The Accuracy of Atmospheric Models in Solar Maximum Years Checked with the Data of CHAMP Accelerometer

A method of processing the data obtained with the CHAMP satelliteborne accelerometer is introduced. Through an analysis of the data the fault in the x-axis of the instrument is verified. We examined the accuracy of the atmospheric models in solar maximum years with the accelerometer data obtained from 2001 to 2002 and the inversion of the atmospheric density from the tangential non-gravitational acceleration. Then from a statistical analysis of the errors of the models, DTM94 and MSIS90, we obtained the following quantitative conclusions. During the solar maximum years the error of DTM94 is 30% to 35%, and that of MSIS90 is smaller at 25% to 30%. The greatest difference between the two models is about 10%.     

Atmospheric densities derived from CHAMP/STAR accelerometer observations

The satellite CHAMP carries the accelerometer STAR in its payload and thanks to the GPS and SLR tracking systems accurate orbit positions can be computed. Total atmospheric density values can be retrieved from the STAR measurements, with an absolute uncertainty of 10-15%, under the condition that an accurate radiative force model, satellite macro-model, and STAR instrumental calibration parameters are applied, and that the upper-atmosphere winds are less than . The STAR calibration parameters (i.e. a bias and a scale factor) of the tangential acceleration were accurately determined using an iterative method, which required the estimation of the gravity field coefficients in several iterations, the first result of which was the EIGEN-1S (Geophys. Res. Lett. 29 (14) (2002) 10.1029) gravity field solution. The procedure to derive atmospheric density values is as follows: (1) a reduced-dynamic CHAMP orbit is computed, the positions of which are used as pseudo-observations, for reference purposes; (2) a dynamic CHAMP orbit is fitted to the pseudo-observations using calibrated STAR measurements, which are saved in a data file containing all necessary information to derive density values; (3) the data file is used to compute density values at each orbit integration step, for which accurate terrestrial coordinates are available. This procedure was applied to 415 days of data over a total period of 21 months, yielding 1.2 million useful observations. The model predictions of DTM-2000 (EGS XXV General Assembly, Nice, France), DTM-94 (J. Geod. 72 (1998) 161) and MSIS-86 (J. Geophys. Res. 92 (1987) 4649) were evaluated by analysing the density ratios (i.e. “observed” to “computed” ratio) globally, and as functions of solar activity, geographical position and season. The global mean of the density ratios showed that the models underestimate density by 10-20%, with an rms of 16-20%. The binning as a function of local time revealed that the diurnal and semi-diurnal components are too strong in the DTM models, while all three models model the latitudinal gradient inaccurately. Using DTM-2000 as a priori, certain model coefficients were re-estimated using the STAR-derived densities, yielding the DTM-STAR test model. The mean and rms of the global density ratios of this preliminary model are 1.00 and 15%, respectively, while the tidal and latitudinal modelling errors become small. This test model is only representative of high solar activity conditions, while the seasonal effect is probably not estimated accurately due to correlation with the solar activity effect. At least one more year of data is required to separate the seasonal effect from the solar activity effect, and data taken under low solar activity conditions must also be assimilated to construct a model representative under all circumstances.     

Variation in Coronal Activity from Solar Cycle 24 Minimum to Maximum Using Three-Dimensional Reconstructions of the Coronal Electron Density from STEREO/COR1

Three-dimensional electron density distributions in the solar corona are reconstructed for 100 Carrington rotations (CR 2054?–?2153) during 2007/03?–?2014/08 using the spherically symmetric method from polarized white-light observations with the inner coronagraph (COR1) onboard the twin Solar Terrestrial Relations Observatory (STEREO). These three-dimensional electron density distributions are validated by comparison with similar density models derived using other methods such as tomography and a magnetohydrodynamics (MHD) model as well as using data from the Solar and Heliospheric Observatory (SOHO)/Large Angle and Spectrometric Coronagraph (LASCO)-C2. Uncertainties in the estimated total mass of the global corona are analyzed based on differences between the density distributions for COR1-A and -B. Long-term variations of coronal activity in terms of the global and hemispheric average electron densities (equivalent to the total coronal mass) reveal a hemispheric asymmetry during the rising phase of Solar Cycle 24, with the northern hemisphere leading the southern hemisphere by a phase shift of 7?–?9 months. Using 14 CR (\(\approx13\)-month) running averages, the amplitudes of the variation in average electron density between Cycle 24 maximum and Cycle 23/24 minimum (called the modulation factors) are found to be in the range of 1.6?–?4.3. These modulation factors are latitudinally dependent, being largest in polar regions and smallest in the equatorial region. These modulation factors also show a hemispheric asymmetry: they are somewhat larger in the southern hemisphere. The wavelet analysis shows that the short-term quasi-periodic oscillations during the rising and maximum phases of Cycle 24 have a dominant period of 7?–?8 months. In addition, it is found that the radial distribution of the mean electron density for streamers at Cycle 24 maximum is only slightly larger (by \(\approx30\%\)) than at cycle minimum.     

