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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Atmospheric infrared sounder

This report summarizes the activities of two Atmospheric Infrared Sounder (AIRS) team members during the first half of 1995. Changes to the microwave first-guess algorithm have separated processing of Advanced Microwave Sounding Unit A (AMSU-A) from AMSU-B data so that the different spatial resolutions of the two instruments may eventually be considered. Two-layer cloud simulation data was processed with this algorithm. The retrieved water vapor column densities and liquid water are compared. The information content of AIRS data was applied to AMSU temperature profile retrievals in clear and cloudy atmospheres. The significance of this study for AIRS/AMSU processing lies in the improvement attributable to spatial averaging and in the good results obtained with a very simple algorithm when all of the channels are used. Uncertainty about the availability of either a Microwave Humidity Sensor (MHS) or AMSU-B for EOS has motivated consideration of possible low-cost alternative designs for a microwave humidity sensor. One possible configuration would have two local oscillators (compared to three for MHS) at 118.75 and 183.31 GHz. Retrieval performances of the two instruments were compared in a memorandum titled 'Comparative Analysis of Alternative MHS Configurations', which is attached.

Rosenkranz, Philip, W.↗
DOE OSTI2015

Providing Diurnal Sky Cover Data at ARM Sites

The Solmirus Corporation was awarded two-year funding to perform a comprehensive data analysis of observations made during Solmirus’ 2009 field campaign (conducted from May 21 to July 27, 2009 at the ARM SGP site) using their All Sky Infrared Visible Analyzer (ASIVA) instrument. The objective was to develop a suite of cloud property data products for the ASIVA instrument that could be implemented in real time and tailored for cloud modelers. This final report describes Solmirus’ research and findings enabled by this grant. The primary objective of this award was to develop a diurnal sky cover (SC) data product utilizing the ASIVA’s infrared (IR) radiometrically-calibrated data and is described in detail. Other data products discussed in this report include the sky cover derived from ASIVA’s visible channel and precipitable water vapor, cloud temperature (both brightness and color), and cloud height inferred from ASIVA’s IR channels.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Four dimensional observations of clouds from geosynchronous orbit using stereo display and measurement techniques on an interactive information processing system

Simultaneous Geosynchronous Operational Environmental Satellite (GOES) 1 km resolution visible image pairs can provide quantitative three dimensional measurements of clouds. These data have great potential for severe storms research and as a basic parameter measurement source for other areas of meteorology (e.g. climate). These stereo cloud height measurements are not subject to the errors and ambiguities caused by unknown cloud emissivity and temperature profiles that are associated with infrared techniques. This effort describes the display and measurement of stereo data using digital processing techniques.

Hasler, A. F.↗
NASA NTRS1977

Measurements of Cumulonimbus Clouds using quantitative satellite and radar data

Results are reported for a preliminary study of SMS-2 digital brightness and IR data obtained at frequent 5-7.5 min intervals. The clouds studied were over the Central and Great Plains in midlatitudes and thus were typical of an environment much different from that of the tropical oceans. The satellite data are compared to radar data for both a severe weather event and weak thundershower activity of the type which might be a target for weather modification efforts. The relative importance of short time interval satellite data is shown for both cases, and possible relationships between the two types of data are presented. It is concluded that (1) using a threshold technique for visible reflected brightness, precipitating vs. nonprecipitating clouds can be discriminated; (2) brightness is well related to cloud size and shape; and (3) satellite-derived growth rates may be a significant parameter to be used in determining storm severity, especially if rapid time sequence data are used during the development phase of the storm.

Negri, A. J.↗
NASA NTRS1988

Space shuttle natural environment analysis

Five major tasks are briefly outlined: development of detailed wind profile measurements for Kennedy Space Center (KSC) and Vandenberg Air Force Base (VAFB): development of software to construct meteorological data tapes for use in the STS Post Ascent Analysis; development of storage, access, and utilization codes for Global Cloud Cover data; development of software and meteorological data bases to establish launch delay risks at KSC and VAFB; and development of the meteorological tower 301 climatological data base at VAFB.

