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NASA NTRS2008

High-Order Energy Stable WENO Schemes

A new third-order Energy Stable Weighted Essentially NonOscillatory (ESWENO) finite difference scheme for scalar and vector linear hyperbolic equations with piecewise continuous initial conditions is developed. The new scheme is proven to be stable in the energy norm for both continuous and discontinuous solutions. In contrast to the existing high-resolution shock-capturing schemes, no assumption that the reconstruction should be total variation bounded (TVB) is explicitly required to prove stability of the new scheme. A rigorous truncation error analysis is presented showing that the accuracy of the 3rd-order ESWENO scheme is drastically improved if the tuning parameters of the weight functions satisfy certain criteria. Numerical results show that the new ESWENO scheme is stable and significantly outperforms the conventional third-order WENO finite difference scheme of Jiang and Shu in terms of accuracy, while providing essentially nonoscillatory solutions near strong discontinuities.

Yamaleev, Nail K.↗
NASA NTRS2008

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5. Diurnal cycles are explicitly resolved by merging geostationary satellite observations with CERES and MODIS. Atmospheric state data are provided from a frozen version of the Global Modeling and Assimilation Office- Data Assimilation System at the NASA Goddard Space Flight Center. In addition to improving the accuracy of top-of-atmosphere (TOA) radiative fluxes, CERES also produces radiative fluxes at the surface and at several levels in the atmosphere using radiative transfer modeling, constrained at the TOA by CERES (ERBE was limited to the TOA). In all, CERES uses 11 instruments on 7 spacecraft all integrated to obtain climate accuracy in TOA to surface fluxes. This presentation will provide an overview of several new CERES datasets of interest to the climate community (including a new adjusted TOA flux dataset constrained by estimates of heat storage in the Earth system), show direct comparisons between CERES ad ERBE, and provide a detailed error analysis of CERES fluxes at various time and space scales. We discuss how observations can be used to reduce uncertainties in cloud feedback and climate sensitivity and strongly argue why we should NOT "call off the quest".

Loeb, Norman G.↗
NASA NTRS2006

A Climatology of Midlatitude Continental Clouds from the ARM SGP Site: Cloud Fraction and Surface Radiative Forcing - Part II

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of cloud fraction and radiative forcing between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layered low (0-3 km), middle (3-6 km), and high clouds (more than 6 km) using ARM SCG ground-based paired lidar-radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties of approximately 10 Wm(exp -2). The annual averages of total, and single-layered low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total and low cloud amounts peak during January and February and reach a minimum during July and August, high clouds occur more frequently than other types of clouds with a peak in summer. The average annual downwelling surface SW fluxes for total and low clouds (151 and 138 Wm(exp-2), respectively) are less than those under middle and high clouds (188 and 201 Wm(exp -2), respectively), but the downwelling LW fluxes (349 and 356 Wm(exp -2)) underneath total and low clouds are greater than those from middle and high clouds (337 and 333 Wm(exp -2)). Low clouds produce the largest LW warming (55 Wm(exp -2) and SW cooling (-91 Wm(exp -2)) effects with maximum and minimum absolute values in spring and summer, respectively. High clouds have the smallest LW warming (17 Wm(exp -2)) and SW cooling (-37 Wm(exp -2)) effects at the surface. All-sky SW CRF decreases and LW CRF increases with increasing cloud fraction with mean slopes of -0.984 and 0.616 Wm(exp -2)%(exp -1), respectively. Over the entire diurnal cycle, clouds deplete the amount of surface insolation more than they add to the downwelling LW flux. The calculated CRFs do not appear to be significantly affected by uncertainties in data sampling and clear-sky screening. Traditionally, cloud radiative forcing includes, not only the radiative impact of the hydrometeors, but also the changes in the environment. Taken together over the ARM SCF, changes in humidity and surface albedo between clear and cloudy conditions offset approximately 20% of the NET radiative forcing caused by the cloud hydrometeors alone. Variations in water vapor, on average, account for 10% and 83% of the SW and LW CRFs, respectively, in total cloud cover conditions. The error analysis further reveals that the cloud hydrometeors dominate the SW CRF, while water vapor changes are most important for LW flux changes in cloudy skies. Similar studies over other locales are encouraged where water and surface albedo changes from clear to cloudy conditions may be much different than observed over the ARM SCF.

