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At least 55 records · Page 3

Reconciliation of asynchronous satellite-based $\mathrm{NO_2}$ and $\mathrm{XCO_2}$ enhancements with mesoscale modeling over two urban landscapes

Fossil fuel carbon dioxide (CO 2ff ), the main driver of global warming and climate change, is often co-emitted with nitrogen oxides (NO x ) and precursors to ground-level ozone from anthropogenic sources like power plants or vehicles. In urban and suburban areas, satellite-based NO 2 can be used as a proxy to track the emissions of CO 2ff . Because of NO 2 ’s shorter lifetime, urban NO 2 plumes are more distinguishable from backgrounds and more sensitive to variations in emissions. However, the combination of these two gases is limited by the asynchrony among NO 2 and CO 2 monitoring satellites. We used CO 2ff simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model to reconcile the tropospheric NO 2 vertical column density (VCD) from the Tropospheric Monitoring Instrument (TROPOMI) and column-averaged dry-air mole fractions of carbon dioxide enhancements (ΔXCO 2 ) from Orbiting Carbon Observatory 3 (OCO-3) Snapshot Area Maps (SAMs) over a multicity area, Washington D.C.-Baltimore (DC-Balt), and a basin city, Mexico City. NO 2 /CO 2ff ratios over DC-Balt are smaller than Mexico City, indicative of stricter emission restrictions, a more combustion-efficient vehicle fleet, and higher combustion efficiency due to lower altitude in DC-Balt. For single-track cases, the spatial correlations between NO 2 and ΔXCO 2 over Mexico City are stronger than DC-Balt because the NO 2 and CO 2 are mostly trapped in the valley of Mexico City, while DC-Balt is severely affected by distant sources (i.e., US East Coast cities). Using multi-track averaging, spatial correlation coefficients increase with the number of days used for averaging. The correlations reached a maximum when averaging >12 continuous images for DC-Balt and > 10 continuous images for Mexico City. This finding indicates that multi-track averaging using modeled CO 2ff as a proxy is helpful to filter the noise in single-track images, to cancel the interference from distant sources, and to magnify correlations between NO 2 and CO 2ff . Mexico City showed stronger spatial correlations but weaker temporal correlations than DC-Balt due to biomass burning hot spots and large transport errors caused by the trapping effects of the surrounding mountains. Tracking the 20-day moving average of CO 2ff emissions using TROPOMI NO 2 seems technically feasible, considering the relationship between correlation coefficients and the number of available satellite images.

54 ENVIRONMENTAL SCIENCES↗

Digital quantum simulation of Floquet symmetry-protected topological phases

Quantum many-body systems away from equilibrium host a rich variety of exotic phenomena that are forbidden by equilibrium thermodynamics. A prominent example is that of discrete time crystals, in which time-translational symmetry is spontaneously broken in periodically driven systems. Pioneering experiments have observed signatures of time crystalline phases with trapped ions, solid-state spin systems, ultracold atoms and superconducting qubits. Here we report the observation of a distinct type of non-equilibrium state of matter, Floquet symmetry-protected topological phases, which are implemented through digital quantum simulation with an array of programmable superconducting qubits. We observe robust long-lived temporal correlations and subharmonic temporal response for the edge spins over up to 40 driving cycles using a circuit of depth exceeding 240 and acting on 26 qubits. We demonstrate that the subharmonic response is independent of the initial state, and experimentally map out a phase boundary between the Floquet symmetry-protected topological and thermal phases. Our results establish a versatile digital simulation approach to exploring exotic non-equilibrium phases of matter with current noisy intermediate-scale quantum processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Limitations of laser transmission measurements due to correlated atmospheric effects

An evaluation is made of results of recent experimental work concerning the effects that atmospherically induced fluctuations and temporal correlations have on the accuracy of atmospheric laser transmission experiments. These experiments directly measured the limitations of signal averaging as a means to the reduction of the standard deviation of laser signals which are backscattered from either a specular or a diffusely reflecting target, by means of both heterodyne and direct detection systems. These limitations are shown to agree with a theory in which the observed, atmospherically induced temporal correlation is taken into account.

