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NASA NTRS2003

Software With Strong Ties to Space

TieFlow is a simple but powerful business process improvement solution. It can automate and simplify any generic or industry-specific work process, helping organizations to transform work inefficiencies and internal operations involving people, paper, and procedures into a streamlined, well-organized, electronicbased process. TieFlow increases business productivity by improving process cycle times. The software can expedite generic processes in the areas of product design and development, purchase orders, expense reports, benefits enrollment, budgeting, hiring, and sales. It can also shore up vertical market processes such as claims processing, loan application and processing, health care administration, contract management, and advertising agency traffic. The processes can be easily and rapidly captured in a graphical manner and enforced together with rules pertaining to assignments that need to be performed. Aside from boosting productivity, TieFlow also reduces organizational costs and errors. TieFlow was developed with Small Business Innovation Research (SBIR) assistance from Johnson. The SBIR support entitles all Federal Government agencies to utilize the TieFlow software technology free of charge. Tietronix emphasizes that TieFlow is an outstanding workflow resource that could produce dramatic productivity and cost improvements for all agencies, just as it has done and continues to do for NASA. The Space Agency is currently using the software throughout several mission-critical offices, including the Mission Operations Directorate and the Flight Director s Office, for worldwide participation of authorized users in NASA processes. At the Flight Director s Office, TieFlow allows personnel to electronically submit and review changes to the flight rules carried out during missions.

Source record↗

NASA NTRS2013

Computational Fluid Dynamics Uncertainty Analysis Applied to Heat Transfer over a Flat Plate

There have been few discussions on using Computational Fluid Dynamics (CFD) without experimental validation. Pairing experimental data, uncertainty analysis, and analytical predictions provides a comprehensive approach to verification and is the current state of the art. With pressed budgets, collecting experimental data is rare or non-existent. This paper investigates and proposes a method to perform CFD uncertainty analysis only from computational data. The method uses current CFD uncertainty techniques coupled with the Student-T distribution to predict the heat transfer coefficient over a at plate. The inputs to the CFD model are varied from a specified tolerance or bias error and the difference in the results are used to estimate the uncertainty. The variation in each input is ranked from least to greatest to determine the order of importance. The results are compared to heat transfer correlations and conclusions drawn about the feasibility of using CFD without experimental data. The results provide a tactic to analytically estimate the uncertainty in a CFD model when experimental data is unavailable

Computational↗

DOE OSTI2019

On the surface energy balance closure at different temporal scales

Measurements of the surface energy fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made in the Columbia River Basin (Oregon) in an area of complex terrain during a 10-month long portion of the second Wind Forecast Improvement Project (WFIP 2) field campaign are used to study the surface energy budget (SEB) and surface fluxes over different temporal scales. This study analyzes and discusses SEB closure based on half-hourly, daily, monthly, seasonal, and sub-annual (~10-month) temporal averages. The data were collected over all four seasons for different states of the underlying ground surface (dry, wet, and frozen). Our half-hourly direct measurements of energy balance show that the sum of the turbulent sensible and latent heat fluxes systematically underestimate positive net radiation by around 20–30% during daytime and overestimate negative net radiation at night. This imbalance of the surface energy budget is comparable to other terrestrial sites. However, on average, the residual energy imbalance is significantly reduced at daily, weekly, and monthly averaging timescales, and moreover, the SEB can be closed for this site within reasonable limits on seasonal and sub-annual timescales (311-day averaging for the entire field campaign dataset). Increasing the averaging time to daily and longer time intervals substantially reduces the ground heat flux and storage terms, because energy locally entering the soil, air column, and vegetation in the morning is released in the afternoon and evening. Averaging on daily to sub-annual timescales also reduces random instrumental measurement errors and other uncertainties as well as smooths out a hysteresis effect (phase lag) in the SEB relationship between different components. This study shows that SEB closure is better for dry soils compared to wet soils and the statistical dependence of the turbulent fluxes and net radiation for freezing soil surfaces appears weak, if not non-existent, apparently due to lack of the latent heat of fusion term in the traditional SEB equation.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1983

Accuracy and resolution of Earth Radiation Budget Estimates

A numerical filter inversion technique that reduces wide-angle satellite measurements to top-of-the-atmosphere radiant exitances has been proposed for the Earth Radiation Budget Experiment (ERBE). The matrix formulation of this technique is presented, and the design of the numerical filter is discussed. The filter is smoothed with a singular value decomposition. The inversion process is simulated by generating synthetic measurements from a 24 degree spherical harmonic radiation field derived from Nimbus 6 ERB data. The numerical filter is applied to these measurements after they are corrupted with instrument error. The results are curves of expected error versus resolution area.

