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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2022

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2023, with start- and end-of-season phenological transition dates derived through the end of autumn 2022. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step Contains 35 files in *.csv format inside a compressed (*.zip) file. Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) Contains one file in *.csv format Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. Contains three files in HTML format, one for each vegetation type One additional file in HTML format with the transition dates plotted for each vegetation type, by year R files for processing Phenocam files and flags. Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/y7z5mau7. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released phenocam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

SPRUCE Experiment, Marcell Experimental Forest, Sp↗
DOE OSTI2024

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2023

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2024, with start- and end-of-season phenological transition dates derived through the end of autumn 2023. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) • Contains one file in *.csv format (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure • Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type • One additional file in HTML format with the transition dates plotted for each vegetation type, by year (2) R files for processing Phenocam files and flags. • Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released data inclusive of the 2015-2022 data (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

Spruce and Peatland Responses Under Changing Envir↗
DOE OSTI2018

Effect of boronization on plasma-facing graphite surfaces and its correlation with the plasma behavior in NSTX-U

Boronization is a Plasma Facing Component (PFC) conditioning technique widely used in tokamak machines. The National Spherical Torus Experiment-Upgrade (NSTX-U) applied this conditioning, using a plasma glow with a deuterated Trimethyl-boron (d-TMB) and He mixture. The use of boronization during the campaign improved the plasma performance, allowing longer plasma discharges and H-mode access. The chemical state of an ATJ graphite sample, used as a proxy for the NSTX-U PFCs, was monitored in-situ using the Materials Analysis Particle Probe (MAPP) diagnostic and X-ray Photoelectron Spectroscopy (XPS). The XPS data showed a progressive rise (from < 5% to 23%) in the oxygen concentration of the boronized ATJ sample as the D+ fluence increased. Filterscopes were used to measure the light emitted by oxygen impurities in the plasma near the surface of the PFC. An increase in the registered magnitude of the OII line, normalized to the Dγ intensity, was observed as the concentration of O on the ATJ surface increased. The plasma performance was found to be strongly correlated to oxygen impurity concentrations at the plasma edge and on the PFC surface, as measured by the discharge length and access to the H-mode regime. In this work, we present a quantitative analysis of the evolution of the chemistry of the ATJ surface, and the oxygen presence in the plasma-material interface, and report relevant plasma parameters observed during the same period of time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Measurement of the Lund jet plane in hadronic decays of top quarks and W bosons with the ATLAS detector

The Lund jet plane (LJP) is measured for the first time in $t\bar{t}$ events, using 140 $\textrm{fb}^{-1}$ of $\sqrt{s} = 13$ TeV pp collision data collected with the ATLAS detector at the LHC. The LJP is a two-dimensional observable of the sub-structure of hadronic jets that acts as a proxy for the kinematics of parton showers and hadron formation. The observable is constructed from charged particles and is measured for R = 1.0 anti-$k_t$ jets with transverse momentum above 350 GeV containing the full decay products of either a top quark or a daughter W boson. The other top quark in the event is identified from its decay into a b-quark, an electron or a muon and a neutrino. The measurement is corrected for detector effects and compared with a range of Monte Carlo predictions sensitive to different aspects of the hadronic decays of the heavy particles. In the W-boson-initiated jets, all the predictions are incompatible with the measurement. In the top quark initiated jets, disagreement with all predictions is observed in smaller subregions of the plane, and with a subset of the predictions across the fiducial plane. The measurement could be used to improve the tuning of Monte Carlo generators, for better modelling of hadronic decays of heavy quarks and bosons, or to improve the performance of jet taggers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Upland tidal brackish marsh specific conductivity and salinity measurements, PIE LTER, Plum Island Sound, MA, 2023

