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 language | English |
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Pages (from-to) | 269-284 |
Number of pages | 16 |
Journal | Space Weather |
Volume | 17 |
Issue number | 2 |
DOIs | |
Publication status | Published - 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.
Funders | Funder number |
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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 Kurumu | 113Y213 |
Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ | STP/GEOMAGNETIC_DATA/INDICES/Kp_AP/ |
Association of Faculties of Medicine of Canada |
Keywords
- CHAMP
- GEM-CEDAR challenge
- IT models
- metrics
- thermospheric neutral density
- validation