Menyuk, N.↗

Signal Quality Influence on Averaging Procedure for DIAL Pollution Monitoring

Presented here is an analysis of the relative effect of each stochastic phenomenon on the accuracy of LIDAR measurements. The preferred averaging procedure to be applied is noted. The analysis takes into account the temporal correlation of the transmitted power variations which are associated with laser modal noise, short term temporal correlation of atmospheric turbulence, and 'white' additive noise. A distinction is made between two types of systems, one that transmits a sequence of pulses tuned into two wavelengths, but with a relatively large time separation, and another that transmits pulses in two wavelengths almost coincidentally. This distinction is important because the effect of speckle noise can be minimized when the pulses at two wavelengths are sent within the correlation time of the atmospheric turbulence. The presented analysis compares the signal to noise ratio in the calculation of the ratio beta (sub 1)/beta (sub 2), as achieved by using two methods of calculations: first averaging the data related to each wavelength and then taking the ratio, and first taking the ratio and then averaging. For both methods, normalization with respect to the transmitted power is considered, either prior to or after the averaging of the signals in each wavelength.

Egert, S.↗

Online Event Detection in Synchrophasor Data with Graph Signal Processing

Online detection of anomalies is crucial to enhancing the reliability and resiliency of power systems. We propose a novel data-driven online event detection algorithm with synchrophasor data using graph signal processing. In addition to being extremely scalable, our proposed algorithm can accurately capture and leverage the spatio-temporal correlations of the streaming PMU data. This paper also develops a general technique to decouple spatial and temporal correlations in multiple time series. Finally, we develop a unique framework to construct a weighted adjacency matrix and graph Laplacian for product graph. Case studies with real-world, large-scale synchrophasor data demonstrate the scalability and accuracy of our proposed event detection algorithm. Compared to the state-of-the-art benchmark, the proposed method not only achieves higher detection accuracy but also yields higher computational efficiency.

Event detection↗

Online Event Detection in Synchrophasor Data with Graph Signal Processing

Online detection of anomalies is crucial to enhancing the reliability and resiliency of power systems. We propose a novel data-driven online event detection algorithm with synchrophasor data using graph signal processing. In addition to being extremely scalable, our proposed algorithm can accurately capture and leverage the spatio-temporal correlations of the streaming PMU data. This paper also develops a general technique to decouple spatial and temporal correlations in multiple time series. Finally, we develop a unique framework to construct a weighted adjacency matrix and graph Laplacian for product graph. Case studies with real-world, large-scale synchrophasor data demonstrate the scalability and accuracy of our proposed event detection algorithm. Compared to the state-of-the-art benchmark, the proposed method not only achieves higher detection accuracy but also yields higher computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Effect of turbulence-induced correlation on laser remote sensing errors

Using a 10.6-micron dual-laser differential-absorption laser remote sensing system, the short- and long-term temporal correlation of the returns from topographic targets and retroreflectors are measured in order to investigate the effect of atmospheric turbulence on laser remote sensing measurement errors. The results quantify the improvement obtained through use of a dual-laser system compared to that of a single-laser system and are in good agreement with those predicted by a theory which considers the effect of partial temporal correlation on the resultant measurement error.

Killinger, D. K.↗

Evaluation of long-term Northern Hemisphere snow water equivalent products

Nine gridded Northern Hemisphere snow water equivalent (SWE) products were evaluated as part of the European Space Agency (ESA) Satellite Snow Product Intercomparison and Evaluation Exercise (SnowPEx). Three categories of datasets were assessed: (1) those utilizing some form of reanalysis (the NASA Global Land Data Assimilation System version 2 – GLDAS-2; the European Centre for Medium-Range Weather Forecasts (ECMWF) interim land surface reanalysis – ERA-Interim/Land and ERA5; the NASA Modern-Era Retrospective Analysis for Research and Applications version 1 (MERRA) and version 2 (MERRA-2); the Crocus snow model driven by ERA-Interim meteorology – Crocus); (2) passive microwave remote sensing combined with daily surface snow depth observations (ESA GlobSnow v2.0); and (3) stand-alone passive microwave retrievals (NASA AMSR-E SWE versions 1.0 and 2.0) which do not utilize surface snow observations. Evaluation included validation against independent snow course measurements from Russia, Finland, and Canada and product intercomparison through the calculation of spatial and temporal correlations in SWE anomalies. The stand-alone passive microwave SWE products (AMSR-E v1.0 and v2.0 SWE) exhibit low spatial and temporal correlations to other products and RMSE nearly double the best performing product. Constraining passive microwave retrievals with surface observations (GlobSnow) provides performance comparable to the reanalysis-based products; RMSE over Finland and Russia for all but the AMSR-E products is ∼50 mm or less, with the exception of ERA-Interim/Land over Russia. Using a seven-dataset ensemble that excluded the stand-alone passive microwave products reduced the RMSE by 10 mm (20 %) and increased the correlation from 0.67 to 0.78 compared to any individual product. The overall performance of the best multiproduct combinations is still at the margins of acceptable uncertainty for scientific and operational requirements; only through combined and integrated improvements in remote sensing, modeling, and observations will real progress in SWE product development be achieved.

