Quantifying the Storm Time Thermospheric Neutral Density Variations Using Model and Observations

E. Ceren Kalafatoglu Eyiguler*, J. S. Shim, M. M. Kuznetsova, Z. Kaymaz, B. R. Bowman, M. V. Codrescu, S. C. Solomon, T. J. Fuller-Rowell, A. J. Ridley, P. M. Mehta, E. K. Sutton

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Accurate determination of thermospheric neutral density holds crucial importance for satellite drag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and three physics-based models of the ionosphere-thermosphere are compared with the neutral densities along the Challenging Micro-Satellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias), (2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set of metrics for the neutral density.

Original languageEnglish
Pages (from-to)269-284
Number of pages16
JournalSpace Weather
Volume17
Issue number2
DOIs
Publication statusPublished - Feb 2019

Bibliographical note

Publisher Copyright:
©2019. American Geophysical Union. All Rights Reserved.

Funding

This work has been supported by the Turkish Scientific and Technological Council (TÜBİTAK), project 113Y213 and 2214/A‐International Doctoral Research Fellowship Programme. We thank the producers of the Dst index at WDC, Kyoto (http://wdc.kugi.kyoto‐u. ac.jp/), and GFZ, Potsdam, for the Kp index values (ftp://ftp.ngdc.noaa.gov/ STP/GEOMAGNETIC_DATA/ INDICES/Kp_AP/). HP index values were obtained from cedarweb (https:// cedarweb.vsp.ucar.edu/wiki/index. php/Tools_and_Models:Emery_HP_ plus_indices_to_11107). F10.7 values were accessed from ftp://ftp.ngdc.noaa. gov/STP/space‐weather/solar‐data/ solar‐features/solar‐radio/noontime‐ flux/penticton/penticton_observed/ listings/listing_drao_noontime‐flux‐ observed_daily.txt. We thank all of the abovementioned for giving open access to the data. Neutral density data were obtained from https://drive.google. com/drive/folders/0BwtX8XEH‐ aEueHJiU1htLVo0cms?usp=drive_ open provided by Mehta et al. (2017). Model runs and results are made available through the NASA Community Coordinated Modeling Center (CCMC) through their public Runs on Request system (http://ccmc. gsfc.nasa.gov). Model results for the individual simulations can be searched from the CCMC‐View Results with the Simulation IDs listed in Table S1. The CCMC is a multiagency partnership between NASA, AFMC, AFOSR, AFRL, AFWA, NOAA, NSF, and ONR. Lastly, we thank the reviewers and especially editor Michael A. Hapgood for their valuable comments, which improved our paper. This work has been supported by the Turkish Scientific and Technological Council (TÜBİTAK), project 113Y213 and 2214/A-International Doctoral Research Fellowship Programme. We thank the producers of the Dst index at WDC, Kyoto (http://wdc.kugi.kyoto-u.ac.jp/), and GFZ, Potsdam, for the Kp index values (ftp://ftp.ngdc.noaa.gov/STP/GEOMAGNETIC_DATA/INDICES/Kp_AP/). HP index values were obtained from cedarweb (https://cedarweb.vsp.ucar.edu/wiki/index.php/Tools_and_Models:Emery_HP_plus_indices_to_11107). F10.7 values were accessed from ftp://ftp.ngdc.noaa.gov/STP/space-weather/solar-data/solar-features/solar-radio/noontime-flux/penticton/penticton_observed/listings/listing_drao_noontime-flux-observed_daily.txt. We thank all of the abovementioned for giving open access to the data. Neutral density data were obtained from https://drive.google.com/drive/folders/0BwtX8XEH-aEueHJiU1htLVo0cms?usp=drive_open provided by Mehta et al. (). Model runs and results are made available through the NASA Community Coordinated Modeling Center (CCMC) through their public Runs on Request system (http://ccmc.gsfc.nasa.gov). Model results for the individual simulations can be searched from the CCMC-View Results with the Simulation IDs listed in Table S1. The CCMC is a multiagency partnership between NASA, AFMC, AFOSR, AFRL, AFWA, NOAA, NSF, and ONR. Lastly, we thank the reviewers and especially editor Michael A. Hapgood for their valuable comments, which improved our paper.

FundersFunder number
Turkish Scientific and Technological Council
National Science Foundation
Office of Naval Research
National Aeronautics and Space Administration
Air Force Office of Scientific Research
National Oceanic and Atmospheric Administration
Air Force Research Laboratory
Association of Fish and Wildlife Agencies
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu113Y213
Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZSTP/GEOMAGNETIC_DATA/INDICES/Kp_AP/
Association of Faculties of Medicine of Canada

    Keywords

    • CHAMP
    • GEM-CEDAR challenge
    • IT models
    • metrics
    • thermospheric neutral density
    • validation

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