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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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At least 721 records · Page 40
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NASA NTRS2018

The NEID Precision Radial Velocity Spectrometer: Port Adapter Overview, Requirements, and Test Plan

The NEID spectrometer is an optical (380-930 nm), fiber-fed, precision Doppler spectrometer currently in development for the WIYN 3.5 m telescope at Kitt Peak National Observatory as part of the NN-EXPLORE partnership. Designed to achieve a radial velocity precision of < 30 cm/s, NEID will be sensitive enough to detect terrestrial-mass exoplanets around low-mass stars. Light from the target stars is focused by the telescope to a bent Cassegrain port at the edge of the primary mirror mechanical support. The specialized NEID "Port Adapter" system is mounted at this bent Cassegrain port and is responsible for delivering the incident light from the telescope to the NEID fibers. In order to provide stable, high-quality images to the science instrument, the Port Adapter houses several sub-components designed to acquire the target stars, correct for atmospheric dispersion, stabilize the light onto the science fibers, and calibrate the spectrometer by injecting known wavelength sources such as a laser frequency comb. Here we provide an overview of the overall opto-mechanical design and system requirements of the Port Adapter. We also describe the development of system error budgets and testplans to meet those requirements.

Cassegrain port↗
NASA NTRS2019

Satellite Ocean Colour: Current Status and Future Perspective

Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and inter-annual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided.

ocean colour↗
NASA NTRSDate not supplied

Airborne HSRL Assessment of CALIOP Aerosol Extinction Retrievals Constrained by Column AOD

Current operational CALIOP aerosol extinction profile retrievals usually rely on accurately specifying the relationship between aerosol extinction and backscattering (i.e. lidar ratio). Uncertainties in the assigned lidar ratios are typically the largest source of systematic error (~30-50%) in the CALIOP retrievals of aerosol extinction, backscatter, and aerosol optical depth. Alternatively, column aerosol optical depth (AOD) can be used to solve the lidar equation and obtain column-equivalent lidar ratios and retrieve aerosol extinction profiles from the CALIOP attenuated backscatter profiles. These derived lidar ratios correspond to the aerosols in the altitude range from 0-7 km. We derive column-equivalent aerosol lidar ratios and aerosol extinction profiles from CALIOP attenuated backscatter profiles constrained using co-located column AODs provided by several instruments/techniques: Synergized Optical Depth of Aerosols (SODA), Ocean-Derived Column Optical Depths (ODCOD), MODIS (dark target), MODIS (Multi-Angle Implementation of Atmospheric Correction-MAIAC), and PARASOL (Generalized Retrieval of Aerosol and Surface Properties-GRASP). These various retrievals of AOD and the column-average aerosol lidar ratios and aerosol extinction profiles derived from CALIOP using these AOD constraints are evaluated using the extensive record of coincident and co-located airborne HSRL measurements of AOD, aerosol lidar ratio, and aerosol extinction profiles acquired during more than 140 HSRL underflights of CALIPSO since 2006. The HSRL technique allows for the independent measurement of extinction and backscatter without the need for external constraints or assumptions regarding the lidar ratios. Initial comparisons with these coincident HSRL aerosol extinction profiles show that the CALIOP aerosol extinction profiles retrieved using these various AOD constraints are generally in better agreement with the HSRL measurements than aerosol extinction profiles from the operational techniques. The quality of agreement depends on the accuracy and magnitude of the AOD constraint. We present these comparisons of AOD, column aerosol lidar ratio, and aerosol extinction profiles for each of the AOD constraints described above.

