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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

NASA/GEWEX Surface Radiation Budget: Integrated Data Product With Reprocessed Radiance, Cloud, and Meteorology Inputs, and New Surface Albedo Treatment

The NASA/GEWEX Surface Radiation Budget (SRB) project produces shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. Spatial resolution is 1 degree. The current release 3.0 (available at gewex-srb.larc.nasa.gov) uses the International Satellite Cloud Climatology Project (ISCCP) DX product for pixel level radiance and cloud information. This product is subsampled to 30 km. ISCCP is currently recalibrating and recomputing their entire data series, to be released as the H product, at 10km resolution. The ninefold increase in pixel number will allow SRB a higher resolution gridded product (e.g. 0.5 degree), as well as the production of pixel-level fluxes. In addition to the input data improvements, several important algorithm improvements have been made. Most notable has been the adaptation of Angular Distribution Models (ADMs) from CERES to improve the initial calculation of shortwave TOA fluxes, from which the surface flux calculations follow. Other key input improvements include a detailed aerosol history using the Max Planck Institut Aerosol Climatology (MAC), temperature and moisture profiles from HIRS, and new topography, surface type, and snow/ice. Here we present results for the improved GEWEX Shortwave and Longwave algorithm (GSW and GLW) with new ISCCP data, the various other improved input data sets and the incorporation of many additional internal SRB model improvements. As of the time of abstract submission, results from 2007 have been produced with ISCCP H availability the limiting factor. More SRB data will be produced as ISCCP reprocessing continues. The SRB data produced will be released as part of the Release 4.0 Integrated Product, recognizing the interdependence of the radiative fluxes with other GEWEX products providing estimates of the Earth's global water and energy cycle (I.e., ISCCP, SeaFlux, LandFlux, NVAP, etc.).

Cox, Stephen J.↗
NASA NTRS2019

Early Results for Version 06 IMERG

The U.S. Global Precipitation Measurement mission (GPM) science team is developing a long-term dataset based on intercalibrated estimates from the international constellation of precipitation-relevant satellites and other data. The Integrated Multi-satellitE Retrievals for GPM (IMERG) merged precipitation product (IMERG) is computed at the half hour, 0.1° x 0.1° resolution globally in three "Runs" Early, Late, and Final (4 hours, 14 hours, and 3.5 months after observation time, respectively). The longer latencies increase the available input data for the resulting estimates, most notably the use of monthly precipitation gauge analyses in the Final run. The Early and Late runs use a climatological gauge adjustment as a proxy for the monthly gauge analyses. At meeting time GPM should be well into computing the new Version 06, which will be the first time IMERG covers the last two decades and routinely provides morphed estimates in polar regions where the surface is snow- and ice-free. In this talk a few salient features of the IMERG algorithm will be summarized, then representative examples of IMERG products will be shown. This starts with basic results, such as animations of near-real-time maps, then extends to preliminary analyses of dataset characteristics. For example, the accumulations during Hurricane Harvey around Houston, Texas, USA, tended to be low, while accumulations along the Texas/Louisiana border to the northeast tended to be high. Furthermore, these opposite-sign differences occurred more or less simultaneously over much of the accumulation period. The working hypothesis is that there were systematic differences in the convective "regime" in the two places. The talk will end with a quick summary of the processing status and the future course of IMERG development.

Huffman, George J.↗
DOE OSTI2025

Real-time neutron multiplicity and source localization for criticality safety during fuel debris removal

Advancing neutron detection and analysis techniques for complex radiation environments is an ongoing focus in nuclear instrumentation and monitoring. This proposal presents research and development of a generalized real-time neutron monitoring and analysis system, applicable to any detector capable of producing time-tagged neutron count data. While the work is demonstrated using the Neutron Multiplication Analysis Detector (NoMAD), a modular 15-tube helium-3 (He-3) array, due to its availability, spatial resolution, and flexible deployment, the methods developed are extensible to other systems, including organic scintillators and fast digital detectors. This research investigates two complementary analytical techniques for real-time characterization of neutron emitting sources: neutron multiplicity estimation based on the Hage-Cifarelli formalism and spatial localization using supervised machine learning applied to spatial count rate patterns. These methods are designed to operate under dynamic, evolving conditions such as fuel debris retrieval or reactor startup, where neutron-emitting material geometries may be partially unknown or changing over time. By integrating statistical neutron emission data with spatial localization, this research aims to develop and evaluate methods for real time neutron monitoring, source characterization, and material verification. Key contributions include implementation of a low-latency data pipeline for continuous neutron multiplicity analysis, development and validation of machine learning models for spatial inference, and experimental evaluation of system performance under variable measurement conditions. The outcomes are intended to support applications in nuclear safeguards, verification, emergency response, and reactor startup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

