The Spatiotemporal Evolution of the Diurnal Cycle in Two WRF Simulations of Tropical Cyclones

The properties of diurnal variability in tropical cyclones (TCs) and the mechanisms behind them remain an intriguing aspect of TC research. This study provides a comprehensive analysis of diurnal variability in two simulations of TCs to explore these mechanisms. One simulation is a well known Hurricane Nature Run, which is a realistic simulation of a TC produced using the Weather Research and Forecasting model (WRF). The other simulation is a realistic simulation produced using WRF of Hurricane Florence (2018) using hourly ERA5 reanalysis data as input. Empirical orthogonal functions and Fourier filtering are used to analyze diurnal variability in the TCs. In both simulations a diurnal squall forms at sunrise in the inner core and propagates radially outwards and intensifies until midday. At midday the upper-level outflow strengthens, surface inflow weakens, and the cirrus canopy reaches its maximum height and radial extent. At sunset and overnight, the surface inflow is stronger, and convection inside the RMW peaks. Therefore, two diurnal cycles of convection exist in the TCs with different phases of maxima: eyewall convection at sunset and at night, and rainband convection in the early morning. This study finds that the diurnal pulse in the cirrus canopy is not advectively-driven, nor can it be attributed to weaker inertial stability at night; rather, the results indicate direct solar heating as a mechanism for cirrus canopy lifting and enhanced daytime outflow. These results show a strong diurnal modulation of tropical cyclone structure, and are consistent with other recent observational and modeling studies of the TC diurnal cycle.

There's more Wrangellia - Magnetic characterization of southern Alaska crust

In southern Alaska, Wrangellia-type magnetic crustal character extends from the Talkeetna Mountains southwest through the Alaska Range to the Bristol Bay region. Magnetic data analyses in the Talkeetna Mountains showed that there are mid-crustal differences in the magnetic properties of Wrangellia and the Peninsular terrane. After converting total field magnetic anomaly data to magnetic potential, we applied Fourier filtering techniques to remove magnetic responses from deep and shallow sources. The resulting mid-crustal magnetic characterization delineates the regional magnetic potential domains that correspond to the Wrangellia and Peninsular terranes throughout southern Alaska. These magnetic potential domains show that Wrangellia-type crust extends southwest to the Illiamna Lake region and that it overlaps the mapped Peninsular terrane. Upon reconsidering geologic ties between Wrangellia, Peninsular, and Alexander terranes we conclude that Peninsular terrane is part of what we here call Western Wrangellia. Western Wrangellia contains the Lower Jurassic Talkeetna volcanic arc and is similar to Wrangellia of the Vancouver Island area, Canada (Southern Wrangellia) which contains the Lower Jurassic Bonanza volcanic arc. Others have previously made this correlation and proposed that the Talkeetna arc-bearing part of southern Alaska was displaced from the Bonanza arc-bearing part of Canada. We generally agree and propose that about 1000 km of dextral displacement along ancestral Border Ranges fault segments and other faults of south-central Alaska separated Western Wrangellia from Southern Wrangellia. We think this displacement was mostly in the Late Jurassic and earliest Cretaceous, perhaps between about 160 and 130 Ma.

Dynamic Wind Turbine Blade Inspection Using Micro-Polarisation Spatial Phase Shift Digital Shearography

Shearography, as a novel non-destructive evaluation technique, has shown notable ability in the detection of composite materials. However, in current shearography practices, the phase shifting and loading methods applied are mainly static. For instance, vacuum hood or force loading facilities are often used in phase-shifting shearography, and these are hard to realise with robotic control, especially for on-board inspection. In this study, a dynamic process for detecting defects in the subsurface of a wind turbine blade (WTB) using spatial phase shift with dynamic thermal loading was proposed. The WTB sample underwent a dynamic thermal loading operation, and its status is captured by a Michelson interferometric-based spatial phase shift digital shearography system using a pixelated micro-polarisation array sensor. The captured images were analysed in a 2D frequency domain and low-pass filtered for phase map acquisition. The initial phase maps underwent a window Fourier filtering process and were integrated to produce a video sequence for realisation of visualising the first derivative of the displacement in the process of thermal loading. The approach was tested in experimental settings and the results obtained were presented and discussed. A comparative assessment of the approach with shearography fringe pattern analysis and temporal phase shift technique is also presented and discussed.

