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Yanqiu Gao
The ensemble Kalman filter is often used in parameter estimation, which plays an essential role in reducing model errors. However, filter divergence is often encountered in an estimation process, resulting in the convergence of parameters to the improper...
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Shaokun Deng, Zheqi Shen, Shengli Chen and Renxi Wang
It is widely recognized that the initial ensemble describes the uncertainty of the variables and, thus, affects the performance of ensemble-based assimilation techniques, which is investigated in this paper with experiments using the Community Earth Syst...
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Ganchang He, Yaning Chen, Gonghuan Fang and Zhi Li
The stationarity test and systematic prediction of hydrometeorological parameters are becoming increasingly important in water resources management. Based on the Ensemble Kalman Filter (EnKF) and wavelet analysis, this study selects precipitation, evapor...
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Yulia Timoshenkova,Sergey Porshnev,Nikolai Safiullin
Pág. 15 - 23
The article describes the method developed by the authors for integration of formal methods of time series (TS) forecasting (autoregressive integrated moving average (ARIMA), singular spectrum analysis, group method of data handling, artificial recurrent...
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Navid Jadidoleslam, Ricardo Mantilla and Witold F. Krajewski
The authors examine the impact of assimilating satellite-based soil moisture estimates on real-time streamflow predictions made by the distributed hydrologic model HLM. They use SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture Ocean Salinity) ...
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Jean Bergeron, Robert Leconte, Mélanie Trudel and Sepehr Farhoodi
An important step when using some data assimilation methods, such as the ensemble Kalman filter and its variants, is to calibrate its parameters. Also called hyper-parameters, these include the model and observation errors, which have previously been sho...
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Ang Su, Liang Zhang, Xuefeng Zhang, Shaoqing Zhang, Zhao Liu, Caili Liu and Anmin Zhang
Due to the model and sampling errors of the finite ensemble, the background ensemble spread becomes small and the error covariance is underestimated during filtering for data assimilation. Because of the constraint of computational resources, it is diffi...
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Hong Liu, Qiulong Yang and Kunde Yang
Geoacoustic inversion is an efficient method to study the physical properties and structure of ocean bottom while sequential geoacoustic inversion is a challenging task due to the complexity and non-linearity of the underwater environment. In this paper,...
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Emilio Sánchez-León, Carsten Leven, Daniel Erdal and Olaf A. Cirpka
Pumping and tracer tests are site-investigation techniques frequently used to determine hydraulic conductivity. Tomographic test layouts, in which multiple tests with different combinations of injection and observation wells are performed, gain a better ...
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Miao Dai, Yaan Li and Kunde Yang
This paper develops a joint approach for time-evolving sound speed field (SSF) inversion and moving source localization in shallow water environment. The SSF is parameterized in terms of the first three empirical orthogonal function (EOF) coefficients. T...
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