This dataset includes raw and corrected specific conductivity, temperature, and calculated salinity measurements collected at 10 cm depth in a Typha angustifolia-dominated tidal brackish wetland at the upper estuary of Plum Island Sound in Newbury, Massachusetts (MA) within the Plum Island Ecosystems Long Term Ecological Research (PIE LTER) site. Measurements were taken to evaluate temporal variation in porewater salinity (a proxy for porewater sulfate concentration) in high frequency to assess soil and plant responses to changes in salinity. Measurements were collected using an Onset HOBO U24-002 Saltwater Conductivity/Salinity data logger deployed in a well. Specific conductivity was corrected using non-linear temperature compensation, and salinity was calculated using the Practical Salinity Scale 1978 via Onset's HOBOware software. Reference conductivity measurements to correct for sensor drift were taken at the start and end of each deployment using a HACH HQ14D Portable Conductivity Meter. Data were then filtered in MATLAB to remove values logged while the sensor was out of the well or during post-deployment equilibration. Detailed metadata, including variable descriptions, sampling methods, QA/QC procedures, and site information, are provided in the files: Typha_ctd_salinity_dd.csv and Typha_MI_ctd_salinity_2023_flmd.csv.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Upland tidal brackish marsh specific conductivity and salinity measurements, PIE LTER, Plum Island Sound, MA, May-December 2022

This dataset includes raw and corrected specific conductivity, temperature, and calculated salinity measurements collected at 10 cm depth in a Typha angustifolia-dominated tidal brackish wetland at the upper estuary of Plum Island Sound in Newbury, Massachusetts (MA) within the Plum Island Ecosystems Long Term Ecological Research (PIE LTER) site. Measurements were taken to evaluate temporal variation in porewater salinity (a proxy for porewater sulfate concentration) in high frequency to assess soil and plant responses to changes in salinity. Measurements were collected using an Onset HOBO U24-002 Saltwater Conductivity/Salinity data logger deployed in a well. Specific conductivity was corrected using non-linear temperature compensation, and salinity was calculated using the Practical Salinity Scale 1978 via Onset's HOBOware software. Reference conductivity measurements to correct for sensor drift were taken at the start and end of each deployment using a HACH HQ14D Portable Conductivity Meter. Data were then filtered in MATLAB to remove values logged while the sensor was out of the well or during post-deployment equilibration. Detailed metadata, including variable descriptions, sampling methods, QA/QC procedures, and site information, are provided in the files: Typha_ctd_salinity_dd.csv and Typha_MI_ctd_salinity_2023_flmd.csv.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

SDSS-IV MaNGA: Cannibalism Caught in the Act—On the Frequency of Occurrence of Multiple Cores in Brightest Cluster Galaxies

Although it is generally accepted that massive galaxies form in a two-phased fashion, beginning with a rapid mass buildup through intense starburst activities followed by primarily dry mergers that mainly deposit stellar mass at outskirts, the late time stellar mass growth of brightest cluster galaxies (BCGs), the most massive galaxies in the universe, is still not well understood. Several independent measurements have indicated a slower mass growth rate than predictions from theoretical models. We attempt to resolve the discrepancy by measuring the frequency of BCGs with multiple cores, which serve as a proxy of the merger rates in the central region and facilitate a more direct comparison with theoretical predictions. Using 79 BCGs at z = 0.06–0.15 with integral field spectroscopic data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) project, we obtain a multiple-core fraction of 0.11 ± 0.04 at z ≈ 0.1 within an 18 kpc radius from the center, which is comparable to the value of 0.08 ± 0.04 derived from mock observations of 218 simulated BCGs from the cosmological hydrodynamical simulation IllustrisTNG. We find that most cores that appear close to the BCGs from imaging data turn out to be physically associated systems. Anchoring on the similarity in the multiple-core frequency between the MaNGA and IllustrisTNG, we discuss the mass growth rate of BCGs over the past 4.5 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Effect of boronization on plasma-facing graphite surfaces and its correlation with the plasma behavior in NSTX-U

