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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Examination of Observation Impacts derived from OSEs and Adjoint Models

With the adjoint of a data assimilation system, the impact of any or all assimilated observations on measures of forecast skill can be estimated accurately and efficiently. The approach allows aggregation of results in terms of individual data types, channels or locations, all computed simultaneously. In this study, adjoint-based estimates of observation impact are compared with results from standard observing system experiments (OSEs) in the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) GEOS-5 system. The two approaches are shown to provide unique, but complimentary, information. Used together, they reveal both redundancies and dependencies between observing system impacts as observations are added or removed. Understanding these dependencies poses a major challenge for optimizing the use of the current observational network and defining requirements for future observing systems.

Gelaro, Ronald↗
NASA NTRS2010

NASA Tech Briefs, June 2010

Topics covered include: Situational Awareness from a Low-Cost Camera System; Data Acquisition System for Multi-Frequency Radar Flight Operations Preparation; Mercury Toolset for Spatiotemporal Metadata; Social Tagging of Mission Data; Integrating Radar Image Data with Google Maps; Demonstration of a Submillimeter-Wave HEMT Oscillator Module at 330 GHz; Flexible Peripheral Component Interconnect Input/Output Card; Interface Supports Lightweight Subsystem Routing for Flight Applications; MMIC Amplifiers and Wafer Probes for 350 to 500 GHz; Public Risk Assessment Program; Particle Swarm Optimization Toolbox; Telescience Support Center Data System Software; Update on PISCES; Ground and Space Radar Volume Matching and Comparison Software; Web-Based Interface for Command and Control of Network Sensors; Orbit Determination Toolbox; Distributed Observer Network; Computer-Automated Evolution of Spacecraft X-Band Antennas; Practical Loop-Shaping Design of Feedback Control Systems; Fully Printed High-Frequency Phased-Array Antenna on Flexible Substrate; Formula for the Removal and Remediation of Polychlorinated Biphenyls in Painted Structures; Integrated Solar Concentrator and Shielded Radiator; Water Membrane Evaporator; Modeling of Failure for Analysis of Triaxial Braided Carbon Fiber Composites; Catalyst for Carbon Monoxide Oxidation; Titanium Hydroxide - a Volatile Species at High Temperature; Selective Functionalization of Carbon Nanotubes: Part II; Steerable Hopping Six-Legged Robot; Launchable and Retrievable Tetherobot; Hybrid Heat Exchangers; Orbital Winch for High-Strength, Space-Survivable Tethers; Parameterized Linear Longitudinal Airship Model; and Physics of Life: A Model for Non-Newtonian Properties of Living Systems.

Source record↗
NASA NTRS2011

Assessing the Impact of Advanced Satellite Observations in the NASA GEOS-5 Forecast System Using the Adjoint Method

The adjoint of a data assimilation system provides a flexible and efficient tool for estimating observation impacts on short-range weather forecasts. The impacts of any or all observations can be estimated simultaneously based on a single execution of the adjoint system. The results can be easily aggregated according to data type, location, channel, etc., making this technique especially attractive for examining the impacts of new hyper-spectral satellite instruments and for conducting regular, even near-real time, monitoring of the entire observing system. In this talk, we present results from the adjoint-based observation impact monitoring tool in NASA's GEOS-5 global atmospheric data assimilation and forecast system. The tool has been running in various off-line configurations for some time, and is scheduled to run as a regular part of the real-time forecast suite beginning in autumn 20 I O. We focus on the impacts of the newest components of the satellite observing system, including AIRS, IASI and GPS. For AIRS and IASI, it is shown that the vast majority of the channels assimilated have systematic positive impacts (of varying magnitudes), although some channels degrade the forecast. Of the latter, most are moisture-sensitive or near-surface channels. The impact of GPS observations in the southern hemisphere is found to be a considerable overall benefit to the system. In addition, the spatial variability of observation impacts reveals coherent patterns of positive and negative impacts that may point to deficiencies in the use of certain observations over, for example, specific surface types. When performed in conjunction with selected observing system experiments (OSEs), the adjoint results reveal both redundancies and dependencies between observing system impacts as observations are added or removed from the assimilation system. Understanding these dependencies appears to pose a major challenge for optimizing the use of the current observational network and defining requirements for future observing systems.

