Developing Earth Upper Atmosphere Forecast Tools

An accurate estimation of variables within the upper atmosphere such as the thermospheric neutral density (TND) and the total electron content (TEC) of the ionosphere is important for many space weather, communication, and satellite-based geodetic applications. Models are often used to determine TND and TEC in these applications. However, it is known that they cannot reproduce the total variability of the thermosphere-ionosphere system including their coupling processes due to various reasons such as simplified model structure, poorly sampled input data sets, and dependencies to the calibration period. Here, we present various frameworks to integrate satellite-based measurements into empirical models to improve their prediction capability. One demonstration is carried out by applying the sequential Calibration and Data Assimilation (C/DA) framework to re-calibrate the NRLMSISE00 model, whose outputs fit well to the introduced space-borne TNDs. The new model is tested for forecasting TNDs and individual neutral mass compositions at any predefined vertical level (between ~100 and ~600 km) with user-defined spatial-temporal sampling. The second demonstration is carried out by calibrating the International Reference Ionosphere (IRI)-2016 model against GNSS measurements. The resulted model is validated against independent GNSS stations and COSMIC products. The results indicate that the C/DA approach is an efficient tool for predicting atmospheric parameter variability, to be used for mission design, navigation, and operation.