon seasons such as deficit (1987), excess (1988) and normal (1989). Sensitivity to various cumulus parameterization and closure schemes of RegCM3 driven by the National Centre for Medium Range Weather Forecasting global spectral model products has been tested. The model integration of the nested RegCM3 is conducted using 90 and 30-km horizontal resolutions for outer and inner domains, respectively. The India Meteorological Department gridded rainfall (1° × 1°) and National Centre for Environment Prediction (NCEP)–Department of Energy (DOE) reanalysis-2 of 2.5° × 2.5° horizontal resolution data has been used for verification. The RegCM3 forced by NCEP–DOE reanalysis-2 data simulates monsoon seasons of 1987 and 1988 reasonably well, but the monsoon season of 1989 is not represented well in the model simulations. The RegCM3 runs driven by the global model are able to bring out seasonal mean rainfall and circulations well with the use of the Grell and Anthes–Kuo cumulus scheme at 90-km resolution. While the rainfall intensity and distribution is brought out well with the Anthes–Kuo scheme, upper air circulation features are brought out better by the Grell scheme. The simulated rainfall distribution is better with RegCM3 using the MIT-Emanuel cumulus scheme for 30-km resolution. Several statistical analyses, such as correlation coefficient, root mean square error, equitable threat score, confirm that the performance of MIT-Emanuel scheme at 30-km resolution is better in simulating all-India summer monsoon rainfall. The RegCM3 simulated rainfall amount is more and closer to observations than that from the global model. The RegCM3 has corrected its driven GCM in terms of rainfall distribution and magnitude over some parts of India during extreme years. This study brings out several weaknesses of the RegCM model which are documented in this paper.  相似文献   

17.
Based on various statistical indices, the abilities of multi-generation reanalyses, namely the NCEP/NCAR Reanalysis 1 (R1), the NCEP-DOE Reanalysis 2 (R2) and the NCEP Climate Forecast System Reanalysis (CFSR), to reproduce the spatiotemporal characteristics of precipitation over Zhejiang Province are comprehensively compared. The mean absolute bias percentages for three reanalyses are 20% (R1), 10% (R2) and 37% (CFSR). R2 (R1) gives the best (worst) general depiction of the spatial characteristics of the observed precipitation climatology, whereas a significant wet bias is noticed in CFSR. All reanalyses reasonably reproduce the interannual variability with the correlation coefficients of 0.72 (R1), 0.72 (R2) and 0.84 (CFSR). All reanalyses well represent the first two modes of the observed precipitation through Empirical Orthogonal Function analysis, with CFSR giving the best capture of the principal components. The root-mean-square error (RMSE) is the largest (smallest) in CFSR (R2). The large RMSE of CFSR in summer (especially in June) contributes mostly to its systematic wet bias. After 2001, the wet-bias of CFSR substantially weakens, probably attributed to increasing observations assimilated in the CFSR. On a monthly basis, the percentage of neutral bias cases are similar for all reanalyses, while the ratio of positive (negative) bias cases for CFSR is distinctly larger (smaller) than that of R1 and R2. The proportions of negative bias cases for R1 and R2 begin to increase after 2001 while keeping stable for CFSR. On a daily basis, all reanalyses give good performances of reproducing light rain; however, the reflection of moderate rain and heavier rain by CFSR is better than R1 and R2. Overall, despite being a third-generation reanalysis product, CFSR does not exhibit comprehensive superiorities over R1 and R2 in all aspects on a regional scale.  相似文献   

18.
This study evaluates the performance of the regional climate model RegCM4 in simulating tropical cyclone (TC) activities over the Western North Pacific (WNP) and their landfalling in China. The model is driven by ERA-Interim boundary conditions at a grid spacing of 25 km, with the simulation period as 1991–2010. Results show that RegCM4 performs well in capturing the main structural features of observed TCs, and in simulating the genesis number and annual cycle of the genesis. The model reproduces the general pattern of the observed TC tracks and occurrence frequency. However, significant underestimation of the occurrence frequency as well as the TC intensity is found. Number of the landfalling TCs over China is also much less than the observed. Bias of the model in reproducing the large-scale circulation pattern and steering flow may contribute to the underestimated landfalling TC numbers.  相似文献   

19.
This study examines the prediction skill of the contiguous United States (CONUS) precipitation in summer, as well as its potential sources using a set of ensemble hindcasts conducted with the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 and initialized from four independent ocean analyses. The multiple ocean ensemble mean (MOCN_ESMEAN) hindcasts start from each April for 26 summers (1982–2007), with each oceanic state paired with four atmosphere-land states. A subset of hindcasts from the NCEP CFS Reanalysis and Reforecast (CFSRR) project for the same period, from the same initial month and with the same total ensemble size, is also analyzed. Compared with CFSRR, MOCN_ESMEAN is distinguished by its oceanic ensemble spread that introduces potentially larger perturbations and better spatial representation of the oceanic uncertainty. The prediction skill of the CONUS precipitation in summer shows a similar spatial pattern in both MOCN_ESMEAN and CFSRR, but the results suggested that initialization from multiple ocean analyses may bring more robust signals and additional skills to the seasonal prediction for both sea surface temperature and precipitation. Among the predictable areas for precipitation, the northwestern CONUS (NWUS) is the most robust. A further analysis shows that the enhanced summer precipitation prediction skill in NWUS is mainly associated with the El Niño/Southern Oscillation, with possible influence also from the Pacific Decadal Oscillation. Through this work, we argue that a large ensemble is necessary for precipitation forecast in mid-latitudes, such as the CONUS, and taking into account of the oceanic initial state uncertainty is an efficient way to build such an ensemble.  相似文献   

20.
基于低频振荡特征的夏季江淮持续性降水延伸期预报方法   总被引:7,自引:1,他引:6  
陈官军  魏凤英 《大气科学》2012,36(3):633-644
本文利用1981~2008年我国南方地区200站逐日降水量、NCEP再分析资料和NCEP气候预报系统 (CFS) 的模式回算数据, 针对降水低频信号, 分析了江淮地区夏季降水的延伸期可预报性, 并选取对江淮持续性强降水有显著影响的东亚环流指数作为预报因子, 以降水20~50天低频分量作为预报量, 进行了针对江淮地区夏季持续性强降水过程的延伸期预报试验。结果表明, 江淮地区夏季降水具有明显的20~50天周期的低频振荡特征。降水的20~50天低频振荡, 尤其是峰谷值位相的变化与实际降水集中期和中断期的交替有较好的关系, 研究20~50天降水低频分量的延伸预报, 对于江淮地区夏季持续性强降水过程的延伸预报有一定的指示意义。本文尝试提出一种基于大气环流低频信号和数值模式预报产品的动力与统计相结合的预报方法, 以期为江淮地区夏季持续性降水过程的延伸期预报提供参考。  相似文献   

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