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Evensen (2003) presents a modification of the Ensemble Kalman Filter (EnKF), in which the observation-error and background-error covariance matrices are both represented by ensembles, in contrast to the usual practice, where only the background error is so represented. It is shown that this modification can cause the ensemble to collapse to a single member, in the common situation where the number of observations is more than twice the number of ensemble members, and to be rank-deficient when the number of observations is greater than or equal to the ensemble size. It is also shown that some further modifications to the scheme, presented by Evensen as offering numerical efficiencies, can prevent this collapse. However, these latter modifications are shown in some simple numerical examples to require tuning to produce acceptable results, which are nevertheless inferior to those of the standard EnKF.Acknowledgements The author acknowledges useful discussions with Peter Steinle, and other participants at the EnKF workshop held in BMRC in November, 2003. 相似文献
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Assimilation of Hourly Surface Observations with the Canadian High-Resolution Ensemble Kalman Filter
An hourly-cycling ensemble Kalman filter (EnKF) working at 2.5?km horizontal grid spacing is implemented over southern Ontario (Canada) to assimilate Meteorological Terminal Aviation Routine Weather Reports (METARs) in addition to the observations assimilated operationally at the Canadian Meteorological Centre. This high-resolution EnKF (HREnKF) system employs ensemble land analyses and perturbed roughness length to prevent an ensemble spread that is too small near the surface. The HREnKF then performs continuously for a four-day period, from which twelve-hour ensemble forecasts are launched every six hours. The impact on analyses and short-term forecasts of assimilating METAR data is given special attention.It is shown that using ensemble land surface analyses increases near-surface ensemble spreads for temperature and specific humidity. Perturbing roughness length enlarges the spread for surface wind. Given sufficient ensemble spread, the four-day case study shows that the near-surface model state is brought closer to surface observations during the cycling process. The impact of assimilating surface data can also be seen at higher levels by using aircraft reports for verification. The ensemble forecast verification suggests that METAR data assimilation improves ensemble forecasts of air temperature and dewpoint near the surface up to a lead time of six hours or even longer. However, only minor improvement is found in surface wind forecasts. 相似文献
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Crushed recycled glass was evaluated as an alternative to silica sand in dual‐media filters. Pilot scale inline filtration experiments were carried out using raw waters from three different water sources with turbidities between 6.0 and 14.0 NTU. Two physically identical filter columns were operated in parallel in the experiments. One filter consisted of 62.5 cm silica sand and 41.5 cm anthracite coal, whereas the other filter contained 62.5 cm crushed recycled glass plus 41.5 cm anthracite coal. The total bed depth was 104 cm for both filters. The properties of the media were as follows: Glass effective size = 0.77 mm, uniformity coefficient = 1.41. Sand effective size = 0.79 mm, uniformity coefficient = 1.33. Coal effective size = 1.45 mm, uniformity coefficient = 1.39. Experiments were repeated five times as follows: (i) Without the use of a coagulant, (ii–iii) with 5 and 10 mg/L of alum, and (iv–v) with 5 and 10 mg/L of ferric chloride. The filtration rate used was 11.5 m/h. Turbidity, particle counts, and head losses were measured and compared as functions of time. The following were observed: (i) Effluent turbidities and particle counts of the two filters were very close, i.e., essentially the same effluent quality was obtained when crushed glass was used instead of silica sand. (ii) In the majority of the tests, the filter with crushed glass generated both a smaller clean‐bed head loss and smaller clogging head losses than those of the filter containing sand. It is concluded that crushed glass may be a good alternative to silica sand in dual‐media filtration. 相似文献
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Kalman滤波方法在黑河出山径流年平均流量预报中的应用 总被引:21,自引:10,他引:11
应用Kalman滤波方法,以流域平均降水量、气温、太阳黑子相对数及莺落峡站6年显著周期序列等为控制参数,对黑河出山径流年平均流量的预测问题进行了初步研究和探讨。 相似文献
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地球表层系统是一个极其复杂的巨系统,为了更精确地表达地球表层系统各种过程的动态演进,解决数据同化系统观测误差的估计与处理已经成为地球科学领域备受关注的问题之一。在地球科学系统数值模拟中,一般采用集合数据同化来探讨地学变量预报时的各种误差。集合类卡尔曼滤波通常会由于集合数过小而带来欠采样、协方差低估、滤波发散和远距离虚假相关等问题。针对背景误差协方差被低估问题,局地分析方法(Local Analysis, LA)在一定程度上能起到抑制作用,但无法彻底解决背景误差协方差的虚假相关问题。因此,本文在集合卡尔曼滤波的算法框架下提出了一种与模糊逻辑控制算法相耦合的局地化分析方法(Fuzzy Analysis, FA)。在强非线性Lorenz-96模型中,对不同模型误差下的LA和FA方法进行了性能优劣方面的探讨,并比较分析了2种方法在集合数、观测数和观测位置、放大因子以及强迫参数变化时的同化性能。实验采用均方根误差作为算法评判依据,同时用功率谱密度(Power Spectral Density, PSD)更直接地对2种算法性能优劣作出了评价。结果表明:在完美模型下,FA相对于LA降低了17.5%的均方根误差(Root Mean Square Error, RMSE);随着模型误差增大,RMSE减小的百分比和减小幅度都在降低;在严重模型误差下,FA降低了8.6%的RMSE。总体而言,新算法FA的有效性和鲁棒性都得到了验证,并且在EnKF同化基础下有效改进了传统的局地化分析方案,优化了观测误差处理,为今后的数据同化研究提供了一个较为全面的观测误差研究平台。 相似文献
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数据同化是在基于物理机制的背景模型上,融合时空不规则分布的观测数据的一种现报方法.同化能够有效弥补数据的时空局限和模型的精度偏差,使二者相互匹配从而获得更加合理可信的模拟效果.本研究利用电离层数据同化方法,针对中国及周边区域(15°N-55°N,70°E-140°E)构建了电离层总电子含量(TEC)同化现报系统.系统使用国际参考电离层(IRI)作为背景场,利用中国科学院空间环境监测网和国际GNSS服务组织(IGS)的部分地基GNSS台站数据作为观测值,并采用三维变分与Gauss-Markov卡尔曼滤波相结合的算法进行背景场和观测值的数据同化,生成覆盖中国及周边区域的电离层TEC和GPS单频接收机延迟误差的格点化准实时现报地图,并在中国科学院空间环境预报中心(http://sepc.ac.cn/TEC_chn.php)网上发布,每15 min进行更新.该系统是我国基于同化算法的电离层现报系统之一,已用于中国及周边区域的电离层环境实时监测,可为卫星导航、雷达成像、短波通信等科学研究和工程应用提供相对及时、准确、有效的电离层TEC和误差修正信息. 相似文献