Boronization is a Plasma Facing Component (PFC) conditioning technique widely used in tokamak machines. The National Spherical Torus Experiment-Upgrade (NSTX-U) applied this conditioning, using a plasma glow with a deuterated Trimethyl-boron (d-TMB) and He mixture. The use of boronization during the campaign improved the plasma performance, allowing longer plasma discharges and H-mode access. The chemical state of an ATJ graphite sample, used as a proxy for the NSTX-U PFCs, was monitored in-situ using the Materials Analysis Particle Probe (MAPP) diagnostic and X-ray Photoelectron Spectroscopy (XPS). The XPS data showed a progressive rise (from + fluence increased. Filterscopes were used to measure the light emitted by oxygen impurities in the plasma near the surface of the PFC. An increase in the registered magnitude of the OII line, normalized to the Dγ intensity, was observed as the concentration of O on the ATJ surface increased. The plasma performance was found to be strongly correlated to oxygen impurity concentrations at the plasma edge and on the PFC surface, as measured by the discharge length and access to the H-mode regime. In this work, we present a quantitative analysis of the evolution of the chemistry of the ATJ surface, and the oxygen presence in the plasma-material interface, and report relevant plasma parameters observed during the same period of time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

ProtoDUNE Vertical Drift needs a selective triggering algorithm. The detector sits on Earth's surface, so cosmic activity dominates its data. Our goal in this paper is to trigger on neutrino events more robustly than the current deployed Analog-to-Digital Converter Simple Window (ADCSW) model and, eventually, search for signals of Beyond Standard Model (BSM) physics at DUNE as our ultimate North Star objective. As a step towards this goal, we evaluate a Wasserstein Normalized Autoencoder (WNAE) on simulated collection-plane only windows of shape $1\times10\times10$ where Neutrinos act as our BSM-proxy and Cosmic-ray Muons serve as our learned background. The network parameters are fitted using only cosmic-ray muon events as background in order to maintain an unsupervised pipeline. Training uses finite-step Langevin $x^-$ samples, positive-sample reconstruction energy, and an empirical sliced $2$-Wasserstein objective to learn a normalized Boltzmann energy model. We then calibrate on a nominal $5\,\mathrm{Hz}$ operating threshold calculated from cosmic validation data. Both WNAE and ADCSW accept 311 of 194,083 held-out cosmic background events at this $5\,\mathrm{Hz}$ threshold. We found that WNAE accepts 9,677 of 34,634 neutrino-proxy events $(27.9\pm0.24)\%$, compared with 10,076 $(29.1\pm0.24)\%$ for ADCSW, an observed WNAE-minus-ADCSW difference of $-1.15\%$. At another nominal $2\,\mathrm{Hz}$ target threshold, the corresponding efficiencies are $(20.5\pm0.22)\%$ and $(22.6\pm0.22)\%$, respectively. Of the WNAE-selected neutrino proxies at $5\,\mathrm{Hz}$, $(20.8\pm0.4)\%$ of the classified neutrino-proxy events are unique to WNAE, where the uncertainty is an absolute binomial standard error of $0.4\%$.

Zheng, Jake [U. Chicago (main)] (ORCID:00090002189↗
DOE OSTI2026

Wasserstein Normalized Autoencoder for Anomaly Detection in ProtoDUNE Vertical-Drift Detector

