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At least 415 records · Page 23

Development and Refinement of DER Steady State Model for QSTS Analysis

EPRI formed a working group of utilities and software vendors called the Distribution Advanced PV Model Working Group (DAWG). The working group has been focused on building consensus regarding the models that represent the reactive power capabilities outlined in Section 5 of IEEE Std 1547™-2018. This report provides an overview of the reactive and active power capabilities specified in IEEE Std 1547™-2018 and outlines a specification of key functions for usage during steady state snapshot and time series power flow analysis. Additionally, it presents a framework for performing tests to verify the correct operation of functions during power flow analysis.

14 SOLAR ENERGY↗

Regional Changes in the Sea Ice Cover and Ice Production in the Antarctic

Coastal polynyas around the Antarctic continent have been regarded as sea ice factories because of high ice production rates in these regions. The observation of a positive trend in the extent of Antarctic sea ice during the satellite era has been intriguing in light of the observed rapid decline of the ice extent in the Arctic. The results of analysis of the time series of passive microwave data indicate large regional variability with the trends being strongly positive in the Ross Sea, strongly negative in the Bellingshausen/Amundsen Seas and close to zero in the other regions. The atmospheric circulation in the Antarctic is controlled mainly by the Southern Annular Mode (SAM) and the marginal ice zone around the continent shows an alternating pattern of advance and retreat suggesting the presence of a propagating wave (called Antarctic Circumpolar Wave) around the circumpolar region. The results of analysis of the passive microwave data suggest that the positive trend in the Antarctic sea ice cover could be caused primarily by enhanced ice production in the Ross Sea that may be associated with more persistent and larger coastal polynyas in the region. Over the Ross Sea shelf, analysis of sea ice drift data from 1992 to 2008 yields a positive rate-of-increase in the net ice export of about 30,000 km2 per year. For a characteristic ice thickness of 0.6 m, this yields a volume transport of about 20 km3/year, which is almost identical, within error bars, to our estimate of the trend in ice production. In addition to the possibility of changes in SAM, modeling studies have also indicated that the ozone hole may have a role in that it causes the deepening of the lows in the western Antarctic region thereby causing strong winds to occur offthe Ross-ice shelf.

Comiso, Josefino C.↗

Near 40 Years MERRA-2 Data at NASA GES DISC -Opportunity and Challenge to Support Extremes Study

To the end of 2019, 40 years NASA climate reanalysis data sets from the Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) will be available at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 consists atmosphere, land, and ocean data, which may be used for the studies ranging from the short scale weather events to the large scale decadal vulnerabilities. The hourly products, such as precipitation, soil moisture, temperature, and aerosols etc., have been used widely to study extreme events.In supporting users from broad communities, GES DISC have developed various data access services, including subsetter for downloading only data of interest with preferred format; OPeNDAP - for machine-to-machine data access; and Giovanni- for online visualization and analysis, etc. A big challenge for extreme study is to downloading and processing long-term hourly or daily data. The data downloading performance is not very satisfied by many users with current services and the native archived data structure. Late June 2019, many people in Europe had experienced extreme heat waves. The temperatures in several countries exceeded 40°C (104°F). For example, MERRA-2 shows that the near surface daily maximum temperature of June 28 2019 over Marseille, a city in southern France, reached 41.1 °C (106°F), which is the record breaking temperature in the last 40 years. GES DISC is working together with domain science experts to improve the performance of long time series access, making analysis ready data sets in supporting application researches, such as extreme study. In this presentation, using Europe heat wave as an example, we will show prototype of the in developing service for finding extremes from near 40 years MERRA-2 data at a given location. MERRA-2 data can be accessed from NASA GES DISC(https://disc.gsfc.nasa.gov/ ) by search keyword "MERRA-2".

