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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Sensitivity of surface radiative fluxes to meteorological parameter errors

A parameterized radiative transfer model is employed to estimate longwave fluxes, while shortwave fluxes are estimated with a broadband absorption and scattering technique. Meteorological parameters of surface radiative fluxes are the profiles of temperature and cloud cover, ozone, water vapor and aerosols. A sensitivity study is presented to estimate the magnitudes of biases in the computed fluxes resulting from the biases in the satellite meteorological data.

Ritchey, Nancy A.↗
NASA NTRS2000

Raman Lidar Measurements of Water Vapor and Cirrus Clouds During The Passage of Hurricane Bonnie

The NASA/GSFC Scanning Raman Lidar (SRL) was stationed on Andros Island in the Bahamas during August - September, 1998 as a part of the third Convection and Moisture Experiment (CAMEX-3) which focussed on hurricane development and tracking. During the period August 21 - 24, hurricane Bonnie passed near Andros Island and influenced the water vapor and cirrus cloud measurements acquired by the SRL. Two drying signatures related to the hurricane were recorded by the SRL and other sensors. Cirrus cloud optical depths (at 351 nm) were also measured during this period. Optical depth values ranged from less than 0.01 to 1.5. The influence of multiple scattering on these optical depth measurements was studied. A correction technique is presented which minimizes the influences of multiple scattering and derives information about cirrus cloud optical and physical properties. The UV/IR cirrus cloud optical depth ratio was estimated based on a comparison of lidar and GOES measurements. Simple radiative transfer model calculations compared with GOES satellite brightness temperatures indicate that satellite radiances are significantly affected by the presence of cirrus clouds if IR optical depths are approximately 0.005 or greater. Using the ISCCP detection threshold for cirrus clouds on the GOES data presented here, a high bias of up to 40% in the GOES precipitable water retrieval was found.

Whiteman, D. N.↗
NASA NTRS2000

Status of TRMM Monthly Estimates of Tropical Precipitation

Nearly three years of Tropical Rainfall Measuring Mission Satellite (TRMM Satellite) monthly estimates of tropical surface rainfall are analyzed to document and understand the differences among the TRMM-based estimates and how these differences relate to the pre-TRMM estimates and current operational analyses. Variation among the TRMM estimates is shown to be considerably smaller than among a pre-TRMM collection of passive microwave-based products. Use of both passive and active microwave techniques in TRMM should lead to increased confidence in converged estimates. Current TRMM estimates are shown to have a range of about 20% for the tropical ocean as a whole, with variations in heavily raining ocean areas of the ITCZ and SPCZ having differences over 30%. In mid-latitude ocean areas the differences are smaller. Over land there is a distinct difference between the tropics and mid-latitude with a reversal between some of the products as to which tends to be relatively high or low. Comparisons of TRMM estimates with ocean atoll and land gauge information point to products that might have significant regional biases. The radar-based product is significantly low biased compared with atoll raingauge data, while the passive microwave product is significantly high compared to raingauge data in the deep tropics. The evolution of rainfall patterns during the recent change from intense El Nino to a long period of La Nina and then a gradual return to near neutral conditions is described using TRMM. The time history of integrated rainfall over the tropical oceans (and land) during this period differs among the passive and active microwave TRMM estimates.

