186,502 research outputs found
New spectral functions of the near-ground albedo derived from aircraft diffraction spectrometer observations
No full textThe airborne spectral observations of the upward and downward irradiances are
revisited to investigate the dependence of the near-ground albedo as a
function of wavelength in the entire solar spectrum for different surfaces
(sand, water, snow) and under different conditions (clear or cloudy sky). The
radiative upward and downward fluxes were determined by a diffraction
spectrometer flown on a research aircraft that was performing multiple flight
paths near the ground. The results obtained show that the near-ground albedo
does not generally increase with increasing wavelengths for all kinds of
surfaces as is widely believed today. Particularly, in the case of water
surfaces it was found that the albedo in the ultraviolet region is more or
less independent of the wavelength on a long-term basis. Interestingly, in
the visible and near-infrared spectra the water albedo obeys an almost
constant power-law relationship with wavelength. In the case of sand surfaces
it was found that the sand albedo is a quadratic function of wavelength,
which becomes more accurate if the ultraviolet wavelengths are neglected.
Finally, it was found that the spectral dependence of snow albedo behaves
similarly to that of water, i.e. both decrease from the ultraviolet to the
near-infrared wavelengths by 20–50%, despite the fact that their values
differ by one order of magnitude (water albedo being lower). In addition, the
snow albedo vs. ultraviolet wavelength is almost constant, while in the
visible near-infrared spectrum the best simulation is achieved by a
second-order polynomial, as in the case of sand, but with opposite slopes
Inaccuracies in seismicity and magnitude data used by Varotsos and co-workers - Reply
No full textA direct comparison of the predicted magnitude values (M(pred)) to the actual magnitude values (M(EQ)) of the earthquakes (EQs) is allowed only when both values, i.e., M(pred) and MEQ, refer to the same scale. In view of the fact that the Seismological Institute of the National Observatory of Athens (SI-NOA) publicly announces as MEQ the M(L)+0.5 value (Where ML the local magnitude), VAN made it clear long ago, that the predicted values M(pred) (after a proper calibration) referred to M(L)+0.5. Therefore, a self-consistent evaluation of VAN-predictions should consist of a direct comparison of M,red with the actual M(L)+0.5. Unfortunately, Wyss [1996] confuses the discussion by proceeding to a direct comparison of M(pred) With M(s)(PDE); this is not allowed because the values of M(L)+0.5 exceed, on the average, M(s)(PDE) by 1.0 unit. An additional confusion arises from the fact that the relation suggested by Hamada [1993], i.e., M(L)+0.5=m(b)+0.3, is misinterpreted by Wyss as saying M(s)(PDE)=m(b)+0.3. These two alterations by Wyss reveal that his Figures 1 and 2 are erroneous. Wyss [1996] also criticizes VAN, because (in an early publication) Varotsos et al. [1981b] used the Preliminary Bulletin of SI-NOA, instead of the final one. First of all, the final bulletin could not be used by VAN at that time, because it appeared (more than one year) after the publication of the paper by Varotsos et al. [1981b]. Secondly, the correlation between SESs and EQs is evident,when we use consistently, either the preliminary, or the final bulletin of SI-NOA. On the other hand, Wyss [1996] claims that he could not find any correlation between EQs and SESs; we show that this is due to the fact that Wyss included, in his study, small EQs that occurred several hundreds km away from the measuring VAN station (i.e., in Albania, western Turkey, etc.), but he simultaneously deleted the small magnitude EQs that occurred very close to that station. Wyss’s procedure is, of course, not acceptable and hence his Appendix B is wrong. Furthermore, Wyss’s claim that VAN added 25% of events to the list, is shown to be untrue. Beyond the unusual fact that Wyss quotes ‘’VAN’s statements” that have never been published by VAN, the following is also noted: although Wyss [1996] uses quotation marks (in order to indicate that he reproduced exactly what VAN said), he adds critical wording to VAN statements and hence their true meaning is drastically changed. For example, Wyss states: ‘’Varotros et al. [l981a] had first formulated that SESs ‘’occurred a few minutes before each earthquake [related to that SES]” (Varotsos et al. [1981a]).” Thus, Wyss leads the reader to the wrong conclusion that VAN initially claimed that SES have a lead time of a few minutes, and that VAN changed it later. However, we show that this lead time (published by VAN) referred to another the of precursor, and not to SES, but the words in brackets (which are added by Wyss) alter the true meaning of our statement