Shen, Suhung↗

Time-resolved biphase signatures of quadratic nonlinearity observed in coupled Alfvén eigenmodes on the DIII-D tokamak

We report the detection of nonstationary quadratic coupling between toroidicity-induced Alfvén eigenmodes (TAEs) on sub-millisecond time scales. Identification of phase coherency between multiple TAEs and nonlinearly generated modes is facilitated by wavelet-based bicoherence analysis of time-series from inductive coils, taken from a DIII-D discharge heated by neutral beam injection (NBI). Characterization of nonlinear three-wave interaction is inferred by stationary local bispectrum phase (biphase) and confirmed via bandpass filtering. Biphase dynamics associated with prominent bispectral features are well-resolved in time and consistent with transient quadratic coupling. Onset and duration of nonlinearity are correlated with enhanced amplitude of participating TAEs; coincident changes in amplitude are observed for modes at difference frequency |f TAE,1 - f TAE,2 |.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Harnessing Satellite Data Alone for Mapping Global Thermal Anisotropy

Mapping thermal anisotropy across global lands is critical for advancing a wide range of Earth science studies. However, a comprehensive understanding of global thermal anisotropy intensity (TAI) and its governing factors remains missing. We introduce a novel data-driven methodology to quantify global TAI exclusively using multi-angle MODIS land surface temperature time series observations. Our analysis reveals distinct seasonal and diurnal TAI patterns, with global mean summertime TAI exceeding 2.9°C. Furthermore, we identify strong associations between TAI and key surface and atmospheric parameters, such as leaf area index and downward shortwave radiation. Our findings advocate for a paradigm shift from model-based to data-driven approaches in correcting thermal anisotropy, thereby addressing a critical bottleneck in Earth observation.

54 ENVIRONMENTAL SCIENCES↗

Modelling stellar activity with Gaussian process regression networks

ABSTRACT Stellar photospheric activity is known to limit the detection and characterization of extrasolar planets. In particular, the study of Earth-like planets around Sun-like stars requires data analysis methods that can accurately model the stellar activity phenomena affecting radial velocity (RV) measurements. Gaussian Process Regression Networks (GPRNs) offer a principled approach to the analysis of simultaneous time series, combining the structural properties of Bayesian neural networks with the non-parametric flexibility of Gaussian Processes. Using HARPS-N solar spectroscopic observations encompassing three years, we demonstrate that this framework is capable of jointly modelling RV data and traditional stellar activity indicators. Although we consider only the simplest GPRN configuration, we are able to describe the behaviour of solar RV data at least as accurately as previously published methods. We confirm the correlation between the RV and stellar activity time series reaches a maximum at separations of a few days, and find evidence of non-stationary behaviour in the time series, associated with an approaching solar activity minimum.

Camacho, J. D. (ORCID:0000000151215560)↗

A Stochastic Multi-Criteria Decision-Making Algorithm for Dynamic Load Prioritization in Grid-Interactive Efficient Buildings

Increasing deployment of advanced sensing, controls, and communication infrastructure enables buildings to provide services to the power grid, leading to the concept of grid-interactive efficient buildings. Since occupant activities and preferences primarily drive the availability and operational flexibility of building devices, there is a critical need to develop occupant-centric approaches that prioritize devices for providing grid services, while maintaining the desired end-use quality of service. In this paper, we present a decision-making framework that facilitates a building owner/operator to effectively prioritize loads for curtailment service under uncertainties, while minimizing any adverse impact on the occupants. The proposed framework uses a stochastic (Markov) model to represent the probabilistic behavior of device usage from power consumption data, and a load prioritization algorithm that dynamically ranks building loads using a stochastic multi-criteria decision-making algorithm. The proposed load prioritization framework is illustrated via numerical simulations in a residential building use-case, including plug-loads, air-conditioners, and plug-in electric vehicle chargers, in the context of load curtailment as a grid service. Suitable metrics are proposed to evaluate the closed-loop performance of the proposed prioritization algorithm under various scenarios and design choices. Scalability of the proposed algorithm is established via computational analysis, while time-series plots are used for intuitive explanation of the ranking choices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CHMMPP: A c++ library for constrained Hidden Markov Models