Green, R. N.↗

NASA NTRS1990

The need for a hypersonic demonstrator

The requirement for research aircraft and demonstrator vehicles has been seriously challenged by tight budgets and erroneous impressions that aeronautical technology has matured to a point where the value added by flight research and/or demonstration is not sufficient to offset the costs. While this issue may be debatable with respect to subsonic/transonic speeds, such is not the case for high-speed (supersonic and hypersonic) operation. The aerodynamic performance, weight/payload fractions, and thermodynamic problems are such that small margins of error can be tantamount to the vehicle being unable to reach its design point or so inefficient as to render it useless. This paper addresses some of the critical design considerations and operational constraints which make it mandatory to carry out flight research and develop a demonstrator vehicle in order that the risks be reduced to an acceptable level to assure technology readiness for viable hypersonic flight.

Ayers, T. G.↗

DOE OSTI2024

Assessing the design of integrated methane sensing networks

Abstract While methane is the second largest contributor to global warming after carbon dioxide, it has a larger warming effect over a much shorter lifetime. Despite accelerated technological efforts to radically reduce global carbon dioxide emissions, rapid reductions in methane emissions are needed to limit near-term warming. Being primarily emitted as a byproduct from agricultural activities and energy extraction, methane is currently monitored via bottom–up (i.e. activity level) or top–down (via airborne or satellite retrievals) approaches. However, significant methane leaks remain undetected and emission rates are challenging to characterize with current monitoring frameworks. In this paper, we study the design of a layered monitoring approach that combines bottom–up and top–down approaches as an integrated sensing network. By recognizing that varying meteorological conditions and emission rates impact the efficacy of bottom–up monitoring, we develop a probabilistic approach to optimal sensor placement in its bottom–up network. Subsequently, we derive an inverse Bayesian framework to quantify the improvement that a design-optimized integrated framework has on emission-rate quantifications and their uncertainties. We find that under realistic meteorological conditions, the overall error in estimating the true emission rates is approximately 1.3 times higher, with their uncertainties being approximately 2.4 times higher, when using a randomized network over an optimized network, highlighting the importance of optimizing the design of integrated methane sensing networks. Further, we find that optimized networks can improve scenario coverage fractions by more than a factor of 2 over experimentally-studied networks, and identify a budget threshold beyond which the rate of optimized-network coverage improvement exhibits diminishing returns, suggesting that strategic sensor placement is also crucial for maximizing network efficiency.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Optimal Client Sampling in Federated Learning with Client-level Heterogeneous Differential Privacy

Federated Learning with client-level differential privacy (DP) provides a promising framework for collaboratively training models while rigorously protecting clients’ privacy. However, classic approaches like DP-FedAvg struggle when clients have heterogeneous privacy requirements, as they must uniformly enforce the strictest privacy level across all clients, leading to excessive DP noise and significant degradation in model utility. Existing methods to improve the model utility in such heterogeneous privacy settings often assume a trusted server and are largely heuristic, resulting in suboptimal performance and lacking strong theoretical foundations. Here, in this work, we address these challenges under a practical attack model where both clients and the server are honest-but-curious. We propose GDPFed, which partitions clients into groups based on their privacy budgets and achieves client-level DP within each group to reduce the privacy budget waste and hence improve the model utility. Based on the privacy and convergence analysis of GDPFed, we find that the magnitude of DP noise depends on both model dimensionality and the per-group client sampling ratios. To further improve the performance of GDPFed, we introduce GDPFed+, which integrates model sparsification to eliminate unnecessary noise and optimizes per-group client sampling ratios to minimize convergence error. Extensive empirical evaluations on multiple benchmark datasets demonstrate the effectiveness of GDPFed+, showing substantial performance gains compared with state-of-the-art methods.