Methods of Projecting Mode Amplitude Changes on the Wavelength Axis in Order to Determine the Bending Radius on the Basis of TFBG Grating Spectra

Tilted fibre Bragg grating (TFBG) are used as sensors to determine many quantities such as refractive index, temperature, stress, rotation and bending. The TFBG spectrum contains a lot of information and various algorithms are used for its analysis. However, most of these algorithms are dedicated to the analysis of spectral changes under the influence of the refractive index. The most popular algorithm used for this purpose is to calculate the area occupied by cladding modes. Among the remaining algorithms, there are those that use the determination of the cut-off wavelength as a surrounding refractive index (SRI) indicator. Projection on the wavelength axis can also be used to calculate the bending radius of the fibre. However, this is a more difficult task than with SRI, because the mode decay in bending is not so easy to catch. In this article, we propose a multi-step algorithm that allows to determine the impact of bending on mode leakage. At the same time, the place on the wavelength from the side of the Bragg mode and the ghost mode is determined, which represents the cladding mode radiated from the cladding under the influence of bending. The developed algorithm consists of the following operations carried out on the transmission spectrum: Fourier filtering, calculation of the cumulative value of the spectral length, low-pass filtering of the cumulative curve or its corresponding polynomial approximation, determination of the first and second derivative of the approximated curve, and projection of the second derivative of the curve on the wavelength axis. The shift of the wavelength determined in this way indirectly indicates the bending radius of the optical fibre. Based on multiple measurements, we prove that the presented algorithm provides better results when determining the bending radius compared to other algorithms adopted for this purpose and proposed for SRI measurements. Additionally, we analyse the method of determining the shift of a fragment of the spectrum using the phase of the discrete Fourier transform.

Spectrally-selective Time-resolved Emission through Fourier-filtering (STEF)

In this manuscript we demonstrate that directing the emitted photon stream from a fluorescent sample through a fixed path-length imbalanced Mach-Zehnder interferometer allows us to separate and resolve the dynamics of different emitters without the use of filtering optics. Our method, Spectrallyselective Time-resolved Emission through Fourier-filtering (STEF) takes advantage of a careful selection of interferometer position where one signal can be canceled (or enhanced) due to its unique spectral characteristics. STEF is straightforward to implement and provides a complementary approach to separate spectrally overlapped signals based on their coherence length and carrier frequency. We also discuss how one can implement STEF with an imperfect Mach-Zehnder interferometer, increasing the utility of this method, and demonstrate how Mach-Zehnder filtering can be used to image fluorophores in biologically relevant samples.

Optical inspection of appearance faults for auto mirrors using Fourier filtering and convex hull arithmetic

Auto mirrors are indispensable essential in reflection of objects behind the car and act a crucial part in driving security. In manufacturing stages of auto mirrors, certain tasks operated unusually will cause producing scratches, chips, pinholes, bubbles, damaged edges, the general surface and profile faults on auto mirrors. Those appearance faults sometimes will severely have an impact on standard of the mirror reflection and grow the driving hazard. At traditional examination of auto mirrors in manufacturing process, almost all works are performed by human examiners. Manual examination is simple to be disturbed by foreign objects reflected on the mirror surfaces and arouse causing mistaken determinations of fault examination. Thence, this study works toward investigating the automatic appearance fault detection of auto mirrors. We propose a fault enhancement technique based on Fourier high-pass filtering and the convex hull arithmetic to inspect appearance faults on auto mirrors. This approach only utilizes their own information of testing images to judge whether there are any irregular appearance changes without the need of standard patterns for matching. Experimental outcomes illustrate that the appearance fault detection rate reaches to 95.13%, and the false alarm rate decreases to 1.88%, and the correct classification rate attains to 98.11%.

