Detection of a long‐term decrease in thermospheric neutral density

Marcos, F. A.; Wise, J. O.; Kendra, M. J.; Grossbard, Neil; Bowman, Bruce R.

doi:10.1029/2004gl021269

Cited by 81 publications

(117 citation statements)

References 15 publications

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“…This long-term decreasing trend of neutral density has been observed using long-term satellite drag data (e.g., Keating et al 2000;Emmert et al 2004Emmert et al , 2008Marcos et al 2005). The estimated density trend at 400 km ranges from −1.7%/decade to −3.0%/decade, for the past 3 to 4 decades.…”

Section: Long-term Trendsmentioning

confidence: 51%

Thermospheric Density: An Overview of Temporal and Spatial Variations

2011

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Neutral density shows complicated temporal and spatial variations driven by external forcing of the thermosphere/ionosphere system, internal dynamics, and thermosphere and ionosphere coupling. Temporal variations include abrupt changes with a time scale of minutes to hours, diurnal variation, multi-day variation, solar-rotational variation, annual/semiannual variation, solar-cycle variation, and long-term trends with a time scale of decades. Spatial variations include latitudinal and longitudinal variations, as well as variation with altitude. Atmospheric drag on satellites varies strongly as a function of thermospheric mass density. Errors in estimating density cause orbit prediction error, and impact satellite operations including accurate catalog maintenance, collision avoidance for manned and unmanned space flight, and re-entry prediction. In this paper, we summarize and discuss these density variations, their magnitudes, and their forcing mechanisms, using neutral density data sets and modeling results. The neutral density data sets include neutral density observed by the accelerometers onboard the Challenging Mini-satellite Payload (CHAMP), neutral density at satellite perigees, and global-mean neutral density derived from thousands of orbiting objects. Modeling results are from the National Center for Atmospheric Research (NCAR) thermosphere-ionosphere-electrodynamics general circulation model (TIE-GCM), and from the NRLMSISE-00 empirical model.

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Section: Long-term Trendsmentioning

confidence: 51%

Thermospheric Density: An Overview of Temporal and Spatial Variations

2011

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“…[21] Global mean trends in thermospheric mass density r have been studied from satellite drag data over the last few decades [Keating et al, 2000;Emmert et al, 2004Emmert et al, , 2008Marcos et al, 2005]. At 400 km the relative trends range from about dr/r = À5% decade À1 at low solar activity [Keating et al, 2000;Emmert et al, 2008] to À2% decade À1 at high activity [Emmert et al, 2004[Emmert et al, , 2008 with average values ranging between À1.7 and À2.7% decade À1 [Marcos et al, 2005;Emmert et al, 2008].…”

Section: Trend Magnitudementioning

confidence: 99%

On estimation and attribution of long‐term temperature trends in the thermosphere

Akmaev

2012

J. Geophys. Res.

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[1] Recent analyses of long-term time series of ion temperature from two midlatitude incoherent-scatter radars have revealed very strong cooling, which is substantially greater than predicted by models for neutral temperature. There is also an indication that the cooling has substantially accelerated after a breakpoint around 1979 when the ozone hole was discovered. This has prompted a hypothesis that the accelerated cooling might have resulted from the ozone depletion and associated reduction in daytime radiative heating in the stratosphere. A lively discussion on relative roles of different cooling mechanisms has followed. The purpose of this note is to contribute to this discussion from a theoretical and modeling perspective. In particular, a possible misinterpretation of the modeling results behind the ozone hypothesis is clarified. It is also shown that model predictions of neutral temperature trends in the thermosphere agree well with, and hence are tightly constrained by, independent observations including trends in heights of ionospheric layers and in neutral density from satellite drag. However, they are up to an order of magnitude smaller than the observational estimates of trends in ion temperature. These widely different results cannot be quantitatively reconciled regardless of what known cooling mechanisms are invoked. This stark discrepancy should be addressed on the data analysis and theoretical fronts.

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“…[4] As well as short-term, storm-driven changes in the thermosphere, satellite studies at middle latitudes have shown that the global thermosphere is gradually contracting [Keating et al, 2000;Marcos et al, 2005;Emmert et al, 2008]. The rate of decrease in density at 400 km has been estimated to range from 2% to 5% per decade at solar maximum and minimum, respectively [Emmert et al, 2004[Emmert et al, , 2008.…”

Section: Introductionmentioning

confidence: 99%

Thermospheric atomic oxygen density estimates using the EISCAT Svalbard Radar

et al. 2013

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[1] Coupling between the ionized and neutral atmosphere through particle collisions allows an indirect study of the neutral atmosphere through measurements of ionospheric plasma parameters. We estimate the neutral density of the upper thermosphere above~250 km with the European Incoherent Scatter Svalbard Radar (ESR) using the year-long operations of the International Polar Year from March 2007 to February 2008. The simplified momentum equation for atomic oxygen ions is used for field-aligned motion in the steady state, taking into account the opposing forces of plasma pressure gradients and gravity only. This restricts the technique to quiet geomagnetic periods, which applies to most of the International Polar Year during the recent very quiet solar minimum. The method works best in the height rangẽ 300-400 km where our assumptions are satisfied. Differences between Mass Spectrometer and Incoherent Scatter and ESR estimates are found to vary with altitude, season, and magnetic disturbance, with the largest discrepancies during the winter months. A total of 9 out of 10 in situ passes by the CHAMP satellite above Svalbard at 350 km altitude agree with the ESR neutral density estimates to within the error bars of the measurements during quiet geomagnetic periods.

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Detection of a long‐term decrease in thermospheric neutral density

Cited by 81 publications

References 15 publications

Thermospheric Density: An Overview of Temporal and Spatial Variations

Thermospheric Density: An Overview of Temporal and Spatial Variations

On estimation and attribution of long‐term temperature trends in the thermosphere

Thermospheric atomic oxygen density estimates using the EISCAT Svalbard Radar

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