North-south components of the annual asymmetry in the ionosphere

Gulyaeva, T.L.; Arıkan, Feza; Hernández‐Pajares, M.; Veselovsky, I. S.

doi:10.1002/2014rs005401

Cited by 24 publications

(13 citation statements)

References 47 publications

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“…To the best of our knowledge, such an extensive set of data, which presents contrasting results of electron density profiles over oceans and landmasses, has not been reported in the literature before. However, the topside sounder data on the International Satellites for Ionospheric Studies exhibited large fluctuations in the F 2 region peak electron density and peak height over oceans compared to those over landmasses [Gulyaeva et al, 2014]. These findings are consistent with the CASSIOPE RO-inferred electron density profiles (Figures 2a and 2b).…”

Section: Electron Density Profiles Over Oceans and Landmasses: Cassiosupporting

confidence: 76%

Electron number density profiles derived from radio occultation on the CASSIOPE spacecraft

et al. 2017

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This paper presents electron number density profiles derived from high‐resolution Global Positioning System (GPS) radio occultation (RO) observations performed using the Enhanced Polar Outflow Probe payload on the high inclination CAScade, Smallsat and IOnospheric Polar Explorer (CASSIOPE) spacecraft. We have developed and applied a novel inverse Abel transform algorithm on high rate RO total electron content measurements performed along GPS to CASSIOPE radio links to recover electron density profiles. The high‐resolution density profiles inferred from the CASSIOPE RO are (1) in very good agreement with density profiles estimated from ionosonde data, measured over stations nearby to the latitude and longitude of the RO tangent points; (2) in good agreement with density profiles inferred from GPS RO measured by the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC); and (3) in general agreement with density profiles estimated using the International Reference Ionosphere climatological model. Using both CASSIOPE and COSMIC RO observations, we identify, for the first time, that there exist differences in the characteristics of the electron number density profiles retrieved over landmasses and oceans. The density profiles over oceans exhibit widespread values and scale heights compared to density profiles over landmasses. We provide an explanation for the ocean‐landmass discrepancy in terms of the unique wave coupling mechanisms operating over oceans and landmasses.

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Section: Electron Density Profiles Over Oceans and Landmasses: Cassiosupporting

confidence: 76%

Electron number density profiles derived from radio occultation on the CASSIOPE spacecraft

et al. 2017

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“…Global Navigation Satellite System (GNSS) data are a valuable source of information for sensing the Earth's ionosphere (Hernández-Pajares et al 1999;Komjathy et al 2005;Li et al 2015;Liu and Gao 2004;Mannucci et al 1993). Although the ionospheric parameters that one can estimate from GNSS data are various (Dyrud et al 2008;Lognonné et al 2006;Yao et al 2013), the Vertical Total Electron Content (VTEC) is generally the most widely used (Brunini and Azpilicueta 2010; Azpilicueta 2009); its empirical importance lies in contributing useful understanding to the physics behind different space weather phenomena (Gulyaeva et al 2014;Komjathy et al 2012), in providing valuable insights into the possible causes of natural and man-made hazardous events (Artru et al 2005;Dautermann et al 2007;Park et al 2011), and in delivering corrections to the ionospheric effects on signals transmitted by the other space geodetic techniques than by the GNSS (Dettmering et al 2014;Sardon et al 1994b). On the other hand, the Satellite Differential Code Biases (SDCBs), defined as the deviations of the satellite code instrumental delays on one frequency from their counterparts on another frequency (Sardon et al 1994a), account for one major source of error in Positioning, Navigation and Timing (PNT) applications that employ undifferenced GNSS code and phase data (Montenbruck et al 2014;Wang et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Joint estimation of vertical total electron content (VTEC) and satellite differential code biases (SDCBs) using low-cost receivers