Adler, Robert F.↗
NASA NTRS2003

Definition of International GPM GV Research Program

The Global Precipitation Measurement (GPM) Mission will consist of a constellation of rain-measuring satellites, the main member of which (the core satellite) will serve as the measurement reference to the other members of the constellation. The core satellite is being developed jointly by the National Aeronautics and Space Administration (NASA) and the newly-named Japan Aerospace Exploration Agency (JAXA -- previously NASDA) along with its government partner, the Communications Research Laboratory (CRL). The GPM mission was proposed as a follow-up mission to the Tropical Rainfall Measuring Mission (TRMM) by both NASA and NASDA based on the unparalleled scientific success of TRMM, and has recently been joined by the European Space Agency (ESA) via its formulation of the European GPM mission (i.e., EGPM). GPM is an ambitious mission designed to produce accurate and frequent global observations of precipitation (both rain and snow) made possible by replacing the TRMM satellite with the new core satellite carrying an advanced radar-radiometer system, and serving as the centerpiece for the constellation of some eight (8) additional satellites being provided through international cooperation. The core satellite is to be flown up to high latitudes (inclined some 65-70 degrees), and will carry a Ku/Ka-band, nadir-scanning, dual-frequency precipitation radar (DPR) that is being developed by JAXA and CRL, along with a large aperture, extended frequency-range, conically-scanning passive microwave radiometer being developed by NASA and its industrial partners. Each constellation satellite will also carry some type of multi-channel passive microwave radiometer (as well as a multi-beam Ka-band radar in the case of EGPM) whose rain estimates will be calibrated and referenced to those made by the core satellite, producing for the first time fully-global, continuous, and bias-free precipitation datasets. GPM data will be delivered in near-realtime, taking a major step toward the operational use of precipitation information for model initialization and data assimilation in a number of application areas such as hazardous weather forecasting, flood warning, fresh water resource assessment, and crop growth prediction. In addition, GPM data will complement the now-existing global temperature record, allowing for improved assessments of climate change, particularly those processes in which the global water cycle both forces and responds to climatic drifts in global temperature conditions. A foremost element of this international constellation mission is a parallel international ground validation (GV) network. This GV network is needed to determine uncertainties in the rain retrievals, critical for application of the retrieval information in weather and hydrometeorological modeling and climate diagnostics, as well as assurances that the satellite retrievals of surface rainfall are consistent with those actually measured at the surface. The key aspects of this network is that it must be worldwide and created through the GPM partnership process. Therefore the network will consist of a confederation of government agencies, academic organizations, private institutions, and individual scientists from a collection of nations who have initiated the process by gathering in Abingdon to develop the fundamentals of the international GPM GV research programme. Therefore in keeping with our responsibilities as the front-runners of the programme, the main objectives of this workshop are: (1) to present and share opinions on interests, perspectives, and concerns about GPM GV research; (2) to examine the conceptual and/or planned GPM GV site templates from NASA, NASDA, ESA, and other partners; (3) to define the main scientific objectives of the international GPM GV research programme; (4) to formulate a preliminary set of international GPM GV science and measurement requirements; and (5) to convene a Steering Committee to aid the organization of the GPM GV program, to document its science implementation plans, and to aid planning for follow-up GPM GV meetings.

Smith, Eric A.↗
NASA NTRS2003

Research on TRMM and GPM Through Collaboration Between JAXA & NASA

The Japan Aerospace Exploration Agency (JAXA) is conducting joint research with the Communications Research Laboratory (CRL) and the National Aeronautics and Space Administration (NASA) on a new constellation satellite observation project called Global Precipitation Measurement (GPM), the main satellite of which is planned for launch in 2008 by JAXA. This GPM project was proposed as a follow-up mission to the Tropical Rainfall Measuring Mission (TRMM) by both the Japanese and American sides based on the unparalleled scientific success of TRMM. A major reason for TRMM's success was the use of the worlds first spaceborne rain radar, the Precipitation Radar (PR) system developed by the National Space Development Agency of Japan (NASDA, now JAXA) and CRL. Measurements from this instrument have ushered in many new scientific findings and have opened a new era of precipitation measuring from space. GPM is an ambitious project which will produce accurate and frequent global observations of precipitation (both rain and snow) made possible by replacing TRMM with a new core satellite carrying an advanced radar-radiometer system, and serving as the centerpiece for a constellation of some eight (8) additional satellites being provided through international cooperation. The core satellite is to be flown up to high latitudes (inclined some 65-70 degrees), and will carry a dual-frequency precipitation radar (DPR) that will be newly developed by JAXA and CRL, along with a large aperture, extended frequency-range passive microwave radiometer being provided by NASA. Each constellation satellite will also carry some type of multi-channel passive microwave radiometer whose rain estimates will be calibrated and referenced to those made by the core satellite, producing for the first time fully-global, continuous, and bias-free precipitation datasets. GPM data will be delivered in near-realtime, taking a major step toward the operational use of precipitation information for model initialization and data assimilation in a number of application areas such as hazardous weather forecasting, flood warning, fresh water resource assessment, and crop growth prediction. In addition, GPM data will complement the now-existing global temperature record, allowing for improved assessments of climate change, particularly those processes in which the global water cycle both forces and responds to climatic drifts in global temperature conditions.

