Spatiotemporal Averaging Research Articles

Spatio-temporal averaging of jets obscures the reinforcement of baroclinicity by latent heating

Abstract. Latent heating modifies the jet stream by modifying the vertical geostrophic wind shear, thereby altering the potential for baroclinic development. Hence, correctly representing diabatic effects is important for modelling the mid-latitude atmospheric circulation and variability. However, the direct effects of diabatic heating remain poorly understood. For example, there is no consensus on the effect of latent heating on the cross-jet temperature contrast. We show that this disagreement is attributable to the choice of spatio-temporal averaging. Jet representations relying on averaged wind tend to have the strongest latent heating on the cold flank of the jet, thus weakening the cross-jet temperature contrast. In contrast, jet representations reflecting the two-dimensional instantaneous wind field have the strongest latent heating on the warm flank of the jet. Furthermore, we show that latent heating primarily occurs on the warm flank of poleward directed instantaneous jets, which is the case for all storm tracks and seasons.

Characterizing normal perinatal development of the human brain structural connectivity.

Early brain development is characterized by the formation of a highly organized structural connectome, which underlies brain's cognitive abilities and influences its response to diseases and environmental factors. Hence, quantitative assessment of structural connectivity in the perinatal stage is useful for studying normal and abnormal neurodevelopment. However, estimation of the connectome from diffusion MRI data involves complex computations. For the perinatal period, these computations are further challenged by the rapid brain development, inherently low signal quality, imaging difficulties, and high inter-subject variability. These factors make it difficult to chart the normal development of the structural connectome. As a result, there is a lack of reliable normative baselines of structural connectivity metrics at this critical stage in brain development. In this study, we developed a computational method based on spatio-temporal averaging in the image space for determining such baselines. We used this method to analyze the structural connectivity between 33 and 44 postmenstrual weeks using data from 166 subjects. Our results unveiled clear and strong trends in the development of structural connectivity in the perinatal stage. We observed increases in measures of network integration and segregation, and widespread strengthening of the connections within and across brain lobes and hemispheres. We also observed asymmetry patterns that were consistent between different connection weighting approaches. Connection weighting based on fractional anisotropy and neurite density produced the most consistent results. Our proposed method also showed considerable agreement with an alternative technique based on connectome averaging. The new computational method and results of this study can be useful for assessing normal and abnormal development of the structural connectome early in life.

Self-organization underlies developmental robustness in plants

Development is a self-organized process that builds on cells and their interactions. Cells are heterogeneous in gene expression, growth, and division; yet how development is robust despite such heterogeneity is a fascinating question. Here, we review recent progress on this topic, highlighting how developmental robustness is achieved through self-organization. We will first discuss sources of heterogeneity, including stochastic gene expression, heterogeneity in growth rate and direction, and heterogeneity in division rate and precision. We then discuss cellular mechanisms that buffer against such noise, including Paf1C- and miRNA-mediated denoising, spatiotemporal growth averaging and compensation, mechanisms to improve cell division precision, and coordination of growth rate and developmental timing between different parts of an organ. We also discuss cases where such heterogeneity is not buffered but utilized for development. Finally, we highlight potential directions for future studies of noise and developmental robustness.

Physics-based thermal noise effect reduction in sonic IR crack length estimation

ABSTRACT Using heat diffusion models in sonic infrared (IR) inspection technology that captures arbitrary frictional heat generation function along a crack lends itself to estimation of crack length using thermal images alone. This study introduces novel physics-based approach that relies on the governing heat diffusion model linearity and superposition of point heat sources along crack to reduce thermal noise effect in crack length estimation. It utilises thermal images and their timestamps in sonic IR inspection to deliver spatiotemporal average representation of the aforementioned point heat sources to reduce thermal noise effect in crack length estimation. The proposed methodology is tested against two-dimensional and three-dimensional finite element simulations with an arbitrary frictional heat generation function along crack. Virtual random thermal noise levels ranging between 50 and 200 mK, which are higher than IR cameras Noise Equivalent Temperature Difference values, are added to simulated results to reflect realistic and drastic thermal noise levels. Spatiotemporal averaging using combined sets of different thermal images captured at various times in single sonic IR inspection delivered about 16% total uncertainty in the estimation of a crack length at 95% confidence level based on 60 experiments. Similar uncertainty level is obtained using independently reported sonic IR experimental data.

