Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cloud systems”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Use NASA Earthdata in the Cloud

With the impending arrival of new, high-data-volume Earth observation missions, NASA’s ability to effectively ingest, process, and archive large amounts of data requires the most cost-effective, flexible, and scalable data-management architectures and technologies. To meet these demands, NASA's Earth Science Data Systems (ESDS) Program is implementing a strategic vision to develop and operate multiple components of NASA's Earth Observing System Data and Information System (EOSDIS) in a commercial cloud environment. As more earth observing data is moved into the cloud, NASA EOSDIS wants to share our reasoning for moving data into the commercial cloud, as well as demonstrate how end-users can take advantage of both data in the cloud and cloud-deployed services. This presentation explains the enterprise reasons for moving data into the cloud, specifically the scalability of cloud systems, the flexibility to pivot to the most optimal language/system/architecture, and the reduced redundancy of a common architecture. Then we primarily focus on the user-driven reasons for moving to the cloud. Equal access to high performance computing helps all parties, especially users that don't have access to their own on-premise computing infrastructure. Rapid deployment allows users to spin up their own systems without needing the extensive platform previously required for large scale development. Cost effectiveness allows users a wide breadth of computing options, from super computer ability to small scale development, which can help underserved communities. Finally we link to internal resources that users can utilize to begin their cloud based development journey without having to be an expert in the field.

Nicholas Doty↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10947-DND

There are large uncertainties in quantifying dust effects on the climate because of the limitations on the measurements and observations of dust-cloud-precipitation-dynamics interactions. As a major terrestrial source of atmospheric aerosols, dusts may serve as a significant climate forcing for the changing climate due to its effect on solar and thermal radiation as well as on clouds and precipitation processes. Latest satellites measurements enable us to determine dust loadings and cloud distributions and can potentially be used to reduce the uncertainties in the estimations of aerosol effects on climate. This study uses sensors on various satellites to investigate the impact of mineral dust on cloud microphysical and precipitation processes in convective systems. A trans-Atlantic dust outbreak of Saharan origin occurring in early March 2004 is considered. For the observed convective systems under a given convective strength, small hydrometeors were found more prevalent in the dusty stratiform regions than in those regions that were dust free. Evidence of abundant cloud ice particles in the dust regions, particularly at altitudes where heterogeneous nucleation of mineral dust prevails, further supports the observed changes of clouds and precipitation. These microphysical effects of the dusts on clouds are to shift the size spectrum of precipitation-sized hydrometeors from heavy precipitation to light precipitation and ultimately to suppress precipitation and increase the lifecycle of cloud systems, especially for stratiform clouds.

B Lin↗
DOE OSTI2021

Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems

Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with cameras and/or LiDAR sensors are being widely used for topographic mapping in a variety of applications such as precision agriculture, coastal monitoring, and archaeological documentation. Integration of image-based and LiDAR point clouds can provide a comprehensive 3D model of the area of interest. For such integration, ensuring a good alignment between data from the different sources is critical. Although many works have been conducted on this topic, there is still a need for a rigorous integration approach that minimizes the discrepancy between camera and LiDAR data caused by inaccurate system calibration parameters and/or trajectory artifacts. This study proposes an automated tightly-coupled camera/LiDAR integration workflow for GNSS/INS-assisted UAV systems. The proposed strategy is conducted in three main steps. First, an image-based point cloud is generated using a LiDAR/GNSS/INS-assisted structure from motion (SfM) strategy. Then, feature correspondences between image-based and LiDAR point clouds are automatically identified. Finally, an integrated-bundle adjustment procedure including image points, LiDAR raw measurements, and GNSS/INS information is conducted to minimize the discrepancy between point clouds from different sensors while estimating system calibration parameters and refining the trajectory information. The proposed SfM strategy and integration framework are evaluated using five datasets. The SfM results show that using LiDAR data can facilitate feature matching and further increase the number of reconstructed 3D points. The experimental results also illustrate that the developed automated camera/LiDAR integration strategy is capable of accurately estimating system calibration parameters to achieve good alignment among camera/LiDAR data from single/multiple systems. Finally, an absolute accuracy in the range of 3–5 cm is achieved for the image/LiDAR point clouds after the integration process.

