Flow-Dependent Optimization of the Observation Performance in NASA GEOS Hybrid 4D-EnVar ADAS
NASA - Weather and Atmospheric Dynamics, 2023 - 2026
Robust and Efficient Adaptive Covariance Tuning for Hybrid Ensemble-Variational Atmospheric Data Assimilation
Naval Research Laboratory, 2019 - 2022
Error Covariance Diagnosis and Impact Estimation in NASA GEOS DAS
NASA - Modeling, Analysis, and Prediction Program, 2013 - 2017
Adaptive Optimization of Parametric Error
Covariance Models in Variational Data Assimilation
Naval Research Laboratory, 2013 - 2016
Collaborative Research: A Computational Framework for Assessing the Observation Impact in Air Quality Forecasting
NSF Division of Mathematical Sciences, Program in Computational Mathematics, 2009 - 2013
Adjoint-based Data Assimilation System Sensitivity, Diagnostics, and Estimation of Input Error Statistics
Naval Research Laboratory, 2010 - 2012
Optimization of the Information Error Statistics in Multi-Sensor
Atmospheric Data Assimilation
2011 NASA Earth and Space Science Fellowship Program 2011 - 2012
Development of a new methodology for adaptive observations in the framework of four-dimensional variational data assimilation
NASA - Modeling, Analysis, and Prediction Program, 2005-2009
High Performance Computing in Applied Mathematics at PSU
2006 Intel Oregon Faculty Fellowship
Cyber-Enabled Ensemble Data Assimilation
for Drought Monitoring, Forecasting and Recovery
NSF Office of Multidisciplinary AC, CyberSEES, Applied Mathematics 2015-2018
PI: Hamid Moradkhani, Co-PI: Karen Karavanic, Portland State University
Collaborative Research: IPY, the Next Generation: A Community Ice Sheet Model for
scientists and educators with demonstration experiments in the Amundsen Sea Embayment
NSF International Polar Year Program 2007-2008
PI C. Hulbe, Portland State University
CMG Collaborative Research:
Ensemble data assimilation based on control theory
NSF Collaborations in Mathematical Geosciences Program, 2003-2006
PI I.M. Navon, Florida State University