Unraveling Spatiotemporal Transient Dynamics at the Nanoscale via Wavelet Transform-Based Kelvin Probe Force Microscopy.

Mechanistic probing of surface potential changes arising from dynamic charge transport is the key to understanding and engineering increasingly complex nanoscale materials and devices. Spatiotemporal averaging in conventional heterodyne detection-based Kelvin probe force microscopy (KPFM) inherently limits its time resolution, causing an irretrievable loss of transient response and higher-order harmonics. Addressing this, we report a wavelet transform (WT)-based methodology capable of quantifying the sub-ms charge dynamics and probing the elusive transient response. The feedback-free, open-loop wavelet transform KPFM (OL-WT-KPFM) technique harnesses the WT's ability to simultaneously extract spatial and temporal information from the photodetector signal to provide a dynamic mapping of surface potential, capacitance gradient, and dielectric constant at a temporal resolution 3 orders of magnitude higher than the lock-in time constant. We further demonstrate the method's applicability to explore the surface-photovoltage-induced sub-ms hole-diffusion transient in bismuth oxyiodide semiconductor. The OL-WT-KPFM concept is readily applicable to commercial systems and can provide the underlying basis for the real-time analysis of transient electronic and electrochemical properties.

A Comparative Study of Ground-Gridded and Satellite-Derived Formaldehyde during Ozone Episodes in the Chinese Greater Bay Area

Formaldehyde (HCHO) plays an important role in atmospheric photochemical reactions. Comparative studies between ground-based and satellite observations are necessary to assess and promote the potential use of column HCHO as a proxy for surface HCHO and volatile organic compound (VOC) oxidation. Previous studies have only validated temporal and vertical profile variations at one point, with limited studies comparing horizontal spatial variations due to sparse monitoring sites. The photochemistry-active Chinese Greater Bay Area (GBA) is a typical megacity cluster as well as a large hotspot of HCHO globally, which recorded a high incidence of ozone (O3) pollution. Here, we conducted the first comparative study of ground-gridded (HCHOgg) and satellite-derived (HCHOsd) HCHO during typical O3 episodes in the GBA. Our results revealed a good correlation between HCHOgg and HCHOsd, with a correlation coefficient higher than 0.5. Cloud coverage and ground pixel sizes were found to be the dominant factors affecting the quality of HCHOsd and contributing to the varying satellite pixel density. Daily averages of HCHOsd effectively improved the HCHOsd accuracy, except in areas with low satellite pixel density. Furthermore, a new quality control procedure was established to improve HCHOsd from Level 2 to Level 3, which demonstrated good application performance in O3 sensitivity analysis. Our findings indicate that the correlation between satellite observations and surface air quality can be optimized by spatiotemporal averaging of hourly HCHOsd, given the advent of geostationary satellites. Considering the representative range of sampling sites in this comparative study, we recommend establishing VOC monitoring stations within a 50 km radius in the GBA to further analyze and control photochemical pollution.

Spatiotemporal spike-centered averaging reveals symmetry of temporal and spatial components of the spike-LFP relationship during human focal seizures

The electrographic manifestation of neural activity can reflect the relationship between the faster action potentials of individual neurons and the slower fluctuations of the local field potential (LFP). This relationship is typically examined in the temporal domain using the spike-triggered average. In this study, we add a spatial component to this relationship. Here we first derive a theoretical model of the spike-LFP relationship across a macroelectrode. This mathematical derivation showed a special symmetry in the spike-LFP relationship wherein a sinc function in the temporal domain predicts a sinc function in the spatial domain. We show that this theoretical result is observed in a real-world system by characterizing the spike-LFP relationship using microelectrode array (MEA) recordings of human focal seizures. To do this, we present a approach, termed the spatiotemporal spike-centered average (st-SCA), that allows for visualization of the spike-LFP relationship in both the temporal and spatial domains. We applied this method to 25 MEA recordings obtained from seven patients with pharmacoresistant focal epilepsy. Of the five patients with MEAs implanted in recruited territory, three exhibited spatiotemporal patterns consistent with a sinc function, and two exhibited spatiotemporal patterns resembling deep wells of excitation. These results suggest that in some cases characterization of the spike-LFP relationship in the temporal domain is sufficient to predict the underlying spatial pattern. Finally, we discuss the biological interpretation of these findings and propose that the sinc function may reflect the role of mid-range excitatory connections during seizure activity.

