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NASA NTRS2019

Providing Data Access and Analysis Capabilities to SERVIR’s Data-Sparse Regions

In developing regions of the world, the communications infrastructure pose enormous challenges for using Earth observation data. Limited internet bandwidth along with the high costs make it almost impossible to process and extract zonal statistics over large periods of time for even small geographic areas. In such cases, downloading daily rainfall data or dekadal series of NDVI data would take days and consume all the bandwidth allocated to an organization (for reference, internet connections in Niger would cost thousands of dollars per month at a maximum - and unreliable - bandwidth of just 10 Mbps). Running crop models or hydrological models typically require several years of historic data over the area of interest (AOI). In some cases, these AOIs are relatively small compared to the footprint of individual earth observation granules. Hence, systems that let the stakeholders subset the data to download to a user specified area, or even submit processing requests that let them download small result files for the AOI become critical. The SERVIR program has developed a tool to provide this type of access to help decision makers in developing regions use long time series of adjusted rainfall data (CHIRPS), NDVI values, seasonal weather forecasts, evaporative stress indices and others in a very efficient manner. This system, named ClimateSERV (https://climateserv.servirglobal.net) ingests the datasets in an automated fashion and allows interactive access (through a web application), or automated access through a simple API that developers can quickly incorporate in independent applications. This way, the extraction of daily averages of rainfall over a 50 square Km area through 30 years of archived data takes only a few seconds to process, and the results can be presented on an online chart or downloaded in a comma separated file that's only a few Kb.

Ashmall, William↗

DOE OSTI2026

Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region

During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.

Poe, Jeralyn [Northern Arizona University, Flagsta↗

NASA NTRS1980

Estimation of incomplete multinomial data

Program estimates cell probabilities for data observed to fall in one of two or more categories when exact category cannot be determined. Data are assumed to be randomly incomplete. Estimation minimizes risk of quadratic loss. Program should be useful in projects where multinomial data is analyzed, but where observations are sometimes incomplete. Program is in FORTRAN IV and Assembler for batch execution on CYBER 173.

Credeur, K. R.↗

NASA NTRSDate not supplied

Goniometric and Polarized Imaging Spectroscopic Lab Measurements of Spacecraft Materials

To better characterize the spectral response of common spacecraft materials, the following laboratory measurements are presented to support the Space Situational Awareness community in the analysis of remotely sensed observational data. Of interest is classifying material reflective properties using directional reflectance spectroscopy and spatially resolved polarized imaging spectroscopy, allowing laboratory data to be applicable to ground-based optical telescope observations. The team acquired a typical CubeSat solar panel and a sample of multi-layer insulation (MLI) commonly used on spacecraft for initial measurements. The directional spectral data were collected at the Goniometer of the Rochester Institute of Technology (GRIT) laboratory with a lab and field goniometer incorporating two AnalyticalSpectral Device (ASD) spectrometers, a small Lab sphere integrating sphere also paired with an ASD spectrometer, and a Headwall micro-Hyperspec E-Series imaging spectrometer with an adjustable linear polarizer. The goniometer measures spectral bi-directional reflectance factor (BRF) data over a broad range from 350−2500 nm at 1 nm spacing with 3 nm spectral resolution in the visible and near infrared and 8 nm in the shortwave infrared. With the same spectral capabilities, the integrating sphere measures hemispherical-directional reflectance (HDR) in a 45◦-nadir configuration. The Headwall imager covers a spectral range from 400−1000 nm with 1.6 nm spectral resolution.Our initial BRF measurements show interference effects for both materials typically observed with thin films and high infrared reflectivity. In contrast, the interference effects are not present in the HDR measurements of the MLI likely due to the interference effects being averaged out over the reflecting hemisphere. Spatially resolved polarization ratio maps show variability across the materials due to the varying surface structure. We outline a plan for expanding our analysis to a broader range of materials to characterize their directional reflectance spectroscopy.

Chris H. Lee↗

NASA NTRS1999

Main Geomagnetic Field Models from Oersted and Magsat Data Via a Rigorous General Inverse Theory with Error Bounds

The purpose of the grant was to study how prior information about the geomagnetic field can be used to interpret surface and satellite magnetic measurements, to generate quantitative descriptions of prior information that might be so used, and to use this prior information to obtain from satellite data a model of the core field with statistically justifiable error estimates. The need for prior information in geophysical inversion has long been recognized. Data sets are finite, and faithful descriptions of aspects of the earth almost always require infinite-dimensional model spaces. By themselves, the data can confine the correct earth model only to an infinite-dimensional subset of the model space. Earth properties other than direct functions of the observed data cannot be estimated from those data without prior information about the earth. Prior information is based on what the observer already knows before the data become available. Such information can be "hard" or "soft". Hard information is a belief that the real earth must lie in some known region of model space. For example, the total ohmic dissipation in the core is probably less that the total observed geothermal heat flow out of the earth's surface. (In principle, ohmic heat in the core can be recaptured to help drive the dynamo, but this effect is probably small.) "Soft" information is a probability distribution on the model space, a distribution that the observer accepts as a quantitative description of her/his beliefs about the earth. The probability distribution can be a subjective prior in the sense of Bayes or the objective result of a statistical study of previous data or relevant theories.

