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Showing 1 to 9 of 9 for “"ensemble data assimilation"”.

  1. Oil reservoir characterization using ensemble data assimilation

    … and properties. 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 …

    mit Repository record for Oil reservoir characterization using ensemble data assimilation (opens in a new tab)

  2. Parameterizing transport maps for ensemble data assimilation

    … at length over the course of the thesis work: EnsembleFiltering.jl, written in Julia for performing automatically-differentiable ensemble-based filtering on the CPU and GPU; and MParT, written in C++ for evaluating and training monotone triangular transport maps.

    mit Repository record for Parameterizing transport maps for ensemble data assimilation (opens in a new tab)

  3. Multivariate Correlations: Balance Operators and Variable Localization in Ensemble Data Assimilation

    Localization is performed in ensemble data assimilation schemes to eliminate correlations that are contaminated by sampling error. This method is frequently necessary within numerical weather prediction (NWP) applications due to the computational constraints present, limiting the number of ensemble

    maryland Repository record for Multivariate Correlations: Balance Operators and Variable Localization in Ensemble Data Assimilation (opens in a new tab)

  4. Combining Data-driven and Theory-guided Models in Ensemble Data Assimilation

    There once was a dream that data-driven models would replace their theory-guided counterparts. We have awoken from this dream. We now know that data cannot replace theory. Data-driven models still have their advantages, mainly in computational efficiency but also providing us with some special …

    vt Repository record for Combining Data-driven and Theory-guided Models in Ensemble Data Assimilation (opens in a new tab)

  5. 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 …

    mit Repository record for Multi-sensor rainfall data assimilation using ensemble approaches (opens in a new tab)

  6. 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 …

    york Repository record for Carbon Data Assimilation Using an Ensemble Kalman Filter (opens in a new tab)

  7. Tropical observability and predictability

    Many studies have investigated tropical data assimilation in the context of global models or specifically for tropical cyclones, but relatively few have focused on the mesoscale predictability and observability of the general tropical environment. This work constructs an ensemble data assimilation

    mit Repository record for Tropical observability and predictability (opens in a new tab)

  8. Data Driven Prediction Without a Model

    Ensemble data assimilation techniques, including the Ensemble Transform Kalman Filter (ETKF), have been successfully used to improve prediction skill in numerical models for weather forecasting. However, less research has been conducted on data assimilation techniques for systems with no numerical …

    maryland Repository record for Data Driven Prediction Without a Model (opens in a new tab)

  9. 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 …

    cambridge Repository record for Real-time data assimilation in nonlinear dynamical systems (opens in a new tab)