Xi, B.↗
NASA NTRS2004

Continued Development of a Precision Cryogenic Dilatometer for the James Webb Space Telescope

As part of the James Webb Space Telescope (JWST) materials working group, a novel cryogenic dilatometer was designed and built at NASA Jet Propulsion Laboratory to help address stringent coefficient of thermal expansion (CTE) knowledge requirements. Previously reported results and error analysis have estimated a CTE measurement accuracy for ULE of 1.7 ppb/K with a 20K thermal load and 0.1 ppb/K with a 280K thermal load. Presented here is a further discussion of the cryogenic dilatometer system and a description of recent work including system modifications and investigations.

thermal strain↗
NASA NTRS2006

Processing TES Level-2 Data

TES Level 2 Subsystem is a set of computer programs that performs functions complementary to those of the program summarized in the immediately preceding article. TES Level-2 data pertain to retrieved species (or temperature) profiles, and errors thereof. Geolocation, quality, and other data (e.g., surface characteristics for nadir observations) are also included. The subsystem processes gridded meteorological information and extracts parameters that can be interpolated to the appropriate latitude, longitude, and pressure level based on the date and time. Radiances are simulated using the aforementioned meteorological information for initial guesses, and spectroscopic-parameter tables are generated. At each step of the retrieval, a nonlinear-least-squares- solving routine is run over multiple iterations, retrieving a subset of atmospheric constituents, and error analysis is performed. Scientific TES Level-2 data products are written in a format known as Hierarchical Data Format Earth Observing System 5 (HDF-EOS 5) for public distribution.

Poosti, Sassaneh↗
NASA NTRS2011

A New Global Mascon Solution Tuned for High-Latitude Ice Studies

A new global mascon solution has been developed with I-arc-degree spatial and IO-day temporal sampling. The global mas cons are estimated from the reduction of nearly 8 years of GRACE K-band range-rate data. Temporal and anisotropic spatial constraints have been applied for land, ocean and ice regions. The solution construction and tuning is focused towards the Greenland and Antarctic ice sheets (GIS and AIS) as well as the Gulf of Alaska mountain glaciers (GoA). Details of the solution development will be discussed, including the mascon parameter definitions, constraints, and the tuning of the constraint damping factor. Results will be presented, exploring the spatial and temporal variability of the ice sheets and GoA regions. A detailed error analysis will be discussed, including solution dependence on iteration, damping factor, forward modeling, and multitechnique comparisons. We also investigate the fundamental resolution of the solution and the spatial correlation of ice sheet inter-annual change. Finally, we discuss future improvements, including specific constraint application for the rest of the major land ice regions and improvements in solution regularization.

Luthcke, S. B.↗
NASA NTRS2011

Estimating Contrail Climate Effects from Satellite Data

An automated contrail detection algorithm (CDA) is developed to exploit six of the infrared channels on the 1-km MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites. The CDA is refined and balanced using visual error analysis. It is applied to MODIS data taken by Terra and Aqua over the United States during 2006 and 2008. The results are consistent with flight track data, but differ markedly from earlier analyses. Contrail coverage is a factor of 4 less than other retrievals and the retrieved contrail optical depths and radiative forcing are smaller by approx.30%. The discrepancies appear to be due to the inability to detect wider, older contrails that comprise a significant amount of the contrail coverage. An example of applying the algorithm to MODIS data over the entire Northern Hemisphere is also presented. Overestimates of contrail coverage are apparent in some tropical regions. Methods for improving the algorithm are discussed and are to be implemented before analyzing large amounts of Northern Hemisphere data. The results should be valuable for guiding and validating climate models seeking to account for aviation effects on climate.

