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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 91 records · Page 5
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NASA NTRS1991

Analysis of terrain map matching using multisensing techniques for applications to autonomous vehicle navigation

This paper describes skyline-based terrain matching, a new method for locating the vantage point of laser range-finding measurements on a global map previously prepared by satellite or aerial mapping. Skylines can be extracted from the range-finding measurements and modelled from the global map, and are represented in parametric, cylindrical form with azimuth angle as the independent variable. The three translational parameters of the vantage point are determined with a three-dimensional matching of these two sets of skylines.

Page, Lance↗
NASA NTRSDate not supplied

Assessing the feasibility of a spaceborne 3D lightning observing concept

The distribution of electrical charge in thunderclouds results from thermodynamic, microphysical, and kinematic processes, which also modulate thunderstorm evolution. It is no surprise that the connection between lightning and these physical processes is so strong that the increase and vertical growth of lightning activity closely follows the vertical growth of the thundercloud, but unraveling these connections is not trivial and requires observations of the three-dimensional (3D) structure of electrical activity in a cloud. Ground-based 3D lightning mapping networks give excellent 3D flash-level detail but are limited to regional coverage. Satellite-based optical lightning mappers give excellent global coverage but are largely limited to 2D summaries of flash rate and radiant intensity, albeit new flash products and stereographic techniques are chipping away this limitation. New observing strategies are needed to expand and diversify the corpus of 3D lightning datasets and motivate studies that unravel connections lightning has with these key physical processes and the surrounding environment. This study examines the feasibility of using a distributed network of orbing satellites with VHF-based lightning detectors to obtain global maps of 3D lightning activity and assess efficacy of this approach for use in a new, small satellite mission concept called CubeSpark. CubeSpark combines new VHF and high-resolution, bispectral optical instruments on a constellation of low-Earth orbiting (LEO) satellites to globally map the 3D electrical structure of thunderstorms and study how it relates to thunderstorm evolution, extreme weather, nitrogen oxide production and distribution, upper atmospheric electrical phenomena, and how 3D flash observations can complement existing satellite-based lightning mappers and improve decision support tools. To locate lightning discharges, CubeSpark seeks to use the VHF time-of-arrival technique, similar to ground-based total lightning mapping networks. The vertical location accuracy of these satellite retrievals will be of poorer quality compared to a ground-based network, which has non-trivial implications for lightning flash reconstruction and lightning-based interpretations of deep convection. We adapt a Lightning Mapping Array (LMA) simulation framework to an orbiting network and use it to address feasibility of 3D lightning detection from space with particular attention to location accuracy of VHF detections of lightning in the vertical. These simulations inform a constellation design study that defines a realistic orbital configuration and depicts the global coverage for CubeSpark. Results indicate that a 3D location accuracy of <1-2 km for each dimension can be achieved across 300-500 km wide swaths, which suggests that CubeSpark can resolve the charge structure of thunderclouds from the tropics to the mid- and high- latitudes.

Lightning↗
NASA NTRS2013

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-Spectral-Resolution Near-Infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 0.5. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

Fluorescence↗
NASA NTRS2013

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-spectral-resolution Near-infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 deg × 0.5 deg. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

remote sensing↗
NASA NTRS2022

A review of Carbon Monitoring in Wet Carbon Systems using Remote Sensing

Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1,622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry.

Anthony D. Campbell↗
NASA NTRS2017

Status of Remote Sensing of Salinity by Aquarius

Aquarius is an L-band instrument designed to measure sea surface salinity from space. The instrument was launched in 2011 and data acquisition ended in June 2015 when control of the spacecraft was lost. Aquarius produced global maps of salinity with accuracy of 0.2 psu (Practical Salinity Unit) and special resolution of 150 kilometers as well as other products such as global maps of RFI (Radio Frequency Interference) and soil moisture. The mission will formally end December 2017.

Le Vine, D. M.↗
NASA NTRS2002

Problems in Assessment of the UV Penetration into Natural Waters from Space-based Measurements