PAVC: The foundation for a Pan-Arctic Vegetation Cover database

Field-measured Arctic vegetation cover data is essential for creating accurate, high-quality vegetation structure and composition maps. Extrapolating field data into high-resolution cover maps provides detailed, function-specific information for use in Earth System Models, vegetation classifications, and monitoring vegetation change over time and space. However, field campaigns that collect plant cover vary substantially in scope, method, and purpose, which makes them difficult to unify across data stores, and they are often not designed to meet remote sensing needs. In this work, we synthesized and harmonized field-based fractional cover data from various data stores to create a high-quality, consistent repository schema for remote sensing-based vegetation cover mapping applications. We developed a reproducible workflow for synthesizing visual estimate and point-intercept fractional cover data. The resultant Pan-Arctic Vegetation Cover (PAVC) database contains synthesized fractional cover at both the species and plant functional type levels. The latter includes absolute foliar cover for deciduous shrubs and trees, evergreen shrubs and trees, forbs, graminoids, lichen, bryophytes, and “other” vegetation, as well as absolute cover for litter and top cover for water and bare ground.

Steckler, Morgan R. [Oak Ridge National Laboratory↗
NASA NTRS2018

NASA Provides the Capability to Deliver Near Real-Time JPSS Data to Users in Order to Monitor Time-Sensitive Applications Such as Wildfires, Floods, Volcanic Eruptions, Tropical Cyclones and Extreme Weather Events

NASA's Land, Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE https://earthdata.nasa.gov/lance) serves near real time (NRT) data to monitor time sensitive applications such as monitoring wildfires, floods, volcanic eruptions, tropical cyclones and extreme weather events. It currently serves data and imagery from the Visible Infrared Imager Radiometer Suite (VIIRS) and Ozone Mapping and Profiler Suite (OMPS) S NPP (Suomi National Polar-orbiting Partnership) instruments and is in the process of integrating continuity data products from VIIRS and OMPS onboard the Joint Polar Satellite System (JPSS), via the JPSS data Hub, to continue to meet the needs of agencies, scientists and members of the general public. NASA's Earth Science Division (ESD) sponsored the EOSDIS development of LANCE in 2009 to provide a central point of access to high quality NRT data products and imagery for applications users. LANCE makes data available to the public within 3 hours of satellite observation and imagery within 4-5 hours of satellite observation. Full resolution browse imagery from LANCE are provided through the Global Imagery Browse Services (GIBS) which also fuels NASA's Worldview tool so that users can interactively browse near real time data. This data supports time critical applications and allows users to view current natural hazards and events and animate the imagery over time.

Near real time↗
NASA NTRS2011

NASA Satellite Data for Seagrass Health Modeling and Monitoring

Time series derived information for coastal waters will be used to provide input data for the Fong and Harwell model. The current MODIS land mask limits where the model can be applied; this project will: a) Apply MODIS data with resolution higher than the standard products (250-m vs. 1-km). b) Seek to refine the land mask. c) Explore nearby areas to use as proxies for time series directly over the beds. Novel processing approaches will be leveraged from other NASA projects and customized as inputs for seagrass productivity modeling

