Analysis of the positive ionospheric response to a moderate geomagnetic storm using a global numerical model

Current theories of F-layer storms are discussed using numerical simulations with the Upper Atmosphere Model, a global self-consistent, time dependent numerical model of the thermosphere-ionosphere-plasmasphere-magnetosphere system including electrodynamical coupling effects. A case study of a moderate geomagnetic storm at low solar activity during the northern winter solstice exemplifies the complex storm phenomena. The study focuses on positive ionospheric storm effects in relation to thermospheric disturbances in general and thermospheric composition changes in particular. It investigates the dynamical effects of both neutral meridional winds and electric fields caused by the disturbance dynamo effect. The penetration of short-time electric fields of magnetospheric origin during storm intensification phases is shown for the first time in this model study. Comparisons of the calculated thermospheric composition changes with satellite observations of AE-C and ESRO-4 during storm time show a good agreement. The empirical MSISE90 model, however, is less consistent with the simulations. It does not show the equatorward propagation of the disturbances and predicts that they have a gentler latitudinal gradient. Both theoretical and experimental data reveal that although the ratio of [O]/[N₂] at high latitudes decreases significantly during the magnetic storm compared with the quiet time level, at mid to low latitudes it does not increase (at fixed altitudes) above the quiet reference level. Meanwhile, the ionospheric storm is positive there. We conclude that the positive phase of the ionospheric storm is mainly due to uplifting of ionospheric F2-region plasma at mid latitudes and its equatorward movement at low latitudes along geomagnetic field lines caused by large-scale neutral wind circulation and the passage of travelling atmospheric disturbances (TADs). The calculated zonal electric field disturbances also help to create the positive ionospheric disturbances both at middle and low latitudes. Minor contributions arise from the general density enhancement of all constituents during geomagnetic storms, which favours ion production processes above ion losses at fixed height under day-light conditions.     

Validation of an annual cycle simulation with a T42-L20 GCM

An annual cycle of an atmospheric general circulation model (AGCM) is presented. The winter and summer zonal averages of the atmospheric fields are compared with an observed climatology. The main features of the observed seasonal means are well reproduced by the model. One of the main discrepancies is that the simulated atmosphere is too cold, particularly in its upper part. Some other discrepancies might be explained by the interannual variability. The AGCM surface fluxes are directly compared to climatological estimates. On the other hand, the calculation of meridional heat transport by the ocean, inferred from the simulated energy budget, can be compared to transport induced from climatologies. The main result of this double comparison is that AGCM fluxes generally are within the range of climatological estimates. The main deficiency of the model is poor partitioning between solar and non-solar heat fluxes in the tropical belt. The meridional heat transport also reveals a significant energy-loss by the Northern Hemisphere ocean north of 45° N. The possible implications of model surface flux deficiencies on coupling with an oceanic model are discussed.This paper was presented at the International Conference on Modelling of Global Climate Change and Variability, held in Hamburg 11–15 September 1989 under the auspices of the Meteorological Institute of the University of Hamburg and the Max Planck Institute for Meteorology. Guest Editor for these papers is Dr. L. Dümenil     

A crustal suture and lineament in North Africa

A possible suture between an old craton in West Africa and the Arabian—Nubian shield is marked by a persistent zone of Phanerozoic weakness. This zone extends between the Nile and Niger deltas and passes through the Qattara embayment, along the Bahariya fault, through the Kufra basin, between the Tibesti and Jabal al Uwaynat massifs, through the Bahr el Ghazal and Lake Chad areas, and along the Benoue trough.     

Fast integration of low orbiter's trajectory perturbed by the earth's non-sphericity

A fast algorithm is proposed to integrate the trajectory of a low obiter perturbed by the earth's non-sphericity. The algorithm uses a separation degree to define the low-degree and the high-degree acceleration components, the former computed rigorously, and the latter interpolated from gridded accelerations. An FFT method is used to grid the accelerations. An optimal grid type for the algorithm depends on the trajectory's permissible error, speed, and memory capacity. Using the non-spherical accelerations computed from EGM96 to harmonic degree 360, orbit integrations were performed for a low orbiter at an altitude of 170 km. For a separation degree of 50, the new algorithm, together with the predict-pseudo correct method, speeds up the integration by 145 times compared to the conventional algorithm while keeping the errors in position and velocity below 10⁻⁴ m and 10⁻⁷ m/s for a 3-day arc. Received: 28 July 1997 / Accepted: 1 April 1998     

A Composite Semisupervised SVM for Classification of Hyperspectral Images

This letter presents a novel composite semisupervised support vector machine (SVM) for the spectral-spatial classification of hyperspectral images. In particular, the proposed technique exploits the following: 1) unlabeled data for increasing the reliability of the training phase when few training samples are available and 2) composite kernel functions for simultaneously taking into account spectral and spatial information included in the considered image. Experiments carried out on a hyperspectral image pointed out the effectiveness of the presented technique, which resulted in a significant increase of the classification accuracy with respect to both supervised SVMs and progressive semisupervised SVMs with single kernels, as well as supervised SVMs with composite kernels.