42 ENGINEERING↗
NASA NTRSDate not supplied

Performance Evaluation of Clouds and the Earth’s Radiant Energy System (CERES) Instruments in Generating A Stable Earth Radiation Budget Multi-Decadal Data Record

Clouds and the Earth’s Radiant Energy System (CERES) instrument is designed to measure the earth-reflected solar and earth-emitted longwave radiances, two components of the Earth Radiation Budget. CERES instrument measure radiances in 0.3 to 5.0 micron region with Shortwave (SW) sensor, 0.3 to >100 microns with Total (TOT) sensor, and either 8 - 12 micron with Window (WN) sensor or 5 – 35 micron with longwave (LW) sensor. The on-board internal calibration module (ICM) is used to monitor the stability of the sensors and to correct the pre-launch determined sensor gains for radiance calculations. Corrections for spectral changes occurring in different wavelength regions observed through vicarious studies were applied to sensor response function used in radiance determination. The resulting global flux long term trends from each instrument have shown consistent behavior and provided a stable global record of Top of the Atmosphere (TOA) shortwave and longwave fluxes for the Earth radiation budget climate data record.

Earth Radiation Budget↗
NASA NTRS1982

METEOSAT studies of clouds and radiation budget

Radiation budget studies of the atmosphere/surface system from Meteosat, cloud parameter determination from space, and sea surface temperature measurements from TIROS N data are all described. This work was carried out on the interactive planetary image processing system (IPIPS), which allows interactive manipulationion of the image data in addition to the conventional computational tasks. The current hardware configuration of IPIPS is shown. The I(2)S is the principal interactive display allowing interaction via a trackball, four buttons under program control, or a touch tablet. Simple image processing operations such as contrast enhancing, pseudocoloring, histogram equalization, and multispectral combinations, can all be executed at the push of a button.

Saunders, R. W.↗
NASA NTRS2001

Measurements of the Vertical Structure of Aerosols and Clouds Over the Ocean Using Micro-Pulse LIDAR Systems

The determination of the vertical distribution of aerosols and clouds over the ocean is needed for accurate retrievals of ocean color from satellites observations. The presence of absorbing aerosol layers, especially at altitudes above the boundary layer, has been shown to influence the calculation of ocean color. Also, satellite data must be correctly screened for the presence of clouds, particularly cirrus, in order to measure ocean color. One instrument capable of providing this information is a lidar, which uses pulses of laser light to profile the vertical distribution of aerosol and cloud layers in the atmosphere. However, lidar systems prior to the 1990s were large, expensive, and not eye-safe which made them unsuitable for cruise deployments. During the 1990s the first small, autonomous, and eye-safe lidar system became available: the micro-pulse lidar, or MPL. The MPL is a compact and eye-safe lidar system capable of determining the range of aerosols and clouds by firing a short pulse of laser light (523 nm) and measuring the time-of-flight from pulse transmission to reception of a returned signal. The returned signal is a function of time, converted into range using the speed of light, and is proportional to the amount of light backscattered by atmospheric molecules (Rayleigh scattering), aerosols, and clouds. The MPL achieves ANSI eye-safe standards by sending laser pulses at low energy (micro-J) and expanding the beam to 20.32 cm in diameter. A fast pulse-repetition-frequency (2500 Hz) is used to achieve a good signal-to-noise, despite the low output energy. The MPL has a small field-of-view (< 100 micro-rad) and signals received with the instrument do not contain multiple scattering effects. The MPL has been used successfully at a number of long-term sites and also in several field experiments around the world.