A continuously scanning spatiotemporal averaging method for obtaining volumetric mean flow measurements with stereoscopic PIV

In this study, a variation of the stacked stereoscopic PIV technique is proposed to perform fully volumetric (3-dimensions, 3-components) measurements of average flow fields within a single experiment through the usage of an automated traversing system that continuously scans the SPIV light sheet over a linear path. The simultaneous measurement of the traverse location and the laser Q-switch pulse enables the automated assignment of instantaneous PIV fields to known physical coordinates, enabling spatiotemporal averaging in post-processing to obtain volumetric measurements of a flow field. This method provides a trade-off between spatial resolution of the volume measurements and statistical convergence of the spatiotemporal averages, enabling volumetric measurements under challenging experimental conditions where only stereoscopic PIV is viable. A comparison with the more traditional temporal averaging method and planar PIV is presented to demonstrate the capabilities and limitations of this technique in realistic, challenging experimental setups. It is found that the spatiotemporal averaging convergence behavior differs slightly from the traditional temporal averaging for the wake of a bluff body model, however relative errors lower than two standard deviations can still be attained. Thus, this technique presents a viable alternative for rapid 3D reconstruction of averaged flow fields that can provide invaluable insight of various flow topologies.

Reducing the Speckle-Induced Measurement Uncertainty in Laser Triangulation Sensors

Laser triangulation sensors are one of the most commonly used optical sensors in dimensional metrology and quality control. This article presents a method for simulating the laser speckle-induced measurement uncertainty, representing a major performance limitation of these sensors, as well as the effects of speckle reduction mechanisms based on spatio-temporal averaging. To investigate the relation between triangulation angle and the resulting speckle-induced uncertainty, simulations are performed for three sensor geometries, revealing that a larger angle results not only in a smaller measurement range but also in a reduced influence of laser speckle and a smaller uncertainty. A parameter study on a speckle-reducing moving diffuser mechanism, integrated into the optical sensor path, investigates the achievable improvement for various combinations of motion frequency and amplitude. The accuracy of the simulation results is validated by measurements conducted with an experimental setup, demonstrating good agreement between the measured and simulated uncertainty values with and without the speckle reduction mechanism. It is shown that the diffuser is capable of reducing the resulting speckle-induced measurement uncertainty by up to 63%.

Archetypal Analysis of Geophysical Data Illustrated by Sea Surface Temperature

Abstract The ability to find and recognize patterns in high-dimensional geophysical data is fundamental to climate science and critical for meaningful interpretation of weather and climate processes. Archetypal analysis (AA) is one technique that has recently gained traction in the geophysical science community for its ability to find patterns based on extreme conditions. While traditional empirical orthogonal function (EOF) analysis can reveal patterns based on data covariance, AA seeks patterns from the points located at the edges of the data distribution. The utility of any objective pattern method depends on the properties of the data to which it is applied and the choices made in implementing the method. Given the relative novelty of the application of AA in geophysics it is important to develop experience in applying the method. We provide an assessment of the method, implementation, sensitivity, and interpretation of AA with respect to geophysical data. As an example for demonstration, we apply AA to a 39-yr sea surface temperature (SST) reanalysis dataset. We show that the decisions made to implement AA can significantly affect the interpretation of results, but also, in the case of SST, that the analysis is exceptionally robust under both spatial and temporal coarse graining. Significance Statement Archetypal analysis (AA), when applied to geophysical fields, is a technique designed to find typical configurations or modes in underlying data. This technique is relatively new to the geophysical science community and has been shown to be beneficial to the interpretation of extreme modes of the climate system. The identification of extreme modes of variability and their expression in day-to-day weather or state of the climate at longer time scales may help in elucidating the interplay between major teleconnection drivers and their evolution in a changing climate. The purpose of this work is to bring together a comprehensive report of the AA methodology using an SST reanalysis for demonstration. It is shown that the AA results are significantly affected by each implementation decision, but also can be resilient to spatiotemporal averaging. Any application of AA should provide a clear documentation of the choices made in applying the method.

Macroscopic effects in high-order harmonic generation - a focal-averaging method based on the integral solution of the wave equation.

