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 8 of 8 for “"4D-Var"”.
-
A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation
… the state of knowledge in four dimensional variational (4D-Var) - data assimilation by developing, implementing, and validating a novel computational framework for estimating observation impact and for optimizing sensor networks. The framework builds on the powerful methodologies of …
-
Uncertainty Quantification and Uncertainty Reduction Techniques for Large-scale Simulations
… Kalman filter (EnKF) and the four-dimensional variational (4D-Var) approach. Each method has its advantages and disadvantages. By exploring the error reduction directions generated in the 4D-Var optimization process, we propose a hybrid approach to construct the error covariance matrix and to …
-
Data assimilation and dynamical downscaling of remotely-sensed precipitation and soil moisture from space
… moisture, and other relevant hydrometeorological variables. This is particularly useful with the active Global Precipitation Measurement and Soil Moisture Active Passive missions. The system consists of two major components: (1) a framework for dynamic downscaling of satellite precipitation …
-
Computational Tools for Chemical Data Assimilation with CMAQ
… advection adjoints on data assimilation, various four dimensional variational (4D-Var) data assimilation experiments are carried out with the 1D advection PDE, and with CMAQ advection using synthetic and real observation data. The results show that optimization procedure gives better …
-
Development of a Python-based Data Assimilation Framework (PyDAF). Case Study: Refining Ammonia Emissions Through Observation Data
… CMAQ and WRF-Chem models with iFDMB, 3D-VAR, 4D-VAR, and adjoint methods, using IASI, CrIS, satellite, and Nexrad radar data. For the validation, the Complex Variable Method and pseudo observations are employed. Applying PyDAF, we analyzed an ozone (O3) exceedance in Seoul on June 3, …
-
Development of a Python-based Data Assimilation Framework (PyDAF). Case Study: Refining Ammonia Emissions Through Observation Data
… CMAQ and WRF-Chem models with iFDMB, 3D-VAR, 4D-VAR, and adjoint methods, using IASI, CrIS, satellite, and Nexrad radar data. For the validation, the Complex Variable Method and pseudo observations are employed. Applying PyDAF, we analyzed an ozone (O3) exceedance in Seoul on June 3, …
-
Efficient Computational Tools for Variational Data Assimilation and Information Content Estimation
… most widely used chemical transport models: Harvard's GEOS-Chem global model and for Environmental Protection Agency's regional CMAQ regional air quality model. Both GEOS-Chem and CMAQ adjoint models are now used by the atmospheric science community to perform sensitivity analysis and data …
-
Large-Scale Simulations Using First and Second Order Adjoints with Applications in Data Assimilation
In large-scale air quality simulations we are interested in the influence factors which cause changes of pollutants, and optimization methods which improve forecasts. The solutions to these problems can be achieved by incorporating adjoint models, which are efficient in computing the derivatives of …