lidar↗
NASA NTRS2023

Shape from spectra

We introduce a new unified atmospheric–topographic correction approach that estimates surface geometry directly from the radiance measurement. Surface topography influences the at-sensor radiance measurement, making precise topography modeling critical in applications like vegetation or snow studies in mountainous terrain. Currently, elevation maps are used to derive topographic variables such as the slope and sky-view factor. This process is error-prone since static global digital elevation models do not generally achieve the accuracy required, and even minor mismatches in spatial resolution can introduce significant artifacts in downstream processing. Here we demonstrate that it is possible to estimate topographic parameters directly from spectral data, ensuring perfect physical consistency, temporal coincidence, and spatial alignment. We present experiments estimating topographic slope in two scenes in Southern California, with data from NASA’s Next Generation Airborne Visible/Near Infrared Imaging Spectrometer (AVIRIS-NG). We compared our radiance-based estimates against high-resolution lidar datasets. Our initial validation result showed a correlation of R 2 = 0.864 (n = 160) over the homogeneous surface of Beckman Auditorium’s cone-shaped roof on the Caltech campus in Pasadena, California. We then validate the model over a larger study site near Santa Clarita, California, finding R 2 = 0.923 (n = 40,000) in a 350 x 350m area. The accuracy of our model estimates, combined with its systematic advantages over the alternative, show the potential of the approach for use in both airborne campaigns and orbital missions.

Nimrod Carmon↗
NASA NTRSDate not supplied

Utilizing Libya-4 to Intercalibrate Overlapping Sensors in the Same Sun-Synchronous Orbit

The NASA CERES observed SW and LW broadband fluxes are utilized by the climate community for monitoring the Earth’s energy imbalance and for climate model validation. The SNPP and NOAA20 CERES instruments and associated VIIRS imagers were launched into the same 1:30 PM mean local time sun-sun-synchronous orbits as well as the future NOAA22 Libera broadband instrument and VIIRS imager. The overlapping sensor records need to be intercalibrated to enable consistent broadband fluxes and imager cloud retrievals. The overlapping satellites are typically placed a half an orbit apart, thus preventing any simultaneous nadir overpass (SNO) events required for time-matched inter-calibration strategies. A Pseudo Invariant Calibration Site (PICS), such as Libya-4, can provide overlapping sensor radiometric scaling factors without the use of SNOs. The clear-sky Libya-4 observed radiances were characterized both spectrally and angularly and corrected for atmospheric effects. The Libya-4 natural variability was found to be consistent across the CERES and VIIRS records. This fact reveals that the sensor onboard calibration anomalies are smaller than the Libya-4 natural variability. By mitigating the Libya-4 natural variability will reduce the radiometric scaling factor uncertainty needed to provide both broadband flux and cloud retrieval continuity across the overlapping sensor records.

D R Doelling↗
NASA NTRS1994

Correcting infrared satellite estimates of sea surface temperature for atmospheric water vapor attenuation

A new satellite sea surface temperature (SST) algorithm is developed that uses nearly coincident measurements from the microwave special sensor microwave imager (SSM/I) to correct for atmospheric moisture attenuation of the infrared signal from the advanced very high resolution radiometer (AVHRR). This new SST algorithm is applied to AVHRR imagery from the South Pacific and Norwegian seas, which are then compared with simultaneous in situ (ship based) measurements of both skin and bulk SST. In addition, an SST algorithm using a quadratic product of the difference between the two AVHRR thermal infrared channels is compared with the in situ measurements. While the quadratic formulation provides a considerable improvement over the older cross product (CPSST) and multichannel (MCSST) algorithms, the SSM/I corrected SST (called the water vapor or WVSST) shows overall smaller errors when compared to both the skin and bulk in situ SST observations. Applied to individual AVHRR images, the WVSST reveals an SST difference pattern (CPSST-WVSST) similar in shape to the water vapor structure while the CPSST-quadratic SST difference appears unrelated in pattern to the nearly coincident water vapor pattern. An application of the WVSST to week-long composites of global area coverage (GAC) AVHRR data demonstrates again the manner in which the WVSST corrects the AVHRR for atmospheric moisture attenuation. By comparison the quadratic SST method underestimates the SST corrections in the lower latitudes and overestimates the SST in th e higher latitudes. Correlations between the AVHRR thermal channel differences and the SSM/I water vapor demonstrate the inability of the channel difference to represent water vapor in the midlatitude and high latitudes during summer. Compared against drifting buoy data the WVSST and the quadratic SST both exhibit the same general behavior with the relatively small differences with the buoy temperatures.