Smith, Eric A.↗
NASA NTRS2016

The Psychology of Cost Estimating

Cost estimation for large (and even not so large) government programs is a challenge. The number and magnitude of cost overruns associated with large Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) programs highlight the difficulties in developing and promulgating accurate cost estimates. These overruns can be the result of inadequate technology readiness or requirements definition, the whims of politicians or government bureaucrats, or even as failures of the cost estimating profession itself. However, there may be another reason for cost overruns that is right in front of us, but only recently have we begun to grasp it: the fact that cost estimators and their customers are human. The last 70+ years of research into human psychology and behavioral economics have yielded amazing findings into how we humans process and use information to make judgments and decisions. What these scientists have uncovered is surprising: humans are often irrational and illogical beings, making decisions based on factors such as emotion and perception, rather than facts and data. These built-in biases to our thinking directly affect how we develop our cost estimates and how those cost estimates are used. We cost estimators can use this knowledge of biases to improve our cost estimates and also to improve how we communicate and work with our customers. By understanding how our customers think, and more importantly, why they think the way they do, we can have more productive relationships and greater influence. By using psychology to our advantage, we can more effectively help the decision maker and our organizations make fact-based decisions.

Price, Andy↗
NASA NTRS2017

Flowing Plasma Interaction with an Electric Sail Tether Element

Electric sails are a relatively new concept for providing high speed propellant-less propulsion. Employing multiple tethers biased to high positive voltage levels (kV), electric sails are designed to gain momentum from the solar wind by repelling solar wind protons. To maximize the area of the sail that interacts with the solar wind, electric sails rely on the formation of a large plasma sheath around each small diameter tether. Motivated by interest in advancing the development of electric sails, a set of laboratory tests has been conducted to study the interaction of a drifting plasma with a sheath formed around a small diameter tether element biased at positive voltages. The laboratory test setup was created with Debye length scaling in mind to offer a path to extrapolate (via modeling) to full scale electric sail missions. Using an instrument known as a Differential Ion Flux Probe (DIFP) the interaction between a positively biased tether element and a drifting plasma has been measured for several scenarios. Clear evidence of the tether element sheath deflecting ions has been obtained. Maps of the flow angle downstream from the tether element have been made and they show the influence of the plasma sheath. Finally, electron current collection measurements have been made for a wide range of plasma conditions and tether element bias voltages. The electron collection data will have an impact on electric sail power requirements, as high voltage power supplies and electron guns will have to be sized to accommodate the electron currents collected by each tether.

Schneider, Todd↗
NASA NTRSDate not supplied

TPSAS-NF1676L-33912-DND

The agricultural, renewable energy management, and science communities need global surface and top-of-atmosphere (TOA) radiative fluxes on a near real-time basis for uses such as building energy performance monitoring and seasonal crop yield modeling. The Clouds and Earth's Radiant Energy System (CERES) FLASHFlux (Fast Longwave and SHortwave radiative Flux) data products address this need by enhancing the speed of CERES processing using simplified calibration, averaging techniques and fast radiation parameterizations to produce global fluxes within a week of satellite observations. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Aqua and Terra observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1degree x 1degree gridded data that combines Aqua and Terra observations. The CERES FLASHFlux Version4A includes an update to process MODIS Collection 6.1 in an improved cloud retrieval algorithm, and an update to the CERES Edition 4 angular distribution models. We inter-compared FLASHFlux Version4A, FLASHFlux Version3C, and CERES EBAF (Energy Balanced and Filled) Top-of-Atmosphere fluxes to evaluate these improvements. We also compare both SSF overpass and TISA radiative flux products to a set of surface measurement sites that are globally distributed and assess agreement. FLASHFlux TISA and CERES EBAF are used in the analysis of TOA anomalies for the annual State of Climate report. This also poster highlights the methodology use to merge the two data products by correcting the bias in FLASHFlux TISA and inter-calibrate to CERES EBAF.

Parnchai K Sawaengphokhai↗
NASA NTRS2019

A TID and SEE Characterization of Multi-Terabit COTS 3D NAND Flash

Single-event effects and total ionizing dose testing are described for a 32-layer NAND flash memory, in both SLC and MLC configurations, with special considerations for unique three-dimensional test results. Extraction of three-dimensional heavy-ion test data presents a unique visualization of angular effects in NAND flash. Pattern dependence differences between SLC and MLC mode are noted, along with slightly non-uniform angular cross-section results due to the complex volume. Finally, TID data under different operating and bias conditions shows that the failure point remains the higher-voltage erasure circuitry.