Backus, George E.↗

NASA NTRSDate not supplied

Goniometric and Polarized Imaging Spectroscopic Lab Measurements ofSpacecraft Materials

To better characterize the spectral response of common spacecraft materials, the following laboratory measurements are presented to support the Space Situational Awareness community in the analysis of remotely sensed observational data. Of interest is classifying material reflective properties using spectral bidirectional reflectance distribution function (BRDF) data and spatially resolved polarized imaging spectroscopy, allowing laboratory data to be applicable to ground-based optical telescope observations. The team acquired a typical CubeSat solar panel and a sample of multi-layer insulation commonly used on spacecraft for initial measurements. The data were collected at the Goniometer of the Rochester Institute of Technology (GRIT) laboratory with a field and laboratory goniometer housing two Analytical Spectral Device (ASD) spectrometers and a Headwall micro-Hyperspec E-Series imaging spectrometer with an adjustable linear polarizer. The goniometer provides spectral reflectance over a broad spectral range from 350-2500 nm at 1 nm spacing with 3 nm spectral resolution in the visible and near infrared and 8 nm in the shortwave infrared. The Headwall imager covers a spectral range from 400-1000 nm with 1.6 nm spectral resolution. We present the results from these initial measurements that show highly reflective regions at various locations in the angular domain for both materials. In addition, the solar cell spectra exhibited strong interference effects typically observed with thin films. Our team is pursuing a variety of typical solar cells to assess variations in product type. The spatially resolved polarization ratio maps show variability across the materials due to surface structure and varying material composition. Based on these results, we outline a plan for simulating spectral radiance light curves of the materials in various orbital configurations as they would be measured from ground- based telescopes for a clear observing sky during twilight. The paper will also present a plan for expanding ours of interest to determine if the results presented are unique to these samples and to categorize the spectral response for different material classes.

Chris H. Lee↗

DOE OSTI2015

Estimation of missing values in solar radiation data using piecewise interpolation methods: Case study at Penang city

The solar radiation values have been composed by automatic weather station using the device that namely pyranometer. The device is functions to records all the radiation values that have been dispersed, and these data are very useful for it experimental works and solar device’s development. In addition, for modeling and designing on solar radiation system application is needed for complete data observation. Unfortunately, lack for obtained the complete solar radiation data frequently occur due to several technical problems, which mainly contributed by monitoring device. Into encountering this matter, estimation missing values in an effort to substitute absent values with imputed data. This paper aimed to evaluate several piecewise interpolation techniques likes linear, splines, cubic, and nearest neighbor into dealing missing values in hourly solar radiation data. Then, proposed an extendable work into investigating the potential used of cubic Bezier technique and cubic Said-ball method as estimator tools. As result, methods for cubic Bezier and Said-ball perform the best compare to another piecewise imputation technique.

14 SOLAR ENERGY↗

DOE OSTI2014

The role of subsurface flows in solar surface convection: modeling the spectrum of supergranular and larger scale flows

We model the solar horizontal velocity power spectrum at scales larger than granulation using a two-component approximation to the mass continuity equation. The model takes four times the density scale height as the integral (driving) scale of the vertical motions at each depth. Scales larger than this decay with height from the deeper layers. Those smaller are assumed to follow a Kolmogorov turbulent cascade, with the total power in the vertical convective motions matching that required to transport the solar luminosity in a mixing length formulation. These model components are validated using large-scale radiative hydrodynamic simulations. We reach two primary conclusions. (1) The model predicts significantly more power at low wavenumbers than is observed in the solar photospheric horizontal velocity spectrum. (2) Ionization plays a minor role in shaping the observed solar velocity spectrum by reducing convective amplitudes in the regions of partial helium ionization. The excess low wavenumber power is also seen in the fully nonlinear three-dimensional radiative hydrodynamic simulations employing a realistic equation of state. This adds to other recent evidence suggesting that the amplitudes of large-scale convective motions in the Sun are significantly lower than expected. Employing the same feature tracking algorithm used with observational data on the simulation output, we show that the observed low wavenumber power can be reproduced in hydrodynamic models if the amplitudes of large-scale modes in the deep layers are artificially reduced. Since the large-scale modes have reduced amplitudes, modes on the scale of supergranulation and smaller remain important to convective heat flux even in the deep layers, suggesting that small-scale convective correlations are maintained through the bulk of the solar convection zone.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Deep Learning-based Non-Stationary Bias Correction (NSBC)

