[PDF] Top 20 Merging particle filter for sequential data assimilation
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Merging particle filter for sequential data assimilation
... for sequential data as- similation, the merging particle filter (MPF), is ...the particle filter (PF), without pro- hibitive computational ...observed data where the application ... See full document
14
Implicit particle filtering for models with partial noise, and an application to geomagnetic data assimilation
... “perfect data,” ...the data, but with a larger gap of r = 10 model steps between ...assimilate data sequen- ...magnetic data assimilation (the velocity field is unknown), however a ... See full document
18
A Kalman filter application to a spectral wave model
... data for updating the wave spectrum (Thomas, 1988; Esteva, 1988; Janssen et al., 1989, Lionello et al., 1992, 1995). These are computational efficient methods and consequently they have been tested in operational ... See full document
8
Earthquake forecasting based on data assimilation: sequential Monte Carlo methods for renewal point processes
... and data assimilation has been concerned with iden- tifying useful, suitable and computationally inexpensive fil- ters for a variety of particular ...non-Gaussian, sequential Bayesian estimation ... See full document
22
Towards the sequential assimilation of SAR derived water stages into hydraulic models using the Particle Filter: proof of concept
... satellite data at a temporal frequency that is compat- ible with real-time flood forecasting requirements, this study presents a new concept for the sequential assimilation of Syn- thetic Aperture ... See full document
13
A local particle filter for high-dimensional geophysical systems
... Sampling importance resampling (SIR) (also known as the bootstrap filter; Gordon et al., 1993) is a commonly used enhancement to the basic sequential importance sam- pling (SIS) particle filter. However, ... See full document
15
A method for retrieving clouds with satellite infrared radiances using the particle filter
... the particle filter (Snyder and Zhang, 2003; van Leeuwen, 2010; Shen and Tang, 2015) technique and Bayesian theory (Karlsson et ...the data assimilation system, the radiative transfer models (RTMs) ... See full document
14
A defensive marginal particle filtering method for data assimilation
... the sequential Monte Carlo (SMC) method (see ...as particle filtering (PF), can deal with problems with strongly nonlinear models, without any linearization or ... See full document
19
A particle filter scheme for multivariate data assimilation into a point-scale snowpack model in an Alpine environment
... With the aim of testing the snow modelling system at a point- scale, the selection of the case studies has been restricted among pilot experimental sites, where automated weather stations supply meteorological and ... See full document
20
Comparison of different sequential assimilation algorithms for satellite-derived leaf area index using the Data Assimilation Research Testbed (version Lanai)
... the Data Assimilation Research Testbed (DART) has been suc- cessfully coupled to the Community Land Model with ex- plicit carbon and nitrogen components (CLM4CN) by as- similating Global Land Surface ... See full document
15
Analysis of data assimilation schemes
... In this paper we have studied the long-time behaviour of filters for partially observed dissipative dynamical systems, using the Lorenz ’96 model as a canonical example. We have highlighted the connection to ... See full document
131
Data assimilation with an improved particle filter and its application in the TRIGRS landslide model
... Abstract. Particle filters have become a popular algorithm in data assimilation for their ability to handle nonlinear or non-Gaussian state-space models, but they have significant ...improved ... See full document
7
Impact of hydrographic data assimilation on the modelled Atlantic meridional overturning circulation
... most assimilation methods (includ- ing the method used here) down-weight hydrographic data on the shelf, due to the presence of unresolved processes in the observa- tions (so-called “representivity error”), ... See full document
14
Optimal adjustment of the atmospheric forcing parameters of ocean models using sea surface temperature data assimilation
... In this approximation, the estimation of P ˆ f involves only the knowledge of the model error Q generated by forcing ˆ errors during the assimilation window. As this matrix must be representative of forcing ... See full document
17
Effectiveness of a Computer Based Syntax Program in Improving the Morphosyntax of Students Who are Deaf/Hard of Hearing
... localization, and DNA sequence analysis (Chen 2004). Gustafsson et al. (2002) developed a framework and several algorithms for the problems of positioning, navigation, and tracking using SMC methods. Fox et al. (2001) ... See full document
131
Overcoming Diminished Motivation
... sensor data provides an observation of the system, and data assimilation assimilates these observations to infer the current system ...state. Data assimilation has been widely used ... See full document
132
Parameter optimisation for a better representation of drought by LSMs: inverse modelling vs sequential data assimilation
... Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bid- lot, J., Bormann, N., ... See full document
18
Localization and mapping in urban environments using mobile Robots
... raw data twice: during the first pass, the robot’s initial pose was unknown, and the filter took some time to converge to a singular pose value; once this pose was established, the data was ... See full document
11
Application of a Sequential Data Assimilation Technique to Improve Modeling of Surface Currents Using Radar Data at a Coastal Domain
... nudging data assimilation ...experiments. Assimilation of the remotely sensing radar data at each model computational time step resulted in a good forecasting performance compared with a “free ... See full document
6
Data Assimilation in the Air Contaminant Dispersion Using Particle Filter and Expectation-Maximization Algorithm with UAV Observations
... two data assimilation methods ...typical particle filter while the other is a combination of particle filter and expectation-maximization algorithm) are proposed to assimilate the UAV ... See full document
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