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NASA NTRSDate not supplied

Short Time Scale Stability Monitoring of GOES-16 Visible Channels by Utilizing Daily Inter-Calibration Events with both VIIRS and MODIS Sensors

The CERES project relies on MODIS, VIIRS and geostationary (GEO) imager retrieved cloud properties to compute surface fluxes and convert CERES and GEO radiances into TOA fluxes. The CERES TOA and surface fluxes need to be of climate quality and any anomaly or discontinuity in the calibration of the MODIS, VIIRS, GEO radiances need to be mitigated or avoided. Due to the nature of the CERES instrument calibration, there is a lag time of 3 months before the processing of the CERES product. This allows the CERES team to investigate any unforeseen problems in the input datasets or GEO calibration discontinuities or anomalies before processing. The CERES geostationary imager calibration team is developing a daily monitoring system of GEO, MODIS and VIIRS visible channel radiances in order to detect any day to day discontinuities as part of the CERES/GEO coincident ray-matching calibration efforts. a GEO discontinuity can be detected using two MODIS and 2 VIIRS sensors simultaneously, thus increasing the sampling greatly over a single GEO/LEO radiance pairs. This method is being automated and has already detected three erroneous radiometric calibration events, which were verified with the GOES-16 event log page. One advantage of daily monitoring is that the time period needed to verify calibration drifts is reduced and the confidence to detect even smaller magnitudes of the calibration drift is increased over monthly monitoring. By utilizing Terra and Aqua MODIS and NPP and NOAA20 VIIRS imagers to inter-calibrate GOES-16, the GOES-16 calibration can be referenced to anyone of these imagers. If the CERES project transitions between the Aqua-MODIS imager to the NOAA20 VIIRS imager, the NOAA-20 VIIRS imager can be radiometrically scale to Aqua-MODIS calibration, thus avoiding a GOES-16 calibration discontinuity.

David Robert Doelling↗

NASA NTRS1979

Visible flux variations across finite clouds

A radiative transfer model developed to computer visible flux variations across and within finite clouds of varying shapes is described. The technique has much of the versatility of Monte Carlo models, as well as the speed of the analytical finite cloud models.

Mosher, F. R.↗

NASA NTRS1980

Fragmentation of rotating protostellar clouds

With a three-dimensional hydrodynamic computer code, the behavior of rotating, isothermal gas clouds as they collapse from Jeans unstable configurations is examined in order to determine whether they are susceptible to fragmentation during the initial dynamic collapse phase of evolution. It is found that a gas cloud will not fragment unless (1) it begins collapsing from a radius much smaller than the Jeans radius (i.e., the cloud initially encloses many Jeans masses) and (2) irregularities in the cloud's initial structure (specifically, density inhomogeneities) enclose more than one Jeans mass of material. Instead of fragmenting, most of the models collapse to a ring configuration. The rings appear to be less susceptible to fragmentation from arbitrary perturbations in their structure than has previously been indicated in other work. Because the models, which include the effects of gas pressure, do not readily fragment during a phase of dynamic collapse, it is suggested that gas clouds in the galactic disk undergo fragmentation only during quasi-equilibrium phases of their evolution.

Tohline, J. E.↗

NASA NTRSDate not supplied

Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗

NASA NTRS2018

Range and Intensity Image-Based Terrain and Vehicle Relative Pose Estimation System

A navigation system includes an image acquisition device for acquiring a range image of a target vehicle, at least one processor, a memory including a target vehicle model and computer readable program code, where the processor and the computer readable program code are configured to cause the navigation system to convert the range image to a point cloud having three dimensions, compute a transform from the target vehicle model to the point cloud, and use the transform to estimate the target vehicle's attitude and position for capturing the target vehicle.

Gill, Nathaniel↗

NASA NTRS1977

Microphysical response of cloud droplets in a fluctuating updraft

The effect of a fluctuating updraft upon a distribution of cloud droplets is examined. Computations are performed for fourteen vertical velocity patterns; each allows a closed parcel of cloud air to undergo downward as well as upward motion. Droplet solution and curvature effects are included. The classical equations for the growth rate of an individual droplet by vapor condensation relies on simplifying assumptions. Those assumptions are isolated and examined. A unique approach is presented in which all energy sources and sinks of a droplet may be considered and is termed the explicit model. It is speculated that the explicit model may enhance the growth of large droplets at greater heights. Such a model is beneficial to the studies of pollution scavenging and acid rain.