A macroscopic theory of high-order harmonic generation (HHG) is presented, which applies a focal-averaging method based on the integral solution of the wave equation. The macroscopic high-harmonic yield is the coherent superposition of the single-atom contributions of all atoms of the generating medium, which are positioned at different spatial points of the laser focus and exposed to the space-time-dependent laser pulse. The HHG spectrum obtained in our macroscopic simulations is qualitatively different from the one obtained using the microscopic or single-atom theory of HHG. Coherent intensity focal averaging, the simpler and more approximate of two methods we introduced, gives the spectrum which forms a declining plateau with the same cutoff position as that of the microscopic spectrum. The second, more precise method, which we call coherent spatio-temporal focal averaging, shows that it is possible, changing the macroscopic conditions, to obtain an observable peak in the harmonic spectrum at an energy much lower than the microscopic cutoff energy. Generally, the high-harmonic yield appears to be dominated by the contributions of laser-pulse spatio-temporal regions with lower intensities as well as by interference, so that the high-energy plateau and its sharp cutoff are quenched in the theoretical simulation and, presumably, in the experiment. The height and position of this peak strongly depend on the macroscopic conditions. We confirmed these findings by applying our macroscopic theory to simulate two recent experiments with mid-infrared laser fields, one with a linearly polarized field and the other one with a bicircular field.

On the combined flow and structural measurements via robotic volumetric PTV

This study describes a novel measurement approach for combined flow and structural measurements in wind tunnels using robotic volumetric particle tracking velocimetry (PTV). The measurement approach is based on the application of a particle tracking algorithm on images including flow or structure tracers, where the latter are implemented by means of fiducial markers. The main steps of the measurement procedure comprise the simultaneous acquisition of flow and structure tracers in the same images, the distinction of the tracers leading to separate flow and structure image sets, the application of Lagrangian particle tracking and the further post-processing, and recombination of the obtained data. The approach is applied to the fluid-structure interaction between a flexible plate with a span of 1.2 m and a periodic gust. The total measurement volume amounts approximately to 150 liters. A phase-averaged description of the FSI problem is presented, with the focus on the effects of the spatio-temporal averaging of the flow information. The structural displacements obtained from the PTV system are validated against a scanning vibrometer. The phase-averaged displacement of the markers is also analyzed, assessing both the validity of the phase-averaged approach and the physical coherence of their motion with respect to a structural model of the plate. It is found that robotic volumetric PTV is suitable for the measurement of large-scale structural displacements, while it should not be used to measure small-scale vibrations. Finally, a visualization of the combined measurement is presented, together with an analysis of the consistency between the measured structure and flow field.

Reconstruction of missing channel in electroencephalogram using spatiotemporal correlation-based averaging

Objective. Electroencephalogram (EEG) recordings often contain large segments with missing signals due to poor electrode contact or other artifact contamination. Recovering missing values, contaminated segments and lost channels could be highly beneficial, especially for automatic classification algorithms, such as machine/deep learning models, whose performance relies heavily on high-quality data. The current study proposes a new method for recovering missing segments in EEG. Approach. In the proposed method, the reconstructed segment is estimated by substitution of the missing part of the signal with the normalized weighted sum of other channels. The weighting process is based on inter-channel correlation of the non-missing preceding and proceeding temporal windows. The algorithm was designed to be computationally efficient. Experimental data from patients (N = 20) undergoing general anesthesia due to elective surgery were used for the validation of the algorithm. The data were recorded using a portable EEG device with ten channels and a self-adhesive frontal electrode during induction of anesthesia with propofol from waking state until burst suppression level, containing lots of variation in both amplitude and frequency properties. The proposed imputation technique was compared with another simple-structure technique. Distance correlation (DC) was used as a measure of comparison evaluation. Main results.: The proposed method, with an average DC of 82.48 ± 10.01 (µ ± σ)%, outperformed its competitor with an average DC of 67.89 ± 14.12 (µ ± σ)%. This algorithm also showed a better performance when increasing the number of missing channels. Significance. the proposed technique provides an easy-to-implement and computationally efficient approach for the reliable reconstruction of missing or contaminated EEG segments.