Flash Memory↗
DOE OSTI2020

Estimating Subhourly Inverter Clipping Loss From Satellite-Derived Irradiance Data: Preprint

Photovoltaic system production simulations are conventionally run using hourly weather datasets. Hourly simulations are sufficiently accurate to predict the majority of long-term system behavior but cannot resolve high-frequency effects like inverter clipping caused by short-duration irradiance variability. Direct modeling of this subhourly clipping error is only possible for the few locations with high-resolution irradiance datasets. This paper describes a method of predicting the magnitude of this error using a machine learning model and 30-minute satellite irradiance data. The method predicts a correction for each 30-minute interval with the potential to roll up into 60-minute corrections to match an hourly energy model. The model is trained and validated at locations where the error can be directly simulated from 1-minute ground data. The validation shows low bias at most ground station locations. The model is also applied to gridded satellite irradiance to produce a heatmap of the estimated clipping error across the United States. Finally, the relative importance of each predictor satellite variable is retrieved from the model and discussed.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Metals and methylotrophy: Via global gene expression studies

A number of minerals, such as copper, cobalt, and rare earth elements (REE), are essential modulators of microbial one carbon metabolism. This chapter provides an overview of the gene expression study design and analysis protocols for uncovering REE-induced changes in methylotrophic bacteria. By interrogating relationships and differences in total gene expression induced by mineral micronutrients, a deeper understanding of gene regulation at a systems scale can be gained. With careful design and execution of RNA-sequencing experiments, thorough processing and assessment of read quality can be utilized to assess and adjust for possible biases. By ensuring only quality data are utilized in downstream processes, differential gene expression, overrepresented analyses, and gene-set enrichment analyses provide reliable and reproducible representation of pathways and functions which are being affected by changes in environmental conditions.

Johnson, Zachary J.↗
DOE OSTI2025

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

Ntampaka, Michelle [Baltimore, Space Telescope Sci↗
DOE OSTI2025

Soft-hard framework with exact four-momentum conservation for small systems

A new framework, called x-scape, for the combined study of both hard and soft transverse momentum sectors in high-energy proton-proton (𝑝−𝑝) and proton-nucleus (𝑝−𝐴) collisions is set up. A dynamical initial state is set up using the 3d-Glauber model with transverse locations of hotspots within each incoming nucleon. A hard scattering that emanates from two colliding hotspots is carried out using the Pythia generator. Initial state radiation from the incoming hard partons is carried out in a new module called I-matter, which includes the longitudinal location of initial splits. The energy-momentum of both the initial hard partons and their associated beam remnants is removed from the hot spots, depleting the energy-momentum available for the formation of the bulk medium. Outgoing showers are simulated using the matter generator, and results are presented for both cases, allowing for and not allowing for energy loss. First comparisons between this hard-soft model and single inclusive hadron and jet data from 𝑝−𝑝 and minimum bias 𝑝−Pb collisions are presented. Single hadron spectra in 𝑝−𝑝 are used to carry out a limited (in number of parameters) Bayesian calibration of the model. Fair comparisons with data are indicative of the utility of this new framework. Theoretical studies of the correlation between jet 𝑝 𝑇 and event activity at mid and forward rapidity are carried out.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bia. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Ref. [2]. The prerequisite for applying machine learning techniques is casting the metadata into a format that can be parsed by the algorithm. This step might seem trivial but requires to find a unique language where metadata that carry the same physics meaning across several experiments must have the same identifier. One example is, for instance, the neutron detector. As seen in Figure 1, the machine learning code identified the use of 6 Li detectors as being related to bias in some datasets of the AIACHNE 252 Cf PFNS experimental database. In fact, here are several experiments that used neutron detectors containing 6Li in the database, for instance for the example below. EXFOR format has a unique keywords describing detectors such as “SCIN” or “GLASD”. One may think that these keywords are already sufficient descriptors for ML to uniquely find an issue. However, “SCIN” (used for [3, 4]) and “GLASD” (used for [5]) fail to inform the algorithm what is the active material in the detector. And, the key common issue leading to bias in 252 Cf related to neutron detectors is not whether it is a glass detector or a scintillator. No, the issue is that 6 Li was within both detector types and that even small mistakes in the detector response functions around approximately 200 keV are amplified by the 6 Li(n,α) resonance there leading to bias in data as highlighted in Fig. 1 and Ref. [1]. Hence, the features describing the neutron detector must call out the active material in the detector, rather than the existing EXFOR detector keyword, that the ML algorithm can find physically meaningful features related to bias. The AIACHNE team used a precursor of the WPEC (Working Party on International Nuclear Data Evaluation Co-operation) SG(Subgroup)-50 format to store the metadata for the ML analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2012