Spiering, Bruce A.↗
NASA NTRSDate not supplied

Dual and Multi-Spectral Band SLS Infrared Camera Systems

Based on the recent success of our strained-layer superlattice (SLS)-based infrared (IR) camera that performed Earth imaging from the International Space Station (ISS) in 2019 we have built, what we consider, to be the next generation multi-band SLS imaging system. The Compact Thermal Imager (CTI) was installed on the Robotic Refueling Mission 3 (RRM3) and attached to the exterior of the ISS. From this location we were able to capture 15 million images of a multitude of fires around the globe in 2019. This unexpected trove of data initiated quite a bit of scientific interest to further utilize this imaging capability but would include features to more precisely monitor terrestrial fires and other surface phenomena. To this end, we developed a technique to install specific bandpass filters directly onto the SLS detector hybrid assembly. Utilizing this technique we have built a CTI-2 camera system with two filters, 4 and 11µm, and have made a second detector assembly with six filter bands from 4-12µm. This second system will also be used to supplement Landsat remote imaging monitoring approximate land surface temperatures, monitor evapotranspiration, sea ice and glacier dynamics. The CTI-2 camera is based on a 1,024x1,024 (1kx1k) format SLS detector hybridized to a FLIR ISC0404 readout integrated circuit (ROIC). The six band SLS focal plane array is based on the 640x512 FLIR ISC 9803 ROIC. This camera system is based on the Landsat 8 and 9 Thermal IR Sensors (TIRS) instrument and one of its purposes is to perform ground truthing for the Landsat 8/9 data at higher spectral resolution. Both Landsat TIRS instruments are dual band thermal IR sensors centered on 11 and 12µm (each with about a 1µm bandpass). Both of our SLS systems utilize a Ricor K548 cryocooler. To streamline costs and development time we used commercial optics and both commercial and custom NASA electronic components. A primary feature of these camera systems is the incorporation of specific filters to collect fire data at ~3.9µm and thermal data at ~11µm. The CTI-2 instrument is designed for 37 m /pixel spatial resolution from 410km orbit (ISS orbit). In this paper, we will present the design and performance of the focal plane, optics, electronics and mechanical structure of the dual‑band CTI-2 and the focal plane performance of the six‑band focal plane.

Murzy Jhabvala↗
NASA NTRSDate not supplied

Compositional Analysis of Titan’s Atmosphere Using Spitzer Infrared Spectrograph Data

We present, for the first time, infrared spectra from the Spitzer Space Telescope’s Infrared Spectrograph (IRS) (2004-2008) of Titan in both the short wavelength-low resolution(SL, R=60~127,5.13-14.29 μm) and short wavelength-high resolution channels (SH, R=600, 9.89-19.51 μm) showing the emissions of CH4, C2H4, C2H2, C2H6, HCN, CO2, HC3N, C3H4, C4H2, and C3H8. Spitzer IRS data has been used to measure atmospheric composition of various Solar System bodies, including Neptune [1] and Uranus [2],[3]. Although Spitzer took multiple dedicated observations of Titan, none of the results have been modeled before. We conduct our own investigation of these datasets and search for new results. We retrieve temperature and gas composition profiles and compare the results obtained for Titan to those of the Cassini Composite Infrared Spectrometer (CIRS) and the Infrared Space Observatory Short Wavelength Spectrometer [4], and comment on the effect of spectral resolution on retrieved information content. We conclude by recommending gaps in current spectroscopic knowledge of molecular bands that could be addressed by theoretical and laboratory study to aid future astronomical studies of Titan, for example the James Webb Space Telescope (JWST) and the Stratospheric Observatory for Infrared Astronomy (SOFIA) Acknowledgments: Data analyzed in this project is public available online on the Spitzer Heritage Archive (sha.ipac.caltech.edu). This research has made use of the NASA/IPAC Infrared Science Archive, which is funded by the National Aeronautics and Space Administration and operated by the California Institute of Technology.

Titan↗
NASA NTRS1999

The Status of the Tropical Rainfall Measuring Mission (TRMM) after 2 Years in Orbit

The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, in related modeling applications and in new datasets tailored specifically for these applications. This paper reports the latest results regarding the calibration of the TRMM Microwave Imager, (TMI), Precipitation Radar (PR) and Visible and Infrared Sensor (VIRS). For the TMI, a new product is in place that corrects for a still unknown source of radiation leaking in to the TMI receiver. The PR calibration has been adjusted upward slightly (by 0.6 dBZ) to better match ground reference targets, while the VIRS calibration remains largely unchanged. In addition to the instrument calibration, great strides have been made with the rainfall algorithms as well, with the new rainfall products agreeing with each other to within less than 20% over monthly zonally averaged statistics. The TRMM Science Data and Information System (TSDIS) has responded equally well by making a number of new products, including real-time and fine resolution gridded rainfall fields available to the modeling community. The TRMM Ground Validation (GV) program is also responding with improved radar calibration techniques and rainfall algorithms to provide more accurate GV products which will be further enhanced with the new multiparameter 10 cm radar being developed for TRMM validation and precipitation studies. Progress in these various areas has, in turn, led to exciting new developments in the modeling area where Data Assimilation, and Weather Forecast models are showing dramatic improvements after the assimilation of observed rainfall fields.