Emery, William J.↗
NASA NTRS2008

The Time Series Technique for Aerosol Retrievals over Land from MODIS: Algorithm MAIAC

Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the 2.1 m channel (B7) for the purpose of aerosol retrieval. Obviously, the subsequent atmospheric correction will produce the same SR in the red and blue bands as predicted, i.e. an empirical function of 2.1. In other words, the spectral, spatial and temporal variability of surface reflectance in the Blue and Red bands appears borrowed from band B7. This may have certain implications for the vegetation and global carbon analysis because the chlorophyll-sensing bands B1, B3 are effectively substituted in terms of variability by band B7, which is sensitive to the plant liquid water. This chapter describes a new recently developed generic aerosol-surface retrieval algorithm for MODIS. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm simultaneously retrieves AOT and surface bi-directional reflection factor (BRF) using the time series of MODIS measurements.

Lyapustin, Alexei↗
NASA NTRS1965

The spectral dependence of lunar emissivity.

The radiance of the lunar surface in the 8.0 to 10.4 μ region of the infrared spectrum was measured as a function of wavelength with a resolution better than 0.2 μ. Measurements were taken from a high altitude station (elevation 11,500 feet) to minimize the corrections required for atmospheric absorption. The radiance values obtained after correction are not compatible with gray or blackbody radiation at any temperature. Emissivities calculated on the basis of a 120°C lunar surface temperature vary from near unity at 8.5 μ to 0.90–0.93 in the region from 10.0 to 10.4 μ.

Infrared spectrum↗
NASA NTRS1984

A new technique for monitoring the water vapor in the atmosphere

In the correction of satellite Doppler data for tropospheric effects the precipitable water vapor (PWV) is inferred at the tracking site. The technique depends on: (1) an ephemeris for the satellite; (2) an analytic model for the refraction range effect that is good to a few centimeters; (3) Doppler data with noise level below 10 centimeters; and (4) a surface pressure/temperature measurement at the tracking site. The PWV is a by product of the computation necessary to correct the Doppler data for tropospheric effects. A formulation of the refraction integral minimizes the necessity for explicit water vapor, temperature and pressure profiles.

Black, H. D.↗
NASA NTRS1999

History of Ozone Research: From Schonbein to the Present

In 1840, C.F. Schonbein recognized that the smell generated in several different electrical and chemical processes was a single substance. He named this substance "ozein" from the Greek for "to smell". This substance we know today as ozone. Several periods can be distinguished in the continued development of our understanding of ozone. Throughout the late 19th century, the identity and properties of ozone were established and described. Ozone was recognized to be a constituent of normal air and tests were established to measure its concentration. Its disinfectant properties were recognized. New methods were developed for making ozone in the laboratory. In 1879, ultraviolet spectroscopic techniques were applied to the measurement of the solar spectrum and it was discovered by Comu that the spectrum was cut off at about 300 nm wavelength. Hartley suggested, based on laboratory measurements, that this cutoff was due to ozone in the atmosphere which he correctly asserted was somewhere in the upper atmosphere. This began the period of development of the amount and distribution of ozone throughout the atmosphere. In 1930, Chapman put forward the first theory of the formation and destruction of ozone. By the mid-1960s it was becoming obvious that the description of the chemical loss term was inadequate. By the early 1970s the chemical destruction of ozone by the oxides of hydrogen, nitrogen, chlorine, and bromine was recognized as an essential element in the chemical balance determining the ozone concentration. Today, ozone is a broad research project which crosses the boundaries of traditional disciplines. Stratospheric ozone loss due to chlorofluorocarbons is a newsworthy item. The Antarctic ozone hole opens up every spring. The provisions of the Montreal Protocol were agreed upon by countries around the world and promise to reduce the future levels of ozone-destroying chlorine in the stratosphere. Ozone concentrations in polluted cities are a subject of local and national regulations to limit its potential for causing health problems and corrosive effects on materials. A lot is known about ozone but many new questions are still being developed.

