New modes and mechanisms of thermospheric mass density variations from GRACE accelerometers

Calabia, Andrés; Jin, Shuanggen

doi:10.1002/2016ja022594

Cited by 40 publications

(51 citation statements)

References 40 publications

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“…Meanwhile, Figs. 6 and 13 in Calabia et al (2016) also show that two maxima peaks are depicted in June in the Northern Hemisphere, but only one in December in the Southern Hemisphere. However, the underlying physical processes for this feature need further investigation.…”

Section: Resultsmentioning

confidence: 98%

“…These results illustrate that the thermospheric annual asymmetry should be associated with the varying Sun-Earth distance. Actually, previous studies suggested that the difference of solar radiation associated with the difference of Sun-Earth distance between June and December would contribute to the annual asymmetry (Qian et al, 2012;Lei et al, 2013Lei et al, , 2016Emmert, 2015;Calabia et al, 2016). Moreover, Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Emmert (2015) reviewed the studies of the thermosphere between 2000 and 2014, summarized several possible mechanisms to explain the seasonal variations, and demonstrated that further investigations are required to understand the seasonal variations of the thermosphere. Recently, Calabia et al (2016) investigated the thermospheric mass density variations from GRACE data for the period 2003-2016 by using the principal component analysis (PCA) method, and discussed the annual variation for different local solar times (LSTs) and solar activities. Moreover, Salinas et al (2016) found that the monthly global-mean CO 2 profiles from TIMED/SABER have annual and semiannual oscillations (AO and SAO), but cannot explain the observed AO and SAO in the thermosphere.…”

Section: Introductionmentioning

confidence: 99%

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Seasonal variations of thermospheric mass density at dawn/dusk from GOCE observations

et al. 2018

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Abstract. Thermospheric mass densities from the GOCE (Gravity field and steady-state Ocean Circulation Explorer) satellite for Sun-synchronous orbits between 83.5 • S and 83.5 • N, normalized to 270 km during 2009-2013, have been used to develop an empirical mass density model at dawn/dusk local solar time (LST) sectors based on the empirical orthogonal function (EOF) method. The main results of this study are that (1) the dawn densities peak in the polar regions, but the dusk densities maximize in the equatorial regions; (2) the relative seasonal variations to the annual mean have similar patterns across all latitudes regardless of solar activity conditions; (3) the seasonal density variations show obvious hemispheric asymmetry, with large amplitudes in the Southern Hemisphere; (4) both amplitude and phase of the seasonal variations have strong latitudinal and solar activity dependences, with high amplitude for the annual variation at higher latitudes and semiannual variation at lower latitudes; (5) the annual asymmetry and effect of the Sun-Earth distance vary with latitude and solar activity.

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Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Seasonal variations of thermospheric mass density at dawn/dusk from GOCE observations

et al. 2018

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“…The nondrag terms can be modeled, fixed, and then deducted from the measurements by using prior procedures in terms of navigational information, spacecraft records, and empirical models (e.g., Tolson et al, 2005Tolson et al, , 2007Tolson et al, , 2008. Subsequently, the aerodynamic acceleration a aero is used to derive the atmospheric mass density as follows (e.g., Calabia & Jin, 2016;Tolson et al, 2005;Keating et al, 2008;Jin et al, 2018):…”

Section: Atmospheric Mass Density From Acc-measured Accelerationmentioning

confidence: 99%

“…In this paper, we standardize the data into several reference altitudes of 10 km intervals in the vertical directions. The normalization equation is as follows (Calabia & Jin, 2016): & Millour, 2009;González-Galindo, Forget, Lpez-Valverde, & Angelats i Coll, 2009). In order to maintain consistency between the measurements and the MCD, the scenarios that reflect the surface dust and solar activities should be set properly based on Millour et al (2015) and Montabone et al (2015).…”