Zhang

Teunissen

Yuan

et al. 2017

J Geod

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Vertical Total Electron Content (VTEC) parameters estimated using Global NavigationSatellite System (GNSS) data are of great interest for ionosphere sensing. Satellite Differential Code Biases (SDCBs) account for one source of error which, if left uncorrected, can deteriorate performance of positioning, timing and other applications. The customary approach to estimate VTEC along with SDCBs from dual-frequency GNSS data, hereinafter referred to as DF approach, consists of two sequential steps. The first step seeks to retrieve ionospheric observables through the Carrier-to-Code Leveling (CCL) technique. This observable, related to the Slant Total Electron Content (STEC) along the satellite-receiver line-of-sight, is biased also by the SDCBs and the Receiver Differential Code Biases (RDCBs). By means of thin-layer ionospheric model, in the second step one is able to isolate the VTEC, the SDCBs and the RDCBs from the ionospheric observables. In this work, we present a 2 / 30 single-frequency (SF) approach, enabling the joint estimation of VTEC and SDCBs using low-cost receivers; this approach is also based on two steps and it differs from the DF approach only in the first step, where we turn to the Precise Point Positioning (PPP) technique to retrieve from the single-frequency GNSS data the ionospheric observables, interpreted as the combination of the STEC, the SDCBs and the biased receiver clocks at the pivot epoch. Our numerical analyses clarify how SF approach performs when being applied to GPS L1 data collected by a single receiver under both calm and disturbed ionospheric conditions. The daily time series of zenith VTEC estimates has an accuracy ranging from a few tenths of a TEC unit (TECU) to approximately 2 TECU. For 73 to 96 percent of GPS satellites in view, the daily estimates of SDCBs do not deviate, in absolute value, more than 1 nanosecond from their ground-truth values published by the Centre for Orbit Determination in Europe (CODE).

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“…They further revealed that changes in solar radiation between December and June solstices and the displacement of the geomagnetic axis from the geographic axis are critical in causing the annual asymmetry, whereas lower atmospheric tides only play a secondary role in producing it. The impact of the magnetosphere structure and dynamics [ Qian et al , ; Förster and Cnossen , ; Lee et al , ; Cnossen and Förster , ] and seismic activity [ Gulyaeva et al , ] on the ionospheric asymmetry has also been discussed previously. In addition to solar radiation differences and magnetic field configuration effects, the possible important differences in underlying chemical and dynamical changes (such as thermospheric temperature and neutral composition and winds) between December and June solstices require further investigation.…”

Section: Introductionmentioning

confidence: 99%

Can atomic oxygen production explain the ionospheric annual asymmetry?

et al. 2016

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The causes of the ionospheric annual asymmetry, which refers to a larger averaged electron density at geomagnetic conjugate latitudes in December than in June, remain an unresolved problem that still generates considerable interest. The ionospheric annual asymmetry in the peak electron density of the F2 layer (NmF2) is typically 20–40%, which cannot be explained by the 7% annual asymmetry in photoionization caused by the shorter Sun‐Earth distance in December. Mikhailov and Perrone (2011, 2015) suggested that the annual asymmetry in atomic oxygen production due to O2 dissociation is sufficient to explain the ionospheric annual asymmetry at middle latitudes. In our study, a series of the Global Mean Model (GMM) simulations have been conducted to test this hypothesis. Although O2 dissociation and eddy diffusion processes are included in the GMM, the simulated annual asymmetry of NmF2 is only 13%. Furthermore, the annual asymmetry increase in neutral composition in our GMM simulations can only explain about one fifth of the ionospheric annual asymmetry. Therefore, the atomic oxygen production mechanism is unlikely to be a major contributor to the ionospheric annual asymmetry.

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North-south components of the annual asymmetry in the ionosphere

Cited by 24 publications

References 47 publications

Electron number density profiles derived from radio occultation on the CASSIOPE spacecraft

Electron number density profiles derived from radio occultation on the CASSIOPE spacecraft

Joint estimation of vertical total electron content (VTEC) and satellite differential code biases (SDCBs) using low-cost receivers

Can atomic oxygen production explain the ionospheric annual asymmetry?

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