Xu, Jiahao [Univ. of Nevada, Reno, NV (United Stat↗

DOE OSTI2021

Adaptive resource allocation for surrogate modeling of systems comprised of multiple disciplines with varying fidelity

We present an adaptive algorithm for constructing surrogate models for integrated systems composed of a set of coupled components. With this goal we introduce ‘coupling’ variables with a priori unknown distributions that allow approximations of each component to be built independently. Once built, the surrogates of the components are combined and used to predict system-level quantities of interest (QoI) at a fraction of the cost of interrogating the full system model. We use a greedy experimental design procedure, based upon a modification of Multi-Index Stochastic Collocation (MISC), to minimize the error of the combined surrogate. This is achieved by refining each component surrogate in accordance with its relative contribution to error in the approximation of the system-level QoI. Our adaptation of MISC is a multi-fidelity procedure that can leverage ensembles of models of varying cost and accuracy, for one or more components, to produce estimates of system-level QoI. Several numerical examples demonstrate the efficacy of the proposed approach on systems involving feed-forward and feedback coupling. For a fixed computational budget, the proposed algorithm is able to produce approximations that are orders of magnitude more accurate than approximations that treat the integrated system as a black-box.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2004

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.

Hou, Arthur Y.↗

DOE OSTI2022

Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations

Optimal experimental design (OED) is the general formalism of sensor placement and decisions on the data collection strategy for engineered or natural experiments. This problem is prevalent in many critical fields such as battery design, numerical weather prediction, geosciences, environmental and urban studies. State-of-the-art computational methods for experimental design do not accommodate correlation structure in observational errors produced by many expensive-to-operate devices such as X-ray machines, radars, and satellites. Discarding evident data correlations leads to biased results, higher expenses, and waste of valuable resources. We present a general formulation of the OED formalism for model-constrained large-scale Bayesian linear inverse problems, where measurement errors are generally correlated. The proposed approach utilizes the Hadamard product of matrices to formulate the weighted-likelihood, and is valid for both finite as well as infinite-dimensional Bayesian inverse problems. Extensive numerical experiments are carried out for empirical verification of the proposed approach using an advection-diffusion model, where the objective is to optimally place a small set of sensors, under a limited budget, to predict the concentration of a contaminant in a closed and bounded domain.

Correlated observations↗

DOE OSTI2017

Searching for Interstellar C{sub 60}{sup +} Using a New Method for High Signal-to-noise HST/STIS Spectroscopy

Due to recent advances in laboratory spectroscopy, the first optical detection of a very large molecule has been claimed in the diffuse interstellar medium (ISM): C{sub 60}{sup +} (ionized Buckminsterfullerene). Confirming the presence of this molecule would have significant implications regarding the carbon budget and chemical complexity of the ISM. Here we present results from a new method for ultra-high signal-to-noise ratio (S/N) spectroscopy of background stars in the near-infrared (at wavelengths of 0.9–1 μm), using the Hubble Space Telescope (HST) Imaging Spectrograph (STIS) in a previously untested “STIS scan” mode. The use of HST provides the crucial benefit of eliminating the need for error-prone telluric-correction methods in the part of the spectrum where the C{sub 60}{sup +} bands lie and where the terrestrial water vapor contamination is severe. Our STIS spectrum of the heavily reddened B0 supergiant star BD+63 1964 reaches an unprecedented S/N for this instrument (∼600–800), allowing the detection of the diffuse interstellar band (DIB) at 9577 Å attributed to C{sub 60}{sup +}, as well as new DIBs in the near-IR. Unfortunately, the presence of overlapping stellar lines, and the unexpected weakness of the C{sub 60}{sup +} bands in this sightline, prevents conclusive detection of the weaker C{sub 60}{sup +} bands. A probable correlation between the 9577 Å DIB strength and interstellar radiation field is identified, which suggests that more strongly irradiated interstellar sightlines will provide the optimal targets for future C{sub 60}{sup +} searches.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1976

A simulation study of earth radiation budget data interpretation

The paper describes a simulation of a filtering analysis which yields radiation distributions, measured by a wide-field-of-view radiometer on board an earth satellite, on a scale smaller than the field of view of the instrument. Mathematical models are developed to represent an orbiting wide-field-of-view radiometer to provide simulated measurement data. The simulated measurements are analyzed by a data inversion technique to obtain estimates of the radiation heat fluxes at the top of the atmosphere. By comparing the estimated field to a real radiation field, the effects of directional model errors and sampling strategies are revealed.