ProtoDUNE Vertical Drift needs a selective triggering algorithm. The detector sits on Earth's surface, so cosmic activity dominates its data. Our goal in this paper is to trigger on neutrino events more robustly than the current deployed Analog-to-Digital Converter Simple Window (ADCSW) model and, eventually, search for signals of Beyond Standard Model (BSM) physics at DUNE as our ultimate North Star objective. As a step towards this goal, we evaluate a Wasserstein Normalized Autoencoder (WNAE) on simulated collection-plane only windows of shape $1\times10\times10$ where Neutrinos act as our BSM-proxy and Cosmic-ray Muons serve as our learned background. The network parameters are fitted using only cosmic-ray muon events as background in order to maintain an unsupervised pipeline. Training uses finite-step Langevin $x^-$ samples, positive-sample reconstruction energy, and an empirical sliced $2$-Wasserstein objective to learn a normalized Boltzmann energy model. We then calibrate on a nominal $5\,\mathrm{Hz}$ operating threshold calculated from cosmic validation data. Both WNAE and ADCSW accept 311 of 194,083 held-out cosmic background events at this $5\,\mathrm{Hz}$ threshold. We found that WNAE accepts 9,677 of 34,634 neutrino-proxy events $(27.9\pm0.24)\%$, compared with 10,076 $(29.1\pm0.24)\%$ for ADCSW, an observed WNAE-minus-ADCSW difference of $-1.15\%$. At another nominal $2\,\mathrm{Hz}$ target threshold, the corresponding efficiencies are $(20.5\pm0.22)\%$ and $(22.6\pm0.22)\%$, respectively. Of the WNAE-selected neutrino proxies at $5\,\mathrm{Hz}$, $(20.8\pm0.4)\%$ of the classified neutrino-proxy events are unique to WNAE, where the uncertainty is an absolute binomial standard error of $0.4\%$.

Zheng, Jake [Chicago U.] (ORCID:0009000218901379)↗
DOE OSTI2025

The Juno mission as a probe of long-range new physics

Orbits of celestial objects, especially the geocentric and heliocentric ones, have been well explored to constrain new long-range forces beyond the Standard Model (SM), often referred to as fifth forces. In this paper, for the first time, we apply the motion of a spacecraft around Jupiter to probe fifth forces that don’t violate the equivalence principle. The spacecraft is the Juno orbiter, and ten of its early orbits already allow a precise determination of the Jovian gravitational field. We use the shift in the precession angle as a proxy to test non-gravitational interactions between Juno and Jupiter. Requiring that the contribution from the fifth force does not exceed the uncertainty of the precession shift inferred from data, we find that a new parameter space with the mass of the fifth-force mediator around 10 −14 eV is excluded at 95% C.L.

new light particles↗
DOE OSTI2022

Chemomechanical weakening of muscovite quantified with in situ liquid nanoindentation

Abstract Chemomechanical weakening of layered phyllosilicate muscovite mica was studied as a function of chemical environment via in situ liquid-nanoindentation under four conditions (dry, deionized water, and two NaCl solutions of different pH). While traditional indentation analyses of layered materials with extreme mechanical anisotropy have been limited due to displacement bursts (pop-ins), here the bursts were used as proxies for delamination, fracture, and spalling events. Since displacement bursts during an indent represent a stochastic process, 120 indents were conducted for each condition to generate statistically significant amounts of data. In total, over 9000 bursts were assessed using a load–displacement threshold criterion, classifying this as a high-throughput nanoscale fracture technique. For each burst, initiation load, initiation displacement, plastic zone volume at initiation, and energy dissipation were analyzed. A power-law relationship between the burst load and burst energy was noted which separated the bursts into two continuous distributions: (1) bursts due only to the mechanics of the indent and (2) bursts due to both the mechanics of the indent and the environment. By using a cumulative probability distribution, it was found that the NaCl solutions decreased the minimum plastic zone volume necessary to initiate a displacement burst by an order of magnitude relative to the dry condition. Finally, the underlying mechanisms explaining the trends in initiation volume as a function of environment were discussed, with a focus on the chemomechanical degradation processes via chemical attack and cation exchange.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Revisiting Bayesian constraints on the transport coefficients of QCD

Multistage models based on relativistic viscous hydrodynamics have proven successful in describing hadron measurements from relativistic nuclear collisions. These measurements are sensitive to the shear and the bulk viscosities of QCD and provide a unique opportunity to constrain these transport coefficients. Bayesian analyses can be used to obtain systematic constraints on the viscosities of QCD, through methodical model-to-data comparisons. In this manuscript, we discuss recent developments in Bayesian analyses of heavy ion collision data. Furthermore, we highlight the essential role of closure tests in validating a Bayesian analysis before comparison with measurements. We discuss the role of the emulator that is used as proxy for the multistage theoretical model. We use an ongoing Bayesian analysis of soft hadron measurements by the JETSCAPE Collaboration as context for the discussion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

