IonoBench Datasets

IonoBench: Evaluating Spatiotemporal Models for Ionospheric Forecasting under Solar-Balanced and Storm-Aware Conditions
Published in Remote Sensing (MDPI)

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These datasets is part of the IonoBench Evaluation Framework, designed to benchmark spatiotemporal deep learning models for ionospheric TEC forecasting across varying solar and geomagnetic conditions.

Highlights

• Stratified Train/Val/Test Splits:

  • Balanced across solar activity levels to support unbiased model training and evaluation
  • Dataset includes 88 geomagnetic storms with the test set comprising 16 geomagnetic storms, with 14 intense (−250 nT ≤ Dst ≤ −100 nT) and 2 superintense (Dst < −250 nT) events

• Chronological Version (also available):

  • Uses natural temporal order for operational forecasting scenario validation

• Covers SC23–SC25 for comprehensive model evaluation under diverse space weather conditions

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Additional Included Resources

• C1PG 1-day CODE Prediction Product
  Provided for baseline comparison with learned models

• IGS VTEC Maps
  Serve as reference (ground truth) for evaluating model and C1PG predictions

• OMNIWeb Solar Parameters File
  Contains solar wind, geomagnetic, and interplanetary conditions at 1-hour resolution

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Dataset Contents

• Dates: Datetime array for each sample
• NormTEC: 71×73 normalized TEC maps (min-max scaled using MinTEC, MaxTEC)
• NormOMNI: 17 normalized OMNI parameters per sample
• OMNI_Names: List of OMNI parameter names
• split_dates: Dictionary of stratified train/val/test period ranges
• stormDetails: Metadata on all 88 included storm periods
• MaxTEC, MinTEC: Global TEC scaling constants for denormalization

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Data Sources

• The IGS GIM and C1PG data are publicly available at https://cddis.nasa.gov/archive/gnss/products (accessed on 23 July 2025).
• Solar and Geomagnetic Parameters: OMNI2 via NASA GSFC OMNIWeb (SPDF) can be accessed via https://omniweb.gsfc.nasa.gov (accessed on 23 July 2025).

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Citation

If you use these datasets, please cite:

Mert C. Turkmen, Yee Hui Lee, Eng Leong Tan (2025).
IonoBench: Evaluating Spatiotemporal Models for Ionospheric Forecasting under Solar-Balanced and Storm-Aware Conditions.
Remote Sensing, 17(15), 2557. https://doi.org/10.3390/rs17152557

And cite the original data providers:

• Hernández-Pajares, M.; et al. The IGS VTEC maps: A reliable source of ionospheric information since 1998. J. Geod. 2009, 83, 263–275. https://doi.org/10.1007/s00190-008-0266-1.
• King, J.H.; Papitashvili, N.E. Solar wind spatial scales and comparisons of hourly Wind and ACE plasma and magnetic field data. J. Geophys. Res. 2005, 110, 2004JA010649. https://doi.org/10.1029/2004JA010649.

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