This work develops the NSBC (non-stationary bias correction) methodology to correct temperature projection bias from E3SM. The NSBC deep learning framework consists of a three-part architecture: an auto-encoder for compressing the spatial information, an LSTM for predicting annual temperature mean, and a U-Net for capturing the residual bias in temperature. The non-stationary bias correction (NSBC) framework can correct the non-stationarity of the biases of the climate models, which significantly improves the accuracy of future temperature prediction and improves the overestimation of extreme high temperatures that many existing bias correction methods suffer from. Getting started 1. Obtain the historical climate simulation and observation data. The E3SM simulation data are available through https://aims2.llnl.gov/search/cmip6/. The pseudo observations, the Geophysical Fluid Dynamics Laboratory (GFDL)-ESM4 model (Krasting et al., 2018) are available through https://aims2.llnl.gov/search/cmip6/. The spatial resolution of E3SM and pseudo observation datasets are both regridded to a common 1° resolution grid using conservative interpolation. The regridded E3SM and pseudo observation with 1° resolution can be found throught ./data/. 2. Train the Auto-encoder model. Python 0-autoencoder.py 3. Train the LSTM Python 1-LSTM.py 4. Generate the annual mean temperature based on trained LSTM Python 2-generate_annual_mean_LSTM.py 5. Train the U-Net. Python 3-unet.py 6. Evaluation and compared with the baseline Python 4_evaluation.py Is there a deadline approaching that requires the release of yo

Lucas, Donald↗

DOE OSTI2015

Disentangling multidimensional spatio-temporal data into their common and aberrant responses

With the advent of high-throughput measurement techniques, scientists and engineers are starting to grapple with massive data sets and encountering challenges with how to organize, process and extract information into meaningful structures. Multidimensional spatio-temporal biological data sets such as time series gene expression with various perturbations over different cell lines, or neural spike trains across many experimental trials, have the potential to acquire insight about the dynamic behavior of the system. For this potential to be realized, we need a suitable representation to understand the data. A general question is how to organize the observed data into meaningful structures and how to find an appropriate similarity measure. A natural way of viewing these complex high dimensional data sets is to examine and analyze the large-scale features and then to focus on the interesting details. Since the wide range of experiments and unknown complexity of the underlying system contribute to the heterogeneity of biological data, we develop a new method by proposing an extension of Robust Principal Component Analysis (RPCA), which models common variations across multiple experiments as the lowrank component and anomalies across these experiments as the sparse component. We show that the proposed method is able to find distinct subtypes and classify data sets in a robust way without any prior knowledge by separating these common responses and abnormal responses. Thus, the proposed method provides us a new representation of these data sets which has the potential to help users acquire new insight from data.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Global properties of rotating neutron stars with qcd equations of state

We numerically investigate global properties of rotating neutron stars (NSs) using the allowed band of QCD equations of state derived by Kurkela et al. This band is constrained by chiral effective theory at low densities and perturbative QCD at high densities, and is thus, in essence, a controlled constraint from first-principles physics. Previously, this band of equations of state was used to investigate non-rotating NSs only; in this work, we extend these results to any rotation frequency below the mass-shedding limit. We investigate mass–radius curves, allowed mass–frequency regions, radius–frequency curves for a typical 1.4M{sub ⊙} star, and the values of the moment of inertia of the double pulsar PSR J0737-3039A, a pulsar for which the moment of inertia may be constrained observationally in a few years. We present limits on observational data coming from these constraints, and identify values of observationally relevant parameters that would further constrain the allowed region for the QCD equation of state. We also discuss how much this region would be constrained by a measurement of the moment of inertia of the double pulsar PSR J0737-3039A.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1972

Nonthermal radio observations of the major planets.

The complex and intriguing source of emission over the entire radio spectrum that Jupiter represents is reviewed in the light of ground radio observation data gathered over a period of seventeen years. The observations indicate the presence of intense radiation belts and a strong magnetic field inclined to the axis of rotation. At decametric wavelengths, several remarkably powerful sources are correlated with the rotation of the planet and the orbital motion of the satellite Io. There is at most marginal evidence of nonthermal emission from Saturn, and no such evidence as yet from Uranus and Neptune.