SPRUCE Vegetation Phenology in Experimental Plots from PhenoCam Imagery, 2015-2024

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2025 (2015-08-24 to 2025-03-31), with start- and end-of-season phenological transition dates derived through the end of autumn 2024. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step. • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e., vegetation type). • Contains one file in *.csv format. (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure. • Contains two files in *.csv format, one for snow on trees and one for snow on ground. This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type. • One additional file in HTML format with the transition dates plotted for each vegetation type, by year. (2) R files for processing PhenoCam files and flags. • Contains five files in R file(*.R) format and the components of the phenocamr package (Version 1.1.4) used for calculating transition dates for 2015-2024. These are contained in a compressed (*.zip) file. User Note: All imagery is posted in near-real time to the PhenoCam Project web page (https://phenocam.nau.edu), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. This data set is based on the complete camera record from SPRUCE and supersedes all previously released PhenoCam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Harvesting the low-hanging fruit of high energy savings -- Virtual Occupancy using Wi-Fi Data

Approximately 20% of primary energy consumed in the U.S. is attributed to HVAC use. Ideally, HVAC operation would be driven by actual building occupancy, but lack of reliable occupancy information often results in the use of conservative static schedules. This disparity is even more pronounced in a college campus, where the function of each space differs by building (classrooms, offices, libraries) and the class schedules change frequently -- every semester, day of week, and hour. While several research papers propose the use of counts of the Wi-Fi connections (e.g., phones, computers) as a proxy for occupancy, few real-world implementations exist. This paper describes the development and deployment of an open-source Wi-Fi-to-Occupancy software library in 65 buildings of a college campus, and the planned integration with the building energy management and control system at the building scale. Over a year of Wi-Fi data was gathered into distinct academic periods, including fall and spring semester, academic breaks, and summer sessions. Patterns such as students moving between classrooms, closing laptops before exams, etc., can be visualized from the data. Approximating occupancy from Wi-Fi data presents challenges which we address in this project -- for example, identifying static devices, or estimating the ratio of devices per person. Utilizing real-time occupancy data to inform optimal HVAC schedules and ventilation rates creates the potential to identify and reduce energy waste. Other potential applications include forecasting occupancy, and using Wi-Fi data to predict peak demands. Finally, the paper discusses how to easily scale these tools to other buildings.

Pritoni, Marco↗
DOE OSTI2022

Declining tropical cyclone frequency under global warming

Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Neural Networks as Surrogates of Nonlinear High-Dimensional Parameter-to-Prediction Maps.

We present a preliminary investigation of the use of Multi-Layer Perceptrons (MLP) and Recurrent Neural Networks (RNNs) as surrogates of parameter-to-prediction maps of com- putational expensive dynamical models. In particular, we target the approximation of Quan- tities of Interest (QoIs) derived from the solution of a Partial Differential Equations (PDEs) at different time instants. In order to limit the scope of our study while targeting a rele- vant application, we focus on the problem of computing variations in the ice sheets mass (our QoI), which is a proxy for global mean sea-level changes. We present a number of neural network formulations and compare their performance with that of Polynomial Chaos Expansions (PCE) constructed on the same data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Neural Networks as Surrogates of Nonlinear High-Dimensional Parameter-to-Prediction Maps

We present a preliminary investigation of the use of Multi-Layer Perceptrons (MLP) and Recurrent Neural Networks (RNNs) as surrogates of parameter-to-prediction maps of computational expensive dynamical models. In particular, we target the approximation of Quantities of Interest (QoIs) derived from the solution of a Partial Differential Equations (PDEs) at different time instants. In order to limit the scope of our study while targeting a relevant application, we focus on the problem of computing variations in the ice sheets mass (our QoI), which is a proxy for global mean sea-level changes. We present a number of neural network formulations and compare their performance with that of Polynomial Chaos Expansions (PCE) constructed on the same data.

97 MATHEMATICS AND COMPUTING↗