Large Scale Infrared-Based Remote Sensing of Turbulence Metrics in Surface Waters: Going Beyond Mean Flow

In recent years field-scale applications of image-based velocimetry methods, often referred to as large scale particle image velocimetry (LSPIV), have been increasingly deployed. These velocimetry measurements have several advantages—they allow high resolution, non-contact measurement of surface velocity over a large two dimensional area, from which the bulk flow can be inferred. However, visiblelight LSPIV methods can have significant limitations. The water surface often lacks natural features that can be tracked in the visible and generally requires seeding with tracer particles, which creates concerns regarding the fidelity with which tracer particles track the flow, and introduces challenges in achieving sufficient and uniform seeding density, in particular in regions with appreciable velocity accelerations such as turbulence. In LSPIV, image collection is generally limited to daylight hours, and can suffer from non-uniformity of illumination across the camera’s field of view. Due to these issues LSPIV often requires spatio-temporal averaging, and as a result is generally able to extracting the mean, but not the instantaneous, velocity field, and hence is often not a suitable tool for calculating turbulence metrics of the flow.

Validation of IASI Satellite Ammonia Observations at the Pixel Scale Using In Situ Vertical Profiles

AbstractSatellite ammonia (NH3) observations provide unprecedented insights into NH3 emissions, spatiotemporal variabilities and trends, but validation with in situ measurements remains lacking. Here, total columns from the Infrared Atmospheric Sounding Interferometer (IASI) were intercompared to boundary layer NH3 profiles derived from aircraft‐ and surface‐based measurements primarily in Colorado, USA, in the summer of 2014. IASI‐NH3 version 3 near real‐time data set compared well to in situ derived columns (windows ±15 km around centroid, ±1 h around overpass time) with a correlation of 0.58, a slope of 0.78 ± 0.14 and an intercept of 2.1 × 1015±1.5 × 1015 molecules cm−2. Agreement degrades at larger spatiotemporal windows, consistent with the short atmospheric lifetime of NH3. We also examined IASI version 3R data, which relies on temperature retrievals from the ERA Reanalysis, and a third product generated using aircraft‐measured temperature profiles. The overall agreement improves slightly for both cases, and neither is biased within their combined measurement errors. Thus, spatiotemporal averaging of IASI over large windows can be used to reduce retrieval noise. Nonetheless, sampling artifacts of airborne NH3 instruments result in significant uncertainties of the in situ‐derived columns. For example, large validation differences exist between ascent and descent profiles, and the assumptions of the free tropospheric NH3 profiles used above the aircraft ceiling significantly impact the validation. Because short‐lived species like NH3 largely reside within the boundary layer with complex vertical structures, more comprehensive validation is needed across a wide range of environments. More accurate and widespread in situ NH3 data sets are therefore required for improved validations of satellite products.

National Mapping of New Zealand Pasture Productivity Using Temporal Sentinel-2 Data

A national map of pasture productivity, in terms of mass of dry matter yield per unit area and time, enables evaluation of regional and local land-use suitability. Difficulty in measuring this quantity at scale directed this research, which utilises four years of Sentinel-2 satellite imagery and collected pasture yield measurements to develop a model of pasture productivity. The model uses a Normalised Difference Vegetation Index (NDVI), with spatio-temporal segmentation and averaging, to estimate mean annual pasture productivity across all of New Zealand’s grasslands with a standard error of prediction of 2.2 t/ha/y. Regional aggregates of pasture yield demonstrate expected spatial variations. The pasture productivity map may be used to classify grasslands objectively into stratified levels of production on a national scale. Due to its ability to highlight areas of land use intensification suitability, the national map of pasture productivity is of value to landowners, land users, and environmental scientists.

Organized structure of turbulence in wave-current combined flow over rough surface using spatio-temporal averaging approach

The present study experimentally investigated near-bed coherent structures of turbulence over rough surface in the presence of surface waves over the steady current by replicating it in a laboratory flume. The rough surface was modelled by using wooden ribs of square cross section extended across the whole channel width of flume. The instantaneous velocities at different positions in the flow field were measured by using an acoustic Doppler velocimeter. The recorded velocities data were examined to investigate the coherent structures of turbulence near rough surface using the spatio-temporal averaging approach. Pre-multiplied velocity spectra, co-spectral, and coherency were evaluated in frequency domain at different vertical positions under different flow conditions. Length scales were determined to quantify the eddy size within the flow domain, and the anisotropy invariant maps were also obtained to characterize the anisotropic flow under different roughness conditions in wave-current flow cases. Results show increased correlation between velocity fluctuations in the large-scale low-frequency region due to the addition of surface waves, which accounts for the major part of Reynolds stress. Furthermore, turbulence dissipation in the near-bed region was found to be strongly dependent on roughness characteristics.