Welton, Ellsworth J.↗
NASA NTRS1977

Cloud elevations in near real time

The paper shows how cloud elevations can be obtained from geosynchronous satellites within 15 min of an event and to an accuracy of less than 250 m. After careful consideration of pertinent factors, it is decided that a dual satellite system in parallel geosynchronous orbits would be the most feasible configuration for stereographic imaging of cloud systems. The discussion covers tracking accuracy, choice of imaging systems, data transmission and processing, image correlation, and proposed cloud heighting system. The described partially man-interactive system is substantially within the present state of the art and could be the basis for an interim system for cloud height determination.

Shull, C. W.↗
DOE OSTI2025

Evaluation of Marine Boundary Layer Clouds Over the Northeast Pacific During the CSET Campaign in E3SM Version 2

It is still challenging to reproduce marine boundary layer (MBL) clouds well in large-scale models despite their importance to the Earth's radiation budget and hydrological cycle. This study evaluates representation of the MBL and clouds in the Energy Exascale Earth System Model (E3SM) version 2. This study compares the E3SM simulation results with remote sensing and reanalysis data during the Cloud System Evolution in the Trades (CSET) field campaign to better understand the stratocumulus-to-cumulus cloud transition (SCT) over the northeast Pacific. E3SM results are extracted along the CSET Lagrangian trajectories. The comparison shows that the E3SM simulation applying horizontal wind nudging performs well in reproducing thermodynamic variables of the MBL and evolution trends of cloud variables along the trajectories. However, substantial overestimations of aerosol and cloud drop number (N d ) are observed, which is explained as an issue with version 2 of the model. Cloud fraction (CF) does decrease from the Californian coast to Hawaii in the E3SM simulation, but most CF values indicate either an overcast or almost clear sky, which differs from satellite and reanalysis data. The effect of N d overestimation on CF evolution is assessed via prescribed-N d simulations. Those simulations with N d modifications show negligible CF changes. A comparison of estimated inversion strength (EIS) also shows that the simulated EIS values are similar to those of reanalysis data. Our study suggests that cloud macrophysics and boundary layer processes are more important in improving the simulation to capture the SCT than refining the model's thermodynamics or cloud microphysics.

Choi, Kyoung Ock [Univ. of Washington, Seattle, WA↗
NASA NTRS2019

Federated Cloud Challenges in NASA's Earth Science Data Systems (Why So Difficult?)

NASA is presented with a number of opportunities and challenges in federating its Earth Science Data Systems in the burgeoning world of cloud computing. Cloud hosting of Earth Science data provides a new way of bringing data together, at least from a virtual location sense, and is one of the main motives for NASA to host data there. However, NASA is also faced with a Big Data Variety challenge, brought on by the variety of the EO datasets in its archives. This diversity requires many diverse science archives to service the different science communities. As a result, nearly every major function in the Earth Observing System Data and Information System (EOSDIS) must also be federated across its data centers. This pattern is repeated with many of the outside agencies and organizations that EOSDIS federates with, such as the Committee for Earth Observing Satellites, leading to pioneering work on "deep federation" in a joint project with the European Space Agency to develop a Multi-Mission Algorithm and Analysis Platform.

Lynnes, Christopher↗
NASA NTRS1998

Characterization of Mesoscale Convective Systems by Means of Composite Radar Reflectivity Data

