scholarly journals An empirical model (CH-Therm-2018) of the thermospheric mass density derived from CHAMP

2018 ◽  
Author(s):  
Chao Xiong ◽  
Hermann Lühr ◽  
Michael Schmidt ◽  
Mathis Bloßfeld ◽  
Sergei Rudenko
Keyword(s):  
Empirical Model ◽  
Solar Minimum ◽  
Mass Density ◽  
Precise Orbit Determination ◽  
Wave Pattern ◽  
Magnetic Activity ◽  
Low Earth Orbit ◽  
Naval Research ◽  
Champ Satellite ◽  
Incoherent Scatter

Abstract. Thermospheric drag is the major non-gravitational perturbation acting on Low Earth Orbit (LEO) satellites at altitudes up to 1000 km. The drag depends on the thermospheric density, which is a key parameter in the planning of LEO missions, e.g. their lifetime, collision avoidance, precise orbit determination, as well as orbit and re-entry prediction. In this study, we present an empirical model, named CH-Therm-2018, of the thermospheric mass density derived from 9-year (from August 2000 to July 2009) accelerometer measurements at altitude from 460 to 310 km, from the CHAllenging Minisatellite Payload (CHAMP) satellite. The CHAMP dataset is divided into two 5-year periods with 1-year overlap (from August 2000 to July 2005 and from August 2004 to July 2009), to represent the high-to-moderate and moderate-to-low solar activity conditions, respectively. The CH-Therm-2018 model is a function of seven key parameters, including the height, solar flux index, season (day of year), magnetic local time, geographic latitude and longitude, as well as magnetic activity represented by the solar wind merging electric field. Predictions of the CH-Therm-2018 model agree well with the CHAMP observations (disagreements within ±20 %), and show different features of thermospheric mass density during solar activities, e.g. the March-September equinox asymmetry and the longitudinal wave pattern. We compare the CH-Therm-2018 predictions with the Naval Research Laboratory Mass Spectrometer Incoherent Scatter Radar Extended (NRLMSISE-00) model. The result shows that CH-Therm-2018 better predicts the density evolution during the last solar minimum (2008-2009) than the NRLMSISE-00 model. By comparing the Satellite Laser Ranging (SLR) observations of the ANDE-Pollux satellites during August-September 2009, we estimate 6-h scaling factors of thermospheric mass density and obtain a median value of 1.27 ± 0.60, indicating that our model, on average, slightly underestimates the thermospheric mass density at solar minimum.

scholarly journals An empirical model of the thermospheric mass density derived from CHAMP satellite

2018 ◽  
Vol 36 (4) ◽  
pp. 1141-1152 ◽  
Author(s):  
Chao Xiong ◽  
Hermann Lühr ◽  
Michael Schmidt ◽  
Mathis Bloßfeld ◽  
Sergei Rudenko
Keyword(s):  
Solar Activity ◽  
Empirical Model ◽  
Mass Density ◽  
Scale Up ◽  
Wave Pattern ◽  
Magnetic Activity ◽  
Naval Research ◽  
Activity Levels ◽  
Champ Satellite ◽  
Incoherent Scatter

Abstract. In this study, we present an empirical model, named CH-Therm-2018, of the thermospheric mass density derived from 9-year (from August 2000 to July 2009) accelerometer measurements from the CHAllenging Mini-satellite Payload (CHAMP) satellite at altitudes from 460 to 310 km. The CHAMP dataset is divided into two 5-year periods with 1-year overlap (from August 2000 to July 2005 and from August 2004 to July 2009) to represent the high-to-moderate and moderate-to-low solar activity conditions, respectively. The CH-Therm-2018 model describes the thermospheric density as a function of seven key parameters, namely the height, solar flux index, season (day of year), magnetic local time, geographic latitude and longitude, as well as magnetic activity represented by the solar wind merging electric field. Predictions of the CH-Therm-2018 model agree well with CHAMP observations (within 20 %) and show different features of thermospheric mass density during the two solar activity levels, e.g., the March–September equinox asymmetry and the longitudinal wave pattern. From the analysis of satellite laser ranging (SLR) observations of the ANDE-Pollux satellite during August–September 2009, we estimate 6 h scaling factors of the thermospheric mass density provided by our model and obtain the median value equal to 1.267±0.60. Subsequently, we scale up our CH-Therm-2018 mass density predictions by a scale factor of 1.267. We further compare the CH-Therm-2018 predictions with the Naval Research Laboratory Mass Spectrometer Incoherent Scatter Radar Extended (NRLMSISE-00) model. The result shows that our model better predicts the density evolution during the last solar minimum (2008–2009) than the NRLMSISE-00 model.