The Effect of Spatiotemporal Resolution Degradation on the Accuracy of IMERG Products over the Huai River Basin

AbstractThe rapid development of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) precipitation product provides new opportunities for a wide range of Earth system and natural hazard applications. Spatiotemporal averaging is a common method for IMERG users to acquire suitable resolutions specific to their research or application purpose and has a direct impact on the overall quality of IMERG precipitation estimates. Here, three different IMERG, version 06 (V06), latency run products (i.e., early, late, and final) are assessed against a ground-based benchmark along a continuous series of spatiotemporal resolutions over the Huai River basin (HuaiRB) between June 2014 and May 2017. In general, IMERG products better capture the spatial pattern of precipitation, and demonstrate better reliability, in the southern portion of the HuaiRB relative to its northern region. Furthermore, the degradation of spatiotemporal resolution is associated with better rain/no-rain determination and the consistent improvement of rainfall product performance metrics. This improvement is more pronounced for IMERG products at fine spatiotemporal resolution. However, due to the presence of autocorrelated errors, the performance improvement associated with the degradation of spatiotemporal resolution is less than theoretical expectations assuming purely uncorrelated errors. Component analysis indicates that while both temporal and spatial aggregation do not mitigate temporally autocorrelated errors, temporal averaging can remove spatially autocorrelated error. Hence, temporal averaging is found to be more effective than spatial averaging for improving the quality of IMERG products. These results will inform users of the reliability of IMERG products at different spatiotemporal scales and assist in unifying former disparate validation assessments applied at different scales within the literature.

Numerical analysis of the mean structure of gaseous detonation with dilute water spray

Two-dimensional (2-D) numerical simulations based on the Eulerian–Lagrangian method that take droplet break-up into account are conducted to clarify the mean structure of gaseous detonation laden with a dilute water spray. The premixed mixture is a slightly diluted stoichiometric hydrogen–oxygen mixture at low pressure. The simulated results are analysed via 2-D flow fields and statistical Favre spatiotemporal averaging techniques. Gaseous detonation with water droplets (WD) propagates stably with a velocity decrease compared with the dry Chapman–Jouguet speed. The mean structure of gaseous detonation with dilute water spray shares a similar structure as the one without water spray. However, the hydrodynamic thickness is changed due to the interaction with water spray. Overall interphase exchanges (mass, momentum and energy) that take place within the hydrodynamic thickness induce a decrease of the detonation velocity and lower the level of fluctuations downstream of the mean leading shock wave. Droplet break-up occurs downstream of the induction zone and in our case, the water vapour from the evaporation of water spray does not affect the reactivity of gaseous detonation. The laminar master equation for gaseous detonation laden with inert WD shows that the hydrodynamic thickness should rely on the gaseous sound speed, and works well as the working mixture is weakly unstable and its cellular structure is regular. The droplet flow regimes and break-up modes have also been determined. The characteristic lengths of detonation and interphase exchanges have been ordered under the present simulation conditions and have been shown to be intimately intertwined.

Spatiotemporal Reliability Ensemble Averaging of Multimodel Simulations

AbstractMultimodel combining approaches can extract reliable climate information from a large number of climate projections by exploiting the strengths and discounting the weaknesses of each climate simulator; however, most of them (e.g., reliability ensemble averaging [REA]) assign weights to climate simulators without accounting for spatial and temporal variabilities in climate model skills. Here we tested several REAs and proposed a full version that reflects the spatiotemporal (ST) variability of climate model skills. Interperformance evaluations between REA versions showed that, on average, ST‐REA reduced the bias by 33.78% and the root mean square error by 11.61%. Therefore, spatial and temporal variabilities in climate model skills can enhance the overall reliability of precipitation projections. ST‐REA was applied to project future precipitations over South Korea by combining seven climate models: The spatially averaged projected changes were 2.77%, 8.15%, and 7.58% for the 2020–2039, 2040–2069, and 2070–2099 periods, respectively.