Minnis, Patrick↗
NASA NTRS2012

Assessment of NASA's Aircraft Noise Prediction Capability

A goal of NASA s Fundamental Aeronautics Program is the improvement of aircraft noise prediction. This document provides an assessment, conducted from 2006 to 2009, on the current state of the art for aircraft noise prediction by carefully analyzing the results from prediction tools and from the experimental databases to determine errors and uncertainties and compare results to validate the predictions. The error analysis is included for both the predictions and the experimental data and helps identify where improvements are required. This study is restricted to prediction methods and databases developed or sponsored by NASA, although in many cases they represent the current state of the art for industry. The present document begins with an introduction giving a general background for and a discussion on the process of this assessment followed by eight chapters covering topics at both the system and the component levels. The topic areas, each with multiple contributors, are aircraft system noise, engine system noise, airframe noise, fan noise, liner physics, duct acoustics, jet noise, and propulsion airframe aeroacoustics.

Dahl, Milo D.↗
NASA NTRS2013

Regional Climate and Variability of the Summertime Continental United States in Reanalyses

Understanding climate variability at regional scales is an important for research and societal needs. Atmospheric retrospective-analyses (or reanalyses) integrate multitudes of observing systems with numerical models to produce continuous data that include variables not easily observed, if at all. The breadth of variables as well as observational influence included in reanalyses make them ideal for investigating climate variability. In this paper, we assess NASA s Modern Era Retrospective-analysis for Research and Application (MERRA) regional variability in North America, specifically the United States, in conjunction with current satellite data reanalyses. Emphasis is placed on summertime precipitation because 1) it is a difficult parameter to capture in the most difficult season, 2) significant observational resources exist to benchmark comparisons, and 3) accurate assessment of precipitation variability is crucial to a multitude of sectors and applications. Likewise, we have also begun to evaluate surface air temperature. While precipitation biases are identified, year to year variability of the precipitation variations, in many cases, are quite reasonable. However, some spurious long term trends and sudden shifts in the time series are also identified. In surface air temperature, analysis of station observations provides ERA Interim a clear overall advantage. However, in a number of regions, all the reanalyses are quite comparable in variability and trend. In other regions, significant precipitation biases may occur, which has implications for the ancillary process data in a reanalysis, such as surface fluxes. We also characterize the reanalyses ability to capture variability related to ENSO. In general, the summertime variations of precipitation in the reanalyses are more highly correlated (positively) to ENSO (using ENSO34) than are the observations. The Northwestern US shows the largest positive correlations to ENSO34, and reanalyses agree with that, and correlate highly with the gauge observations there. Additional evaluation of the data assimilation using the MERRA Gridded Innovations and Observations (GIO) data, which consists of the assimilated observations as well as forecast an analysis error fields. This work represents an initial evaluation of using the MERRA reanalysis to study regional climate variations of the United States, and identifying its applied limitations

Bosilovich, M G.↗
NASA NTRS2016

Reducing Multisensor Satellite Monthly Mean Aerosol Optical Depth Uncertainty: 1. Objective Assessment of Current AERONET Locations

Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)- based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by approximately 27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty reduction, indicating its representativeness level.

aerosol optical depth↗
NASA NTRS2011

A High-Resolution Measurement of Ball IR Black Paint's Low-Temperature Emissivity

High-emissivity paints are commonly used on thermal control system components. The total hemispheric emissivity values of such paints are typically high (nearly 1) at temperatures above about 100 Kelvin, but they drop off steeply at lower temperatures. A precise knowledge of this temperature-dependence is critical to designing passively-cooled components with low operating temperatures. Notable examples are the coatings on thermal radiators used to cool space-flight instruments to temperatures below 40 Kelvin. Past measurements of low-temperature paint emissivity have been challenging, often requiring large thermal chambers and typically producing data with high uncertainties below about 100 Kelvin. We describe a relatively inexpensive method of performing high-resolution emissivity measurements in a small cryostat. We present the results of such a measurement on Ball InfraRed BlackTM(BIRBTM), a proprietary surface coating produced by Ball Aerospace and Technologies Corp (BATC), which is used in spaceflight applications. We also describe a thermal model used in the error analysis.

