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funding. References 1. Small-scale reconstruction in three-dimensional Kolmogorov flows using four-dimensional variational data assimilation (https://www.cambridge.org/core/journals/journal-of-fluid
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 22 days ago
(GMAO), is a comprehensive Earth system model and data assimilation system. The GMAO assimilates aerosol optical depth (AOD) observations from space-borne (e.g. MODIS, VIIRS) and ground-based (AERONET
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 23 days ago
. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The Goddard Earth Observing System (GEOS) global 4D hybrid Ensemble-Variational (EnVar) data assimilation
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are seeking a highly motivated candidate to strengthen our enthusiastic research group, Data Assimilation and Optimization, working at the forefront of ensemble-based data assimilation methodology, optimization
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 21 days ago
distribution on a global scale. This project will focus on developing a strategy to best utilize this data in a global atmospheric data assimilation framework. Activities that would be involved in this project
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innovative tools combining high-fidelity simulations based on a Lattice Boltzmann Method (LBM) CFD code with advanced data assimilation techniques, notably the Ensemble Kalman Filter (EnKF). By integrating
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of Community Multiscale Air Quality program (CMAQ), Sparse Matrix Operator Kerner Emissions program (SMOKE), Data Assimilation, Surrogate Tools, and other modeling skillsets. Instructions to Applicants: For full
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. Skills: Applicants should have a strong foundation in the practice of clinical veterinary medicine; the ability to utilize and assimilate available clinical information to make decisions regarding patient
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modelling techniques and the embedding of such models within data assimilation frameworks to enable their self-correction. During this project, you will develop expertise in machine learning-based reduced
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, retrieval models informed by routinely available remote sensing data in the visible-near infrared spectrum, or more complex land surface models which assimilate those data. However, biophysical variables