A mesoscale convective system (MCS) is broadly defined as a cloud and precipitation system of mesoscale dimensions (often too large for most aircraft to circumnavigate) with deep-convective activity concentrated in at least part of the MCS, or present during part of its evolution. A large areal fraction of MCSs is stratiform in nature, yet estimates from MCSs over the Great Plains, the Southeast, and tropical waters indicate that at least half of the precipitation is of convective origin. The presence of localized convection is important, because within convective towers cloud particles and hydrometeors are carried upward towards the cloud top. Ice crystals then move over more stratiform regions, either laterally, or through in situ settling over decaying and spreading convection. These ice crystals then grow to precipitation-size particles in mid- to upper tropospheric mesoscale updrafts. The convective portion of a MCS is often a more or less continuous line of thunderstorms, and may be either short-lived or long-lived. Geerts (1997) presents a preliminary climatology of MCSs in the southeastern USA, using just one year of composite digital radar reflectivity data. In this study MCSs are identified and characterized by means of visual inspection of animated images. A total of 398 MCSs were identified. In the warm season MCSs were found to be about twice as frequent as in the cold season. The average lifetime and maximum length of MCSs are 9 hours, and 350 km, respectively, but some MCSs are much larger and more persistent. In the summer months small and short-lived MCSs are relatively more common, whereas in winter larger and longer-lived systems occur more frequently. MCSs occur more commonly in the afternoon, in phase with thunderstorm activity, but the amplitude of the diurnal cycle is small compared to that of observed thunderstorms. It is estimated that in the Southeast more than half of all precipitation and severe weather results from MCSs.

Geerts, Bart↗
NASA NTRS2019

The NASA Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) Mission: an Emerging Era of Global, Hyperspectral Earth System Remote Sensing

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission represents NASA's next investment in satellite ocean color and the study of Earth's ocean-atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth's changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will also provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their reflectance. The primary PACE instrument - the Ocean Color Instrument (OCI) - is a hyperspectral imaging radiometer that spans the ultraviolet to shortwave infrared, with a ground sample distance of 1-kilometer at nadir. This includes continuous collection of spectra from 340 to 890 nanometers in 5-nanometer steps. The PACE payload is complemented by two multi-angle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022-to-early 2023, the PACE observatory will enable significant advances in the study of Earth's biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean-atmosphere system. We present a brief overview of the PACE mission, followed by a detailed discussion of the capabilities and design concept of OCI.

Passive Remote Sensing↗
NASA NTRS2019

The NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Mission: An Emerging Era of Global, Hyperspectral Earth System Remote Sensing

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission represents NASA’s next investment in satellite ocean color and the study of Earth’s ocean-atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth's changing climate. PACE objectives include extending systematic cloud, aerosol, ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles and ecosystem responses to a changing climate, as well as improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will also provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their reflectance. The primary PACE instrument – the Ocean Color Instrument (OCI) – is a hyperspectral imaging radiometer that spans the ultraviolet to shortwave infrared, with a ground sample distance of 1-km at nadir. This includes continuous collection of spectra from 340 nm to 890 nm in 5 nm steps. The PACE payload is complemented by two multi-angle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022-to-early 2023, the PACE observatory will enable significant advances in the study of Earth’s biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean-atmosphere system. We present a brief overview of the PACE mission, followed by a discussion of the capabilities and design concept of OCI.

hyperspectral radiometer↗
NASA NTRS2006

Statistical Analyses of Satellite Cloud Object Data from CERES: Tropical Convective Cloud Objects During 1998 El Nino and Validation of the Fixed Anvil Temperature Hypothesis - Part II

Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January-August 1998 are examined using the Tropical Rainfall Measuring Mission/ Clouds and the Earth s Radiant Energy System single scanner footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud-object size, sea surface temperature (SST), and satellite precessing cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the Earth composed of satellite footprints within a single dominant cloud-system type. It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100 - 150 km (small), 150 - 300 km (medium), and > 300 km (large), respectively, except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed towards high SSTs, high cloud tops, low cloud-top temperature, large ice water path, high cloud optical depth, low outgoing longwave (LW) radiation, and high albedo than the smaller-size category. As SST varied from one satellite precessing cycle to another, the changes in macrophysical properties of cloud objects over the entire tropical Pacific were small for the large-size category of cloud objects, relative to those of the small- and medium-size categories. This result suggests that the fixed anvil temperature hypothesis of Hartmann and Larson may be valid for the large-size category. Combining with the result that a higher percentage of the large-size category of cloud objects occurs during higher SST subperiods, this implies that macrophysical properties of cloud objects would be less sensitive to further warming of the climate. On the other hand, when cloud objects are classified according to SSTs where large-scale dynamics plays important roles, statistical characteristics of cloud microphysical properties, optical depth and albedo are not sensitive to the SST, but those of cloud macrophysical properties are strongly dependent upon the SST. Frequency distributions of vertical velocity from the European Center for Medium-range Weather Forecasts model that is matched to each cloud object are used to interpret some of the findings in this study.

