Stability of Coalescence Hidden variable Fractal Interpolation Surfaces

In the present paper, the stability of Coalescence Hidden variable Fractal Interpolation Surfaces(CHFIS) is established. The estimates on error in approximation of the data generating function by CHFIS are found when there is a perturbation in independent, dependent and hidden variables. It is proved that any small perturbation in any of the variables of generalized interpolation data results in only small perturbation of CHFIS. Our results are likely to be useful in investigations of texture of surfaces arising from the simulation of surfaces of rocks, sea surfaces, clouds and similar natural objects wherein the generating function depends on more than one variable

Binaries discovered by the SPY project. IV, Five single-lined DA double white dwarfs

We present results from our ongoing follow-up observations of double white dwarf binaries detected in the ESO SN Ia Progenitor SurveY (SPY). We discuss our observing strategy and data analysis and present the orbital solutions of five close double white dwarf binaries: HE0320−1917, HE1511−0448, WD0326−273, WD1013−010 and WD1210+140. Their periods range from 0.44 to 3.22 days. In none of these systems we find any spectral lines originating from the companion. This rules out main sequence companions and indicates that the companion white dwarfs are significantly older and cooler than the bright component. Infrared photometry suggests the presence of a cool, helium-rich white dwarf companion in the binary WD 0326−273. We briefly discuss the consequences of our findings for our understanding of the formation and evolution of double white dwarfs

Burst dynamics during drainage displacements in porous media: Simulations and experiments

We investigate the burst dynamics during drainage going from low to high injection rate at various fluid viscosities. The bursts are identified as pressure drops in the pressure signal across the system. We find that the statistical distribution of pressure drops scales according to other systems exhibiting self-organized criticality. The pressure signal was calculated by a network model that properly simulates drainage displacements. We compare our results with corresponding experiments.Comment: 7 pages, 4 figures. Submitted to Europhys. Let

A climate change simulation starting from 1935

Due to restrictions in the available computing resources and a lack of suitable observational data, transient climate change experiments with global coupled ocean-atmosphere models have been started from an initial state at equilibrium with the present day forcing. The historical development of greenhouse gas forcing from the onset of industrialization until the present has therefore been neglected. Studies with simplified models have shown that this "cold start" error leads to a serious underestimation of the anthropogenic global warming. In the present study, a 150-year integration has been carried out with a global coupled ocean-atmosphere model starting from the greenhouse gas concentration observed in 1935, i.e., at an early time of industrialization. The model was forced with observed greenhouse gas concentrations up to 1985, and with the equivalent C02 concentrations stipulated in Scenario A ("Business as Usual") of the Intergovernmental Panel on Climate Change from 1985 to 2085. The early starting date alleviates some of the cold start problems. The global mean near surface temperature change in 2085 is about 0.3 K (ca. 10) higher in the early industrialization experiment than in an integration with the same model and identical Scenario A greenhouse gas forcing, but with a start date in 1985. Comparisons between the experiments with early and late start dates show considerable differences in the amplitude of the regional climate change patterns, particularly for sea level. The early industrialization experiment can be used to obtain a first estimate of the detection time for a greenhouse-gas-induced near-surface temperature signal. Detection time estimates are obtained using globally and zonally averaged data from the experiment and a long control run, as well as principal component time series describing the evolution of the dominant signal and noise modes. The latter approach yields the earliest detection time (in the decade 1990-2000) for the time-evolving near-surface temperature signal. For global-mean temperatures or for temperatures averaged between 45°N and 45°S, the signal detection times are in the decades 2015-2025 and 2005-2015, respectively. The reduction of the "cold start" error in the early industrialization experiment makes it possible to separate the near-surface temperature signal from the noise about one decade earlier than in the experiment starting in 1985. We stress that these detection times are only valid in the context of the coupled model's internally-generated natural variability, which possibly underestimates low frequency fluctuations and does not incorporate the variance associated with changes in external forcing factors, such as anthropogenic sulfate aerosols, solar variability or volcanic dust. © 1995 Springer-Verlag