Smith, A. G.↗

NASA NTRS1974

Measurements of trace constituents from atmospheric infrared emission and absorption spectra, a feasibility study

The feasibility of detecting eight trace constituents (CH4, HCl, HF, HNO3, NH3, NO, NO2 and SO2) against the rest of the atmospheric background at various altitudes from infrared emission and absorption atmospheric spectra was studied. Line-by-line calculations and observational data were used to establish features that can be observed in the atmospheric spectrum due to each trace constituent. Model calculations were made for experimental conditions which approximately represent state of the art emission and absorption spectrometers.

Goldman, A.↗

NASA NTRS1976

The case for an unfractionated Pu-244/U-238 ratio in high-temperature condensates

The coarse-grained, Ca-rich inclusions in the Allende meteorite are the highest-temperature condensates from the cooling solar nebula and, as such, the oldest solid objects in the solar system. All refractory elements with condensation points above the accretion temperature of the inclusions whose concentrations in them have been measured are seen to be present in the inclusions in unfractionated proportion to one another relative to Cl chondrites when data are averaged for a large number of inclusions. Observational data for U and theoretical data for both U and Pu suggest that these elements exhibited refractory behavior in the solar nebula. An experiment is proposed in which fissiogenic Xe and U contents are measured in a suite of these inclusions to obtain the Pu-244/U-238 ratio of the solar system at the time of initial condensation with an uncertainty of plus or minus 15%.

Ganapathy, R.↗

NASA NTRS1984

Multisensor satellite data integration for sea surface wind speed and direction determination

Techniques to integrate meteorological data from various satellite sensors to yield a global measure of sea surface wind speed and direction for input to the Navy's operational weather forecast models were investigated. The sensors were launched or will be launched, specifically the GOES visible and infrared imaging sensor, the Nimbus-7 SMMR, and the DMSP SSM/I instrument. An algorithm for the extrapolation to the sea surface of wind directions as derived from successive GOES cloud images was developed. This wind veering algorithm is relatively simple, accounts for the major physical variables, and seems to represent the best solution that can be found with existing data. An algorithm for the interpolation of the scattered observed data to a common geographical grid was implemented. The algorithm is based on a combination of inverse distance weighting and trend surface fitting, and is suited to combing wind data from disparate sources.

Glackin, D. L.↗

NASA NTRS1988

Diabatic initialization for a mesoscale model simulation experiment

A mesoscale model simulation of a 'surrogate' atmosphere designed for the evaluation of adiabatic initialization and moisture enhancement techniques is briefly described. The simulation provides mesoscale precipitation rates and associated diabatic heating fields which are known exactly and are internally consistent within the context of the model. The advantage of this approach is that a numerical model can easily serve as a source of mesoscale data in the usual absence of internally consistent mesoscale observed data sets.

Kalb, Michael W.↗

NASA NTRS1988

Fractal distributions of stress and strength and variations of b-value

A two-dimensional planar fault zone on which the difference between stress and strength follows a fractal distribution is simulated to study the variation of the frequency-magnitude b-value under different distributions of heterogeneities and ambient stress levels. It is suggested that earthquakes occur in regions where this difference exceeds a specified value and that the size of these regions is a measure of the magnitude of the associated earthquake. A systematic variation in b-value is observed. It is found that the b-value has a positive correlation with the fractal dimension of the distribution and is inversely related to the ambient stress level. Observational data are compared with the simulation, showing that the observed b-value variation before and during earthquake sequences is a result of changes in both the ambient stress level and in the fractal dimension of the stress-strength distribution.

Huang, J.↗

NASA NTRS1991

The 1980 solar maximum mission event listing

Information is contained on solar burst and transient activity observed by the Solar Maximum Mission (SMM) during 1980 pointed observations. Data from the following SMM experiments are included: (1) Gamma Ray Spectrometer, (2) Hard X-Ray Burst Spectrometer, (3) Hard X-Ray Imaging Spectrometer, (4) Flat Crystal Spectrometer, (5) Bent Crystal Spectrometer, (6) Ultraviolet Spectrometer and Polarimeter, and (7) Coronagraph/Polarimeter. Correlative optical, radio, and Geostationary Operational Environmental Satellite (GOES) x ray data are also presented. Where possible, bursts or transients observed in the various wavelengths were grouped into discrete flare events identified by unique event numbers. Each event carries a qualifier denoting the quality or completeness of the observations. Spacecraft pointing coordinates and flare site angular displacement values from Sun center are also included.

Speich, D. M.↗