Modeling of Topside Ionospheric Vertical Scale Height Based on Ionospheric Radio Occultation Measurements

Hu, Andong; Carter, Brett; Currie, Julie; Norman, Robert; Wu, Suqin; Wang, Xiaoming; Zhang, Kefei

doi:10.1029/2018ja026280

Cited by 11 publications

(11 citation statements)

References 30 publications

(58 reference statements)

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“…From this regression we obtain VSH values of 205 km on the dayside (6 ≤ MLT < 18) and 167 km on the nightside (MLT < 6 and MLT ≥ 18). These scale heights are within the range of typical estimates at geodetic altitudes of 350-500 km (e.g., Figure 2 in Hu et al, 2019 andFigure 1b in Stankov &Jakowski, 2006).…”

Section: Appendix A: Correction and Adjustment Of Nesupporting

confidence: 83%

“…From 380 conjunctions between Swarm B and either Swarm A or Swarm C for which Swarm LP data are currently available (December 2013 through February 2020), we derive the Vertical Scale Height VSH ≡ dh∕(d ln N e ) (e.g., Hu et al, 2019). We use "robust regression" (e.g., Holland & Welsch, 1977;Huber, 1973) to estimate VSH from the ratio of plasma density measurements during the 380 identified conjunctions ( Figure S2c in supporting information).…”

Section: Appendix A: Correction and Adjustment Of Nementioning

confidence: 99%

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Seasonal and Hemispheric Asymmetries of F Region Polar Cap Plasma Density: Swarm and CHAMP Observations

et al. 2020

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One of the primary mechanisms of loss of Earth's atmosphere is the persistent "cold" (T ≲ 20 eV) ion outflow that has been observed in the magnetospheric lobes over large volumes with dimensions of order several Earth radii. As the main source of this cold ion outflow, the polar cap F region ionosphere and conditions within it have a disproportionate influence on these magnetospheric regions. Using 15 years of measurements of plasma density N e made by the Swarm spacecraft constellation and the Challenging Mini Satellite Payload (CHAMP) spacecraft within the F region of the polar cap above 80 • Apex magnetic latitude, we report evidence of several types of seasonal asymmetries in polar cap N e. Among these, the transition between "winter-like" and "summer-like" median polar cap N e occurs 1 week prior to local spring equinox in the Northern Hemisphere (NH) and 1 week after local spring equinox in the Southern Hemisphere (SH). Thus, the median SH polar cap N e lags the median NH polar cap N e by approximately 2 weeks with respect to hemispherically local spring and fall equinox. From interhemispheric comparison of statistical distributions of polar cap plasma density around each equinox and solstice, we find that distributions in the SH are often flatter (i.e., less skewed and kurtotic) than those in the NH. Perhaps of most significance to cold ion outflow, we find no evidence of an F region plasma density counterpart to a previously reported hemispheric asymmetry whereby cold plasma density is higher in the NH magnetospheric lobe than in the SH lobe. Plain Language Summary The Earth's magnetic poles are not perfectly aligned with the Earth's geographic poles, and the degree of misalignment is greater in the Southern Hemisphere. Furthermore, as a result of the Earth's elliptical orbit around the Sun, summer and fall in the Northern Hemisphere together are approximately 1 week longer than summer and fall in the Southern Hemisphere, because the Earth is very slightly closer to the Sun around December solstice (summer in the Southern Hemisphere). These seasonal asymmetries, together with the asymmetric displacement of the Earth's magnetic poles relative to the geographic poles, suggest that the plasma density in the topside ionosphere's geomagnetic polar regions may also be subject to seasonal and hemispheric asymmetries. The polar regions are the primary site of loss of the Earth's atmosphere via so-called ion outflow processes that, over geological time scales, are believed to lead to loss of the Earth's atmosphere. Using 15 years of plasma density measurements made by four different satellites to statistically study the plasma density of each hemisphere's geomagnetic polar cap ionosphere in the altitude range 350-520 km, we find that the polar cap ionosphere at these altitudes exhibits a variety of seasonal and hemispheric asymmetries.

