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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Simulation of Properties of Images with Atomic Resolution in a Scanning Probe Microscope

A method for simulation of images in a scanning probe microscope (SPM) using simultaneous wavelet transform and median filtering is proposed. The wavelet transform with the fourth-order Daubechies kernel is used. Such a transform makes it possible to select details of different scales in the SPM image and, hence, study fractal properties of surfaces. Simulation is used to show that ultrahigh (atomic) resolution is possible in SPM provided that the size of the contact region in the probe–sample system is significantly greater than atomic size and the lattice atoms are randomly distributed. Contrast inversion in the SPM images in the multiscan mode is interpreted.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

sparse-msrf:A package for sparse modeling and estimation of fossil-fuel CO2 emission fields

The software is used to fit models of emission fields (e.g., fossil-fuel CO2 emissions) to sparse measurements of gaseous concentrations. Its primary aim is to provide an implementation and a demonstration for the algorithms and models developed in J. Ray, V. Yadav, A. M. Michalak, B. van Bloemen Waanders and S. A. McKenna, "A multiresolution spatial parameterization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions", accepted, Geoscientific Model Development, 2014. The software can be used to estimate emissions of non-reactive gases such as fossil-fuel CO2, methane etc. The software uses a proxy of the emission field being estimated (e.g., for fossil-fuel CO2, a population density map is a good proxy) to construct a wavelet model for the emission field. It then uses a shrinkage regression algorithm called Stagewise Orthogonal Matching Pursuit (StOMP) to fit the wavelet model to concentration measurements, using an atmospheric transport model to relate emission and concentration fields. Algorithmic novelties described in the paper above (1) ensure that the estimated emission fields are non-negative, (2) allow the use of guesses for emission fields to accelerate the estimation processes and (3) ensure that under/overestimates in the guesses do not skew the estimation.

None, JinaLee↗
DOE OSTI2026

WFSUITE: A PYTHON SOFTWARE SUITE FOR X-RAY WAVEFRONT SENDING AND AT-WAVELENGTH METROLOGY

SF-26-025 WFSuite is a graphical and command-line toolkit for coded-mask-based X-ray wavefront sensing and phase reconstruction at synchrotron beamlines. It integrates analysis tools for both relative and absolute speckle-based measurements. In the relative metrology module, WFSuite implements Wavelet-transform-based X-ray Speckle Tracking (WXST) and Wavelet-transform-based Speckle Vector Tracking (WSVT) methods to retrieve differential phase and wavefront distortions by comparing speckle patterns recorded with and without the test sample. In the absolute phase module, WFSuite uses coded-mask speckle patterns and replaces the measured reference with a numerically simulated one, enablingsingle-shot wavefront reconstruction using either WXST or a neural-network-based method (SPINNet).

