Ionospheric Scintillation Neural Network Prediction System
Carlos Molina, Adriano Camps - UPC/IEEC © 2025Neural network-based prediction of ionospheric scintillation parameters using Rino's theory. Configure geophysical conditions and system parameters below.
Configure the parameters in the left panel and click "Generate Scintillation Map" to create global predictions.
IonoSciNN employs neural networks trained on extensive observational datasets to predict ionospheric scintillation input parameters for Rino's weak scintillation theory (CkL, and q).
C. Molina, B. E. B. Semlali, H. Park and A. Camps, "A Neural Network Approach to Predict the Ionospheric Scintillation Wbmod Model Variables," IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 7731-7733, doi: 10.1109/IGARSS52108.2023.10282900.
C. Molina and A. Camps, "An Improved Neural-Network to Estimate the Inputs of Rino's Ionospheric Scintillation Model," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, under revision (2025).