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Section: Appendix A: Correction and Adjustment Of Nesupporting

confidence: 83%

Section: Appendix A: Correction and Adjustment Of Nementioning

confidence: 99%

Seasonal and Hemispheric Asymmetries of F Region Polar Cap Plasma Density: Swarm and CHAMP Observations

et al. 2020

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“…Additionally, the value of the month variable is decimal with the value range of from 0.0 (on 1 January) to 12.0 (on 31 December). The example for the four new variables (i.e.,

N m F 2

h m F 2

V S H

, and

r

) are shown in Figure 1 of Hu et al ().…”

Section: Methodsmentioning

confidence: 99%

“…The procedure used this study follows that of Hu et al (), which is shown in the flowchart in Figure , the blue cylinders denote the databases used in this study, white rectangles are the procedure steps, and the parallelograms are the dependent variable set. In this study, part of the independent variables, LT, month, altitude, and the

N_{e}

profile are extracted from the ISR data.…”

Section: Methodsmentioning

confidence: 99%

“…Additionally, the value of the month variable is decimal with the value range of from 0.0 (on 1 January) to 12.0 (on 31 December). The example for the four new variables (i.e., NmF2, hmF2, VSH, and r) are shown in The procedure used this study follows that of Hu et al (2019), which is shown in the flowchart in Figure 1, the blue cylinders denote the databases used in this study, white rectangles are the procedure steps, and the parallelograms are the dependent variable set. In this study, part of the independent variables, LT, month, altitude, and the N e profile are extracted from the ISR data.…”

Section: Methodsmentioning

confidence: 99%

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A Deep Neural Network Model of Global Topside Electron Temperature Using Incoherent Scatter Radars and Its Application to GNSS Radio Occultation

Carter

Currie

et al. 2020

JGR Space Physics

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The goal of this study is to present a new model for global topside electron temperature ( Te) using a deep neural network (DNN) that is trained using measurements from incoherent scatter radars (ISRs). This study is also an investigation into whether this model can be used to generate the electron temperature in the topside ionosphere using GNSS ionospheric radio occultation (GNSS‐IRO) data as the input. ISR is one of the most reliable and long‐term sources to measure topside ionospheric electron density and plasma temperature information simultaneously. However, a drawback of ISR databases is the relatively poor spatial coverage due to the low number of ISR stations around the world. In contrast, GNSS‐IRO can be used to measure the global distributed electron density, but Te information is not directly detected. The relationship between the electron density and the electron temperature has been investigated by many researchers, but these studies have not explicitly considered the parameters that are known to influence the electron temperature, such as solar and geomagnetic activity level, and the features of electron density profile ( hmF2, NmF2, and scale height). This study uses a DNN technique to create a new global topside electron temperature model from three submodels that have been trained using data from three ISR stations: Arecibo (low latitude), Millstone Hill (midlatitude), and Poker Flat (high latitude). This global model is trained using electron density profile information (e.g., vertical scale height [VSH], hmF2, and NmF2) and solar and geomagnetic activity ( F10.7 and Kp, respectively) in addition to traditional spatial and temporal variables (e.g., local time, month, and latitude) as the independent variables. After the Te model is developed, Te information can be generated from the GNSS‐IRO electron density profiles using a newly created Ne−Te model. This model's outputs are assessed with regard to out‐of‐sample ISR data and compared to the latest International Reference Ionosphere model. It is found that the electron temperature profiles from the DNN have a root‐mean‐square deviation of 259 K in the low‐latitude region (i.e., against Arecibo data), 254 K in the midlatitude region (i.e., against Millstone Hill data), and 314 K in high‐latitude region (i.e., against Poker Flat data), and all of them are smaller than the root‐mean‐square deviation from International Reference Ionosphere. An additional comparison between the model results versus the Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model outputs is also conducted. A statistical analysis of the diurnal electron temperature profiles obtained from GNSS‐IRO is shown to agree with the Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model outputs. The full codes and outputs can be found at the Zenodo (10.5281/zenodo.3637617).

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Impact of geomagnetic storms on ionospheric TEC at high latitude stations: a comparative analysis of GPS observations and the IRI-2016 model

Idosa Uga,

Prasad Gautam,

Beshir Seba

2023

Astrophys Space Sci

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Modeling of Topside Ionospheric Vertical Scale Height Based on Ionospheric Radio Occultation Measurements

Cited by 11 publications

References 30 publications

Seasonal and Hemispheric Asymmetries of F Region Polar Cap Plasma Density: Swarm and CHAMP Observations

Seasonal and Hemispheric Asymmetries of F Region Polar Cap Plasma Density: Swarm and CHAMP Observations

A Deep Neural Network Model of Global Topside Electron Temperature Using Incoherent Scatter Radars and Its Application to GNSS Radio Occultation

Impact of geomagnetic storms on ionospheric TEC at high latitude stations: a comparative analysis of GPS observations and the IRI-2016 model

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