Space Weather Forecasting in the Ionosphere and Thermosphere Using a Dynamically Steered Incoherent Scatter Radar

Funded by NSF DDDAS Program
Dates: September 2005-August 2008.

Collaborators: Dennis S. Bernstein and Aaron Ridley

Graduate student researchers:

In Sung Kim
David Pawlowski

The goal of this project is to develop and implement algorithms for large-scale data assimilation in the ionosphere-thermosphere. The project is based on the Global Ionosphere-Thermosphere code, which is a finite-volume CFD code that includes fluid mechanics, atmospheric chemistry, and space weather drivers.

Publications:

1. I. Kim, J. Chandrasekar, A.J. Ridley, and D.S. Bernstein, "Data Assimilation Using the Global Ionosphere-Thermosphere Model," Proc. ICCS, pp. 489--496, Reading, UK, May 2006.

2. J. Chandrasekar, I.S. Kim, A.J. Ridley, and D.S. Bernstein, "Reduced-Order Covariance-Based Unscented Kalman Filtering with Complementary Steady-State Correlation," Proc. Amer. Contr. Conf., pp. 4452--4457, New York, NY, July 2007.

3. D.J. Pawlowski, A.J. Ridley, and I.S. Kim, and D.S. Bernstein, " Global Model Comparison with Millstone Hill During September 2005," submitted.

4. J. Chandrasekar, I.S. Kim, D.S. Bernstein, A.J. Ridley, "Reduced-Rank Unscented Kalman Filtering Using Cholesky-Based Decomposition," submitted.

5. S. Kim, D.J. Pawlowski, A.J. Ridley, and D.S. Bernstein, "Data Assimilation in the Ionosphere-Thermosphere Using a Localized Sampled-data Unscented Kalman Filter," submitted.