Harding, D. D.↗

NASA NTRS2000

Sensitivity of Cirrus Bidirectional Reflectance at MODIS Bands to Vertical Inhomogeneity of Ice Crystal Habits and Size Distribution

A common assumption in satellite imager-based cirrus retrieval algorithms is that the radiative properties of a cirrus cloud may be represented by those associated with a specific ice crystal shape (or habit) and a single particle size distribution. However, observations of cirrus clouds have shown that the shapes and sizes of ice crystals may vary substantially with height within the clouds. In this study we investigate the sensitivity of the top-of-atmosphere bidirectional reflectances at two MODIS bands centered at 0.65 micron and 2.11 micron to the cirrus models assumed to be either a single homogeneous layer or three distinct but contiguous, layers. First, we define the single- and three-layer cirrus cloud models with respect to ice crystal habit and size distribution on the basis of in situ replicator data acquired during the First ISCCP Regional Experiment (FIRE-II), held in Kansas during the fall of 1991. Subsequently, fundamental light scattering and radiative transfer theory is employed to determine the single scattering and the bulk radiative properties of the cirrus cloud. Regarding the radiative transfer computations, we present a discrete form of the adding/doubling principle by introducing a direct transmission function, which is computationally straightforward and efficient an improvement over previous methods. For the 0.65 micron band, at which absorption by ice is negligible, there is little difference between the bidirectional reflectances calculated for the one- and three-layer cirrus models, suggesting that the vertical inhomogeneity effect is relatively unimportant. At the 2.11 micron band, the bidirectional reflectances computed for both optically thin (tau = 1) and thick (tau = 10) cirrus clouds show significant differences between the results for the one- and three-layer models. The reflectances computed for the three-layer cirrus model are substantially larger than those computed for the single-layer cirrus. Finally, we find that cloud reflectance is very sensitive to the optical properties of the small crystals that predominate in the top layer of the three-layer cirrus model. It is critical to define the most realistic geometric shape for the small "quasi-spherical" ice crystals in the top layer for obtaining reliable single-scattering parameters and bulk radiative properties of cirrus.

Yang, P.↗

NASA NTRS2017

Archive Management of NASA Earth Observation Data to Support Cloud Analysis

NASA collects, processes and distributes petabytes of Earth Observation (EO) data from satellites, aircraft, in situ instruments and model output, with an order of magnitude increase expected by 2024. Cloud-based web object storage (WOS) of these data can simplify the execution of such an increase. More importantly, it can also facilitate user analysis of those volumes by making the data available to the massively parallel computing power in the cloud. However, storing EO data in cloud WOS has a ripple effect throughout the NASA archive system with unexpected challenges and opportunities. One challenge is modifying data servicing software (such as Web Coverage Service servers) to access and subset data that are no longer on a directly accessible file system, but rather in cloud WOS. Opportunities include refactoring of the archive software to a cloud-native architecture; virtualizing data products by computing on demand; and reorganizing data to be more analysis-friendly.

Lynnes, Christopher↗

NASA NTRS2017

Archive Management of NASA Earth Observation Data to Support Cloud Analysis

Lynnes, Christopher↗

NASA NTRS1993

Inference of cirrus cloud properties using satellite-observed visible and infrared radiances. I - Parameterization of radiance fields

The impact of using phase functions for spherical droplets and hexagonal ice crystals to analyze radiances from cirrus is examined. Adding-doubling radiative transfer calculations are employed to compute radiances for different cloud thicknesses and heights over various backgrounds. These radiances are used to develop parameterizations of top-of-the-atmosphere visible reflectance and IR emittance using tables of reflectances as a function of cloud optical depth, viewing and illumination angles, and microphysics. This parameterization, which includes Rayleigh scattering, ozone absorption, variable cloud height, and an anisotropic surface reflectance, reproduces the computed top-of-the-atmosphere reflectances with an accruacy of +/- 6 percent for four microphysical models: 10-micron water droplet, small symmetric crystal, cirrostratus, and cirrus uncinus. The accuracy is twice that of previous models.

Minnis, Patrick↗

NASA NTRS2002

Parameterization of Shortwave Cloud Optical Properties for a Mixture of Ice Particle Habits for use in Atmospheric Models

Based on the single-scattering optical properties pre-computed with an improved geometric optics method, the bulk absorption coefficient, single-scattering albedo, and asymmetry factor of ice particles have been parameterized as a function of the effective particle size of a mixture of ice habits, the ice water amount, and spectral band. The parameterization has been applied to computing fluxes for sample clouds with various particle size distributions and assumed mixtures of particle habits. It is found that flux calculations are not overly sensitive to the assumed particle habits if the definition of the effective particle size is consistent with the particle habits that the parameterization is based. Otherwise, the error in the flux calculations could reach a magnitude unacceptable for climate studies. Different from many previous studies, the parameterization requires only an effective particle size representing all ice habits in a cloud layer, but not the effective size of individual ice habits.

