Publication Date:
2023-01-20
Description:
Abstract
Description:
Here, we present model files and example scripts for the Neural network-based model of Electron density in the Topside ionosphere (NET). The model is based on radio occultation data from Gravity Recovery And Climate Experiment (GRACE), Challenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC-1) missions from 2001 until 2019. The NET model is based on alpha-Chapman functions with a linear decay of scale height with altitude, and consists of 4 sub-models (2 parameters of the F2-peak and 2 parameters of the linear scale height decay). The model uses geographic and magnetic latitude and longitude, magnetic local time, day of year, altitude, solar flux index P10.7, geomagnetic activity index Kp, storm-time SYM-H index as inputs. An example data frame to run the model is provided, as well as the Jupyter notebook to perform an example run.
Keywords:
ionosphere
;
machine learning
;
empirical model
;
neural network
;
EARTH SCIENCE 〉 SUN-EARTH INTERACTIONS 〉 IONOSPHERE/MAGNETOSPHERE DYNAMICS
;
EARTH SCIENCE SERVICES 〉 MODELS 〉 SOLAR-ATMOSPHERE/SPACE-WEATHER MODELS
Type:
Model
,
Model
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