Interplanetary Shocks and Solar Wind Structure Approaching Solar Maximum: Helios,IMP-8 and Voyager Observations

We studied solar wind observations of five different spacecraft: Helios 1, Helios 2, IMP-8, Voyager 1 and Voyager 2, from November 1977 to February 1978. In this period the large-scale dynamics of the solar wind near of the ecliptic plane was characterized by transient forward shocks (TFSs), ejecta, unstable corotating interaction regions (CIRs), and complex and variable magnetic sector structures. We identified 12 forward shock events of different origin. We did not find any clear tendency of the shock parameters with heliocentric distance nor longitudinal angle, but comparing the observations of each shock event we found local variations in the shock strength and the mean propagation velocities from one spacecraft to another. These unsystematic variations indicate that there were local deformations of the shock fronts, which we attribute to the inhomogenuos solar wind structure that affects the shock propagation. This revised version was published online in August 2006 with corrections to the Cover Date.     

Association of optical tracklets from a geosynchronous belt survey via the direct Bayesian admissible region approach

The direct Bayesian admissible region approach is an a priori state free measurement association and initial orbit determination technique for optical tracks. In this paper, we test a hybrid approach that appends a least squares estimator to the direct Bayesian method on measurements taken at the Zimmerwald Observatory of the Astronomical Institute at the University of Bern. Over half of the association pairs agreed with conventional geometric track correlation and least squares techniques. The remaining pairs cast light on the fundamental limits of conducting tracklet association based solely on dynamical and geometrical information.     

Validation on MERSI/FY-3A precipitable water vapor product

The precipitable water vapor is one of the most active gases in the atmosphere which strongly affects the climate. China's second-generation polar orbit meteorological satellite FY-3A equipped with a Medium Resolution Spectral Imager (MERSI) is able to detect atmospheric water vapor. In this paper, water vapor data from AERONET, radiosonde and MODIS were used to validate the accuracy of the MERSI water vapor product in the different seasons and climatic regions of East Asia. The results show that the values of MERSI water vapor product are relatively lower than that of the other instruments and its accuracy is generally lower. The mean bias (MB) was ?0.8 to ?12.7?mm, the root mean square error (RMSE) was 2.2–17.0?mm, and the mean absolute percentage error (MAPE) varied from 31.8% to 44.1%. On the spatial variation, the accuracy of MERSI water vapor product in a descending order was from North China, West China, Japan -Korea, East China, to South China, while the seasonal variation of accuracy was the best for winter, followed by spring, then in autumn and the lowest in summer. It was found that the errors of MERSI water vapor product was mainly due to the low accuracy of radiation calibration of the MERSI absorption channel, along with the inaccurate look-up table of apparent reflectance and water vapor within the water vapor retrieved algorithm. In addition, the surface reflectance, the mixed pixels of image cloud, the humidity and temperature of atmospheric vertical profile and the haze were also found to have affected the accuracy of MERSI water vapor product.     

Upgrading CCIR's foF2 maps using available ionosondes and genetic algorithms

We have developed a new approach towards a new database of the ionospheric parameter $f_{o}F2$. This parameter, being the frequency of the maximum of the ionospheric electronic density profile and its main modeller, is of great interest not only in atmospheric studies but also in the realm of radio propagation. The current databases, generated by CCIR (Committee Consultative for Ionospheric Radiowave propagation) and URSI (International Union of Radio Science), and used by the IRI (International Reference Ionosphere) model, are based on Fourier expansions and have been built in the 60s from the available ionosondes at that time. The main goal of this work is to upgrade the databases by using new available ionosonde data. To this end we used the IRI diurnal/spherical expansions to represent the $f_{o}F2$ variability, and computed its coefficients by means of a genetic algorithm (GA). In order to test the performance of the proposed methodology, we applied it to the South American region with data obtained by RAPEAS (Red Argentina para el Estudio de la Atmósfera Superior, i.e. Argentine Network for the Study of the Upper Atmosphere) during the years 1958–2009. The new GA coefficients provide a global better fit of the IRI model to the observed $f_{o}F2$ than the CCIR coefficients. Since the same formulae and the same number of coefficients were used, the overall integrity of IRI’s typical ionospheric feature representation was preserved. The best improvements with respect to CCIR are obtained at low solar activities, at large (in absolute value) modip latitudes, and at night-time. The new method is flexible in the sense that can be applied either globally or regionally. It is also very easy to recompute the coefficients when new data is available. The computation of a third set of coefficients corresponding to days of medium solar activity in order to avoid the interpolation between low and high activities is suggested. The same procedure as for $f_{o}F2$ can be perfomed to obtain the ionospheric parameter M(3000)F2.     

Order out of Randomness: Self-Organization Processes in Astrophysics

Self-organization is a property of dissipative nonlinear processes that are governed by a global driving force and a local positive feedback mechanism, which creates regular geometric and/or temporal patterns, and decreases the entropy locally, in contrast to random processes. Here we investigate for the first time a comprehensive number of (17) self-organization processes that operate in planetary physics, solar physics, stellar physics, galactic physics, and cosmology. Self-organizing systems create spontaneous “order out of randomness”, during the evolution from an initially disordered system to an ordered quasi-stationary system, mostly by quasi-periodic limit-cycle dynamics, but also by harmonic (mechanical or gyromagnetic) resonances. The global driving force can be due to gravity, electromagnetic forces, mechanical forces (e.g., rotation or differential rotation), thermal pressure, or acceleration of nonthermal particles, while the positive feedback mechanism is often an instability, such as the magneto-rotational (Balbus-Hawley) instability, the convective (Rayleigh-Bénard) instability, turbulence, vortex attraction, magnetic reconnection, plasma condensation, or a loss-cone instability. Physical models of astrophysical self-organization processes require hydrodynamic, magneto-hydrodynamic (MHD), plasma, or N-body simulations. Analytical formulations of self-organizing systems generally involve coupled differential equations with limit-cycle solutions of the Lotka-Volterra or Hopf-bifurcation type.     

Jets Downstream of Collisionless Shocks

Space Science Reviews - Particles are accelerated to very high, non-thermal energies in solar and space plasma environments. While energy spectra of accelerated electrons often exhibit a power law,...     

Comprehensive data reduction package for the Immersion GRating INfrared Spectrograph: IGRINS

We present a Python-based data reduction pipeline package (PLP) for the Immersion GRating INfrared Spectrograph (IGRINS), an instrument that covers the complete H- and K-bands in one exposure with a spectral resolving power of 40,000. The reduction steps carried out by the PLP include flat-fielding, background removal, order extraction, distortion correction, wavelength calibration, and telluric correction using spectra of A type standard stars. As the spectrograph has no moving parts, the PLP automatically reduces the data using predefined functions for the processes of order extraction, distortion correction, and wavelength calibration. Before the telluric correction of the target spectra, the intrinsic hydrogen absorption features of the standard A star are removed with a Gaussian fitting algorithm. The final result is the flux of the target as a function of wavelength. Users can customize the predefined functions for the extraction of the spectrum from the echellogram and adjust the parameters for the fitting functions for the spectra of celestial objects, using “fine-tuning” options, as necessary. Presently, the PLP produces the best results for point-source targets.