Rebuffi, Luca [Argonne National Laboratory (ANL), ↗
DOE OSTI2023

Vortex Structure of Head Bubble in Convective Cloud Starting Plume

Abstract A developing cumulus cloud (Cu) was modeled, and dynamic, thermodynamic, and microphysical properties of an ascending head bubble reproducing the upper part of a developing Cu were investigated. The data for analysis are taken from 10-m-resolution LES of trade wind Cu under BOMEX conditions. The detection of a rising bubble is carried out using wavelet filtering of the velocity fields and microphysical fields, while a low-frequency signal of the filtering is associated with the convective-scale structure of cloud. We substantiate and discuss the representation of the bubble as a vortex ring, and estimate the parameters of this vortex ring. The simplest Hill’s vortex was chosen as a model of a vortex ring inside cloud. Analytical approximations of the radial profiles of the vertical velocity and of conservative quantities (such as total water mixing ratio and liquid water potential temperature inside and outside the bubble) are obtained. The spatial structure of these quantities is investigated using analytical expressions. Analytical models for spatial distributions of liquid water content (LWC) and adiabatic fraction (AF) are also designed and analyzed. The results demonstrate the existence of a cloud core with high values of LWC and AF up to the height of 1800 m. The horizontally averaged value of the adiabatic fraction, calculated analytically using the Hill’s vortex concept, is evaluated as 0.39, which is the typical AF value in the upper parts of such Cu. The vertical profiles of different important quantities characterizing cloud structure are presented. The analysis performed in this study allows us to conclude that a rising vortex ring plays the dominating role in formation of the thermodynamic and microphysical structure of developing Cu. Significance Statement 1) Dynamic and thermodynamic fields of a developing cumulus cloud simulated by high-resolution LES with spectral bin microphysics are separated into convective and turbulent components by means of the wavelet technique. 2) The analysis of convective component of the cloud revealed the existence of a vortex ring at the developing stage of the cloud and evaluate its parameters. 3) The analysis performed in this study allows us to conclude that a rising vortex ring plays the important role in formation of the thermodynamic and microphysical structure of developing Cu. 4) The study provides a novel insight into the cloud–environment interaction. 5) The approximating equations describing the vortex ring can be usefully applied for developing new schemes of convective parameterization.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Estimating SHmax azimuth with P sources and vertical geophones: Use P-P reflection amplitudes or use SV-P reflection times?

We compared two methods for extracting the azimuth of maximum horizontal stress (SHmax) from 3D land-based seismic data generated by a P source and recorded with vertical geophones. In the first method, we used the direct-SV mode that is produced by all land-based P sources. P sources generate SV illumination that radiates in all azimuth directions from a source station and creates SV-P reflections that are recorded by vertical geophones. Unless stratigraphy has steep dip, SV-P raypaths recorded by vertical geophones are the reverse of P-SV raypaths recorded by horizontal geophones. Thus, SV-P data provide the same S-wave sensitivity to stress fields as popular P-SV data do. In the second method, we retrieved P-P reflections and then performed an amplitude-variation-with-azimuth (AVA) analysis of the amplitude-gradient behavior of P-P reflection wavelets. We did this analysis in narrow azimuth corridors to determine the gradient of reflection-wavelet amplitudes as a function of azimuth. This P-P AVA amplitude-gradient method has been of great interest in the reflection seismology community since it was introduced in the late 1990s. Each of these methods, AVA analysis of the gradient of P-P reflection amplitudes and azimuth-dependent arrival times of SV-P reflections, can be used to determine the azimuth of SHmax stress. We compare the results of the two methods with ground truth measurements of SHmax azimuth at a CO 2 sequestration site in the Michigan Basin. SHmax azimuths were determined from P-P and SV-P data at three major boundaries at depths of approximately 3500 ft (1067 m), 5500 ft (1676 m), and 7500 ft (2286 m). Two estimates of SHmax azimuth (one using SV-P data and one using P-P data) were made at each stacking bin inside a 24 mi 2 (62 km 2 ) image space. The result was approximately 98,000 estimates of SHmax azimuth across each of these three boundaries for each of these two prediction strategies. Histogram displays of PP AVA gradient estimates had peaks at correct azimuths of SHmax at all three depths, but the spread of the distributions widened with depth and split into two peaks at the deepest boundary. In contrast, each histogram of SHmax azimuth predicted by azimuth-dependent SV-P traveltimes had a single, definitive peak that was positioned at the correct SHmax azimuth at all three boundary depths.