Smith, G. L.↗

NASA NTRS1995

Assessment of the global monthly mean surface insolation estimated from satellite measurements using global energy balance archive data

Global sets of surface radiation budget (SRB) have been obtained from satellite programs. These satellite-based estimates need validation with ground-truth observations. This study validates the estimates of monthly mean surface insolation contained in two satellite-based SRB datasets with the surface measurements made at worldwide radiation stations from the Global Energy Balance Archive (GEBA). One dataset was developed from the Earth Radiation Budget Experiment (ERBE) using the algorithm of Li et al. (ERBE/SRB), and the other from the International Satellite Cloud Climatology Project (ISCCP) using the algorithm of Pinker and Laszlo and that of Staylor (GEWEX/SRB). Since the ERBE/SRB data contain the surface net solar radiation only, the values of surface insolation were derived by making use of the surface albedo data contained GEWEX/SRB product. The resulting surface insolation has a bias error near zero and a root-mean-square error (RMSE) between 8 and 28 W/sq m. The RMSE is mainly associated with poor representation of surface observations within a grid cell. When the number of surface observations are sufficient, the random error is estimated to be about 5 W/sq m with present satellite-based estimates. In addition to demonstrating the strength of the retrieving method, the small random error demonstrates how well the ERBE derives from the monthly mean fluxes at the top of the atmosphere (TOA). A larger scatter is found for the comparison of transmissivity than for that of insolation. Month to month comparison of insolation reveals a weak seasonal trend in bias error with an amplitude of about 3 W/sq m. As for the insolation data from the GEWEX/SRB, larger bias errors of 5-10 W/sq m are evident with stronger seasonal trends and almost identical RMSEs.

Li, Zhanqing↗

NASA NTRS1984

Nimbus-Earth radiation budget instrument analysis

The Wide Field Of View (WFOV) Earth Flux Channels of the Nimbus Earth Radiation Budget (ERB) instrument are studied with the objective of improving the understanding and confidence in the data. Laboratory tests on flight space Earth flux subassemblies followed by a set of in flight verification procedures are examined to see if the laboratory derived correction factors produced consistent results. Intercomparisons between the WFOV data and integrated scanner data as well as other truth are used in these verificaton procedures. The main source of errors are temperature and temperature gradient related offsets. The findings led to construction of a model for the short wave WFOV channel which use instrument temperatures and temperature differences to predict or establish offsets which need to be applied to data reduction algorithms for maximum final data product accuracy.

Maschhoff, R. M.↗

NASA NTRS1988

High-resolution Interferometer Sounder (HIS), phase 2

The High-resolution Interferometer Sounder (HIS) was successfully built, tested, and flight proven on the NASA U-2/ER-2 high altitude aircraft. The HIS demonstration has shown that, by using the technology of Fourier Transform Spectroscopy (FTS), it is possible to measure the spectrum of upwelling infrared radiance needed for temperature and humidity sounding with high spectral resolution and high radiometric precision. By resolving individual carbon dioxide lines, the retrieved temperature profiles have vertical resolutions of 1 to 2 km and RMS errors less than 1 C, about 2 to 4 times better than possible with current sounders. Implementing this capability on satellite sounders will greatly enhance the dynamical information content of temperature measurements from space. The aircraft model HIS is now a resource which should be used to support field experiments in mesoscale meteorology, to monitor trace gas concentrations and to better understand their effects on climate, to monitor the surface radiation budget and the radiative effects of clouds, and to collect data for research into retrieval techniques, especially under partially cloudy conditions.