Northern Hemisphere snow water equivalent (SWE) pr↗

Assimilation of Terrestrial Water Storage from GRACE in a Snow-Dominated Basin

Terrestrial water storage (TWS) information derived from Gravity Recovery and Climate Experiment (GRACE) measurements is assimilated into a land surface model over the Mackenzie River basin located in northwest Canada. Assimilation is conducted using an ensemble Kalman smoother (EnKS). Model estimates with and without assimilation are compared against independent observational data sets of snow water equivalent (SWE) and runoff. For SWE, modest improvements in mean difference (MD) and root mean squared difference (RMSD) are achieved as a result of the assimilation. No significant differences in temporal correlations of SWE resulted. Runoff statistics of MD remain relatively unchanged while RMSD statistics, in general, are improved in most of the sub-basins. Temporal correlations are degraded within the most upstream sub-basin, but are, in general, improved at the downstream locations, which are more representative of an integrated basin response. GRACE assimilation using an EnKS offers improvements in hydrologic state/flux estimation, though comparisons with observed runoff would be enhanced by the use of river routing and lake storage routines within the prognostic land surface model. Further, GRACE hydrology products would benefit from the inclusion of better constrained models of post-glacial rebound, which significantly affects GRACE estimates of interannual hydrologic variability in the Mackenzie River basin.

Forman, Barton A.↗

A Search for MeV to TeV Neutrinos from Fast Radio Bursts with IceCube

We present two searches for IceCube neutrino events coincident with 28 fast radio bursts (FRBs) and 1 repeating FRB. The first improves on a previous IceCube analysis - searching for spatial and temporal correlation of events with FRBs at energies greater than roughly 50 GeV - by increasing the effective area by an order of magnitude. The second is a search for temporal correlation of MeV neutrino events with FRBs. No significant correlation is found in either search; therefore, we set upper limits on the time-integrated neutrino flux emitted by FRBs for a range of emission timescales less than one day. These are the first limits on FRB neutrino emission at the MeV scale, and the limits set at higher energies are an order-of-magnitude improvement over those set by any neutrino telescope.

79 ASTRONOMY AND ASTROPHYSICS↗

Heat release surrogates for NH 3 /H 2 /N 2 –air premixed flames

The present study investigates the performance of NH, NH 2 , O-atom, and H-atom as heat release rate (HRR) surrogates for NH 3 /H 2 /N 2 –air premixed flame through simulations. The simulations are conducted across different pressures, reactant inlet temperatures, fuel blend compositions, and equivalence ratios. Cantera is used to simulate one-dimensional (1D) freely propagating flames to investigate the spatial correlations of the species with the HRR. PeleLMeX, a low-Mach direct numerical simulation (DNS) code with Adaptive Mesh Refinement (AMR), is used to simulate two-dimensional (2D) flame-vortex interactions to investigate the temporal correlations including stretch effects. Three different mechanisms (Jiang et al. 2020; Glarborg et al. 2018; Okafor et al. 2018) were considered in the 1D flame simulations, whereas only the Jiang mechanism was considered in the flame-vortex simulations. The HRR surrogate performance for the 2D flames is evaluated at two different locations: (1) the centerline and (2) the flame cusp. The cusp is defined as the region in the flame front with the greatest curvature and the centerline encounters the highest tangential strain rate. The 1D flame results suggest that, although there is not uniformly good spatial correlation for HRR across all flame conditions, NH is the best overall as a HRR surrogate for laminar flames. The 2D flame results, however, suggest that O-atom and H-atom have satisfactory temporal correlations at different conditions—the former for rich flames, the latter for high-pressure flames. Furthermore, these simulations provide guidance to experimental measurements of surrogate HRR markers in unsteady multi-dimensional flames using laser diagnostics to detect species such as NH, O-atom, and H-atom.