Kummerow, C.↗
NASA NTRS1980

Measurement of Electromagnetic Properties of Lightning with 10 Nanosecond Resolution

Electromagnetic data recorded from lightning strikes are presented. The data analysis reveals general characteristics of fast electromagnetic fields measured at the ground including rise times, amplitudes, and time patterns. A look at the electromagnetic structure of lightning shows that the shortest rise times in the vicinity of 30 ns are associated with leader leader streamers. Lightning location is based on electromagnetic field characteristics and is compared to a nearby sky camera. The fields from both leaders and return strokes were measured and are discussed. The data were obtained during 1978 and 1979 from lightning strikes occuring within 5 kilometers of an underground metal instrumentation room located on South Baldy peak near Langmuir Laboratory, New Mexico. The computer controlled instrumentation consisted of sensors previously used for measuring the nuclear electromagnetic pulse (EMP) and analog-digital recorders with 10 ns sampling, 256 levels of resolution, and 2 kilobytes of internal memory.

Baum, C. E.↗
NASA NTRS2014

Assessing the Utility of 3-km Land Information System Soil Moisture Data for Drought Monitoring and Hydrologic Applications

The NASA Short term Prediction Research and Transition (SPoRT) Center in Huntsville, AL has been running a real-time configuration of the Noah land surface model within the NASA Land Information System (LIS) since June 2010. The SPoRT LIS version is run as a stand-alone land surface model over a Southeast Continental U.S. domain with 3-km grid spacing. The LIS contains output variables including soil moisture and temperature at various depths, skin temperature, surface heat fluxes, storm surface runoff, and green vegetation fraction (GVF). The GVF represents another real-time SPoRT product, which is derived from the Moderate Resolution Imaging Spectroradiometer instrument aboard NASA's Aqua and Terra satellites. These data have demonstrated operational utility for drought monitoring and hydrologic applications at the National Weather Service (NWS) office in Huntsville, AL since early 2011. The most relevant data for these applications have proven to be the moisture availability (%) in the 0-10 cm and 0-200 cm layers, and the volumetric soil moisture (%) in the 0-10 cm layer. In an effort to better understand their applicability among locations with different terrain, soil and vegetation types, SPoRT is conducting the first formal assessment of these data at NWS offices in Houston, TX, Huntsville, AL and Raleigh, NC during summer 2014. The goal of this assessment is to evaluate the LIS output in the context of assessing flood risk and determining drought designations for the U.S. Drought Monitor. Forecasters will provide formal feedback via a survey question web portal, in addition to the NASA SPoRT blog. In this presentation, the SPoRT LIS and its applications at NWS offices will be presented, along with information about the summer assessment, including training module development and preliminary results.

White, Kristopher D.↗
NASA NTRSDate not supplied

(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series

The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.

Aeronautics↗
NASA NTRS1999

Fast Time-Varying Volume Rendering Using Time-Space Partition (TSP) Tree

We present a new, algorithm for rapid rendering of time-varying volumes. A new hierarchical data structure that is capable of capturing both the temporal and the spatial coherence is proposed. Conventional hierarchical data structures such as octrees are effective in characterizing the homogeneity of the field values existing in the spatial domain. However, when treating time merely as another dimension for a time-varying field, difficulties frequently arise due to the discrepancy between the field's spatial and temporal resolutions. In addition, treating spatial and temporal dimensions equally often prevents the possibility of detecting the coherence that is unique in the temporal domain. Using the proposed data structure, our algorithm can meet the following goals. First, both spatial and temporal coherence are identified and exploited for accelerating the rendering process. Second, our algorithm allows the user to supply the desired error tolerances at run time for the purpose of image-quality/rendering-speed trade-off. Third, the amount of data that are required to be loaded into main memory is reduced, and thus the I/O overhead is minimized. This low I/O overhead makes our algorithm suitable for out-of-core applications.

Shen, Han-Wei↗
NASA NTRS2005

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

AVHRR (ADVANCED VERY HIGH RESOLUTION RADIOMETER)↗
NASA NTRS1981

Direct strike lightning measurement system

A research data system developed for in-flight measurement of direct and nearby lightning-strike characteristics is described. The measurement system consists of a wide-band analog recorder which records the continuous lightning scenario and fast sample-rate digital transient recorders with augmented memory capacity for increased time resolution of specific times of interest. Electromagnetic sensors with bandwidths exceeding 100 MHz are used which respond to rates of change of the quantities being measured. Data system immunity from electromagnetic interference is accomplished by the use of a dynamotor for power isolation, shielded system enclosure and fiber-optic data links.