Satellite instruments currently provide global maps of surface UV (ultraviolet) irradiance by combining backscattered radiance data with radiative transfer models. The models are often limited by uncertainties in physical input parameters of the atmosphere and surface. Global mapping of the underwater UV irradiance creates further challenges for the models. The uncertainties in physical input parameters become more serious because of the presence of absorbing and scattering quantities caused by biological processes within the oceans. In this paper we summarize the problems encountered in the assessment of the underwater UV irradiance from space-based measurements, and propose approaches to resolve the problems. We have developed a radiative transfer scheme for computation of the UV irradiance in the atmosphere-ocean system. The scheme makes use of input parameters derived from satellite instruments such as TOMS (Total Ozone Mapping Spectrometer) and SeaWiFS (Sea-viewing Wide Field-of-view Sensor). The major problem in assessment of the surface UV irradiance is to accurately quantify the effects of clouds. Unlike the standard TOMS UV algorithm, we use the cloud fraction products available from SeaWiFS and MODIS (Moderate Resolution Imaging Spectrometer) to calculate instantaneous surface flux at the ocean surface. Daily UV doses can be calculated by assuming a model of constant cloudiness throughout the day. Both SeaWiFS and MODIS provide some estimates of seawater optical properties in the visible. To calculate the underwater UV flux the seawater optical properties must be extrapolated down to shorter wavelengths. Currently, the problem of accurate extrapolation of visible data down to the UV spectral range is not solved completely, and there are few available measurements. The major difficulty is insufficient correlation between photosynthetic and photoprotective pigments of phytoplankton absorbing in the visible and UV respectively. We propose to empirically parameterize seawater absorption in the UV on a basis of available data sets of bio-optical measurements from a variety of ocean waters. Another problem is the lack of reliable data on pure seawater absorption in the UV. Laboratory measurements of the UV absorption of both pure water and pure seawater are required.

Vasilkov, Alexander P.↗
NASA NTRS1990

Skyline based terrain matching

Skyline-based terrain matching, a new method for locating the vantage point of stereo camera or laser range-finding measurements on a global map previously prepared by satellite or aerial mapping is described. The orientation of the vantage is assumed known, but its translational parameters are determined by the algorithm. Skylines, or occluding contours, can be extracted from the sensory measurements taken by an autonomous vehicle. They can also be modeled from the global map, given a vantage estimate from which to start. The two sets of skylines, represented in cylindrical coordinates about either the true or the estimated vantage, are employed as 'features' or reference objects common to both sources of information. The terrain matching problem is formulated in terms of finding a translation between the respective representations of the skylines, by approximating the two sets of skylines as identical features (curves) on the actual terrain. The search for this translation is based on selecting the longest of the minimum-distance vectors between corresponding curves from the two sets of skylines. In successive iterations of the algorithm, the approximation that the two sets of curves are identical becomes more accurate, and the vantage estimate continues to improve. The algorithm was implemented and evaluated on a simulated terrain. Illustrations and examples are included.

Page, Lance A.↗
NASA NTRS2012

The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status

The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status of the SMAP data products. The Testbed simulations are designed to capture various sources of errors in the products including environment effects, instrument effects (nonideal aspects of the measurement system), and retrieval algorithm errors. The SMAP project has developed a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level l) and derived geophysical products (Level 2 and higher).

Nloku, E.↗
NASA NTRS2012

Mapping of CO2 at High Spatiotemporal Resolution using Satellite Observations: Global distributions from OCO-2

Satellite observations of CO2 offer new opportunities to improve our understanding of the global carbon cycle. Using such observations to infer global maps of atmospheric CO2 and their associated uncertainties can provide key information about the distribution and dynamic behavior of CO2, through comparison to atmospheric CO2 distributions predicted from biospheric, oceanic, or fossil fuel flux emissions estimates coupled with atmospheric transport models. Ideally, these maps should be at temporal resolutions that are short enough to represent and capture the synoptic dynamics of atmospheric CO2. This study presents a geostatistical method that accomplishes this goal. The method can extract information about the spatial covariance structure of the CO2 field from the available CO2 retrievals, yields full coverage (Level 3) maps at high spatial resolutions, and provides estimates of the uncertainties associated with these maps. The method does not require information about CO2 fluxes or atmospheric transport, such that the Level 3 maps are informed entirely by available retrievals. The approach is assessed by investigating its performance using synthetic OCO-2 data generated from the PCTM/ GEOS-4/CASA-GFED model, for time periods ranging from 1 to 16 days and a target spatial resolution of 1deg latitude x 1.25deg longitude. Results show that global CO2 fields from OCO-2 observations can be predicted well at surprisingly high temporal resolutions. Even one-day Level 3 maps reproduce the large-scale features of the atmospheric CO2 distribution, and yield realistic uncertainty bounds. Temporal resolutions of two to four days result in the best performance for a wide range of investigated scenarios, providing maps at an order of magnitude higher temporal resolution relative to the monthly or seasonal Level 3 maps typically reported in the literature.

Hammerling, Dorit M.↗
NASA NTRS2011

The NASA Soil Moisture Active Passive (SMAP) Mission - Algorithm and Cal/Val Activities and Synergies with SMOS and Other L-Band Missions

