Sean L. Bruinsma

The DTM-2000 empirical thermosphere model with new data assimilation and constraints at lower boundary: accuracy and properties

Abstract The drag temperature model (DTM) is a semi-empirical model describing the temperature, density and composition of the Earths thermosphere. Its first version (Ann. Geophys. 34 (1978) 9) used direct measurements of exospheric temperature and atmospheric densities derived from satellite drag data. It has later been refined (J. Geodesy 72 (1998) 161). However, both models have their lower boundaries at 120 km , which are not constrained by observations. Consequently in the lower thermosphere, the modelled temperature and density structure is uncertain. For predicting satellite orbits in the lower thermosphere, more realistic density models are required. We present a new DTM model having the following improvements: (a) Temperature and its gradient at 120 km are represented in agreement with theory and observation, using incoherent scatter radar and satellite-borne interferometer data. (b) Atmosphere explorer (AE) data, which have not been assimilated in DTM-94, are used as they cover a complete solar activity cycle. (c) The Mg II index is used whenever possible to represent the solar UV and EUV emission intensity instead of the solar decimetre radio flux, since it is more representative of solar instantaneous chromospheric activity than F10.7 is. The basic DTM mathematical representation of temperature and composition is used, with, however, some additions and modifications to take into account the variations at 120 km altitude. The temperature modelling accuracy has improved by 5–8%, and there is no model bias as a function of solar activity. The oxygen and helium modelling has improved as well, and this is demonstrated by the estimated drag scale coefficients issued from precise orbit computation. The scaling coefficients estimated using DTM-2000 are systematically closer to unity than those resulting from employing DTM-94 and MSIS-86 in the orbit computation. The minor constituents (O2 and H) modelling is unchanged. The molecular nitrogen modelling is not improved, but this is, at least partly, caused by the poor data quality. Despite these improvements, semi-empirical thermosphere models still suffer of weaknesses. First, they assume a steady-state equilibrium which is not necessarily reached in any circumstances. Second, the basic process of atmospheric heating by EUV is assumed to be represented by some indices (Mg II, F10.7), while particle precipitation is represented by an index associated to a latitude without a longitude effect (Kp), although winds that transport energy suggest this effect. Third, the data accuracy and their incomplete geographical and temporal coverage are significant sources of uncertainty. Assimilation of a long time series of data, with a complete geographical coverage, and using the Mg II index will probably increase model accuracy from the present-day RMS of 19% to 10–15%. The complete CHAMP accelerometer data set may allow the achievement of that goal after 5 years of operations in 2005.

Total Densities Derived from Accelerometer Data

The German satellite Challenging Minisatellite Payload (CHAMP), carrying the STAR accelerometer onboard, was launched in July 2000. The CHAMP mission profile is compatible with studies of the thermosphere: it will providegood geographical and altitude coverage over a period of five years. The preprocessing of the accelerometer data consists of correcting them for maneuvers, specific events, and instrumental bias. The total density can then be reconstituted, employing a model for the aerodynamic coefficient. We have employed a theory based on diffuse reemission applied to a 15-plate macromodel. The accuracy of the observed densities depends mainly on the uncertainties of the estimated accelerometer calibration parameters and of the aerodynamic coefficient, as well as on geomagnetic activity. The six weeks of data analyzed in this preliminary study showed their high precision and model shortcomings. Assimilation of at least one year of data in a thermosphere model will significantly increase its accuracy, which, in turn, will improve satellite drag modeling.

ESA's satellite‐only gravity field model via the direct approach based on all GOCE data

Gravity field and steady state Ocean Circulation Explorer (GOCE) gravity gradient data of the entire science mission and data from LAGEOS 1/2 and Gravity Recovery and Climate Experiment (GRACE) were combined in the construction of a satellite-only gravity field model to maximum degree 300. When compared to Earth Gravitational Model 2008, it is more accurate at low to medium resolution, thanks to GOCE and GRACE data. When compared to earlier releases of European Space Agency GOCE models, it is more accurate at high degrees owing to the larger amount of data ingested, which was moreover taken at lower altitude. The impact of orbiting at lower altitude in the last year of the mission is large: a model based on data of the last 14 months is significantly more accurate than the release 4 model constructed with the first 28 months. The (calibrated) cumulated geoid error estimate at 100 km resolution is 1.7 cm. The optimal resolution of the GOCE model for oceanographic application is between 100 and 125 km.

