Next-generation Ionospheric Model for Operations &ndash; Validation and Demonstration for Space Weather and Research

Burrell, Angeline G.; McDonald, Sarah E.; Hickey, Dustin A.; Burleigh, Meghan R.; Nossa, Eliana; Metzler, Christopher A.; Dhadly, Manbharat; Tate, Jennifer; Wagner, Ellen J.

doi:https://doi.org/10.5194/egusphere-2025-4967

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https://doi.org/10.5194/egusphere-2025-4967

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16 Oct 2025

| 16 Oct 2025

Status: this preprint is open for discussion and under review for Annales Geophysicae (ANGEO).

Next-generation Ionospheric Model for Operations – Validation and Demonstration for Space Weather and Research

Angeline G. Burrell, Sarah E. McDonald, Dustin A. Hickey, Meghan R. Burleigh, Eliana Nossa, Christopher A. Metzler, Manbharat Dhadly, Jennifer Tate, and Ellen J. Wagner

Abstract. The Next-generation Ionospheric Model for Operations (NIMO) is an assimilative geospace model developed to address the space weather operational needs in the ionosphere. NIMO harnesses contributions from both near real-time data and state-of-the-art implementation of ionospheric theory to provide hindcasts, nowcasts, and forecasts for operational or research purposes. NIMO is currently configured to assimilate various types of electron density measurements through the Ionospheric Data Assimilation Four-Dimensional (IDA-4D) data assimilation schema. Information from the neutral atmosphere is provided by empirical models. The ionospheric chemistry and transport calculations are handled within NIMO using a version of SAMI3 is also a Model of the Ionosphere (SAMI3) designed to have a realistic geomagnetic field and work effectively on a parallel processing system. This article discusses how NIMO is configured, demonstrates potential use cases for the research community, and validates hindcast runs using a new suite of metrics designed to allow repeatable, quantitative, model-independent evaluations against publicly available observations that may be adopted by any ionospheric global circulation or regional space weather model.

Received: 07 Oct 2025 – Discussion started: 16 Oct 2025

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Angeline G. Burrell, Sarah E. McDonald, Dustin A. Hickey, Meghan R. Burleigh, Eliana Nossa, Christopher A. Metzler, Manbharat Dhadly, Jennifer Tate, and Ellen J. Wagner

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RC1:
'Comment on egusphere-2025-4967', Anonymous Referee #1, 04 Nov 2025 reply
Title: Next-generation Ionospheric Model for Operations (NIMO): Validation and Demonstration for Space Weather and Research

Authors: A. G. Burrell et al.

Journal: EGUsphere

Recommendation: Moderate revision before acceptance
General Comments
This paper presents the Next-generation Ionospheric Model for Operations (NIMO), a data assimilation, physics-based system that combines the SAMI3 model with the IDA-4D framework. The authors provide a detailed description of the model configuration and a validation using multiple data sources, including ionosondes, incoherent scatter radars, GPS TEC, JASON altimetry, and in-situ plasma density from CINDI, DMSP, and ICON.
Overall, this is a well-structured contribution to the ionospheric modelling and space weather community. It demonstrates NIMO’s ability to deliver high-fidelity ionospheric specifications and forecasts and to outperform empirical models such as IRI-2016 under various geomagnetic conditions.
The study is methodologically sound, comprehensive, and of clear relevance for both research and operational use. However, a few issues require clarification or enhancement before publication.
Specifically, the manuscript would benefit from:
a clearer statement of novelty relative to existing assimilative models.

greater transparency in validation design (distinguishing assimilated from independent data)

some improve readability and reproducibility.

With these improvements, I would recommend acceptance after minor to moderate revision.
Specific Comments
The manuscript gives an overview of NIMO’s structure but does not fully highlight how it differs from previous SAMI3/IDA-4D configurations or other assimilative systems. A concise comparison of capabilities and computational improvements would strengthen the case for novelty.

Several of the validation datasets (ionosondes and GPS TEC) are also assimilated into NIMO. The authors acknowledge this but the distinction between assimilated and independent datasets should be made explicit.

Validation against IRI-2016 is appropriate for a first version, but the authors should discuss briefly why other empirical or assimilative models were not included. If such comparisons are reserved for future work, this should be mentioned in the discussion.

Figure 6 adds little beyond methodological illustration and could be moved to Supplementary Material

The discussion section could more explicitly quantify the improvement of NIMO over IRI-2016 (percentage reduction in RMSE or increase in correlation).

When describing storm-time performance (March 2015 run), it would be valuable to show a figure illustrating NIMO’s dynamic response versus IRI.

The conclusion could briefly describe operational readiness to substantiate the claim that NIMO is suitable for real-time space weather operations.

Technical Corrections
#118: “knowledgable” → “knowledgeable”

#125: “hmF2 has an added complication that the conversion…” → “hmF2 estimation is complicated by the conversion…”

“Data base” or “database” (ensure consistency)

Avoid repetitive phrasing such as “NIMO outperformed IRI-2016…”

There are some acronyms not defined at first use.

Summary tables could be moved from the main text to a supplementary appendix.

Improve figure readability (axes labels, font size, color balance).

Provide DOI or URL references for the datasets used (COSMIC-2, Madrigal, JASON, ICON).

Summary Recommendation
Decision: Recommended for publication after minor revision.
Suggested Actions Before Acceptance
Clarify the novelty and operational improvements of NIMO relative to other models.

Explicitly separate assimilated from independent validation datasets.

Improve figure readability and reduce redundancy in tables.

Revise minor grammatical errors.

Overall assessment:

This manuscript represents a valuable contribution to the field of space weather modelling. After addressing the relatively minor methodological clarifications and presentation issues listed above, it will merit acceptance for publication in Annales Geophysicae (or equivalent EGU journal).

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Citation: https://doi.org/10.5194/egusphere-2025-4967-RC1

Angeline G. Burrell, Sarah E. McDonald, Dustin A. Hickey, Meghan R. Burleigh, Eliana Nossa, Christopher A. Metzler, Manbharat Dhadly, Jennifer Tate, and Ellen J. Wagner

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Short summary

The Next-generation Ionospheric Model for Operations (NIMO) is a space weather model developed to provide historic, current, and forecasted information about the density of the ionosphere. This article discusses how NIMO is configured, demonstrates potential use cases for the research community, and validates historic runs using a new suite of metrics designed to allow repeatable, quantitative, model-independent evaluations against observations that may be adopted by other ionospheric models.


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