Thermodynamics of climate change between cloud cover, atmospheric temperature and humidity

On a global and annual average, we find a parameterization in which the cloud cover increase is proportional to the mid tropospheric temperature increase, with a negative proportionality factor. If the relative humidity is conserved throughout the troposphere, a 1 °C heating (cooling) of the mid troposphere, decreases (increases) the cloud cover by 1.5 percentage points (pp). But if the relative humidity is not conserved, then the cloud cover decreases (increases) by 7.6 pp. If the shortwave reflection effect of the cloud cover is dominant on a global scale, this parameterization leads to a predominant positive feedback: if the temperature increases like in the current climate change, the cloud cover decreases and more solar radiation reaches the surface increasing the temperature even more. The contribution of the present work consists in finding that the negative sign of the proportionality factor is due to the Clausius–Clapeyron equation; that is, to the magnitude of the derivative of the saturation vapor pressure at the typical standard surface temperature of 288 K. The negative sign of the factor is independent on the conservation or non-conservation of relative humidity in the troposphere under climate change.

Distribution of the Proportionality Coefficient of Winter Route Accounting

In previous studies it was shown that the coefficient of proportionality of the winter route count (WRC) of animals included in the formula of WRC in the form of a constant multiplier π/2, is actually a random variable – the same as the average number of intersections account route traces per unit length, and the average length of the diurnal animals. The value π/2 is the mathematical expectation value of the proportionality factor, provided that the count route equiprobably crosses the daily footprint at any place and at any angle from 0 to 2π during a winter route counting of animals. At the same time, both the nature of the distribution of the coefficient as a random variable and the values of its variance as its other statistical characteristics remained unknown. In this study, it was found that when the above-mentioned count conditions are met, the distribution of the proportionality coefficient of WRC as a random variable will be exponential or power-like. This allows calculating the values of its variance and relative statistical error in advance without collecting additional count data.

Mesoscale numerical modeling of the boundary layer of the atmosphere adapted to the Northwestern Black Sea region. Part 2. Finite-difference solution and adaptation to real physical and geographical conditions of the area

The article describes the finite-difference solution of the system of differential equations of the atmospheric boundary layer hydrothermodynamics adapted to the Northwestern Black Sea region. The research presents the description of the sequence of calculations schematically shown on the flowchart. The applied mathematical model was adapted in relation to five aspects: coast geomorphology (coastline shape), land geomorphology (actual terrain of the studied territory), thermal and physical characteristics of soil (density, specific gravity, porosity, thermal conductivity factor), roughness (roughness parameter) and optical characteristics (albedo) of the underlying surface. The coastline shape was described with consideration of water proportion available in the current cell of the spatial grid. If the proportion exceeded 50 %, it was assumed that such cell includes land, and vice versa. The terrain matrix was formed by removing the elevation values at each point of the calculated area from official electronic elevation maps. The thermal and physical characteristics of the soil were set depending on a type of soil observed at the current calculated point. The method of roughness elements double recording during growing and non-growing periods of the year was used to consider the roughness of the underlying surface. This method consists in the fact that, depending on the agricultural zoning and its subject content, there is a certain background weighted average value of roughness elements ensemble elevation that transforms into a roughness parameter through the proportionality factor. In such a case, the proportionality factor is linked to a type of a real roughness element at a specific point. Thus, a comprehensive assessment of roughness features of the territory under study was obtained. The albedo of the underlying surface was taken for three various periods of the year: growing period (April-September), post-growing period – months before winter and the first month of spring (October-November, March) and winter period (December-February). Nature of the external coating of the underlying surface related to optical properties should be also taken into account.

Prediction of performance of 2D DCT-based filter and adaptive selection of its parameters

To enhance images, one often has to apply a filtering operation (denoising). However, there are several issues within the denoising. One of them is that sometimes denoising can be not efficient. Another issue regards a selection of an appropriate filter and setting of its parameters. As a particular case, we consider a 2D DCTbased filter with 8x8 pixel fully overlapping blocks where one of the parameters is a proportionality factor (PF) used in the threshold setup. We show that a performance of the considered filter in the sense of standard PSNR and visual quality metric PSNR-HVS-M can be predicted before applying image filtering procedure. This prediction is sufficiently faster than the denoising itself and accurate enough. We demonstrate that, having DCT statistics in a limited number of image blocks, such a prediction can be done for several values of PF. This allows deciding is it worth applying filtering to an image at hand. If the denoising is desired, it is also possible to select the PF optimal value for the considered image and noise intensity. Such a procedure, in some cases, can result in improvement of output PSNR or PSNR-HVS-M by up to 1 dB in comparison to the default parameters setup.

Distances and parallax bias in Gaia DR2

ABSTRACT We derive Bayesian distances for all stars in the radial velocity sample of Gaia DR2, and use the statistical method of Schönrich, Binney & Asplund to validate the distances and test the Gaia parallaxes. In contrast to other methods, which rely on special sources, our method directly tests the distances to all stars in our sample. We find clear evidence for a near-linear trend of distance bias f with distance s, proving a parallax offset δp. On average, we find ${\delta _{\rm p}}= -0.054 \, {\rm mas}$ (parallaxes in Gaia DR2 need to be increased) when accounting for the parallax uncertainty underestimate in the Gaia set (compared to ${\delta _{\rm p}}= -0.048 \, {\rm mas}$ on the raw parallax errors), with negligible formal error and a systematic uncertainty of about $0.006 \, {\rm mas}$. The value is in concordance with results from asteroseismic measurements, but differs from the much lower bias found on quasar samples. We further use our method to compile a comprehensive set of quality cuts in colour, apparent magnitude, and astrometric parameters. Lastly, we find that for this sample δp appears to strongly depend on σp (when including the additional $0.043 \, {\rm mas}$) with a statistical confidence far in excess of 10σ and a proportionality factor close to 1, though the dependence varies somewhat with σp. Correcting for the σp dependence also resolves otherwise unexplained correlations of the offset with the number of observation periods ${n_{\rm vis}}$ and ecliptic latitude. Every study using Gaia DR2 parallaxes/distances should investigate the sensitivity of its results on the parallax biases described here and – for fainter samples – in the DR2 astrometry paper.

Thermal Convection Forecast using a Theoretical Model Calibrated with Statistical Data from Soaring Flights

A forecasting scheme of the thermal updraft velocity based on a theoretical model and data collected from flights records at gliding competitions, is presented. The forecasting scheme was based on the hypothesis that there is linear relationship between the overheat function at ground surface and the temperature difference between soil and air. The proportionality factor of this relationship was determined experimentally using observations recorded during gliding flights. The results showed that based on this simple scheme forecasting thermal convection is possible at any geographical location.

Characterization of Triboelectric Charge Generation between PTFE and Nylon after Repeated Contacts

The charge generation between PTFE and Nylon 6,6 has been analyzed under different settings of temperature, humidity and mechanical load. It is found that the charging characteristics of the sample materials in terms of the parameters investigated in this study (e.g. temperature, relative humidity and applied force) are linear. Furthermore, the experimental results show that the proportionality factor between applied load and maximum achievable surface charge is affected by the sample temperature. As we show this fact is most likely attributed to the strongly temperature-dependent elastic properties of polymeric materials. The discoveries lead us to a mathematical formulation for the surface charge density which allows the investigation of maximum charge density for every single operating point within the parameter variation limits. The model parameter for two different structured material pairs are obtained from measurements and applied to the mathematical formulation. The theoretical data demonstrates that the proportionality factor between sample temperature and surface charge is strongly affected by relative humidity.