Tuttle, Jim↗
NASA NTRS2018

Confirming Variability in the Secondary Eclipse Depth of the Super-Earth 55 Cancri e

We present a reanalysis of five transit and eight eclipse observations of the ultrashort-period super-Earth 55 Cancri e observed using the Spitzer Space Telescope during 2011-2013. We use pixel-level decorrelation to derive accurate transit and eclipse depths from the Spitzer data, and we perform an extensive error analysis. We focus on determining possible variability in the eclipse data, as was reported in Demory et al. From the transit data, we determine updated orbital parameters, yielding T (sub 0) = 2,455,733.0037 +/- 0.0002, P = 0.7365454 +/- 0.0000003 days, i = 83.5 +/- 1fdg3, and R p = 1.89 +/- 0.05 R ⊕. Our transit results are consistent with a constant depth, and we conclude that they are not variable. We find a significant amount of variability between the eight eclipse observations and confirm agreement with Demory et al. through a correlation analysis. We convert the eclipse measurements to brightness temperatures, and generate and discuss several heuristic models that explain the evolution of the planet's eclipse depth versus time. The eclipses are best modeled by a year-to-year variability model, but variability on shorter timescales cannot be ruled out. The derived range of brightness temperatures can be achieved by a dark planet with inefficient heat redistribution intermittently covered over a large fraction of the substellar hemisphere by reflective grains, possibly indicating volcanic activity or cloud variability. This time-variable system should be observable with future space missions, both planned (JWST) and proposed (i.e., ARIEL).

Tamburo, P.↗
NASA NTRS2018

The Convergence of Analysis Produced by Overlapping Assimilation Streams

When conducting a reanalysis for a long period, it is common to do so using multiple, parallel computational schemes. A period of overlap is included to foster continuity between successive streams. At the GMAO, the overlap period is one year. By the end of that period, the time mean anlysis for corresponding overlapped months are almost identical, as desired. The variances of differences at corresponding analysis times within each month, however, do not converge to zero. Instead their monthly variances converge to values that are a significant fraction of the the estimated variances of analysis errors. This occurs although the overlapping streams use the same observations, assimilation model, and assimilation algorithm, differing only in the background applied information applied at the beginning of the overlap period.

Errico, Ronald M.↗
NASA NTRS2018

Learning Model Structural Uncertainty with Gaussian Processes

The advent of commercially available quantum computers has marked the beginning of quantum computing as a reality. Both quantum gate and annealing computers have been released by major computer hardware companies. In this work, the D-Wave 2XTM quantum annealing computer housed at the NASA Advanced Systems computational facility is investigated to accelerate Machine Learning (ML) for image registration. NASA collects large amounts of images over the globe remotely using space-based monitoring. Images of a fixed areas of the land surface are taken over time. Due to the orbit of the sensors, the viewing angles deviate slightly, and it is necessary to align or register the images precisely to create image time series over the land surface. Unaligned images can lead to substantial analysis errors. These time-series are then used in modeling Earth Systems models such as hydrological, weather, and carbon monitoring models. In this work, we consider the Moderate Resolution Image Spectrometer (MODIS) data collected by the NASA's terra satellite. Artificial Neural Networks (ANNs) is a natural fit for ML modelling of images. Several successes have been reported using machine learning related to image processing. We investigate the use of ML to register MODIS images. ANNs are investigated in combination with a Restricted Boltzmann Machines (RBM) as an auto-encoder. We will present results showing the accuracy and efficiency of this approach.The D-Wave 2XTM quantum annealer samples the ground-state wave-function of a spin-Ising systems with quadratic interactions between qubits and a Chimera connectivity. The system sits in a ~15 mK thermal bath. One can think of the system as being placed in the ground state initially and subject to thermal excitations governed by Boltzmann statistics. If this is assumed true, one can use the statistics from the D-Wave 2XTM to train RBMs. Generating statistics for training Boltzmann machines is an NP-hard problem and constitutes the largest compute cost. We investigate the use of the D-Wave 2XTM to accelerate the training of the RBMs in our ANNs and report on the results.