Stolarski, Richard S.↗
NASA NTRS2023

Heterogeneity and Chemical Reactivity of the Remote Troposphere Defined By Aircraft Measurements - Corrected

The NASA Atmospheric Tomography (ATom) mission built a photochemical climatology of air parcels based on in situ measurements with the NASA DC-8 aircraft along objectively planned profiling transects through the middle of the Pacific and Atlantic oceans. In this paper we present and analyze a data set of 10 s (2 km) merged and gap-filled observations of the key reactive species driving the chemical budgets of O3 and CH4 (O3, CH4, CO, H2O, HCHO, H2O2, CH3OOH, C2H6, higher alkanes, alkenes, aromatics, NOx, HNO3, HNO4, peroxyacetyl nitrate, and other organic nitrates), consisting of 146 494 distinct air parcels from ATom deployments 1 through 4. Six models calculated the O3 and CH4 photochemical tendencies from this modeling data stream for ATom 1. We find that 80 %–90 % of the total reactivity lies in the top 50 % of the parcels and 25 %–35 % in the top 10 %, supporting previous model-only studies that tropospheric chemistry is driven by a fraction of all the air. Surprisingly, the probability densities of species and reactivities averaged on a model scale (100 km) differ only slightly from the 2 km ATom 10 s data, indicating that much of the heterogeneity in tropospheric chemistry can be captured with current global chemistry models. Comparing the ATom reactivities over the tropical oceans with climatological statistics from six global chemistry models, we find generally good agreement with the reactivity rates for O3 and CH4. Models distinctly underestimate O3 production below 2 km relative to the mid-troposphere, and this can be traced to lower NOx levels than observed. Attaching photochemical reactivities to measurements of chemical species allows for a richer, yet more constrained-to-what-matters, set of metrics for model evaluation.

Tropospheric Chemistry↗
NASA NTRS1995

Accuracy of sea ice temperature derived from the advanced very high resolution radiometer

The accuracy of Arctic sea ice surface temperatures T(sub s) dericed from advanced very high resolution radiometer (AVHRR) thermal channels is evaluated in the cold seasons by comparing them with surface air temperatures T(sub air) from drifting buoys and ice stations. We use three different estimates of satellite surface temperatures, a direct estimate from AVHRR channel 4 with only correction for the snow surface emissivity but not for the atmosphere, a single-channel regression of T(sub s) with T(sub air), and Key and Haefliger's (1992) polar multichannel algorithm. We find no measurable bias in any of these estimates and few differences in their statistics. The similar performance of all three methods indicates that an atmospheric water vapor correction is not important for the dry winter atmosphere in the central Arctic, given the other sources of error that remain in both the satellite and the comparison data. A record of drifting station data shows winter air temperature to be 1.4 C warmer than the snow surface temperature. `Correcting' air temperatures to skin temperature by subtracting this amount implies that satellite T(sub s) estimates are biased warm with respect to skin temperature by about this amount. A case study with low-flying aircraft data suggests that ice crystal precipitation can cause satellite estimates of T(sub s) to be several degrees warmer than radiometric measurements taken close to the surface, presumably below the ice crystal precipitation layer. An analysis in which errors are assumed to exist in all measurements, not just the satellite measurements, gives a standard deviation in the satellite estimates of 0.9 C, about half the standard deviation of 1.7 C estimated by assigning all the variation between T(sub s) and T(sub air) to errors in T(sub s).

Yu, Y.↗
NASA NTRS1992

Mars: Correcting surface albedo observations for effects of atmospheric dust loading

We have developed a radiative transfer model which allows the effects of atmospheric dust loading on surface albedo to be investigated. This model incorporates atmospheric dust opacity, the single scattering albedo and particle phase function of atmospheric dust, the bidirectional reflectance of the surface, and variable lighting and viewing geometry. The most recent dust particle properties are utilized. The spatial and temporal variability of atmospheric opacity (Tan) strongly influences the radiative transfer modelling results. We are currently using the approach described to determine Tan for IRTM mapping sequences of selected regions. This approach allows Tan to be determined at the highest spatial and temporal resolution supported by the IRTM data. Applying the radiative transfer modelling and determination of Tan described, IRTM visual brightness observations can be corrected for the effects of atmospheric dust loading a variety of locations and times. This approach allows maps of 'dust-corrected surface albedo' to be constructed for selected regions. Information on the variability of surface albedo and the amount of dust deposition/erosion related to such variability results. To date, this study indicates that atmospheric dust loading has a significant effect on observations of surface albedo, amounting to albedo corrections of as much as several tens of percent. This correction is not constant or linear, but depends upon surface albedo, viewing and lighting geometry, the dust and surface phase functions, and the atmospheric opacity. It is clear that the quantitative study of surface albedo, especially where small variations in observed albedo are important (such as photometric analyses), needs to account for the effects of the atmospheric dust loading. Maps of 'dust-corrected surface albedo' will be presented for a number of regions.