Geochemistry & Geophysics↗
DOE OSTI2022

Water Quality Parameters at the Elkhorn Slough National Estuarine Research Reserve (ESNERR)

The following dataset includes water quality and meteorological forcing data between 2003 and 2019 across four Elkhorn Slough National Estuarine Research Reserve (ESNERR) stations. The data are monthly averaged and include orthophosphate, ammonium, Nitrite, Nitrate, Nitrite + Nitrate, Chlorophyll, Temperature of water, Specific Conductance, Salinity, Dissolved Oxygen, Air Temperature and Precipitation. The data were compiled for wavelet and other statistical analyses. All data included herein are associated with the following manuscript: Venkatesh*, S., B. Arora, D. Dwivedi, S. Vezhaperambu, M. V. Ramesh (2021), Temporal Variability of Water Quality Parameters at the Elkhorn Slough Estuary using Wavelets, IEEE Proceedings on 6th International Conference for Convergence in Technology, DOI:10.1109/I2CT51068.2021.9418159.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Final Technical Report Recovery Act: Online Nonintrusive Condition Monitoring and Fault Detection for Wind Turbines

The penetration of wind power has increased greatly over the last decade in the United States and across the world. The U.S. wind power industry installed 1,118 MW of new capacity in the first quarter of 2011 alone and entered the second quarter with another 5,600 MW under construction. By 2030, wind energy is expected to provide 20% of the U.S. electricity needs. As the number of wind turbines continues to grow, the need for effective condition monitoring and fault detection (CMFD) systems becomes increasingly important [3]. Online CMFD is an effective means of not only improving the reliability, capacity factor, and lifetime, but it also reduces the downtime, energy loss, and operation and maintenance (O&M) of wind turbines. The goal of this project is to develop novel online nonintrusive CMFD technologies for wind turbines. The proposed technologies use only the current measurements that have been used by the control and protection system of a wind turbine generator (WTG); no additional sensors or data acquisition devices are needed. Current signals are reliable and easily accessible from the ground without intruding on the wind turbine generators (WTGs) that are situated on high towers and installed in remote areas. Therefore, current-based CMFD techniques have great economic benefits and the potential to be adopted by the wind energy industry. Specifically, the following objectives and results have been achieved in this project: (1) Analyzed the effects of faults in a WTG on the generator currents of the WTG operating at variable rotating speed conditions from the perspective of amplitude and frequency modulations of the current measurements; (2) Developed effective amplitude and frequency demodulation methods for appropriate signal conditioning of the current measurements to improve the accuracy and reliability of wind turbine CMFD; (3) Developed a 1P-invariant power spectrum density (PSD) method for effective signature extraction of wind turbine faults with characteristic frequencies in the current or current demodulated signals, where 1P stands for the shaft rotating frequency of a WTG; (4) Developed a wavelet filter for effective signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (5) Developed an effective adaptive noise cancellation method as an alternative to the wavelet filter method for signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (6) Developed a statistical analysis-based impulse detection method for effective fault signature extraction and evaluation of WTGs based on the 1P-invariant PSD of the current or current demodulated signals; (7) Validated the proposed current-based wind turbine CMFD technologies through extensive computer simulations and experiments for small direct-drive WTGs without gearboxes; and (8) Showed, through extensive experiments for small direct-drive WTGs, that the performance of the proposed current-based wind turbine CMFD technologies is comparable to traditional vibration-based methods. The proposed technologies have been successfully applied for detection of major failures in blades, shafts, bearings, and generators of small direct-drive WTGs. The proposed technologies can be easily integrated into existing wind turbine control, protection, and monitoring systems and can be implemented remotely from the wind turbines being monitored. The proposed technologies provide an alternative to vibration-sensor-based CMFD. This will reduce the cost and hardware complexity of wind turbine CMFD systems. The proposed technologies can also be combined with vibration-sensor-based methods to improve the accuracy and reliability of wind turbine CMFD systems. When there are problems with sensors, the proposed technologies will ensure proper CMFD for the wind turbines, including their sensing systems. In conclusion, the proposed technologies offer an effective means to achieve condition-based smart maintenance for wind turbines and have a great potential to be adopted by the wind energy industry due to their almost no-cost, nonintrusive features. Although only validated for small direct-drive wind turbines without gearboxes, the proposed technologies are also applicable for CMFD of large-size wind turbines with and without gearboxes. However, additional investigations are recommended in order to apply the proposed technologies to those large-size wind turbines.