Kouatchou, Jules↗
NASA NTRS2016

MUlti-SpEctral, MUlti-SpEcies, MUlti-SatEllite (MUSES) Retrieval Algorithm: Towards Extending Multi-Decadal NASA EOS Atmospheric Composition Data Records

Multi-Spectra, Multi-Species, Multi-Sensors (MUSES): Builds off of heritage from the Tropospheric Emission Spectrometer (TES) optimal estimation (OE) algorithm to combine a priori and satellite data, including rigorous error analysis diagnostics and observation operators needed for trend analysis, climate model evaluation, and data assimilation; has generic design to incorporate forward model radiances from hyperspectral measurements from multiple sensors into the joint retrieval algorithm.

Fu, Dejian↗
NASA NTRS2010

TPSAS-NF1676L-10658-DND

The systematic methodology for constructing fourth-order finite domain Energy Stable WENO schemes is developed. We prove that for hyperbolic systems, the finite domain ESWENO scheme is stable in the energy norm for both continuous and discontinuous solutions. The eigenvalues of the finite domain ESWENO dissipation operator are located in the left-half plane. Based on the rigorous truncation error analysis, the new weight functions are developed, which drastically improve the accuracy of the ESWENO scheme and provide excellent shock-capturing capabilities. Numerical experiments show that the new finite domain ESWENO scheme with the new weights outperform the conventional WENO schemes in terms of accuracy.

Travis Fisher↗
NASA NTRS2010

TPSAS-NF1676L-10863-DND

One important aspect of successful climate monitoring is satellite calibration. There is at least a 25-year of operational geostationary (GEO) record available for climate studies, if properly calibrated. The Global Space-based Inter-Calibration System (GSICS) project is another effort to provide the climate community consistent calibration across multiple platforms. Also, the Clouds and the Earth's Radiant Energy System (CERES) project, provides consistent GEO retrieved cloud properties and derived broadband fluxes across multiple platforms. This year GSICS is focusing on geostationary visible channel calibration. The GSICS strategy is to use multiple approaches, such as cross-calibrating the GEO radiances against MODIS as a reference, deep convective clouds as bright stable targets, deserts, sun-glint, stars, moon and other model based calibration methods. Each of these methods is independent of each other and can assess the stability of the GEO visible instrument with differing uncertainties. This study focuses on the inter-calibration of the GEO radiances against MODIS as a reference by using collocated, and coincident ray-matched radiances. The advantage of the ray-matching technique is that it provides a full dynamic range of radiances to check the linearity of the GEO visible instrument. This presentation will focus on the technique, some error analysis, comparisons with other methods, and an approach to inter-calibrate historical GEOs before MODIS.

D R Doelling↗
NASA NTRS2019

Camera modeling, centroiding performance, and geometric camera calibration on ASTERIA

The Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) is a 10-kg, 6U CubeSat in low-Earth orbit that was able to achieve subarcsecond pointing stability and repeatability. To date, this is the best pointing on a spacecraft of its size. This paper will analyze various aspects of the performance of its key piece of hardware—the payload. First,a model of the optics and imager, which is used to simulate stellar images, will be presented. The imager parameters used in this model were derived from simple ground measurements. Next, a centroiding algorithm is provided and used on the simulated images to predict centroiding performance. These results will be shown to match on-orbit telemetry of centroiding performance, validating the modeling approach. This paper will then describe an approach for and results of a geometric camera calibration algorithm to estimate the focal length,distortion,and alignment parameters. The modeling, analyses, and results presented in this paper provide key information that can be used in a time domain pointing simulation or a frequency-domain pointing error analysis.

Smith, Matthew W.↗