EIGEN-6C: A High-Resolution Global Gravity Combination Model Including GOCE Data

GOCE satellite gradiometry data were combined with data from the satellite missions GRACE and LAGEOS and with surface gravity data. The resulting high-resolution model, EIGEN-6C, reproduces mean seasonal variations and drifts to spherical harmonic degree and order (d/o) 50 whereas the mean spherical harmonic coefficients are estimated to d/o 1420. The model is based on satellite data up to d/o 240, and determined with surface data only above degree 160. The new GOCE data allowed the combination with surface data at a much higher degree (160) than was formerly done (70 or less), thereby avoiding the propagation of errors in the surface data over South America and the Himalayas in particular into the model.

Atmospheric gravity waves due to the Tohoku‐Oki tsunami observed in the thermosphere by GOCE

Oceanic tsunami waves couple with atmospheric gravity waves, as previously observed through ionospheric and airglow perturbations. Aerodynamic velocities and density variations are computed from Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) accelerometer and thruster data during Tohoku-Oki tsunami propagation. High-frequency perturbations of these parameters are observed during three expected crossings of the tsunami-generated gravity waves by the GOCE satellite. From theoretical relations between air density and vertical and horizontal velocities inside the gravity wave, we demonstrate that the measured perturbations are consistent with a gravity wave generated by the tsunami and provide a way to estimate the propagation azimuth of the gravity wave. Moreover, because GOCE measurements can constrain the wave polarization, a marker (noted C3) of any gravity wave crossing by the GOCE satellite is constructed from correlation coefficients between the observed atmospheric state parameters. These observations validate a new observation tool of thermospheric gravity waves generated by tsunamis above the open ocean.

Interannual and latitudinal variability of the thermosphere density annual harmonics

[1] In this paper we investigate the intra-annual variation in thermosphere neutral density near 400 km using 4 years (2002–2005) of CHAMP measurements. The intra-annual variation, commonly referred to as the ‘‘semiannual variation,’’ is characterized by significant latitude structure, hemispheric asymmetries, and interannual variability. The magnitude of the maximum yearly difference, from the yearly minimum to the yearly maximum, varies by as much as 60% from year to year, and the phases of the minima and maxima also change by 20–40 days from year to year. Each annual harmonic of the intraannual variation, namely, annual, semiannual, terannual and quatra-annual, exhibits a decreasing trend from 2002 through 2005 that is correlated with the decline in solar activity. In addition, some variations in these harmonics are correlated with geomagnetic activity, as represented by the daily mean value of Kp. Recent empirical models of the thermosphere are found to be deficient in capturing most of the latitude dependencies discovered in our data. In addition, the solar flux and geomagnetic activity proxies that we have employed do not capture some latitude and interannual variations detected in our data. It is possible that these variations are partly due to other effects, such as seasonallatitudinal variations in turbopause altitude (and hence O/N2 composition) and ionosphere coupling processes that remain to be discovered in the context of influencing the intraannual variations depicted here. Our results provide a new data set to challenge and validate thermosphere-ionosphere general circulation models that seek to delineate the thermosphere intra-annual variation and to understand the various competing mechanisms that may contribute to its existence and variability. We furthermore suggest that the term ‘‘intra-annual’’ variation be adopted to describe the variability in thermosphere and ionosphere parameters that is well-captured through a superposition of annual, semiannual, terannual, and quatra-annual harmonic terms, and that ‘‘semiannual’’ be used strictly in reference to a pure 6-monthly sinusoidal variation. Moreover, we propose the term ‘‘intraseasonal’’ to refer to those shorter-term variations that arise as residuals from the above Fourier representation.

Synoptic radio observations as proxies for upper atmosphere modelling

The specification of the upper atmosphere strongly relies on solar proxies that can properly reproduce the solar energetic input in the UV. Whilst the microwave flux at 10.7 cm (also called F10.7 index) has been routinely used as a solar proxy, we show that the radio flux at other wavelengths provides valuable complementary information that enhances their value for upper atmospheric modelling. We merged daily observations from various observatories into a single homogeneous data set of fluxes at wavelengths of 30, 15, 10.7, 8 and 3.2 cm, spanning from 1957 to today. Using blind source separation (BSS), we show that their rotational modulation contains three contributions, which can be interpreted in terms of thermal bremsstrahlung and gyro-resonance emissions. The latter account for 90% of the rotational variability in the F10.7 index. Most solar proxies, such as the MgII index, are remarkably well reconstructed by simple linear combination of radio fluxes at various wavelengths. The flux at 30 cm stands out as an excellent proxy and is better suited than the F10.7 index for the modelling the thermosphere-ionosphere system, most probably because it receives a stronger contribution from thermal bremsstrahlung. This better performance is illustrated here through comparison between the observed thermospheric density, and reconstructions by the Drag Temperature Model.