SAND2024-13027O The CHMMPP: A c++ Library for Constrained Hidden Markov Models (HMM) software supports the analysis of multivariate time series data to detect patterns using HMM. Many applications involve the detection and characterization of hidden or latent states in a complex system using observable states and variables. This software supports inference of latent states integrating both an HMM and application-specific constraints that reflect known relationships in hidden states. The CHMMPP software supports application-specific and generic methods for constrained inference. This includes a framework for customized Viterbi methods, constrained inference of hidden states with A* and integer programming methods, and various constraint-informed methods for learning HMM model parameters. CHMMPP focuses on supporting generic methods that enable the agile expression of complex sets of constraints that naturally arise in many real-world applications.

Hart, William↗

Polar Cloud Microphysics and Surface Energy Budget from AWARE (Final Technical Report)

This was a collaborative project between the Scripps Institution of Oceanography at the University of California San Diego (SIO), Byrd Polar and Climate Research Center at The Ohio State University (BPCRC), The Department of Meteorology and Atmospheric Science at The Pennsylvania State University (Penn State), and Brookhaven National Laboratory (BNL). The project’s over-arching objectives involved maximizing the scientific potential of the ARM West Antarctic Radiation Experiment (AWARE) data set, in two respects: (1) application of polar-optimized climate models to test the most current and comprehensive cloud microphysical parameterizations; and (2) analysis of the most advanced ARM Mobile Facility sensors (e.g., cloud radar, spectroradiometer, and aerosol observing system data) to advance understanding of Antarctic cloud microphysical and radiative properties, particularly on a climatological basis with emphasis on contrasts with the high Arctic. The team’s efforts have resulted in 16 peer-review publications, in addition to an overview of the AWARE campaign in the Bulletin of the American Meteorological Society. Our emphasis throughout this program was to go beyond the traditional “case study” approach to model evaluation, in which a “classical” or otherwise well-characterized surface-atmosphere-cloud system of short duration is simulated by several climate models. Instead, we attempted analysis of longer time series in the AWARE data, both climatologically and with models. We have numerous successful results from both AWARE locations: The main AMF-2 deployment at McMurdo Station on Ross Island (13 months duration), and the extended facility at the West Antarctic Ice Sheet (WAIS) Divide Ice Camp (40 days during austral summer 2015-16).

54 ENVIRONMENTAL SCIENCES↗

Refractivity Observations from Radar Phase Measurements: The 22 May 2002 Dryline Case during IHOP Project

The dryline, often associated with the development of severe storms in the Southern Great Plains of the United States of America, is a boundary layer phenomenon that occurs when a warm and moist air mass from the Gulf of Mexico meets a hot and dry air mass from the southwest desert area. An accurate knowledge of the water vapor spatio-temporal variability in the lower part of the atmosphere is crucial for a better understanding of the evolution of the dryline. The tropospheric refractivity, directly related to water vapor content, is a proxy for the water vapor content of the troposphere. It has already been demonstrated that the refractivity and the refractivity vertical gradient can be jointly estimated from radar phase measurements. In fact, it has been shown that using kriging interpolation techniques, accurate refractivity maps within the coverage area of the radar can be obtained with high temporal resolution. In this paper, a detailed analysis of the time series of radar-based refractivity maps obtained during a dryline that occurred on the afternoon of 22 May 2002 during the International H 2 O Project is presented. Comparisons between the time series of radar refractivity maps, obtained with the NCAR S-Pol radar, and the refractivity measurements derived from automatic ground-based weather stations and the AERI instrument, placed at different locations within the coverage area of the NCAR S-Pol radar, demonstrate the accuracy of radar refractivity estimates even for highly variable conditions, both in time and space, in the troposphere. Correlation coefficients higher than 0.95 are obtained in all weather station locations. Regarding the RMSE, errors less than 6 N-units are obtained for all cases, being even as low as 2.92 N-units at some locations.