Ammonia↗

Multiwavelength monitoring of the BL Lacertae object PKS 2155-304. 4: Multiwavelength analysis

Simultaneous X-ray, ultraviolet, optical, infrared, and radio monitoring data were used to test and constrain models of continuum emission from the BL Lacertae object PKS 2155-304. Intensively sampled ultraviolet and soft X-ray light curves showed a clear temporal correlation with the X-rays leading the ultraviolet by 2-3 hr. This lag was found to be significantly different from zero after an exhaustive comparison of four different techniques for measuring temporal correlations. Variations in the ultraviolet trough optical wave bands were also strongly correlated, with no measurable lag down to limiting timescales of approximately less than 1-2 hr. This strong correlation extends to the near-infrared, but the less intensive sampling precludes measurement of any lag beyomnd an upper limit of approximately less than 1 day. These lags and limits of the order of hours are much shorter than most rapid observed single-band variations. Because of the very sparse radio sampling, it was not possible to measure quantitatively the correlation and lag with shorter wavelengths, but the data do suggest that the radio may lag the optical/ultraviolet by approximately 1 week, with longer delays and weaker variations to longer radio wavelengths. The epoch-folding Q(exp 2) statistic was used to test for periodicity, and no evidence for strict or quasi-periodicity was found in any of the light curves. Because they lead the lower frequencies, the soft X-rays (approximately less than 1 keV) cannot arise from synchrotron self-Compton scattering. These results also rule out the accretion disk model, which predicts a measurable lag between ultraviolet/optical wavelength bands and a correlation between hardness and brightness, neither of which were seen. They are consistent with the entire radio through X-ray continuum arising from direct synchrotron emission from a relativistic jet. However, the tapered jet model, in which the X-ray emission is produced closer in, has problems explaining the magnitude of the ultraviolet/X-ray lag, because the X-ray-emitting electrons have very short lifetimes (t(sub 1/2) much less than 1 s). The result that the lag is much smaller than the variability timescale suggests instead that the radiation may be produced in a flattened region such as a shock front.

Edelson, R.↗

Enhanced Tensor Completion Based Approaches for State Estimation in Distribution Systems

Grid state estimation is essential for effective control and management of distribution systems. While weighted least squares has been the conventional method for state estimation, sparsity-aware methods have become popular due to their superior performance with limited data. Matrix completion and compressed sensing-based state estimation approaches exploit the underlying smoothness in the state variables. However, classic matrix completion methods do not take into account the temporal correlation of system states. Compressed sensing methods, on the other hand, require an appropriate choice of sparsifying basis that may not be easy to identify. This paper proposes a blocktensor completion based framework which uses an alternative approach to estimate voltage phasor, power injections and branch currents. This approach utilizes the temporal correlation of the system states in a tensor trace-norm minimization formulation with power flow equations as constraints. Herein, feature scaling is introduced in the problem formulation to benefit from the improved sensitivity of the tensor trace norm to the matrix columns in the scaled unfoldings of the tensor. Weighted tensor norm is utilized to exploit the structures of the different unfoldings of the state measurement tensor to improve the voltage estimation. The estimation accuracy is further improved by alternatively estimating the tensor columns and increasing the available data at each stage in the tensor completion process. The proposed methods are evaluated on the IEEE-33, 37 test systems and a 100- node test system. The proposed methods are shown to provide significant performance gains relative to the classic matrix and tensor completion based approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ultra-Broad-Band Optical Parametric Amplifier or Oscillator

A concept for an ultra-broad-band optical parametric amplifier or oscillator has emerged as a by-product of a theoretical study in fundamental quantum optics. The study was originally intended to address the question of whether the two-photon temporal correlation function of light [in particular, light produced by spontaneous parametric down conversion (SPDC)] can be considerably narrower than the inverse of the spectral width (bandwidth) of the light. The answer to the question was found to be negative. More specifically, on the basis of the universal integral relations between the quantum two-photon temporal correlation and the classical spectrum of light, it was found that the lower limit of two-photon correlation time is set approximately by the inverse of the bandwidth. The mathematical solution for the minimum two-photon correlation time also provides the minimum relative frequency dispersion of the down-converted light components; in turn, the minimum relative frequency dispersion translates to the maximum bandwidth, which is important for the design of an ultra-broad-band optical parametric oscillator or amplifier. In the study, results of an analysis of the general integral relations were applied in the case of an optically nonlinear, frequency-dispersive crystal in which SPDC produces collinear photons. Equations were found for the crystal orientation and pump wavelength, specific for each parametric-down-converting crystal, that eliminate the relative frequency dispersion of collinear degenerate (equal-frequency) signal and idler components up to the fourth order in the frequency-detuning parameter

Strekalov, Dmitry↗

Signal averaging limitations in heterodyne- and direct-detection laser remote sensing measurements