Self-diffusion in sodium under pressure revisited
No full textThe pressure - volume relation in sodium has been measured up to 100 GPa using high-resolution angle-dispersive synchrotron x-ray diffraction (Hanfland et al 2002 Phys. Rev. B 65 184109). In the light of these data, we show that a model suggested long ago (e.g., Varotsos et al 1978 J. Phys. C: Solid State Phys. 11 L305 - 15) can satisfactorily answer the long-standing question of the variation of the diffusion coefficient D under pressure P, which resulted in a curved ln D versus P plot, in the frame of a single operating mechanism (monovacancies). This is achieved without using any adjustable parameters
Correlation between positron lifetime spectroscopy and self-diffusion parameters in indium
No full textWeiler and Schaefer (1985) have recently published vacancy formation parameters for indium from a detailed analysis of positron lifetime spectra. Flower et al. (1985) have simultaneously published the pressure variation of the elastic constants. It is shown that these two sets of data when combined with earlier self-diffusion studies are interconnected through a thermodynamic relation published by Varotsos and Alexopoulos (1986)
Difficulty of statistical evaluation of an earthquake prediction method - Reply
No full textSeveral remarks of Utada [1996] are in agreement with the points discussed by Varotsos et al. [1996a]. Simple examples show that Mulargia and Gasperini’s [1992] main conclusion (i.e., that ‘’VAN predictions can be ascribed to chance”) is not due to ‘’ambiguities” of the VAN method, but to obvious mistakes in their calculation. These mistakes are also responsible for the paradox we revealed in the Appendix of Varotsos er al. [1996a]. The paradox (i.e., if we apply the procedure of Mulargia and Gasperini [1992], we ‘’conclude” that the results of an Ideally Perfect Earthquake Prediction Method, IPEPM, can be ascribed to chance) vanishes after correcting some of their mistakes
Calculation of point defect parameters in diamond
No full textWe show that the most recent values of the defect entropy and the defect enthalpy for the vacancy formation in diamond have a ratio which is comparable to the one predicted by a model suggested three decades ago [P. Varotsos and K. Alexopoulos, Phys. Rev. B 15, 4111 (1977); 18, 2683 (1978)]. This model, which interconnects the formation Gibbs energy with the bulk elastic and expansivity data, has been also recently found of value in high T-c superconductors as well as in glass-forming liquids
Summary of the five principles suggested by Varotsos et al. [1996] and the additional questions raised in this debate
No full textThe present paper cannot be considered, either as a rebuttal to any participant, or our overview of the debate. Its publication became necessary due to the fact that various participants raised additional questions, i.e., beyond the points suggested by Varotsos et al. [1996]. We clarify these questions that concern the noise discrimination from our electrical recordings, the recent laboratory experiments which support the emission of electrical precursors, and the question on whether, or not, a retroactive adjustment of the VAN prediction parameters was made, after the period 1987-1989 discussed in this debate. We draw attention to the fact that a continuous 9 year (i.e., 1987-1995) sample of VAN predictions is now available. For the benefit of the reader, the present paper also summarizes the essence of the five Principles suggested by Varotsos et al. [1996] (as a consequence, attention is drawn to a correct definition of the success rate). This essence remains exactly the same as it was initially suggested, because we do not feel, after the debate, that the various contributions cast a sound doubt on the correctness of any of these Principles. The calculations which claim that VAN predictions can be ascribed to chance strongly violate these Principles; the incorrectness of these calculations is beyond any doubt, because they 'reject' even an ideal earthquake prediction method. On the other hand, several well founded calculations convince that the VAN's success (and alarm) rate is very far beyond chance. The study of this paper is highly recommended to the reader before going through the details of each of our individual Replies
On the recent advances in the study of seismic electric signals (VAN method)