ChainLineNet: Deep-Learning-Based Segmentation and Parameterization of Chain Lines in Historical Prints

The paper structure of historical prints is sort of a unique fingerprint. Paper with the same origin shows similar chain line distances. As the manual measurement of chain line distances is time consuming, the automatic detection of chain lines is beneficial. We propose an end-to-end trainable deep learning method for segmentation and parameterization of chain lines in transmitted light images of German prints from the 16th Century. We trained a conditional generative adversarial network with a multitask loss for line segmentation and line parameterization. We formulated a fully differentiable pipeline for line coordinates’ estimation that consists of line segmentation, horizontal line alignment, and 2D Fourier filtering of line segments, line region proposals, and differentiable line fitting. We created a dataset of high-resolution transmitted light images of historical prints with manual line coordinate annotations. Our method shows superior qualitative and quantitative chain line detection results with high accuracy and reliability on our historical dataset in comparison to competing methods. Further, we demonstrated that our method achieves a low error of less than 0.7 mm in comparison to manually measured chain line distances.

DEPENDENCE OF THE QUALITY OF MACHINE TRANSLATION OF THE TEXT ON THE USED FOURIER TRANSFORMATION

Machine translation is widely used in the translation of commercial, technical, scientific information that is connected with the process of globalization and, accordingly, the expansion of the network of business relations. Mathematical methods related to machine translation of the texts have recently received new development due to the intensive development of Fourier transformation theory. Thus, the requirements for filtering accuracy in the processing of contrast signals and images have increased, allowing to create efficient filtering algorithms. Frequency algorithms are the most efficient of all the existing filtering algorithms, i.e., those where the coefficients of decomposition of the noisy signal by Fourier basis are the subject to processing. When using Fourier filtering algorithms, the properties of Fourier transformation play an important role, that depend on belonging to a particular class of differential functions. The necessary condition for the existence of the continuous Fourier transformation is the absolute convergence of some functions by means of which the real studied process is describing. In practice, the so-called “summation functions” are often used as simulated functions, which can be constructed using a linear matrix summation of Fourier series. As for the latter, scientists distinguish between both triangular and rectangular linear matrix methods. This paper is devoted to the study of the convergence conditions of Fourier transformations of both triangular and rectangular linear matrix methods for summing Fourier series. Moreover, this article shows that the rate of convergence of Fourier transformation of the rectangular linear Abel-Poisson method is at times faster than the rate of convergence of the analogous triangular linear Abel-Poisson method. This result can further significantly influence the choice of the more effective Fourier transformation used in the process of machine translation of the text.

Disentangling the mechanisms of wave-convection coupling using idealized simulations in a tropical channel: wave composites of the moist static energy budget

<p>Recent studies found that the coupling of equatorial waves to convection is key to improving weather forecasts in the tropics on the synoptic to the subseasonal timescale but many models struggle to realistically represent this coupling. To study the underlying mechanisms of convectively coupled equatorial waves, we use aquaplanet simulations with the ICOsahedral Nonhydrostatic (ICON) model in a tropical channel configuration with a horizontal grid spacing of 13 km and with a prescribed zonally symmetric, latitudinally varying sea surface temperature. We compare simulations with parameterized and explicit deep/shallow convection. Using wave identification tools that are based on Fourier filtering in time and space and on projections of dynamical fields on theoretical wave patterns, we observe a predominance of equator-symmetric equatorial waves such as Kelvin waves and slow large-scale variability resembling the Madden-Julian Oscillation.</p><p>To diagnose interactions between the equatorial waves and convection, we use a moist static energy (MSE) framework. A budget analysis for column integrated MSE shows that spatial anomalies of the net shortwave and longwave radiation and the surface enthalpy flux increase the spatial variance of the column MSE, while advection dampens variability. For wave-convection coupling we employ a wave composite technique for the terms of the MSE budget. Results from this analysis will be presented at the conference. The same filtering tools and diagnostics are applied to a realistic ICON simulation with a 2.5 km horizontal grid spacing from the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project.</p>