Xu, Kuan-Man↗
DOE OSTI2021

Control architecture for predictive and optimal vehicle operations in a single vehicle environment

There is disclosed a cloud computing control system for vehicle speed control and also for control of a vehicle in a platoon. The cloud computing control system determines a speed trajectory and neutral coasting command for a first vehicle of the platoon and a vehicle controller determines a reference speed for the first vehicle in response to the speed trajectory and the neutral coasting command, and is response to one or more vehicle specific factors associated with the first vehicle.

Borhan, Hoseinali↗
NASA NTRS1989

Jupiter's Great Red Spot as a shallow water system

Voyager cloud-top velocity data for Jupiter's Great Red Spot (GRS) is used to derive the bottom topography up to a constant that depends on the unknown radius of deformation. The bottom topography is inferred from the Bernoulli streamfunction, kinetic energy per unit mass, and absolute vorticity values derived from the velocity data. The results are used to calculate potential vorticity versus latitude far from the vortex. It is found that the deep atmosphere is in differential motion and that the far-field potential vorticity gradient changes sign at several latitudes. Numerical experiments are conducted to study the time-dependent behavior of the shallow water analog of Jupiter's analog.

Dowling, Timothy E.↗
NASA NTRS2014

First Satellite-detected Perturbations of Outgoing Longwave Radiation Associated with Blowing Snow Events over Antarctica

We present the first satellite-detected perturbations of the outgoing longwave radiation (OLR) associated with blowing snow events over the Antarctic ice sheet using data from Cloud-Aerosol Lidar with Orthogonal Polarization and Clouds and the Earth's Radiant Energy System. Significant cloud-free OLR differences are observed between the clear and blowing snow sky, with the sign andmagnitude depending on season and time of the day. During nighttime, OLRs are usually larger when blowing snow is present; the average difference in OLRs between without and with blowing snow over the East Antarctic Ice Sheet is about 5.2 W/m2 for the winter months of 2009. During daytime, in contrast, the OLR perturbation is usually smaller or even has the opposite sign. The observed seasonal variations and day-night differences in the OLR perturbation are consistent with theoretical calculations of the influence of blowing snow on OLR. Detailed atmospheric profiles are needed to quantify the radiative effect of blowing snow from the satellite observations.

outgoing longwave radiation (OLR)↗
NASA NTRS2017

Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel Definition

The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC delivers adequate spatial resolution imagery but only in shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and longwave broadband windows. Accurate calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud properties retrievals from low earth orbit (LEO, including NASA Terra and Aqua MODIS, Suomi-NPP VIIRS, and NOAA AVHRR) and geosynchronous (GEO, including GOES east and west, METEOSAT, INSAT-3D, MTSAT-2, and Himawari-8) satellite imagers. The cloud properties are derived using the Clouds and the Earth's Radiant Energy System (CERES) mission Cloud Subsystem group algorithms. These properties have to be co-located with EPIC pixels to provide the scene identification and to select anisotropic directional models (ADMs), which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiance and cloud property parameters derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. Selection of satellite data for each 5-km pixel is based on an aggregated rating that incorporates five parameters: nominal satellite resolution, pixel time relative to the EPIC time, viewing zenith angle, distance from day/night terminator, and probability of sun glint. To provide a smoother transition in the merged output, in regions where candidate pixel data from two satellite sources have comparable aggregated rating, the selection decision is defined by the cumulative function of the normal distribution so that abrupt changes in the visual appearance of the composite data are avoided. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling.

Khlopenkov, Konstantin V.↗