54 ENVIRONMENTAL SCIENCES↗

Comparison of CEAS and Williams-type models for spring wheat yields in North Dakota and Minnesota

The CEAS and Williams-type yield models are both based on multiple regression analysis of historical time series data at CRD level. The CEAS model develops a separate relation for each CRD; the Williams-type model pools CRD data to regional level (groups of similar CRDs). Basic variables considered in the analyses are USDA yield, monthly mean temperature, monthly precipitation, and variables derived from these. The Williams-type model also used soil texture and topographic information. Technological trend is represented in both by piecewise linear functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test of each model (1970-1979) demonstrate that the models are very similar in performance in all respects. Both models are about equally objective, adequate, timely, simple, and inexpensive. Both consider scientific knowledge on a broad scale but not in detail. Neither provides a good current measure of modeled yield reliability. The CEAS model is considered very slightly preferable for AgRISTARS applications.

Barnett, T. L.↗

Mesospheric ozone changes associated with 27-day solar ultraviolet flux variations

Solar ultraviolet flux changes associated with the 27-day solar rotational period cause corresponding variations in mesospheric ozone near the maximum of the 11-year sunspot cycle. This statement is based on a correlation and spectral analysis of ozone mixing ratios, deduced from Solar Mesospheric explorer satellite-based measurements of 1.27-micron O2 airglow emission and solar flux observations made from the same spacecraft in 1982. With the Lyman-alpha flux taken as an indicator of solar ultraviolet variability, spectral analysis shows a primary period of 27.1 days with a secondary period of 13.5 days. The 27.1-day period is observed in the ozone mixing ratio data together with other periods, including 13.5 days. Both a classical statistical analysis and a time series treatment show that, for 244 days, there is a correlation between ozone and solar flux near 50 km and between 65 and 70 km. Calculations predict a positive correlation over the entire mesosphere if there is no change in temperature accompanying the solar flux. Lack of correlation is temperature induced.

Aikin, A. C.↗

A study of gravity-wave spectra in the troposphere and stratosphere at 5-min to 5-day periods with the Poker Flat MST radar

An analysis of frequency spectra at periods of about 5 days to 5 min from two 20-day sets of velocity measurements in the stratosphere and troposphere region obtained with the Poker Flat mesosphere-stratosphere-troposphere (MST) radar during January and June, 1984 is presented. A technique based on median filtering and averaged order statistics for automatic editing, smoothing and spectral analysis of velocity time series contaminated with spurious data points or outliers is outlined. The validity of this technique and its effects on the inferred spectral index was tested through simulation. Spectra obtained with this technique are discussed. The measured spectral indices show variability with season and height, especially across the tropopause. The discussion briefly outlines the need for obtaining better climatologies of velocity spectra and for the refinements of the existing theories to explain their behavior.

Bemra, R. S.↗

Location and characteristics of the reconnection X-line deduced from low-altitude satellite and radar observations

We present an analysis of a cusp ion step observed between two poleward-moving events of enhanced ionospheric electron temperature. From the computed variation of the reconnection rate and the onset times of the associated ionospheric events, the distance between the satellite and the X-line can be estimated, but with a large uncertainty due to that in the determination of the low-energy cut-off of the ion velocity distribution function, f(E). Nevertheless, analysis of the time series f(t) shows the reconnection site to be on the dayside magnetopause, consistent with the pulsating cusp model, and the best estimate of the X-line location is 13 R(E) from the satellite. The ion precipitation is used to reconstruct the field-parallel part of the Cowley-D ion distribution function injected into the open low latitude boundary layer (LLBL) in the vicinity of the X-line. From this the Alfven speed, plasma density, magnetic field, parallel ion temperature, and flow velocity of the magnetosheath near the X-line can be derived.