Thomas, M. E.↗
DOE OSTI2025

Synchro-Waveform-Based Event Identification Using Multi-Task Time-Frequency Transform Networks

Influenced by the transient dynamics and reduced inertia characteristics of high-penetration renewable energy systems, power system events frequently exhibit distinct characteristics such as high-frequency components including wide-band oscillations and hyper-harmonics. This makes standard systems face challenges including significant latency and reduced accuracy due to limited data resolution. However, current methods face significant limitations, including insufficient pattern capture ability, low noise immunity, limited feature learning, and restricted localization capabilities, thereby hindering real-time performance. To tackle this issue, this paper proposed a novel synchro-waveform-based event identification approach via a Multi-task Time-frequency Transform Network (MTTNet). Initially, a Time-frequency Transform Block (TTB) is developed to extract both local and global information. The TTB leverages both Fourier and S-transforms to derive comprehensive time-frequency information from synchro-waveforms. Subsequently, a multi-task learning strategy is employed to identify the type and distinguish localization of events. Integrating the TTB and multi-task learning, the MTTNet is designed for synchro-waveform-based event identification, incorporating an adaptive weighting strategy and simplified computation for the S-transform. Two different datasets, comprising simulated and actual synchro-waveforms, are collected from the IEEE 123 bus system and a real-world high-penetration renewable energy system using a universal grid analyzer. Extensive experiments on various conditions are carried out. In conclusion, results demonstrated that the MTTNet consistently surpasses both basic and advanced baselines, with maximum improvements of 13.24% and 9.86%, respectively, while reducing the calculation burden by 15-19 times to achieve real-time event identification.

Event identification↗
DOE OSTI2026

Picosecond measurements of plastic scintillator pulse shapes from gamma-ray interactions

An understanding of the pulse shape of organic scintillators can provide insight into scintillation mechanisms and inform the selection of the optimal detector material for a given application. Although the timing properties of organic scintillators have been extensively studied, significant discrepancies persist in reported rise and decay times. New plastic scintillating media have also been developed in recent years for which no literature data exist. The goal of this work is to provide high-precision measurements of the pulse shape of a suite of fast plastic organic scintillators from Eljen Technology—EJ-200, EJ-204, EJ-208, EJ-230, EJ-232, and EJ-232Q (with 0.5% benzophenone)—under excitation from $γ$-ray sources. The contributors to the system temporal resolution were quantified, and the dominant source of uncertainty was identified as the determination of the start time of a scintillation event. A pulse shape model was applied to the reconstructed temporal distributions, and rise and decay times were extracted and compared with manufacturer specifications. This work outlines a measurement approach to obtain the pulse shape of organic scintillators in response to $γ$-rays with temporal resolution on the order of tens of picoseconds, yielding data required for modeling plastic scintillator based detection systems for a range of applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1994

Arctic sea ice concentrations from special sensor microwave imager and advanced very high resolution radiometer satellite data

Nearly coincident data from the special sensor microwave imager (SSM/I) and the advanced very high resolution radiometer (AVHRR) are used to compute and compare Arctic sea ice concentrations for different regions and times of the year. To help determine overall accuracies and to highlight sources of differences between passive microwave, optical wavelength, and thermal wavelength data, ice concentrations are estimated using two operational SSM/I ice concentration algorithms and with visible- and thermal-infrared wavelength AVHRR data. All algorithms capture the seasonal patterns of ice growth and melt. The ranges of differences fall within the general levels of uncertainty expected for each method and are similar to previous accuracy estimates. The estimated ice concentrations are all highly correlated, with uniform biases, although differences between individual pairs of observations can be large. On average, the NASA Team algorithm yielded 5% higher ice concentrations than the Bootstrap algorithm, while during nonmelt periods the two SSM/I algorithms agree to within 0.5%. These seasonal differences are consistent with the ways that the 19-GHz and 37-GHz microwave channels are used in the algorithms. When compared to the AVHRR-derived ice concentrations, the Team-algorithm results are more similar on average in terms of correlation and mean differences. However, the Team algorithm underestimates concentrations relative to the AVHRR output by 6% during cold months and overestimates by 3% during summer. Little seasonal difference exists between the Bootstrap and AVHRR results, with a mean difference of about 5%. Although the mean differences are less between the SSM/I-derived concentrations and concentrations estimated using AVHRR channel 1, the correlations appear substantially better between the SSM/I data and concentrations derived from AVHRR channel 4, particularly for the Team algorithm output.

Emery, W. J.↗