A simultaneous calibration and data assimilation (C/DA) to improve NRLMSISE00 using thermospheric neutral density (TND) from space-borne accelerometer measurements

2020 ◽  
Vol 224 (2) ◽  
pp. 1096-1115
Author(s):  
E Forootan ◽  
S Farzaneh ◽  
M Kosary ◽  
M Schmidt ◽  
M Schumacher
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Precise Orbit Determination ◽  
Low Earth Orbit ◽  
Model Parameters ◽  
Neutral Density ◽  
Incoherent Scatter ◽  
Drag Forces ◽  
Gravity Recovery ◽  
Limited Accuracy

SUMMARY Improving thermospheric neutral density (TND) estimates is important for computing drag forces acting on low-Earth-orbit (LEO) satellites and debris. Empirical thermospheric models are often used to compute TNDs for the precise orbit determination experiments. However, it is known that simulating TNDs are of limited accuracy due to simplification of model structure, coarse sampling of model inputs and dependencies to the calibration period. Here, we apply TND estimates from accelerometer measurements of the Challenging Minisatellite Payload (CHAMP) and the Gravity Recovery and Climate Experiment (GRACE) missions as observations to improve the NRLMSISE-00 model, which belongs to the mass spectrometer and incoherent scatter family of models. For this, a novel simultaneous calibration and data assimilation (C/DA) technique is implemented that uses the ensemble Kalman filter and the ensemble square-root Kalman filter as merger. The application of C/DA is unique because it modifies both model-derived TNDs, as well as the selected model parameters. The calibrated parameters derived from C/DA are then used to predict TNDs in locations that are not covered by CHAMP and GRACE orbits, and forecasting TNDs of the next day. The C/DA is implemented using daily CHAMP- and/or GRACE-TNDs, for which compared to the original model, we find 27 per cent and 62 per cent reduction of misfit between model and observations in terms of root mean square error and Nash coefficient, respectively. These validations are performed using the observations along the orbital track of the other satellite that is not used in the C/DA during 2003 with various solar activity. Comparisons with another empirical model, that is, Jacchia-Bowman, indicate that the C/DA results improve these quality measurements on an average range of 50 per cent and 60 per cent, respectively.

The Martian ionosphere at solar minimum: Empirical model validation using MAVEN ROSE data

Icarus ◽  
2021 ◽  
pp. 114609
Author(s):  
Sophie R. Phillips ◽  
Clara Narvaez ◽  
František Němec ◽  
Paul Withers ◽  
Marianna Felici ◽  
...  
Keyword(s):  
Model Validation ◽  
Empirical Model ◽  
Solar Minimum ◽  
Martian Ionosphere

scholarly journals The Accuracy of Real-Time hmF2 Estimation from Ionosondes

2020 ◽  
Vol 12 (17) ◽  
pp. 2671
Author(s):  
Carlo Scotto ◽  
Dario Sabbagh
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Root Mean Square ◽  
Magnetic Activity ◽  
Mean Square ◽  
Incoherent Scatter Radar ◽  
Incoherent Scatter ◽  
Scatter Radar ◽  
Mean Square Errors

A total of 4991 ionograms recorded from April 1997 to December 2017 by the Millstone Hill Digisonde (42.6°N, 288.5°E) were considered, with simultaneous Ne(h)[ISR] profiles recorded by the co-located Incoherent Scatter Radar (ISR). The entire ionogram dataset was scaled with both the Autoscala and ARTIST programs. The reliability of the hmF2 values obtained by ARTIST and Autoscala was assessed using the corresponding ISR values as a reference. Average errors Δ and the root mean square errors RMSE were computed for the whole dataset. Data analysis shows that both the Autoscala and ARTIST systems tend to underestimate hmF2 values with |Δ| in all cases less than 10 km. For high magnetic activity ARTIST offers better accuracy than Autoscala, as evidenced by RMSE[ARTIST] < RMSE[Autoscala], under both daytime and nighttime conditions, and considering all hours of the day. Conversely, under low and medium magnetic activity Autoscala tends to estimate hmF2 more accurately than the ARTIST system for both daytime and nighttime conditions, when RMSE[Autoscala] < RMSE[ARTIST]. However, RMSE[Autoscala] slightly exceeds RMSE[ARTIST] for the day as a whole. RMSE values are generally substantial (RMSE > 16 km in all cases), which places a limit on the results obtainable with real-time models that ingest ionosonde data.

scholarly journals Empirical model of equatorial electrojet based on ground-based magnetometer data during solar minimum in fall

2015 ◽  
Vol 67 (1) ◽  
Author(s):  
Nurul Shazana Abdul Hamid ◽  
Huixin Liu ◽  
Teiji Uozumi ◽  
Akimasa Yoshikawa
Keyword(s):  
Empirical Model ◽  
Solar Minimum ◽  
Equatorial Electrojet ◽  
Magnetometer Data
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