No full textSeismic electric signals (SES) are low frequency (≤1 Hz) changes of the electric field of the earth that have been first observed in Greece [Varotsos, P., Alexopoulos, K., Nomicos, K., 1981a. Seismic electric currents. Pract. Athens Acad. 56, 277-286; Varotsos, P., Alexopoulos, K., Nomicos, K., 1981b. Seven-hour precursors to earthquakes determined from telluric currents. Pract. Athens Acad. 56, 417-433; Varotsos, P., Alexopoulos, K., 1984a. Physical properties of the variations of the electric field of the earth preceding earthquakes, I. Tectonophysics 110, 73-98; Varotsos, P., Alexopoulos, K., 1984b. Physical properties of the variations of the electric field of the earth preceding earthquakes, II. Tectonophysics 110, 99-125] to precede earthquakes, with a lead time from several hours to a couple of months. Here, we review the recent advances on the SES observation and analysis, main points of which are the following: First, at epicentral distances of the order of 100 km, the SES electric field precedes markedly the time-derivative of the magnetic field; this finds applications in the determination of the epicenter of the impending earthquake and in the distinction between true SES and noise emitted from artificial sources. Second, a detectable difference in the time evolutions of the electric field components of SES exists, which can also be used for the determination of the epicenter of the impending earthquake. Third, the analysis of SES is significantly advanced in a recently introduced [Varotsos, P., Sarlis, N., Skordas, E., 2001. Spatio-temporal complexity aspects on the interrelation between seismic electric signals and seismicity. Pract. Athens Acad. 76, 294-321; Varotsos, P., Sarlis, N., Skordas, E., 2002a. Long-range correlations in the electric signals that precede rupture. Phys. Rev. E 66, 011902] new time-domain, termed as natural time domain. This has been inspired from the theory of critical phenomena, which has been suggested long ago by our group. The natural time-domain, beyond other applications in diverse fields, enables the distinction of similar looking electric signals that are emitted from systems of different dynamics as well as provides a better estimation for the time window of an impending mainshock. The spectral content of the seismic activity in natural time, evolves consecutively in time upon the occurrence of every new event, and finally coincides to that of the SES a few hours to a few days before the mainshock, thus allowing the estimation of the occurrence time of the impending mainshock with an accuracy that was not hitherto available. © 2006 Elsevier Ltd. All rights reserved
On the question of the calculation of migration volumes in ionic crystals
No full textThe migration volume vm consists of two contributions vms= - T(∂sm/∂P)|T and vhm = (∂hm/∂P)|T where ∂m, hm denote the migration entropy and enthalpy. By analysing the recent experimental data of Andeen, Hayden and Fontanella (1980) on SrF2 + Er+3, obtained by dielectric-loss techniques under various pressures, the term vsm is found to be a considerable contribution t o vm. At 330 K the ratio|vsm|vhm is 23%. Further the compressibility ∼m of the migration volume is found to exceed the bulk compressibility K by one order of magnitude. The application of a recent macroscopic model proposed by Varotsos and Alexopoulos (1978) not only explains that ∼m is appreciably larger than but it also leads t o a value of vsm/vhm appreciably different than zero. The common disagreement between the ‘static lattice’ calculations of vm and experiments lies in the fact that the contribution cannot be neglected. © 1980 Taylor & Francis Group, LLC
A few considerations for ascribing statistical significance to earthquake predictions - Reply
No full textSeveral remarks made by Stark [1996] are in basic agreement with those of Varotsos et al. [1996a] (e.g., ‘’If we choose to issue a prediction only when the expected magnitude exceeds 5.0, then, if our prediction algorithm works, we would expect to fail to predict some events with magnitude 5.0 and smaller (and even some larger events)”, ‘’ It is generally accepted that ‘’raw” seismicity series are not Poisson distributed...”, etc.). However, in this Reply we clarify a few misunderstandings that led Stark [1996] to state that Varotsos et al. [1996a] made some erroneous suggestions. We emphasize that the tolerance limits in the big majority of the VAN predictions were not calibrated a posteriori, because these limits were published one year before the period 1987-1989 under discussion. Only in two, out of 25, successful correlations the Delta t-value was extended, a posteriori; we emphasize, however, that these two predictions were recognized well in advance as belonging to a new case which was then labelled as SES electrical activity (sequence of SESs) that differs from the case of single (isolated) SES. We do agree with the Stark’s [1996] suggestions according to which one ‘’avoids the necessity of specifying a probability distribution for earthquake variables, a task that is both controversial and problematic.
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