17 WIND ENERGY↗
DOE OSTI2013

A multiresolution spatial parametrization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions.

The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. To that end, we construct a multiresolution spatial parametrization for fossil-fuel CO2 emissions (ffCO2), to be used in atmospheric inversions. Such a parametrization does not currently exist. The parametrization uses wavelets to accurately capture the multiscale, nonstationary nature of ffCO2 emissions and employs proxies of human habitation, e.g., images of lights at night and maps of built-up areas to reduce the dimensionality of the multiresolution parametrization. The parametrization is used in a synthetic data inversion to test its suitability for use in atmospheric inverse problem. This linear inverse problem is predicated on observations of ffCO2 concentrations collected at measurement towers. We adapt a convex optimization technique, commonly used in the reconstruction of compressively sensed images, to perform sparse reconstruction of the time-variant ffCO2 emission field. We also borrow concepts from compressive sensing to impose boundary conditions i.e., to limit ffCO2 emissions within an irregularly shaped region (the United States, in our case). We find that the optimization algorithm performs a data-driven sparsification of the spatial parametrization and retains only of those wavelets whose weights could be estimated from the observations. Further, our method for the imposition of boundary conditions leads to a 10 computational saving over conventional means of doing so. We conclude with a discussion of the accuracy of the estimated emissions and the suitability of the spatial parametrization for use in inverse problems with a significant degree of regularization.

Ray, Jaideep↗
DOE OSTI2024

Exploration of signal processing methods for superconducting magnet and quench data

Quenching is the phenomenon of a superconducting magnetic material carrying current transitioning into a regular conducting material. This may cause severe and irreparable damage to the superconductor due to Joule heating. The Magnet Department at Fermi National Accelerator Laboratory (FNAL) has acquired experimental data through quench antenna arrays that are recorded when the quench is detected. These data are in terms of voltage signals that are sampled at 100kHz for several minutes. There are multiple channels and each channel provides a data set of more than 20 million observations, while there is one channel, called the trigger channel which shows the time when quench is detected. Despite some advancements that were made including machine learning, data complexity still shadows the progress. In this work, we studied a multi-resolution analysis of the quench antenna data through the Haar wavelet transform. In particular, we applied the maximally overlapped discrete w avelet transform (MODWT) of a suitable level L to the given data and then projected it onto the wavelet basis. This decomposes a given signal (Original data) $x ϵ \mathbb{R}^N$ into $L + 1$ subspaces of $\mathbb{R}^N$. One of the subspaces called the approximation, captures the trend of the signal, and the others, called the details, capture the fluctuations at different frequency bands. This decomposition provides a clear trend of the data at a suitable level and also various activities (spikes) are seen in the details of the decomposition at every level. These spikes might reveal some information about the quench under investigation but in any case, give information about magnet behavior. Also, this decomposition is seen to be very useful in removing noise present in the data due to the source or mechanism of the experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Pattern Mining and Anomaly Detection based on the Power System Synchrophasor Measurements

Real-time monitoring of power system dynamics using phasor measurement units (PMUs) data improves situational awareness and system reliability and potentially can help prevent blackouts due to early anomaly detection. The study presented in the paper is based on the actual PMU measurements of the U.S. western interconnection system. Given the nonlinear and nonstationary PMUs data, we developed a robust anomaly detection framework. Wavelet-based multi-resolution analysis, combined with moving-window-based outlier detection and anomaly scoring, were deployed to identify potential PMU events. The candidate events were evaluated using spatiotemporal correlation analysis, and then classified for a better understanding of the event types. The results demonstrated successful anomaly detection and classification, compared with the recorded real-world events.