The improvement in measurement uncertainty brought about by the averaging of increasing numbers of pulse return signals in both heterodyne- and direct-detection lidar systems is investigated. A theoretical analysis is presented which shows the standard deviation of the mean measurement to decrease as the inverse square root of the number of measurements, except in the presence of temporal correlation. Experimental measurements based on a dual-hybrid-TEA CO2 laser differential absorption lidar system are reported which demonstrate that the actual reduction in the standard deviation of the mean in both heterodyne- and direct-detection systems is much slower than the inverse square-root dependence predicted for uncorrelated signals, but is in agreement with predictions in the event of temporal correlation. Results thus favor the use of direct detection at relatively short range where the lower limit of the standard deviation of the mean is about 2 percent, but advantages of heterodyne detection at longer ranges are noted.

Menyuk, N.↗

Technical note: Using long short-term memory models to fill data gaps in hydrological monitoring networks

Abstract. Quantifying the spatiotemporal dynamics in subsurface hydrological flows over a long time window usually employs a network of monitoring wells. However, such observations are often spatially sparse with potential temporal gaps due to poor quality or instrument failure. In this study, we explore the ability of recurrent neural networks to fill gaps in a spatially distributed time-series dataset. We use a well network that monitors the dynamic and heterogeneous hydrologic exchanges between the Columbia River and its adjacent groundwater aquifer at the U.S. Department of Energy's Hanford site. This 10-year-long dataset contains hourly temperature, specific conductance, and groundwater table elevation measurements from 42 wells with gaps of various lengths. We employ a long short-term memory (LSTM) model to capture the temporal variations in the observed system behaviors needed for gap filling. The performance of the LSTM-based gap-filling method was evaluated against a traditional autoregressive integrated moving average (ARIMA) method in terms of error statistics and accuracy in capturing the temporal patterns of river corridor wells with various dynamics signatures. Our study demonstrates that the ARIMA models yield better average error statistics, although they tend to have larger errors during time windows with abrupt changes or high-frequency (daily and subdaily) variations. The LSTM-based models excel in capturing both high-frequency and low-frequency (monthly and seasonal) dynamics. However, the inclusion of high-frequency fluctuations may also lead to overly dynamic predictions in time windows that lack such fluctuations. The LSTM can take advantage of the spatial information from neighboring wells to improve the gap-filling accuracy, especially for long gaps in system states that vary at subdaily scales. While LSTM models require substantial training data and have limited extrapolation power beyond the conditions represented in the training data, they afford great flexibility to account for the spatial correlations, temporal correlations, and nonlinearity in data without a priori assumptions. Thus, LSTMs provide effective alternatives to fill in data gaps in spatially distributed time-series observations characterized by multiple dominant frequencies of variability, which are essential for advancing our understanding of dynamic complex systems.

54 ENVIRONMENTAL SCIENCES↗

Experimental study of high-k turbulence during an energy confinement degradation phase in EAST ohmic plasmas

In this paper, we present experimental studies of both high-k(r) ( cm(-1), and , respectively; ) and high- ( cm(-1), and , respectively; ) turbulence behavior during an ohmic energy confinement degradation phase in experimental advanced superconducting tokamak (EAST). High-k(r) turbulence from density fluctuation at and high- turbulence from density fluctuation at -0.97 were measured by tangential and poloidal CO2 laser collective scattering diagnostics, respectively. Note that k(r), , and are radial wavenumber, poloidal wavenumber, perpendicular wavenumber and ion gyroradius at electron temperature, respectively. Both high-k(r)/ turbulence power and energy confinement time are found to be temporally correlated to line-averaged electron density n(e) in the plasma current flat-top phase (I-p = 0.4 MA): when the n(e) shows continuous increase/decrease, the high-k(r)/ turbulence power increases/decreases correspondingly and the shows corresponding decrease/increase; the stable n(e) is related to stable both and high-k(r)/ turbulence power. Statistical results of high-k(r)/ turbulence power versus further imply that high-k(r)/ turbulence shows a strong correlation with plasma energy confinement degradation in high line-averaged n(e) condition, but high-k(r) and high- turbulence have relatively weak and no dependence on the transition between linear range in low-n(e) condition and energy confinement degradation in the high-n(e) condition, respectively. Moreover, profiles of electron temperature T-e and n(e) as well as their normalized gradients in a part of high- density fluctuation measurement region also have been given to qualitatively explain the enhancement of turbulence power with the increase of line-averaged n(e).

EAST tokamak↗