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A comparison of the effects of initializing different thermosphere‐ionosphere model fields on storm time plasma density forecasts
Author(s) -
Chartier Alex T.,
Jackson David R.,
Mitchell Cathryn N.
Publication year - 2013
Publication title -
journal of geophysical research: space physics
Language(s) - English
Resource type - Journals
eISSN - 2169-9402
pISSN - 2169-9380
DOI - 10.1002/2013ja019034
Subject(s) - data assimilation , thermosphere , ionosphere , geomagnetic storm , storm , initialization , environmental science , meteorology , total electron content , atmospheric sciences , computer science , tec , plasma , geology , geophysics , physics , solar wind , quantum mechanics , programming language
Data assimilation has been used successfully for real‐time ionospheric specification, but it has not yet proved advantageous for forecasting. The most challenging and important ionospheric events to forecast are storms. The work presented here examines the effectiveness of data assimilation in a storm situation, where the initial conditions are known and the model is considered to be correct but the external solar and geomagnetic drivers are poorly specified. The aim is to determine whether data assimilation could be used to improve storm time forecast accuracy. The results show that, in the case of the storm of Halloween 2003, changes made to the model's initial thermospheric conditions improve electron density forecasts by at least 10% for 18 h, while changes to ionospheric fields alone result in >10% forecast accuracy improvement for less than 4 h. Further examination shows that the neutral composition is especially important to the accuracy of ionospheric electron density forecasts. Updating the neutral composition gives almost all the benefits of updating the complete thermospheric state. A comparison with real, globally distributed observations of vertical total electron content confirms that updating the thermospheric composition can improve forecast accuracy.