Lee, S. W.↗
DOE OSTI2026

High-Resolution ESM Projections for Energy Applications Over the CONUS

Assessing energy resources under future scenarios requires high-resolution meteorological information that is physically consistent and suitable for regional-scale analysis. While Earth system model (ESM) projections provide valuable large-scale information, their coarse resolution and systematic biases limit direct applicability for energy system modeling and planning. In this study, we develop a high-resolution dynamical downscaling framework based on the Weather Research and Forecasting (WRF) model to translate global-scale ESM data into energy-relevant regional projections over the contiguous United States (CONUS). The framework identifies an optimized WRF configuration through numerical experiments and evaluates raw and bias-corrected ESM initial and boundary conditions, with soil moisture (SM) and soil temperature (ST) bias correction implemented as an integral part of the bias-corrected ESM forcing to improve land-atmosphere coupling prior to WRF dynamical downscaling. Using an optimized WRF configuration at 4-km resolution, we show that raw ESM forcing introduces systematic dry and cold soil biases that propagate into pronounced warm biases in near-surface air temperature and positive biases in solar irradiance, particularly during summer. Applying bias-corrected atmospheric forcing together with bias-corrected SM and ST substantially reduces these downstream biases and improves the surface energy balance and near-surface atmospheric fields. These results demonstrate that bias-aware treatment of initial conditions is critical for producing high-resolution downscaled projections suitable for energy system modeling and planning applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1979

Compensation for atmospheric effects in LANDSAT data

Preprocessing algorithms were developed to remove or reduce the variations in multispectral data caused by variations in Sun angle and by changes in the atmospheric aerosol and water vapor levels. The two most significant algorithms developed by using mathematical models to define interrelations between the required multiplicative and additive correction factors so that just a few statistical characteristics of a LANDSAT distribution model would be sufficient to drive the mathematical model and to calculate the preprocessing corrections are examined. These are the atmospheric correction (ATCOR) computer program and the XSTAR haze correction algorithm. Neither the ATCOR nor the XSTAR algorithm provides an explicit compensation for the effects of changing LANDSAT view angle. Development efforts are underway to address this aspect of the preprocessing problem.

Lambeck, P. F.↗
NASA NTRS2006

Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System

In an initial investigation, remotely sensed surface temperature is assimilated into a coupled atmosphere/land global data assimilation system, with explicit accounting for biases in the model state. In this scheme, an incremental bias correction term is introduced in the model's surface energy budget. In its simplest form, the algorithm estimates and corrects a constant time mean bias for each gridpoint; additional benefits are attained with a refined version of the algorithm which allows for a correction of the mean diurnal cycle. The method is validated against the assimilated observations, as well as independent near-surface air temperature observations. In many regions, not accounting for the diurnal cycle of bias caused degradation of the diurnal amplitude of background model air temperature. Energy fluxes collected through the Coordinated Enhanced Observing Period (CEOP) are used to more closely inspect the surface energy budget. In general, sensible heat flux is improved with the surface temperature assimilation, and two stations show a reduction of bias by as much as 30 Wm(sup -2) Rondonia station in Amazonia, the Bowen ratio changes direction in an improvement related to the temperature assimilation. However, at many stations the monthly latent heat flux bias is slightly increased. These results show the impact of univariate assimilation of surface temperature observations on the surface energy budget, and suggest the need for multivariate land data assimilation. The results also show the need for independent validation data, especially flux stations in varied climate regimes.

Bosilovich, Michael G.↗