Global ionospheric and thermospheric response to the 5 April 2010 geomagnetic storm: An integrated data-model investigation

We present a case study of the 5 April 2010 geomagnetic storm using observations and numerical simulations. The event was driven by a fast-moving coronal mass ejection and despite being a moderate storm with a minimum Dst near −50 nT, the event exhibited elevated thermospheric density and surges of traveling atmospheric disturbances (TADs) more typically seen during major storms. The Thermosphere-Ionosphere-Mesosphere-Electrodynamics General Circulation Model (TIMEGCM) was used to assess how these features were generated and developed during the storm. The model simulations gave rise to TADs that were highly nonuniform with strong latitude and longitude/local time dependence. The TAD phase speeds ranged from 640 m/s to 780 m/s at 400 km and were ~5% lower at 300 km and approximately 10–15% lower at 200 km. In the lower thermosphere around 100 km, the TAD signatures were nearly unrecognizable due to much stronger influence of upward propagating atmospheric tides. The thermosphere simulation results were compared to observations available from the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE), CHAllenging Minisatellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE) satellites. Comparison with GOCE data shows that the TIMEGCM reproduced the cross-track winds over the polar region very well. The model-data comparison also revealed some differences, specifically, the simulations underestimated neutral mass density in the upper thermosphere above ~300 km and overestimated the storm recovery tome by 6 h. These discrepancies indicate that some heating or circulation dynamics and potentially cooling processes are not fully represented in the simulations, and also that updates to some parameterization schemes in the TIMEGCM are warranted.

A statistical study of the observed and modeled global thermosphere response to magnetic activity at middle and low latitudes

[1] From one year (2004) of thermosphere total density data inferred from CHAMP/ STAR accelerometer measurements, we calculate the global thermosphere response to auroral magnetic activity forcing at middle and low latitudes using a method based on a singular value decomposition of the satellite data. This method allows separating the large-scale spatial variations in the density, mostly related to altitude/latitude variations and captured by the first singular component, from the time variations, down to timescales on the order of the orbital period, which are captured by the associated projection coefficient. This projection coefficient is used to define a disturbance coefficient that characterizes the global thermospheric density response to auroral forcing. For quiet to moderate magnetic activity levels (Kp < 6), we show that the disturbance coefficient is better correlated with the magnetic am indices than with the magnetic ap indices. The latter index is used in all empirical thermosphere models to quantify the auroral forcing. It is found that the NRLMSISE-00 model correctly estimates the main features of the thermosphere density response to geomagnetic activity, i.e., the morphology of Universal Time variations and the larger relative increase during nighttime than during daytime. However, it statistically underestimates the amplitude of the thermosphere density response by about 50%. This underestimation reaches 200% for specific disturbed periods. It is also found that the difference between daytime and nighttime responses to auroral forcing can statistically be explained by local differences in magnetic activity as described by the longitude sector magnetic indices. Citation: Lathuillere, C., M. Menvielle, A. Marchaudon, and S. Bruinsma (2008), A statistical study of the observed and modeled global thermosphere response to magnetic activity at middle and low latitudes,

Storm-Time Equatorial Density Enhancements Observed by CHAMP and GRACE

Total atmospheric densities have been simultaneously acquired from accelerometer measurements on the CHAMP (challenging minisatellite payload) and GRACE (gravity recovery and climate experiment) satellites over the past years. Both satellites have observed a large number of geomagnetic storms, most of them simultaneously, offering unique opportunities to study the temporal and latitudinal responses of the thermosphere to geomagnetic disturbances. The equatorial density enhancements observed during fast and significant increases in geomagnetic activity are calculated. The relationship between the density enhancements and local time, and the increase and maximum value of the geomagnetic activity are analyzed. The enhancements top 100% only if geomagnetic activity exceeds a minimum value, are larger on the nightside than on the dayside, and increase with altitude. The largest enhancement observed was 800%. The day-to-night density ratios become smaller during storm periods and are closest to unity for a local time of 0800=2000.The relative delay of the equatorial enhancementwith respect to the ones observed at 60 S and 60 N is a function of geomagnetic activity, and it is shorter in the night sector than in the daylight sector. Equatorial propagation speeds of the density disturbance that are derived from the delay are of the order 400–1200 ms .