An Alternative Inter-Satellite Calibration of the UMD HIRS OLR Retrievals

Outgoing Longwave Radiation (OLR) at the top-of-atmosphere (TOA) is a fundamental component of Earth's energy balance and represents the heat energy in the thermal bands rejected to space by the planet. Determination of OLR from satellites has a long and storied history, but the observational record remains largely fragmented with gaps in satellite measurements over the past three decades. Perhaps the most semi-continuous set of retrievals comes from the University of Maryland (UMD) algorithm that uses four HIRS (High Resolution Infrared Sounder) channels on the NOAA polar orbiting satellites to estimate OLR. This data set shows great promise in helping to bridge the discontinuous ERBS (Earth Radiation Budget Satellite) and CERES (Clouds and the Earth s Radiant Energy System) measurements. However, significant satellite inter-calibration biases persist with the present UMD data, principally outside the tropics. Difficulties relate to the combination of drift of the satellite equator crossing time through the diurnal cycle and changes in HIRS channel response function design. Here we show how an ad hoc recalibration of the UMD retrievals among the different satellites removes much of the remaining uncertainty due to diurnal drift of the satellite orbit. The adjusted HIRS data (using no other external information) show much better agreement with OLR from the European Center Interim Reanalysis (EC-Int), longer-term signals in the Global Energy and Water Cycle Experiment / Surface Radiation Budget (GEWEX/SRB) retrievals, and also agree well with ERBS and CERES OLR measurements. These results augur well for narrowing the uncertainties in multi-decadal estimates of this important climate variable.

Robertson, Franklin R.↗
NASA NTRS1999

Validation of the Land-Surface Energy Budget and Planetary Boundary Layer for Several Intensive field Experiments

Land-surface processes in a data assimilation system influence the lower troposphere and must be properly represented. With the recent incorporation of the Mosaic Land-surface Model (LSM) into the GEOS Data Assimilation System (DAS), the detailed land-surface processes require strict validation. While global data sources can identify large-scale systematic biases at the monthly timescale, the diurnal cycle is difficult to validate. Moreover, global data sets rarely include variables such as evaporation, sensible heat and soil water. Intensive field experiments, on the other hand, can provide high temporal resolution energy budget and vertical profile data for sufficiently long periods, without global coverage. Here, we evaluate the GEOS DAS against several intensive field experiments. The field experiments are First ISLSCP Field Experiment (FIFE, Kansas, summer 1987), Cabauw (as used in PILPS, Netherlands, summer 1987), Atmospheric Radiation Measurement (ARM, Southern Great Plains, winter and summer 1998) and the Surface Heat Budget of the Arctic Ocean (SHEBA, Arctic ice sheet, winter and summer 1998). The sites provide complete surface energy budget data for periods of at least one year, and some periods of vertical profiles. This comparison provides a detailed validation of the Mosaic LSM within the GEOS DAS for a variety of climatologic and geographic conditions.

Bosilovich, Michael G.↗
NASA NTRS1994

Comparison of TOPEX/POSEIDON sigma(sub 0) and significant wave height distributions to Geosat

Monthly Ku band sigma(sub 0) and significant wave height (SWH) histograms from the NASA altimeter on the TOPEX/POSEIDON satellite are preseneted for January through June 1993 for three latitude bands between +/- 60 degrees. The data are compared to distributions from the Geosat mission for the same months in 1987-1989. Generally, the distributions agree quite well, although there are some seasonal/hemispherical differences. The sigma(sub 0) comparison reveals an overall bias between the two altimeters with the TOPEX sigma(sub 0) higher by about 0.7 dB, which is consistent with algorithm improvements for TOPEX. The SWH distributions show strong hemispherical/seasonal changes. The seasonal/hemispherical differences between TOPEX and Geosat are consistent for SWH and sigma(sub 0). The joint distribution of sigma(sub 0) and SWH is extremely stable friom month to month. The typical SWH is independent of sigma(sub 0) for sigma(sub 0) greater than 11.3 dB. The minimum SWH grows exponentially with wind speed. This joint distribution may be useful for understanding electromagnetic bias in altimeter measurements. Finally, altimeter data are compared to buoy values from 21 overflights of the NASA verification site near Pt. Conception, California. Wave heights agree well with an root mean square (RMS) difference of only 0.2 m. Altimeter sigma(sub 0) values are compared to buoy wind speeds. The results are consistent with the -0.7 dB sigma(sub 0) offset from the histogram comparisons.

Callahan, Philip S.↗