Statistical Analysis of Solar Events Associated with Storm Sudden Commencements over One Year of Solar Maximum During Cycle 23: Propagation from the Sun to the Earth and Effects

Taking the 32 storm sudden commencements (SSCs) listed by the International Service of Geomagnetic Indices (ISGI) of the Observatory de l’Ebre during 2002 (solar activity maximum in Cycle 23) as a starting point, we performed a multi-criterion analysis based on observations (propagation time, velocity comparisons, sense of the magnetic field rotation, radio waves) to associate them with solar sources, identified their effects in the interplanetary medium, and looked at the response of the terrestrial ionized and neutral environment. We find that 28 SSCs can be related to 44 coronal mass ejections (CMEs), 15 with a unique CME and 13 with a series of multiple CMEs, among which 19 (68%) involved halo CMEs. Twelve of the 19 fastest CMEs with speeds greater than 1000 km?s^?1 are halo CMEs. For the 44 CMEs, including 21 halo CMEs, the corresponding X-ray flare classes are: 3 X-class, 19 M-class, and 22 C-class flares. The probability for an SSC to occur is 75% if the CME is a halo CME. Among the 500, or even more, front-side, non-halo CMEs recorded in 2002, only 23 could be the source of an SSC, i.e. 5%. The complex interactions between two (or more) CMEs and the modification of their trajectories have been examined using joint white-light and multiple-wavelength radio observations. The detection of long-lasting type IV bursts observed at metric–hectometric wavelengths is a very useful criterion for the CME–SSC events association. The events associated with the most depressed Dst values are also associated with type IV radio bursts. The four SSCs associated with a single shock at L1 correspond to four radio events exhibiting characteristics different from type IV radio bursts. The solar-wind structures at L1 after the 32 SSCs are 12 magnetic clouds (MCs), 6 interplanetary coronal mass ejections (ICMEs) without an MC structure, 4 miscellaneous structures, which cannot unambiguously be classified as ICMEs, 5 corotating or stream interaction regions (CIRs/SIRs), one CIR caused two SSCs, and 4 shock events; note than one CIR caused two SSCs. The 11 MCs listed in 3 or more MC catalogs covering the year 2002 are associated with SSCs. For the three most intense geomagnetic storms (based on Dst minima) related to MCs, we note two sudden increases of the Dst, at the arrival of the sheath and the arrival of the MC itself. In terms of geoeffectiveness, the relation between the CME speed and the magnetic-storm intensity, as characterized using the Dst magnetic index, is very complex, but generally CMEs with velocities at the Sun larger than 1000 km?s^?1 have larger probabilities to trigger moderate or intense storms. The most geoeffective events are MCs, since 92% of them trigger moderate or intense storms, followed by ICMEs (33%). At best, CIRs/SIRs only cause weak storms. We show that these geoeffective events (ICMEs or MCs) trigger an increased and combined auroral kilometric radiation (AKR) and non-thermal continuum (NTC) wave activity in the magnetosphere, an enhanced convection in the ionosphere, and a stronger response in the thermosphere. However, this trend does not appear clearly in the coupling functions, which exhibit relatively weak correlations between the solar-wind energy input and the amplitude of various geomagnetic indices, whereas the role of the southward component of the solar-wind magnetic field is confirmed. Some saturation appears for Dst values \(< -100\) nT on the integrated values of the polar and auroral indices.     

Proposal to Use MAGDAS/CPMN to Study the Equatorial Electrojet: A Philippine Contribution to the International Heliophysical Year

As a Philippine contribution to the International Heliophysical Year, we propose to use the MAGnetic Data Acquisition System/Circum Pan-Pacific Magnetometer Network (MAGDAS/CPMN), installed by the Space Environment Research Center (SERC), Kyushu University along the 210° magnetic meridian and the magnetic equator, to study the equatorial electrojet (EEJ) and counter electrojet (CEJ). Through this installation, it is made possible to observe geomagnetic field variations in real time. By utilizing this network of ground-based instruments, we hope to elucidate their regular day-to-day and seasonal variabilities and variations during magnetic storms and substorms. We also want to study the behavior of this ionospheric current system before, during, and after the occurrence of an earthquake.