Section: Density Normalization With Reference Modelmentioning

confidence: 99%

Seasonal Variations and Global Wave Distributions in the Mars Thermosphere From MAVEN and Multisatellites Accelerometer‐Derived Mass Densities

Liu

Jin

2019

JGR Space Physics

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Martian lower thermospheric variations are complex due to internal surface dust storms and external solar activities. However, limited Martian measurement data are restricted to observe and understand its variations in the past. In this paper, multisatellite accelerometer-derived densities and the Mars Climate Database are used to investigate seasonal variations, gravity waves, and coupling effects with the internal and external inputs, including Mars Global Surveyor, Mars Reconnaissance Orbiter, Mars Odyssey, and Mars Atmosphere and Volatile EvolutioN Mission. The diurnal and seasonal structures are reconstructed by the data, and the phase of the cycles is formed by solar heating/ionizing processes. Both amplitude and phase are impacted by surface dust activities during autumn and winter, for which density increases about 1.5-3.5 times compared to spring and summer seasons. A parameterized model that includes a newly introduced dust index is proposed to well fit and reinterpret the seasonal cycles. Furthermore, the coupling process between internal atmospheric gravity waves (IAGWs) and dust activities are investigated and explained. During dust storm times/seasons, the IAGWs exhibit both narrower amplitude peaks and deposit their energy at higher altitudes relative to "clear sky" times. The IAGWs could extend their energies into higher layers beyond exobase due to a thermospheric layer expansion (i.e., density increase) during dust seasons. Plain Language Summary The new spacecraft Mars Atmosphere and Volatile EvolutioNMission aims to observe Mars lower thermosphere from 100 to 200 km, namely, the lower thermosphere. The daily and yearly variations of the Mars thermospheric density are illustrated for the first time with this data. An improved fitting function is proposed for the yearly density variations. We found that the yearly variations are explained by seasonal solar illumination changes experienced by Mars during its orbit, which can be fit by a superposition of sine and cosine functions. The amplitude of the variations is impacted by surface dust storms during dust seasons (Mars northern autumn and winter). The behaviors of the vertically propagating internal atmospheric gravity waves (IAGWs) are investigated in different seasons. The interaction between these IAGWs and lower atmosphere dust storms is analogous to ocean waves hitting a beach, where the changes in the lower atmosphere dust function like the changing ocean depth close to shore that allow the ocean waves (i.e., IAGWs) to propagate more energy onto the shore (into the upper atmosphere).

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An Exospheric Temperature Model Based On CHAMP Observations and TIEGCM Simulations

et al. 2018

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In this work, thermospheric densities from the accelerometer measurement on board the CHAMP satellite during 2002–2009 and the simulations from the National Center for Atmospheric Research Thermosphere Ionosphere Electrodynamics General Circulation Model (NCAR‐TIEGCM) are employed to develop an empirical exospheric temperature model (ETM). The two‐dimensional basis functions of the ETM are first provided from the principal component analysis of the TIEGCM simulations. Based on the exospheric temperatures derived from CHAMP thermospheric densities, a global distribution of the exospheric temperatures is reconstructed. A parameterization is conducted for each basis function amplitude as a function of solar‐geophysical and seasonal conditions. Thus, the ETM can be utilized to model the thermospheric temperature and mass density under a specified condition. Our results showed that the averaged standard deviation of the ETM is generally less than 10% than approximately 30% in the MSIS model. Besides, the ETM reproduces the global thermospheric evolutions including the equatorial thermosphere anomaly.

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New modes and mechanisms of thermospheric mass density variations from GRACE accelerometers

Cited by 40 publications

References 40 publications

Seasonal variations of thermospheric mass density at dawn/dusk from GOCE observations

Seasonal variations of thermospheric mass density at dawn/dusk from GOCE observations

Seasonal Variations and Global Wave Distributions in the Mars Thermosphere From MAVEN and Multisatellites Accelerometer‐Derived Mass Densities

An Exospheric Temperature Model Based On CHAMP Observations and TIEGCM Simulations

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