Ren, Huiying↗
DOE OSTI2020

Detection of Extreme Phenomena in the Stable Boundary Layer over the Amazonian Forest

We apply different methods for detection of extreme phenomena (EP) in air-turbulent time series measured in the nocturnal boundary layer above the Amazon forest. The methods used were: (a) a Morlet complex wavelet transform, which is often used in analysis of non-linear application processes. Through the use of the wavelet, it is possible to observe a phase singularity that involves a strong interaction between an extensive range of scales; (b) recurrence plot tests, which were used to identify a sudden change between different stable atmospheric states. (c) statistical analysis of early-warning signals, which verify simultaneous increases in the autocorrelation function and in the variance in the state variable; and (d) analysis of wind speed versus turbulent kinetic energy to identify different turbulent regimes in the stable boundary layer. We found it is adequate to use a threshold to classify the cases of strong turbulence regime, as a result of the occurrence of EP in the tropical atmosphere. All methods used corroborate and indicate synergy between events that culminate in what we classify as EP of the stable boundary layer above the tropical forest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

ON THE PROPERTIES OF SLOW MHD SAUSAGE WAVES WITHIN SMALL-SCALE PHOTOSPHERIC MAGNETIC STRUCTURES

The presence of magnetoacoustic waves in magnetic structures in the solar atmosphere is well-documented. Applying the technique of solar magneto-seismology (SMS) allows us to infer the background properties of these structures. Here, we aim to identify properties of the observed magnetoacoustic waves and study the background properties of magnetic structures within the lower solar atmosphere. Using the Dutch Open Telescope and Rapid Oscillations in the Solar Atmosphere instruments, we captured two series of high-resolution intensity images with short cadences of two isolated magnetic pores. Combining wavelet analysis and empirical mode decomposition (EMD), we determined characteristic periods within the cross-sectional (i.e., area) and intensity time series. Then, by applying the theory of linear magnetohydrodynamics (MHD), we identified the mode of these oscillations within the MHD framework. Several oscillations have been detected within these two magnetic pores. Their periods range from 3 to 20 minutes. Combining wavelet analysis and EMD enables us to confidently find the phase difference between the area and intensity oscillations. From these observed features, we concluded that the detected oscillations can be classified as slow sausage MHD waves. Furthermore, we determined several key properties of these oscillations such as the radial velocity perturbation, the magnetic field perturbation, and the vertical wavenumber using SMS. The estimated range of the related wavenumbers reveals that these oscillations are trapped within these magnetic structures. Our results suggest that the detected oscillations are standing harmonics, and this allows us to estimate the expansion factor of the waveguides by employing SMS. The calculated expansion factor ranges from 4 to 12.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Temporal Variation of the Rotation of the Solar Mean Magnetic Field

Based on continuous wavelet transformation analysis, the daily solar mean magnetic field (SMMF) from 1975 May 16 to 2014 July 31 is analyzed to reveal its rotational behavior. Both the recurrent plot in Bartels form and the continuous wavelet transformation analysis show the existence of rotational modulation in the variation of the daily SMMF. The dependence of the rotational cycle lengths on solar cycle phase is also studied, which indicates that the yearly mean rotational cycle lengths generally seem to be longer during the rising phase of solar cycles and shorter during the declining phase. The mean rotational cycle length for the rising phase of all of the solar cycles in the considered time is 28.28 ± 0.67 days, while for the declining phase it is 27.32 ± 0.64 days. The difference of the mean rotational cycle lengths between the rising phase and the declining phase is 0.96 days. The periodicity analysis, through the use of an auto-correlation function, indicates that the rotational cycle lengths have a significant period of about 10.1 years. Furthermore, the cross-correlation analysis indicates that there exists a phase difference between the rotational cycle lengths and solar activity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Optimal Matched Filter in the Low-number Count Poisson Noise Regime and Implications for X-Ray Source Detection