Chou, Ming-Dah↗

DOE OSTI2025

torc (Torc Workflow Management System) [SWR-24-127]

This software package orchestrates execution of a workflow of jobs on distributed computing resources. It is optimized for use on HPCs with Slurm, but also can be used in the cloud and on local computers. Please refer to the documentation at https://nrel.github.io/torc

Thom, Daniel [National Renewable Energy Laboratory↗

NASA NTRS1967

Results of adaptive predictor studies, II

Conditional expectation predictor applied to data compression, and computer simulation of Tiros cloud cover picture data

TIROS SATELLITE↗

NASA NTRSDate not supplied

Integrating Multi-agency Data Products in a Cloud-based Platform for Streamlined Discovery, Visualization, and Use

Earth science data users almost always have an interest in utilizing geospatial data from multiple agencies. As computing capability and cloud-based infrastructures accelerate the pace at which scientific research can be done, there is a growing need to enable search, discovery, and use of multi-agency geospatial observations relevant for a common use case - without undergoing the search and discovery process in a less efficient, disparate path with each agency. NASA’s Earth Observing System Data and Information System (EOSDIS) and NOAA’s National Environmental Satellite, Data and Information Service (NESDIS) both support a wide range of Earth science disciplines’ research, operations, and applications activities. Presently, however, there are few examples of data discovery frameworks supporting an inquiry of both NASA’s and NOAA’s extensive archives of Earth observations that are equally suitable for a particular science scenario, regardless of the agency that “owns” the data. NASA and NOAA are collaborating on a data expedition platform for exploring fire weather using data products from both agencies. Users will be able to search, discover, and visualize NASA and NOAA products in one interface. Each agency will curate metadata for its respective datasets, providing for a rich search experience. The collaboration will pilot a shared search interface into these metadata datastores. Data products will be stored in the cloud in cloud-optimized format(s). These formats will allow for optimized data access and visualization to support the “data expedition”. Avenues for further development and application of this cloud-based, multi-agency data provisioning platform will also be discussed.

cloud-based technology↗

NASA NTRS2019

Jumping the Queue: From NASA to the Commercial Cloud

NASA's High-End Computing Capability (HECC) Project has made it possible for its users to run on commercial cloud resources in a seamless way. In the first of three phases, we implemented a pilot project for a few users, enabling them to “jump the queue” and burst jobs from the HECC environment to Amazon Web Services (AWS). By using GPU-accelerated nodes at AWS, the users were able to make significant advances in their research. The second phase of the project made AWS access available to all HECC users and added accounting to make users responsible for cloud charges. We are also enabling export-controlled work through the use of AWS GovCloud. In the third phase, we will add web-based mechanisms to permit non-HECC users to access cloud resources for their HPC projects.

Hood, Robert↗

NASA NTRS1989

Reflection of solar radiation by a cylindrical cloud

Potential applications of an analytic method for computing the solar radiation reflected by a cylindrical cloud are discussed, including studies of radiative transfer within finite clouds and evaluations of these effects on other clouds and on remote sensing problems involving finite clouds. The pattern of reflected sunlight from a cylindrical cloud as seen at a large distance has been considered and described by the bidirectional function method for finite cloud analysis, as previously studied theoretically for plane-parallel atmospheres by McKee and Cox (1974); Schmetz and Raschke (1981); and Stuhlmann et al. (1985). However, the lack of three-dimensional radiative transfer solutions for anisotropic scattering media have hampered theoretical investigations of bidirectional functions for finite clouds. The present approach permits expression of the directional variation of the radiation field as a spherical harmonic series to any desired degree and order.

Smith, G. L.↗

NASA NTRS1981

Transport of infrared radiation in cuboidal clouds

The transport of infrared radiation in a single cuboidal cloud is modeled using a variable azimuth two-stream approximation. Computations are made at 10 microns for a Deirmendjian (1969) C-1 water cloud where the single scattering albedo is equal to 0.638 and the asymmetry parameter is 0.865. The results indicate that the emittance of the top face of the model cloud is always less than that for a plane parallel cloud of the same optical depth. The hemispheric flux escaping from the cloud top possesses a gradient from the center to the edges which are warmer when the cloud is over warmer ground. Cooling rate calculations in the 8-13.6 micron region demonstrate that there is cooling out of the sides of the cloud at all levels even when there is heating of the core from the ground below. The radiances exiting from model cuboidal clouds are computed by path integration over the source function obtained with the two-stream approximation. Results indicate that the brightness temperature measured from finite clouds will overestimate the cloud-top temperature.

Harshvardhan, MR.↗

NASA NTRS1982

Applications of stereoscopic height computations from dual geosynchronous satellite data/joint NASA-Japan stereo project

Stereoscopic heights of the top of an Oklahoma thunderstorm were computed, finding that high cloud tops are not always characterized by very cold IR temperature. The identical method was also applied to the computation of stereo heights based on GOES West and GMS stereo pairs obtained under the NASA-JAPAN cooperative program. It was found that stereo techniques are extremely useful in understanding the structure of thunderstorms in the United States, as well as that of hurricanes over the South Pacific.

Fujita, T. T.↗