Search Results - "LEEUWEN, Peter Jan VAN"

Observation impact in data assimilation: the effect of non-Gaussian observation error by Fowler, Alison, Jan Van Leeuwen, Peter

“…Data assimilation methods which avoid the assumption of Gaussian error statistics are being developed for geoscience applications. We investigate how the…”
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Particle Filtering and Gaussian Mixtures – On a Localized Mixture Coefficients Particle Filter (LMCPF) for Global NWP by ROJAHN, Anne, SCHENK, Nora, LEEUWEN, Peter Jan VAN, POTTHAST, Roland

“…In a global numerical weather prediction (NWP) modeling framework we study the implementation of Gaussian uncertainty of individual particles into the…”
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Gaussian anamorphosis in the analysis step of the EnKF: a joint state-variable/observation approach by Amezcua, Javier, Van Leeuwen, Peter Jan

“…The analysis step of the (ensemble) Kalman filter is optimal when (1) the distribution of the background is Gaussian, (2) state variables and observations are…”
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A weak-constraint 4DEnsembleVar. Part II: experiments with larger models by Goodliff, Michael, Amezcua, Javier, Van Leeuwen, Peter Jan

“…In recent years, hybrid data-assimilation methods which avoid computation of tangent linear and adjoint models by using ensemble 4-dimensional cross-time…”
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When can we expect extremely high surface temperatures? by Sterl, Andreas, Severijns, Camiel, Dijkstra, Henk, Hazeleger, Wilco, Jan van Oldenborgh, Geert, van den Broeke, Michiel, Burgers, Gerrit, van den Hurk, Bart, Jan van Leeuwen, Peter, van Velthoven, Peter

“…In the Essence project a 17‐member ensemble simulation of climate change in response to the SRES A1b scenario has been carried out using the ECHAM5/MPI‐OM…”
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A systematic method of parameterisation estimation using data assimilation by Lang, Matthew, Jan Van Leeuwen, Peter, Browne, Philip

“…In numerical weather prediction, parameterisations are used to simulate missing physics in the model. These can be due to a lack of scientific understanding or…”
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Comparing hybrid data assimilation methods on the Lorenz 1963 model with increasing non-linearity by Goodliff, Michael, Amezcua, Javier, Van Leeuwen, Peter Jan

“…We systematically compare the performance of ETKF-4DVAR, 4DVAR-BEN and 4DENVAR with respect to two traditional methods (4DVAR and ETKF) and an ensemble…”
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Measures of observation impact in non-Gaussian data assimilation by Fowler, Alison, Jan Van Leeuwen, Peter

“…Non-Gaussian/non-linear data assimilation is becoming an increasingly important area of research in the Geosciences as the resolution and non-linearity of…”
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Particle filters for high‐dimensional geoscience applications: A review by Leeuwen, Peter Jan, Künsch, Hans R., Nerger, Lars, Potthast, Roland, Reich, Sebastian

“…Particle filters contain the promise of fully nonlinear data assimilation. They have been applied in numerous science areas, including the geosciences, but…”
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A consistent interpretation of the stochastic version of the Ensemble Kalman Filter by Leeuwen, Peter Jan

“…Ensemble Kalman Filters are used extensively in all geoscience areas. Often a stochastic variant is used, in which each ensemble member is updated via the…”
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Representation errors and retrievals in linear and nonlinear data assimilation by van Leeuwen, Peter Jan

“…This article shows how one can formulate the representation problem starting from Bayes' theorem. The purpose of this article is to raise awareness of the…”
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Implicit equal‐weights particle filter by Zhu, Mengbin, van Leeuwen, Peter Jan, Amezcua, Javier

“…Filter degeneracy is the main obstacle for the implementation of particle filters in nonlinear high‐dimensional models. A new scheme, the implicit…”
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Using the (Iterative) Ensemble Kalman Smoother to Estimate the Time Correlation in Model Error by Amezcua, Javier, Ren, Haonan, van Leeuwen, Peter Jan

“…Numerical weather prediction systems contain model errors related to missing and simplified physical processes, and limited model resolution. While it has been…”
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A framework for causal discovery in non-intervenable systems by van Leeuwen, Peter Jan, DeCaria, Michael, Chakraborty, Nachiketa, Pulido, Manuel

“…Many frameworks exist to infer cause and effect relations in complex nonlinear systems, but a complete theory is lacking. A new framework is presented that is…”
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Near‐Cloud Aerosol Retrieval Using Machine Learning Techniques, and Implied Direct Radiative Effects by Yang, C. Kevin, Chiu, J. Christine, Marshak, Alexander, Feingold, Graham, Várnai, Tamás, Wen, Guoyong, Yamaguchi, Takanobu, Jan van Leeuwen, Peter

“…There is a lack of satellite‐based aerosol retrievals in the vicinity of low‐topped clouds, mainly because reflectance from aerosols is overwhelmed by…”
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State-of-the-art stochastic data assimilation methods for high-dimensional non-Gaussian problems by Vetra-Carvalho, Sanita, van Leeuwen, Peter Jan, Nerger, Lars, Barth, Alexander, Altaf, M. Umer, Brasseur, Pierre, Kirchgessner, Paul, Beckers, Jean-Marie

“…This paper compares several commonly used state-of-the-art ensemble-based data assimilation methods in a coherent mathematical notation. The study encompasses…”
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A weak-constraint 4DEnsembleVar. Part I: formulation and simple model experiments by Amezcua, Javier, Goodliff, Michael, Van Leeuwen, Peter Jan

“…4DEnsembleVar is a hybrid data assimilation method which purpose is not only to use ensemble flow-dependent covariance information in a variational setting,…”
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Observational Constraints on Warm Cloud Microphysical Processes Using Machine Learning and Optimization Techniques by Chiu, J. Christine, Yang, C. Kevin, van Leeuwen, Peter Jan, Feingold, Graham, Wood, Robert, Blanchard, Yann, Mei, Fan, Wang, Jian

“…We introduce new parameterizations for autoconversion and accretion rates that greatly improve representation of the growth processes of warm rain. The new…”
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Non-local Observations and Information Transfer in Data Assimilation by van Leeuwen, Peter Jan

“…Non-local observations are observations that cannot be allocated one specific spatial location. Examples are observations that are spatial averages of linear…”
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A Variational Approach to Retrieve Rain Rate by Combining Information from Rain Gauges, Radars, and Microwave Links by Bianchi, Blandine, van Leeuwen, Peter Jan, Hogan, Robin J., Berne, Alexis

“…Accurate and reliable rain rate estimates are important for various hydrometeorological applications. Consequently, rain sensors of different types have been…”
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