Gelaro, Ron↗
NASA NTRS2012

Assessing the Impact of Observations on Numerical Weather Forecasts Using the Adjoint Method

The adjoint of a data assimilation system provides a flexible and efficient tool for estimating observation impacts on short-range weather forecasts. The impacts of any or all observations can be estimated simultaneously based on a single execution of the adjoint system. The results can be easily aggregated according to data type, location, channel, etc., making this technique especially attractive for examining the impacts of new hyper-spectral satellite instruments and for conducting regular, even near-real time, monitoring of the entire observing system. This talk provides a general overview of the adjoint method, including the theoretical basis and practical implementation of the technique. Results are presented from the adjoint-based observation impact monitoring tool in NASA's GEOS-5 global atmospheric data assimilation and forecast system. When performed in conjunction with standard observing system experiments (OSEs), the adjoint results reveal both redundancies and dependencies between observing system impacts as observations are added or removed from the assimilation system. Understanding these dependencies may be important for optimizing the use of the current observational network and defining requirements for future observing systems

Gelaro, Ronald↗
NASA NTRS2018

An Overview of Mesoscale Aerosol Processes, Comparisons, and Validation Studies from DRAGON Networks

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

Holben, Brent N.↗
NASA NTRS2015

Observing System Simulation Experiments for Fun and Profit

Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed

Observational Networks↗
NASA NTRS2024

Observing System Simulation Experiments Exploring Potential Spaceborne Deployment Options for a Differential Absorption Radar Measuring Marine Surface Pressures

A new technology for remote measurements of marine surface pressure has been proposed, employing a V-band differential absorption radar and a radiometric temperature sounder to calculate the total column atmospheric mass. Observing System Simulation Experiments (OSSEs) are performed to evaluate the potential impact of Spaceborne Marine Surface Pressure (SMSP) on Numerical Weather Prediction. These experiments build on prior efforts (Privé, McLinden, et al., 2023, https://doi.org/10.16993/tellusa.3254), but with an updated version of the OSSE framework and with more sophisticated simulation of the SMSP observations and a longer experiment period. Several different instrument configurations are compared, including both scanning and non-scanning orbits. SMSP impacts are calculated for analysis quality and forecast skill, and a forecast sensitivity observation impact tool is employed to place SMSP observations in context with the global observing network. The effects of rain contamination on observation quality are explored. Different magnitudes of simulated SMSP observation error are tested in the context of data assimilation to show the range of potential behaviors. Overall, SMSP observations are found to be most beneficial in the southern hemisphere extratropics, with statistically significant forecast improvements for the first 72 hr of the forecast. A constellation of four non-scanning SMSP satellites is found to outperform a single scanning instrument with a 250 km wide swath.

N C Prive↗
NASA NTRS2019

Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction

Developments in ocean data assimilation (DA) and observing system technologies are intertwined. New observation types lead to new DA methods, and new DA methods such as Coupled Data Assimilation can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners are encouraged to make better use of observations that are already available, for example in strongly coupled data assimilation where ocean observations can be used to improve atmospheric analyses and vice versa. Ocean reanalyses are useful for the analysis of climate,as well as initializing operational long-range prediction models. There are remaining challenges for ocean reanalyses due to biases and abrupt changes in the ocean observing system throughout its history, the presence of biases and drifts in models, and simplifying assumptions made in the DA methods. From a governance point of view, more support is needed to interface the observing community and the ocean DA community. For prediction applications, the ocean DA community must work with the ocean observing community to establish protocols for rapid communication of ocean observing data on NWP timescales. There is potential for new observations to enhance the observing system by supporting prediction on multiple timescales, ranging from the typical timescale of numerical weather prediction covering hours to weeks, out to multiple decades. It is highly encouraged that communication be fostered between thesecommunities to allow operational prediction centers the ability to provide guidance to the design of a sustained and adaptive observing network.