Lockwood, M.↗

Ground-based microwave monitoring of middle atmosphere ozone: Comparison to lidar and Stratospheric and Gas Experiment 2 satellite observations

A dedicated ground-based microwave radiometer was in operation to monitor the middle atmospheric ozone concentration at Table Mountain Facility (TMF) of the Jet Propulsion Laboratory (JPL), California (34.4 deg N, 117.7 deg W) from July 1989 to June 1992, as a part of the Network for Detection of Stratospheric Change. Ozone profiles from 56 to 0.04 mbar (approximately 20 - 70 km) were retrieved from the microwave data. The focus in this paper is to validate the microwave ozone observations from 56 to 1 mbar by comparing the results from a JPL ground-based lidar located at the same site and from the Stratospheric Aerosol and Gas Experiment 2 (SAGE 2) satellite overpasses within 1000 km of TMF and to examine the ability of these instruments to detect short-term, seasonal, and annual variations in ozone. The profile comparison results show that the mean differences of microwave ozone from lidar and SAGE 2 are about 5% or less and the root-mean-square scatter about the mean is mainly from the precision of the instruments. A correlation analysis of ozone time series suggests highly significant correlations up to 2.4 mbar between lidar and microwave measurements and up to 1 mbar between SAGE 2 and microwave. The short-term and seasonal variation of the ozone profile seen in the microwave measurements is shown to be consistent with the observations of lidar and SAGE 2, and the interannual variation of ozone appears to be detectable within an accuracy of a few percent with the microwave instrument.

Tsou, J. J.↗

Analysis of Daily, Seasonal, and Interannual Changes in Hofsjokull Ice Cap, Iceland, using Satellite Data

Analysis of a time series of European Remote Sensing Satellite (ERS)-1 and -2, RADARSAT ScanSAR synthetic aperture radar (SAR) and Landsat images from 1973 to 1998, shows daily to interannual changes in Hofsjokull, a 923 sq km ice cap in central Iceland. A digital elevation model of Hofsjokull was constructed using interferometry, and then SAR backscatter coefficient (d) was plotted with elevation, and air temperature along a transect across the ice cap. Most of the a' changes measured along the transect are caused by a change in the state (frozen or thawed) of the surficial snow or ice when air temperature rises above or below about -5 to O C. Seasonal (sigma)deg patterns are identified in a 4-year time series of 57 ERS-1 and -2 images. In addition, June 1997 ScanSAR images display rapid changes in brightness that are tied closely to daily meteorological events. SAR and Landsat data were also used to measure changes in the areal extent of Hofsjokull, from 1973 to 1997, and to locate (sigma)deg and reflectance boundaries that relate to the glacier facies. Late-summer 1997 (sigma)deg and reflectance boundaries agree and are coincident with the approximate location of the fim line, and the January 1998 position of the equilibrium line as determined from ERS-2 data.

Hall, D. K.↗

Spectroscopic Measurement of Leaf Water Status

A leaf drying experiment was carried out in the laboratory in which simultaneous spectral reflectance in the 350-2450 nm region, and leaf weights, were measured at 10 second intervals over a 40 minute period. As the leaf water weight dropped from approximately 60 to 38%. a nearly-linear rise in reflectance at all wavelengths beyond 1000 nm was observed. A principal components analysis of the time series of spectra in the 2000-2500 nm wavelength region showed that over 99% of the variance in the spectra, that were individually scaled to have a sum equal to that of the mean spectrum and subsequently mean corrected, was in the first component. This result shows that it is feasible to determine leaf water content remotely with an imaging spectrometer independent of the surface irradiance effects caused by topography.

Goetz, Alexander F. H.↗

Statistical analysis of geodetic networks for detecting regional events

We present an application of hidden Markov models (HMMs) to analysis of geodetic time series in Southern California. Our model fitting method uses a regularized version of the deterministic annealing expectation-maximization algorithm to ensure that model solutions are both robust and of high quality.

geodetic networks↗