NASA's Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has as its key measurement objective the frequent, global mapping of near-surface soil moisture and its freeze-thaw state. SMAP soil moisture and freeze/thaw measurements at 10 km and 3 km resolutions respectively, would enable significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections Soil moisture measurements are also of great importance in assessing floods and for monitoring drought. In addition, observations of soil moisture and freeze/thaw timing over the boreal latitudes can help reduce uncertainties in quantifying the global carbon balance. The SMAP measurement concept utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The SMAP radiometer and radar flight hardware and ground processing designs are incorporating approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). The radar and radiometer instruments are planned to operate in a 680 km polar orbit, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments would yield global maps of soil moisture and freeze/thaw state to be provided at 10 km and 3 km resolutions respectively, every two to three days. Plans are to provide also a radiometer-only soil moisture product at 40-km spatial resolution. This product and the underlying brightness temperatures have characteristics similar to those provided by the Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are unique opportunities for common data product development and continuity between the two missions. SMAP also has commonalities with other satellite missions having L-band radiometer and/or radar sensors applicable to soil moisture measurement, such as Aquarius, SAO COM, and ALOS-2. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. The algorithms are developed and evaluated in the SDS Testbed using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including SMOS. The SMAP project is developing a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level I) and derived geophysical products (Level 2 and higher). In this presentation we report on the development status of the SMAP data product algorithms, and the planning and implementation of the SMAP Cal/Val program. Several components of the SMAP algorithm development and Cal/Val plans have commonality with those of SMOS, and for this reason there are shared activities and resources that can be utilized between the missions, including in situ networks, ancillary data sets, and long-term monitoring sites.

Njoku, Eni↗
NASA NTRS2017

Development and Validation of The SMAP Enhanced Passive Soil Moisture Product

Since the beginning of its routine science operation in March 2015, the NASA SMAP observatory has been returning interference-mitigated brightness temperature observations at L-band (1.41 GHz) frequency from space. The resulting data enable frequent global mapping of soil moisture with a retrieval uncertainty below 0.040 cu m/cu m at a 36 km spatial scale. This paper describes the development and validation of an enhanced version of the current standard soil moisture product. Compared with the standard product that is posted on a 36 km grid, the new enhanced product is posted on a 9 km grid. Derived from the same time-ordered brightness temperature observations that feed the current standard passive soil moisture product, the enhanced passive soil moisture product leverages on the Backus-Gilbert optimal interpolation technique that more fully utilizes the additional information from the original radiometer observations to achieve global mapping of soil moisture with enhanced clarity. The resulting enhanced soil moisture product was assessed using long-term in situ soil moisture observations from core validation sites located in diverse biomes and was found to exhibit an average retrieval uncertainty below 0.040 cu m/cu m. As of December 2016, the enhanced soil moisture product has been made available to the public from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center.

SMAP Enhanced↗
NASA NTRS1992

The role of global cloud climatologies in validating numerical models

Global maps of the monthly mean net upward longwave radiation flux at the ocean surface were obtained for April, July, October 1985 and January 1986. These maps were produced by blending information obtained from a combination of general circulation model cloud radiative forcing fields, the top of the atmosphere cloud radiative forcing from ERBE and TOVS profiles and sea surface temperature on ISCCP C1 tapes. The fields are compatible with known meteorological regimes of atmospheric water vapor content and cloudiness. There is a vast area of high net upward longwave radiation flux (greater than 80/sq Wm) in the eastern Pacific Ocean throughout most of the year. Areas of low net upward longwave radiation flux ((less than 40/sq Wm) are the tropical convective regions and extra tropical regions that tend to have persistent low cloud cover.The technique used relies on General Circulation Model simulations and so is subject to some of the uncertainties associated with the model. However, all input information regarding temperature, moisture, and cloud cover is from satellite data having near global coverage. This feature of the procedure alone warrants its consideration for further use in compiling global maps of longwave radiation.

HARSHVARDHAN↗
NASA NTRS2019

Turning Satellite Data into Global Precipitation Maps

It's really obvious how to measure rain and snowfall just put a container out in the yard. But, it turns out the physical processes that create precipitation, and the practicalities of taking measurements everywhere, make satellites key tools in mapping rain and snowfall around the globe. Employing satellites in this meteorological detective story involves some science, some technology, a lot of computing, and, yes, rocket science. The payoff is that we know more about how much rain and snow fell in, say, 2010, than we knew at the time that it fell, and we're ready to make the same kind of estimate for tomorrow's storms. There is still a lot of work to be done to make these estimates more reliable and accurate.Dr. George J. Huffman is a Research Meteorologist at NASA Goddard Space Flight Center (GSFC), Greenbelt, Maryland. After completing a B.S. in Physics at The Ohio State University (1976) and a Ph.D. in Meteorology at Massachusetts Institute of Technology (1982), he was an Assistant Professor at University of Maryland, College Park before moving to GSFC in 1988, where he consulted for 24 years before joining NASA in 2012. Dr. Huffman focuses on the design, implementation, and extension of combined estimates of global precipitation, seeking to incorporate all available precipitation-relevant satellite and global surface data. He is the Deputy Project Scientist for the Global Precipitation Measurement (GPM) mission, the Chair of the GPM Multi-satellite Algorithm Working Group, and Chief of the Mesoscale Atmospheric Processes Lab.

Huffman, George J.↗