Ocean reanalysis↗
NASA NTRS1976

The emission-line spectrum of a sunspot in the far-ultraviolet

The emission-line spectrum between 1200 and 1817 A from a sunspot in McMath region 12510 near the solar center is discussed. The spectrum was obtained by the normal-incidence spectrograph on Skylab. The principal results are: (1) the widths of emission lines originating in the chromosphere and lower transition region over the sunspot are much narrower than those previously reported for a polar coronal hole observed above the limb and a quiet chromospheric network observed near the solar center, indicating that the mass motions in the sunspot are less than in these other regions; (2) the sunspot spectrum, aside from the narrow widths of emission lines, is similar to spectra from the chromospheric network boundary. The intensities of lines in the sunspot are much enhanced relative to the network interior. From the full-width at half-maximum of the 1207-A Si III line, an optical depth at line center of 3.6 is deduced. Comparison with Parker's (1974) theory of sunspots shows that, if the enhancement of emission lines is due to enhanced transport of hydromagnetic waves generated in the sunspot convective zone, the mode of the waves is predominately Alfvenic.

Cheng, C.-C.↗
NASA NTRS1999

Mass Transport in Global Geophysical Fluids

Mass transports occurring in the atmosphere-hydrosphere-solid Earth-core system (the "global geophysical fluids") are important geophysical phenomena. They occur on all temporal and spatial scales. Examples include air mass and ocean circulations, tides, hydrological water redistribution, mantle processes such as post-glacial rebound, earthquakes and tectonic motions, and core geodynamo activities. With only a few exceptions on the Earth surface, the temporal history and spatial pattern of such mass transport are often not amenable to direct observations. Space geodesy techniques, however, have the capability of monitoring certain direct consequences of the mass transport, including Earth's rotation variations, gravitational field variations, and the geocenter motion. These techniques include the very-long-baseline interferometry, satellite laser ranging and Doppler tracking, and the Global Positioning System, all entail global observational networks. While considerable advances have been made in observing and understanding of the dynamics of Earth's rotation, only the lowest-degree gravitational variations have been observed and limited knowledge of geocenter motion obtained. New space missions, projects and initiatives promise to further improve the measurements and hence our knowledge about the global mass transports. The latter contributes to our understanding and modeling capability of the geophysical processes that produce and regulate the mass transports, as well as the solid Earth's response to such changes in constraining the modeling of Earth's mechanical properties.

Chao, B. F.↗
NASA NTRS1985

Calculation of geopotential and temperature fields from an array of nearly continuous wind observations

The accuracy is studied of temperature estimates derived from the divergence equation when wind observations of various spatial and temporal resolutions and accuracies are available. The basic data set used is the high resolution model data set used by Kuo and Anthes (1984a) in observing systems simulation experiments (OSSE) designed to estimate the errors in heat and moisture budgets (Kuo and Anthes, 1984b) calculated from the AVE-SESAME-1979 spatial observational network. This model data set is modified in ways to simulate wind observations that appear feasible from an operational regional network of wind profilers.

Kuo, Ying-Hwa↗
NASA NTRS2016

Why Do Models Overestimate Surface Ozone in the Southeast United States?

Ozone pollution in the Southeast US involves complex chemistry driven by emissions of anthropogenic nitrogen oxide radicals (NO(x) triple bond NO + NO2) and biogenic isoprene. Model estimates of surface ozone concentrations tend to be biased high in the region and this is of concern for designing effective emission control strategies to meet air quality standards. We use detailed chemical observations from the SEAC(exp 4)RS aircraft campaign in August and September 2013, interpreted with the GEOS-Chem chemical transport model at 0.25 deg x 0.3125 deg horizontal resolution, to better understand the factors controlling surface ozone in the Southeast US. We find that the National Emission Inventory (NEI) for NO(x) from the US Environmental Protection Agency (EPA) is too high. This finding is based on SEAC(exp 4)RS observations of NO(x) and its oxidation products, surface network observations of nitrate wet deposition fluxes, and OMI satellite observations of tropospheric NO2 columns. Our results indicate that NEI NO(x) emissions from mobile and industrial sources must be reduced by 30-60%, dependent on the assumption of the contribution by soil NO(x) emissions. Upper-tropospheric NO2 from lightning makes a large contribution to satellite observations of tropospheric NO2 that must be accounted for when using these data to estimate surface NO(x) emissions. We find that only half of isoprene oxidation proceeds by the high-NO(x) pathway to produce ozone; this fraction is only moderately sensitive to changes in NO(x) emissions because isoprene and NO(x) emissions are spatially segregated. GEOS-Chem with reduced NO(x) emissions provides an unbiased simulation of ozone observations from the aircraft and reproduces the observed ozone production efficiency in the boundary layer as derived from a regression of ozone and NO(x) oxidation products. However, the model is still biased high by 6 plus or minus 14 ppb relative to observed surface ozone in the Southeast US. Ozonesondes launched during midday hours show a 7 ppb ozone decrease from 1.5 km to the surface that GEOS-Chem does not capture. This bias may reflect a combination of excessive vertical mixing and net ozone production in the model boundary layer.

