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Thermospheric Density Nowcasting and Forecasting

Ching-Chung
Cheng
SWx TREC, University of Colorado Boulder
Abstract text

Whole Atmosphere Model (WAM) is operated by NOAA’s Space Weather Prediction Center (SWPC) and simulates the whole atmosphere neutral compositions in real time, while WAM tended to have a positive bias compared to various observations. SpaceX is operating thousands of Starlink satellites, and the orbit-averaged densities can be derived by monitoring the dissipation of orbital energy. The Starlink density estimates from January–April 2023 were assimilated to WAM, using the Iterative Driver Estimation and Assimilation (IDEA) data assimilation (DA) technique. The study period covers four solar rotations and two moderate storms. Results show that the data assimilative WAM density (WAM-DA) effectively captured the Starlink orbit-averaged density during both quiet and storm time, with a root-mean-square error (RMSe) at 4.6%. In addition, a cross-comparison was conducted with the accelerometer estimates of neutral density from GRACE-FO. The good agreement (RMSe = 6.5%) between WAM-DA and GRACE-FO shows that the Starlink neutral density estimates could be used to improve the WAM neutral density outputs in the IDEA DA scheme. A 2-day neutral density forecast has also been performed to evaluate the performance in the forecast mode with DA initial conditions and issued forecasted solar wind drivers. With the rapid growth in the number of spacecraft and debris objects in LEO (Low Earth Orbis), reducing neutral density uncertainty remains one of the most effective ways to improve orbit prediction and collision avoidance, and this study can be of benefit to improve thermospheric neutral density specification.

Authors
Ching-Chung Cheng, SWx TREC, CU Boulder
Eric Sutton, SWx TREC, CU Boulder
Tzu-Wei Fang, NOAA SWPC
Zhuxiao Li, CIRES, CU Boulder
Timothy Fuller-Rowell, NOAA SWPC
Non-Student
Poster category
DATA - Data Assimilation, Data Analytics, Methods and Management
Poster number
2