Detection of templates (e.g., sources) embedded in low-number count Poisson noise is a common problem in astrophysics. Examples include source detection in X-ray images, γ-rays, UV, neutrinos, and search for clusters of galaxies and stellar streams. However, the solutions in the X-ray-related literature are sub-optimal in some cases by considerable factors. Using the lemma of Neyman–Pearson, we derive the optimal statistics for template detection in the presence of Poisson noise. We demonstrate that, for known template shape (e.g., point sources), this method provides higher completeness, for a fixed false-alarm probability value, compared with filtering the image with the point-spread function (PSF). In turn, we find that filtering by the PSF is better than filtering the image using the Mexican-hat wavelet (used by wavdetect). For some background levels, our method improves the sensitivity of source detection by more than a factor of two over the popular Mexican-hat wavelet filtering. This filtering technique can also be used for fast PSF photometry and flare detection; it is efficient and straightforward to implement. We provide an implementation in MATLAB. The development of a complete code that works on real data, including the complexities of background subtraction and PSF variations, is deferred for future publication.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Kronoseismology. IV. Six Previously Unidentified Waves in Saturn’s Middle C Ring

Recent studies of stellar occultations observed by the Visual and Infrared Mapping Spectrometer on board the Cassini spacecraft have demonstrated that multiple spiral wave structures in Saturn’s rings are probably generated by normal-mode oscillations inside the planet. Wavelet-based analyses have been able to unambiguously determine both the number of spiral arms and the rotation rate of many of these patterns. However, there are many more planetary normal modes that should have resonances in the rings, implying that many normal modes do not have sufficiently large amplitudes to generate obvious ring waves. Fortunately, recent advances in wavelet analysis allow weaker wave signals to be uncovered by combining data from multiple occultations. These new analytical tools reveal that a pattern previously identified as a single spiral wave actually consists of two superimposed waves, one with five spiral arms rotating at 1593.°6/day and one with 11 spiral arms rotating at 1450.°5/day. Furthermore, a broad search for new waves revealed four previously unknown wave patterns with six, seven, eight, and nine spiral arms rotating around the planet at 1538.°2/day, 1492.°5/day, 1454.°2/day, and 1421.°8/day, respectively. These six patterns provide precise frequencies for another six fundamental normal modes inside Saturn, yielding what is now a complete sequence of fundamental sectoral normal modes with azimuthal wavenumbers from 2 to 10. These frequencies should place strong constraints on Saturn’s interior structure and rotation rate, while the relative amplitudes of these waves should help clarify how the corresponding normal modes are excited inside the planet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Detection and Interpretation of Long-lived X-Ray Quasi-periodic Pulsations in the X-class Solar Flare on 2013 May 14

Quasi-periodic pulsations (QPP) seen in the time derivative of the GOES soft X-ray light curves are analyzed for the X3.2 event on 2013 May 14. The pulsations are apparent for a total of at least two hours from the impulsive phase to well into the decay phase, with a total of 163 distinct pulses evident to the naked eye. A wavelet analysis shows that the characteristic timescale of these pulsations increases systematically from ∼25 s at 01:10 UT, the time of the GOES peak, to ∼100 s at 02:00 UT. A second “ridge” in the wavelet power spectrum, most likely associated with flaring emission from a different active region, shows an increase from ∼40 s at 01:40 UT to ∼100 s at 03:10 UT. We assume that the QPP that produced the first ridge result from vertical kink-mode oscillations of the newly formed loops following magnetic reconnection in the coronal current sheet. This allows us to estimate the magnetic field strength as a function of altitude given the density, loop length, and QPP timescale as functions of time determined from the GOES light curves and Ramaty High Energy Solar Spectroscopic Imager ( RHESSI ) images. The calculated magnetic field strength of the newly formed loops ranges from ∼500 G at an altitude of 24 Mm to a low value of ∼10 G at 60 Mm, in general agreement with the expected values at these altitudes. Fast sausage-mode oscillations are also discussed and cannot be ruled out as an alternate mechanism for producing the QPP.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Influence of Intermittency on the Quasi-perpendicular Scaling in Three-dimensional Magnetohydrodynamic Turbulence