Oxidation↗
NASA NTRS2019

Intercomparison of Aerosol Volume Size Distributions Derived from AERONET Ground-Based Remote Sensing and LARGE in Situ Aircraft Profiles During the 2011–2014 DRAGON and DISCOVER-AQ Experiments

Aerosol volume size distribution (VSD) retrievals from the Aerosol Robotic Network (AERONET) aerosol monitoring network were obtained during multiple DRAGON (Distributed Regional Aerosol Gridded Observational Network) campaigns conducted in Maryland, California, Texas and Colorado from 2011 to 2014. These VSD retrievals from the field campaigns were used to make comparisons with near-simultaneous in situ samples from aircraft profiles carried out by the NASA Langley Aerosol Group Experiment (LARGE) team as part of four campaigns comprising the DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) experiments. For coincident (1 h) measurements there were a total of 91 profile-averaged fine-mode size distributions acquired with the LARGE ultra-high sensitivity aerosol spectrometer (UHSAS) instrument matched to 153 AERONET size distributions retrieved from almucantars at 22 different ground sites. These volume size distributions were characterized by two fine-mode parameters, the radius of peak concentration (rpeak_conc) and the VSD fine-mode width (widthpeak_conc). The AERONET retrievals of these VSD fine-mode parameters, derived from ground-based almucantar sun photometer data, represent ambient humidity values while the LARGE aircraft spiral profile retrievals provide dried aerosol (relative humidity; RH< 20 %) values. For the combined multiple campaign dataset, the average difference in rpeak_conc was 0:0330:035 μm (ambient AERONET values were 15.8% larger than dried LARGE values), and the average difference in widthpeak_conc was 0:0420:039 μm (AERONET values were 25.7% larger). For a subset of aircraft data, the LARGE data were adjusted to account for ambient humidification. For these cases, the AERONET–LARGE average differences were smaller, with rpeak_conc differing by 0:0110:019 μm (AERONET values were 5.2% larger) and widthpeak_conc average differences equal to 0:0300:037 μm (AERONET values were 15.8% larger).

Schafer, Joel S.↗
NASA NTRS1980

Error estimation for ORION baseline vector determination

Effects of error sources on Operational Radio Interferometry Observing Network (ORION) baseline vector determination are studied. Partial derivatives of delay observations with respect to each error source are formulated. Covariance analysis is performed to estimate the contribution of each error source to baseline vector error. System design parameters such as antenna sizes, system temperatures and provision for dual frequency operation are discussed.

Wu, S. C.↗
NASA NTRS2008

The South American Land Data Assimilation System (SALDAS) 5-Year Retrospective Atmospheric Forcing Datasets

The definition and derivation of a 5-year, 0.125deg, 3-hourly atmospheric forcing dataset for the South America continent is described which is appropriate for use in a Land Data Assimilation System and which, because of the limited surface observational networks available in this region, uses remotely sensed data merged with surface observations as the basis for the precipitation and downward shortwave radiation fields. The quality of this data set is evaluated against available surface observations. There are regional difference in the biases for all variables in the dataset, with biases in precipitation of the order 0-1 mm/day and RMSE of 5-15 mm/day, biases in surface solar radiation of the order 10 W/sq m and RMSE of 20 W/sq m, positive biases in temperature typically between 0 and 4 K, depending on region, and positive biases in specific humidity around 2-3 g/Kg in tropical regions and negative biases around 1-2 g/Kg further south.

deGoncalves, Luis Gustavo G.↗
NASA NTRS2011

Daily and Hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We distributed monthly GFED3 emissions during 2003-2009 on a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) active fire observations. We found that patterns of daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of bunting in savannas. On diurnal timescales, our analysis of the GOES active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗
NASA NTRS2011

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003.2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS) ]derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top ]down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