Batts, Wade↗
NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗
NASA NTRS2019

Advances in Neural Network Detection and Retrieval of Multilayer Clouds for CERES Using Multispectral Satellite Data

An artificial neural network (ANN) algorithm, employing several Aqua MODIS infrared channels, the retrieved total cloud visible optical depth, and vertical humidity profiles is trained to detect multilayer (ML) ice-over-water cloud systems as identified by matched CloudSat and CALIPSO (CC) data. The multilayer ANN, or MLANN, algorithm is also trained to retrieve the optical depth and the top and base heights of the upper-layer ice clouds in ML systems. The trained MLANN was applied to independent MODIS data resulting in a combined ML and single layer hit rate of 80% (77%) for nonpolar regions during the day (night). The results are more accurate than currently available methods and the previous version of the MLANN. Upper-layer cloud top and base heights are accurate to ±1.2 km and ±1.6 km, respectively, while the uncertainty in optical depth is ±0.457 and ±0.556 during day and night, respectively. Areas of further improvement and development are identified and will be addressed in future versions of the MLANN.

CERES↗
NASA NTRS1982

SASS wind ambiguity removal by direct minimization

An objective analysis procedure is presented which combines Seasat-A satellite scatterometer (SASS) data with other available data on wind speeds by minimizing an objective function of gridded wind speed values. The functions are defined as the loss functions for the SASS velocity data, the forecast, the SASS velocity magnitude data, and conventional wind speed data. Only aliases closest to the analysis were included, and a method for improving the first guess while using a minimization technique and slowly changing the parameters of the problem is introduced. The model is employed to predict the wind field for the North Atlantic on Sept. 10, 1978. Dealiased SASS data is compared with available ship readings, showing good agreement between the SASS dealiased winds and the winds measured at the surface. Expansion of the model to take in low-level cloud measurements, pressure data, and convergence and cloud level data correlations is discussed.

Hoffman, R. N.↗
NASA NTRSDate not supplied

Surface and Atmospheric Shortwave Radiative Fluxes From ISCCP Data and Fu-Liou Algorithm at Higher Spatial and Vertical Resolution

NASA/GEWEX Surface Radiation Budget (SRB) has provided surface and TOA shortwave and longwave radiative fluxes using International Satellite Cloud Climatology data as the primary input. Release 4.0 came out in 2019, with data from July 1983 through June 2017, and improved validation stats relative to Release 3.0 (Stackhouse et al., 2012). Release 4.0 used the newly reprocessed ISCCP H data set. The shortwave algorithm for versions 3 and 4 has been based on the Pinker and Laszlo (1992) algorithm, which relies on the satellite-measured shortwave radiance to produce a TOA albedo. This background TOA albedo is made utilizing the background clear-sky visible radiance (called clear-sky composite radiance in the ISCCP data) and applying narrowband-to-broadband angular distribution models. Using a climatological aerosol assumption, the surface albedo is estimated using radiative transfer based (i.e., Fu/Liou radiative transfer model; Fu and Liou, 1993) look-up tables. Using this surface albedo and an instantaneous TOA albedo, the look-up tables are used to adjust both the aerosol optical depth (for clear sky) and cloud optical depth (for cloudy sky) for each scene. These properties and look up tables are then used to generate surface fluxes. While this has worked well to provide useful fluxes, it has occasionally resulted in inaccurate direct and diffuse surface SW fluxes due to the overreliance on aerosol optical depth. With increased computational power and storage now available, a more direct approach is now possible. Here we present a different approach for a future high resolution SRB Release 5.0. We replace the Pinker-Laszlo lookup table approach with a forward call to the Fu-Liou radiative transfer model as modified by the CERES team (Rose et al., 2006). In addition to being a proven radiation code, Fu-Liou allows the calculation of fluxes at different atmospheric levels and spectral bands, which will provide more insight into the surface radiation budget, its variability and attribution. It is expected that horizontal resolution will increase to at least 0.5°x0.5° from the current 1°x1°. Here we demonstrate a preliminary look at the next SRB, and show comparisons with the current release.

Earth Radiation Budget↗