The DTM-2013 thermosphere model

Bruinsma, Sean

doi:10.1051/swsc/2015001

Cited by 154 publications

(108 citation statements)

References 11 publications

Supporting

Mentioning

102

Contrasting

Order By: Relevance

“…As expected, densities from our GOCE model are in good agreement with the observations. However, densities predicted from the MSIS00 model are greater than the GOCE observations, consistent with the results of Zhang et al (2014) and Bruinsma et al (2014Bruinsma et al ( , 2015Bruinsma et al ( , 2017. The mean ratios between the results of our GOCE and MSISE00 models and the observations are 1.012 and 1.334, with standard deviations of about 0.101 and 0.176, respectively.…”

Section: Goce Density Modelsupporting

confidence: 85%

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

et al. 2018

View full text Add to dashboard Cite

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.

show abstract

Section: Goce Density Modelsupporting

confidence: 85%

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

et al. 2018

View full text Add to dashboard Cite

show abstract

“…The F10.7 model cannot reproduce the densities without significant bias after 2010, reaching 50-60% for periods that F10.7 is 10-20 sfu lower than F30*. The mean (RMS) of the density ratios using all data is 1.172 (0.321) and 1.061 (0.233) with F10.7 and F30*, respectively; for the period April 2003-December 2009(2010-2015 the mean and standard deviation of the density ratios is 1.056 and 0.143 (1.352 and 0.172) and 1.022 and 0.119 (1.105 and 0.132), respectively. So it appears that we have two distinct periods: for the first period, both models predict density with rather small biases on average, but from about 2010 onwards both models are underestimating density systematically.…”

Section: Model Performance With F30 and F107mentioning

confidence: 93%

The 30 cm radio flux as a solar proxy for thermosphere density modelling

Wit

Bruinsma²

2017

J. Space Weather Space Clim.

Self Cite

View full text Add to dashboard Cite

The 10.7 cm radio flux (F10.7) is widely used as a proxy for solar UV forcing of the upper atmosphere. However, radio emissions at other centimetric wavelengths have been routinely monitored since the 1950 s, thereby offering prospects for building proxies that may be better tailored to space weather needs. Here we advocate the 30 cm flux (F30) as a proxy that is more sensitive than F10.7 to longer wavelengths in the UV and show that it improves the response of the thermospheric density to solar forcing, as modelled with DTM (Drag Temperature Model). In particular, the model bias drops on average by 0-20% when replacing F10.7 by F30; it is also more stable (the standard deviation of the bias is 15-40% smaller) and the density variation at the the solar rotation period is reproduced with a 35-50% smaller error. We compare F30 to other solar proxies and discuss its assets and limitations.

show abstract

“…Currently, the atmospheric forecasts are based on semiempirical models for the gas neutral composition; among those models there are MSIS-90 (Hedin, 1991), NRLMSISE-00 (Picone et al, 2002), DTM (Bruinsma, 2015) and JB2008 (Bowman et al, 2008). These models are finely tuned to match a database of flight measurements, but when applied outside the interpolated ranges they are subjected to large uncertainties in atmosphere density and composition.…”

Section: Introductionmentioning

confidence: 99%

Effect of the solar activity variation on the Global Ionosphere Thermosphere Model (GITM)

et al. 2016

View full text Add to dashboard Cite

Abstract. The accuracy of global atmospheric models used to predict the middle/lower thermosphere characteristics is still an open topic. Uncertainties in the prediction of the gas properties in the thermosphere lead to inaccurate computations of the drag force on space objects (i.e. satellites or debris). Currently the lifetime of space objects and therefore the population of debris in low Earth orbit (LEO) cannot be quantified with a satisfactory degree of accuracy. In this paper, the Global Ionosphere Thermosphere Model (GITM) developed at the University of Michigan has been validated in order to provide detailed simulations of the thermosphere. First, a sensitivity analysis has been performed to investigate the effect of the boundary conditions on the final simulations results. Then, results of simulations have been compared with flight measurements from the CHallenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE) satellites and with existing semiempirical atmospheric models (IRI and MSIS). The comparison shows a linear dependency of the neutral density values with respect to the solar activity. In particular, GITM shows an over-predicting or under-predicting behaviour under high or low solar activity respectively. The reasons for such behaviour can be attributed to a wrong implementation of the chemical processes or the gas transport properties in the model.

show abstract

The DTM-2013 thermosphere model

Cited by 154 publications

References 11 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

The 30 cm radio flux as a solar proxy for thermosphere density modelling

Effect of the solar activity variation on the Global Ionosphere Thermosphere Model (GITM)

Contact Info

Product

Resources

About