Source record↗

NASA NTRS1995

Remote sounding of surface radiative fluxes in cirrus cloudy conditions

It has been long recognized that radiation and radiation perturbations play a critical role in the climate system. Surface radiative fluxes are useful parameters for monitoring global change, for understanding of the effects of clouds on the radiation field, and for improving parameterization of surface sensible and latent heat fluxes. Monitoring of the radiation budget at the top of the atmosphere has been one of the prime satellite programs for the last 30 years. However, monitoring radiative fluxes at the surface over the globe from space cannot be performed in a direct way at the present time. In particular, since clouds are the prime regulators of the radiative fluxes, uncertainties in the retrieved cloud parameters, which are inputs to radiative transfer models, can introduce significant errors in the computed radiative fluxes. Thus, remote sounding of surface radiative fluxes in cloudy conditions requires the development of both satellite cloud retrieval scheme and radiation models. In this paper, we present results of computed surface radiative fluxes in cirrus cloudy conditions using a cirrus cloud retrieval scheme and a detailed radiative transfer program. Comparisons have been made between the computed surface radiative fluxes and the ground-based radiometer measurements obtained during FIRE-II-IFO, which was carried out near Coffeyville, Kansas, during November and December, 1991.

Ou, S. C.↗

NASA NTRS2005

Interannual Variability in Surface LW Fluxes Over the Tropical Oceans As Seen in ISCCP-FD and GEWEX SRB Data Sets

One notable aspect of Earth s climate is that although the planet appears to be very close to radiative balance at top-of-atmosphere (TOA), the atmosphere itself and underlying surface are not. Profound exchanges of energy between the atmosphere and oceans, land and cryosphere occur over a range of time scales. Recent evidence from broadband satellite measurements suggests that even these TOA fluxes contain some detectable variations. Our ability to measure and reconstruct radiative fluxes at the surface and at the top of atmosphere is improving rapidly. In this work we will evaluate two recently released estimates of radiative fluxes, focusing primarily on surface estimates. The International Satellite Cloud Climatology Project FD radiative flux profiles are available from mid-1 983 to near present and have been constructed by driving the radiative transfer physics from the Goddard Institute for Space Studies (GISS) global model with ISCCP clouds and TOVS (TIROS Operational Vertical Sounder)thermodynamic profiles. Fu!l and clear sky SW and LW fluxes are produced. A similar product from the NASA/GEWEX Surface Radiation Budget Project using different radiative flux codes and thermodynamics from the NAS/Goddard Earth Observing System (GEOS-1) assimilation model makes a similar calculation of surface fluxes. However this data set currently extends only through 1995. Significant differences in both interannual variability as well as trends are found between among these data sets. For radiative fluxes these differences are traced to TOVS thermodynamic soundings used to drive the ISCCP-FD calculations. Errors in near surface temperature and precipitable water cascade into ISCCP upward and downward IR flux components, demonstrably affecting interannual variability. Revised estimates of clear-sky fluxes over ocean are made using statistical algorithms and water vapor from the (SSM/I) Special Sensor Microwave Imager. These calculations show strong near-surface water vapor feedback over the tropical oceans in association with SST changes. However, it is also shown that ISCCP longwave cloud forcing, common to both the ISCCP-FD and GEWEX SRB retrievals, is the main driver of a long-term decrease in net LW flux to the surface during the near-20 year period covered by these revised estimates.

Robertson, F. R.↗

NASA NTRS1992

Seasonal variation of surface radiation budget derived from International Satellite Cloud Climatology Project C1 data

Surface radiation budget data are presented for the midseasonal months of July and October of 1983 and January and April of 1984. These data allow the examination of geographical and seasonal variations of the entire surface radiation budget from pole to pole. The latest flux estimation techniques have been used along with data from the International Satellite Cloud Climatology Project and the Earth Radiation Budget Experiment. Regional, zonal, and hemispheric distributions of the downward and net components of both shortwave and longwave fluxes and of the net total surface fluxes are determined. Seasonal flux variation per region, expressed as flux range, is illustrated for these components also. The estimated fluxes appear to be accurate to about 16 W/sq m on a global average, based on sensitivity analyses and comparisons with ground data. An analysis of flux errors showed that most of the error was attributable to errors in input data.

Darnell, Wayne L.↗