Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 176 for “"data assimilation"”.
-
Data Assimilation and Applications in Forecasting
… here spans two projects which are connected by data assimilationand specifically the ensemble Kalman filter (EnKF). The first explores how spatial localization, an important method commonly used in the EnKF, can be extended to multiscale problems. Rather than using a single length scale when …
-
Modeling volcanic unrest by data assimilation
… work focuses on developing and applying a robust data-model fusion framework to investigate the mechanisms involved in volcanic unrest, such as deformation, failure, and pore fluid migration. First, using a series of tests based on the synthetic data, I optimize a data assimilation technique, …
-
Marine ecosystem model analysis using data assimilation
… two marine ecosystem models were calibrated to data. Results demonstrated that all prior parameter information must include realistic error estimates if model uncertainty is to be quantified. Five simple ecosystem models were calibrated to observations from two North Atlantic sites; the Bermuda …
-
Variational data assimilation for two interface problems
<p>“Variational data assimilation (VDA) is a process that uses optimization techniques to determine an initial condition of a dynamical system such that its evolution best fits the observed data. In this dissertation, we develop and analyze the variational data assimilation method with finite …
-
Forecasting volcanic unrest through geodetic data assimilation
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
-
Oil reservoir characterization using ensemble data assimilation
… The proposed algorithm uses an ensemble data assimilation approach to provide stochastic characterization of reservoir attributes by conditioning individual prior ensemble members on dynamic production observations at wells. The conditioning is based on the second-order Kalman filter …
-
Parameterizing transport maps for ensemble data assimilation
This thesis discusses methods for Bayesian parameter estimation, particularly in the case of state space models (SSMs). We begin by reviewing established methods for filtering in SSMs, and by examining the graphical model structure of a parameterized SSM. Then we discuss established methods for …
-
Carbon Data Assimilation Using an Ensemble Kalman Filter
As a first step to build an ensemble data assimilation and source inversion system for atmospheric carbon, I implemented column-integrated carbon monoxide (CO) mixing ratio assimilation capability in an ensemble Kalman filter (EnKF) data assimilation system with the Weather Research and Forecasting …
-
Real-time data assimilation in nonlinear dynamical systems
… goal of this thesis is to develop real-time data assimilation methods, which are applied to create digital twins of thermoacoustic instabilities. Central to digital twins are physics-based low-order models and experimental data. On the one hand, low-order models are computationally cheap, but …
-
Evolutionary data assimilation at Long Valley Caldera, CA
… are methods for combining extensive monitoring data sets with dynamic models. Sequential data assimilation has been shown to be powerful approach for linking models and data to improve the use of both. One such approach, Evolutionary Data Assimilation (EDA), previously used in hydrological …
-
High order stochastic transport and Lagrangian data assimilation
… (DO) approach. The second goal is to merge data from both Eulerian and Lagrangian observations with predictions such that the whole information content of observations is utilized. In the first part of this thesis, we develop high-order numerical schemes for the DO equations that ensure …
-
Multi-sensor rainfall data assimilation using ensemble approaches
… from the atmosphere to the surface. Rainfall data is needed over large scales for improved understanding of the Earth climate system. Although there are many instruments for measuring rainfall, none of them can provide continuous global coverage at fine spatial and temporal resolutions. This …
-
Computational Tools for Chemical Data Assimilation with CMAQ
… sensitivity analysis and chemical data assimilation. This thesis presents the construction, validation, and properties of new adjoint modules in CMAQ, and illustrates their use in sensitivity analyses and data assimilation experiments. The new module of discrete adjoint of advection …
-
Stochastic Data Assimilation Approaches For Magnetic Resonance Temperature Imaging
… validation, and implementation of stochastic data-driven processing techniques to increase the robustness of MR temperature monitoring during thermal therapies. MR temperature imaging was demonstrated to achieve a high degree of accuracy in damage predictions during rapid ablation procedures. …
-
Data assimilation for verification of dry storage cask content
… between calculated and measured results by a data consistency indicator χ². Conventional statistical tests using the χ² value can be used to eliminate proposed cask loadings which are too-inconsistent with experimental measurements, but cannot be used to accept any particular cask loading and …
-
WRF-Var implementation for data assimilation experimentation at MIT
… to implement the WRF model with 3D variational assimilation (3DVAR) at MIT. A working version of WRF extends the scope of experimentation to mesoscale problems in both real and idealized scenarios. A state-of-the-art model and assimilation package can now be used to conduct science or as a …
-
Inner Shelf Circulation in Coastal Virginia: A Data Assimilation Approach
… The tidal and subtidal fields were studied using data assimilation techniques on a numerical model. The model described the spatial and temporal dynamics of the area and included vertically averaged shallow water equations. Current velocity measurements were assimilated into the model using the …
-
A dynamical system approach to data assimilation in chaotic models
The Assimilation in the Unstable Subspace (AUS) was introduced by Trevisan and Uboldi in 2004, and developed by Trevisan, Uboldi and Carrassi, to minimize the analysis and forecast errors by exploiting the flow-dependent instabilities of the forecast-analysis cycle system, which may be thought of …
Page 1 of 9