Solar wind fluctuations reveal the ubiquity of intermittency, which is believed to affect the spectral signatures of turbulence. In this work, based on simulation of driven compressible MHD turbulence, we apply the wavelet technique to the magnetic field and velocity to identify intermittency, and we analyze the influence of the intermittency on the quasi-perpendicular scaling in the inertial range. The numerical results show that the original magnetic and velocity fluctuations are anisotropic, and have a power anisotropy with a spectral index approaching the Iroshnikov–Kraichnan −3/2 scaling in the direction quasi-perpendicular to the local mean magnetic field. As in observations of the solar wind fluctuations, as the scale decreases in the simulation, the calculated probability distribution functions (pdfs) of the wavelet coefficients become extended on both tails of the non-Gaussian distribution, with a rapid increase in flatness. After intermittency has been removed from the driven turbulence, at each scale, the pdfs approach a Gaussian distribution, with the flatness being ∼3. Meanwhile, the quasi-perpendicular scaling for both fluctuations becomes steeper and close to a Kolmogorov −5/3 scaling, which may be a result of the stronger intermittency in the quasi-perpendicular direction and at the smaller scales. These results suggest that there is intermittency superposed on the “background” turbulence that seems to have the Kolmogorov scaling, whereby the overall slope is getting flatter with the involvement of intermittency.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Airborne flux measurements of Biogenic Isoprene over California

Biogenic Volatile Organic Compound (BVOC) fluxes were measured onboard the CIRPAS Twin Otter aircraft as part of the California Airborne BVOC Emission Research in Natural Ecosystem Transects (CABERNET) campaign during June 2011. The airborne virtual disjunct eddy covariance (AvDEC) approach used measurements from a PTR-MS and a wind radome probe to directly determine fluxes of isoprene, MVK+MAC, methanol, monoterpenes, and MBO over ~10,000-km of flight paths focusing on areas of California predicted to have the largest emissions of isoprene. The Fast Fourier Transform (FFT) approach was used to calculate fluxes over long transects of more than 15 km, most commonly between 50 and 150 km. The Continuous Wavelet Transformation (CWT) approach was used over the same transects to also calculate "instantaneous" fluxes with localization of both frequency and time independent of non-stationarities. Vertical flux divergence of isoprene is expected due to its relatively short lifetime and was measured directly using "racetrack" profiles at multiple altitudes. It was found to be linear and in the range 5% to 30% depending on the ratio of aircraft altitude to PBL height (z/zi). Fluxes were generally measured by flying consistently 1 at 400 m ±50 m (a.g.l.) altitude, and extrapolated to the surface according to the determined flux divergence. The wavelet-derived surface fluxes of isoprene averaged to 2 km spatial resolution showed good correspondence to Basal Emission Factor (BEF) landcover datasets used to drive biogenic VOC (BVOC) emission models. The surface flux of isoprene was close to zero over Central Valley crops and desert shrublands, but was very high (up to 15 mg m-2 h-1) above oak woodlands, with clear dependence of emissions on temperature and oak density. Isoprene concentrations of up to 8 ppb were observed at aircraft height on the hottest days and over the dominant source regions. While isoprene emissions from agricultural crop regions, shrublands, and coniferous forests were extremely low, high concentrations of methanol and monoterpenes were found above some of these regions. These observations demonstrate the ability to measure fluxes from specific sources by eddy covariance from an aircraft, and suggest the utility of measurements using fast response chemical sensors to constrain emission inventories and map out source distributions for a much broader array of trace gases than was observed in this study. This paper reports the first regional direct eddy covariance fluxes of isoprene. The emissions of VOCs measured from aircraft with 2 km spatial resolution can quantify the distribution of major sources providing the observations required for testing statewide emission inventories of these important trace gases. These measurements will be used in a future study to assess BVOC emission models and their driving variable datasets.

Misztal, P.↗