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NASA NTRS2012

Determination of Ice Cloud Models Using MODIS and MISR Data

Representation of ice clouds in radiative transfer simulations is subject to uncertainties associated with the shapes and sizes of ice crystals within cirrus clouds. In this study, we examined several ice cloud models consisting of smooth, roughened, homogeneous and inhomogeneous hexagonal ice crystals with various aspect ratios. The sensitivity of the bulk scattering properties and solar reflectances of cirrus clouds to specific ice cloud models is investigated using the improved geometric optics method (IGOM) and the discrete ordinates radiative transfer (DISORT) model. The ice crystal habit fractions in the ice cloud model may significantly affect the simulations of cloud reflectances. A new algorithm was developed to help determine an appropriate ice cloud model for application to the satellite-based retrieval of ice cloud properties. The ice cloud particle size retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data, collocated with Multi-angle Imaging Spectroradiometer (MISR) observations, is used to infer the optical thicknesses of ice clouds for nine MISR viewing angles. The relative differences between view-dependent cloud optical thickness and the averaged value over the nine MISR viewing angles can vary from −0.5 to 0.5 and are used to evaluate the ice cloud models. In the case for 2 July 2009, the ice cloud model with mixed ice crystal habits is the best fit to the observations (the root mean square (RMS) error of cloud optical thickness reaches 0.365). This ice cloud model also produces consistent cloud property retrievals for the nine MISR viewing configurations within the measurement uncertainties.

MODIS↗

DOE OSTI2023

Measurement and applications: Exploring the challenges and opportunities of hierarchical federated learning in sensor applications

Sensor applications have become ubiquitous in modern society as the digital age continues to advance. AI-based techniques (e.g., machine learning) are effective at extracting actionable information from large amounts of data. An example would be an automated water irrigation system that uses AI-based techniques on soil quality data to decide how to best distribute water. However, these AI-based techniques are costly in terms of hardware resources, and Internet-of-Things (IoT) sensors are resource-constrained with respect to processing power, energy, and storage capacity. These limitations can compromise the security, performance, and reliability of sensor-driven applications. To address these concerns, cloud computing services can be used by sensor applications for data storage and processing. Unfortunately, cloud-based sensor applications that require real-time processing, such as medical applications (e.g., fall detection and stroke prediction), are vulnerable to issues such as network latency due to the sparse and unreliable networks between the sensor nodes and the cloud server [1]. As users approach the edge of the communications network, latency issues become more severe and frequent. A promising alternative is edge computing, which provides cloud-like capabilities at the edge of the network by pushing storage and processing capabilities from centralized nodes to edge devices that are closer to where the data are gathered, resulting in reduced network delays [2], [3].

Po-Leen Ooi, Melanie↗

NASA NTRS2016

Lessons Learned while Exploring Cloud-Native Architectures for NASA EOSDIS Applications and Systems

As new, high data rate missions begin collecting data, the NASAs Earth Observing System Data and Information System (EOSDIS) archive is projected to grow roughly 20x to over 300PBs by 2025. To prepare for the dramatic increase in data and enable broad scientific inquiry into larger time series and datasets, NASA has been exploring the impact of applying cloud technologies throughout EOSDIS. In this talk we will provide an overview of NASAs prototyping and lessons learned in applying cloud architectures.

NGAP↗

NASA NTRS2011

Understanding Effective Diameter and Its Application to Terrestrial Radiation in Ice Clouds

The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, D(sub e), and their cloud water content (CWC), henceforth referred to as the D(sub e)-CWC assumption. This study challenges this assumption, showing that while the D(sub e)-CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De less than ~60 m, which is where this D(sub e)-CWC assumption appears poorest. Treating optical properties solely in terms of D(sub e) and IWC may lead to errors up to 24%, 26% and 20% for terrestrial radiation in the window region regarding the absorption and extinction coefficients and the single scattering albedo, respectively. Outside the window region, errors may reach 33% and 42% regarding absorption and extinction. The magnitude and sign of these errors can change rapidly with wavelength, which may produce significant errors in climate modeling, remote sensing and other applications concerned with the wavelength dependence of radiation. Where the D(sub e)-CWC assumption breaks down, ice cloud optical properties appear to depend on D(sub e), IWC and the PSD shape. Optical property parameterizations in climate models and remote sensing algorithms based on historical PSD measurements may exhibit errors due to previously unknown PSD errors (i.e. the presence of ice artifacts due to the shattering of larger ice particles on the probe inlet tube during sampling). More recently developed cloud probes are designed to mitigate this shattering problem. Using realistic PSD shapes for a given temperature (and/or IWC) and cloud type may minimize errors associated with PSD shape in ice optics parameterizations and remote sensing algorithms. While this topic was investigated using two ice optics schemes (the Yang et al., 2005 database and the modified anomalous diffraction approximation, or MADA), a physical understanding of the limitations of the D(sub e)-IWC assumption was made possible by using MADA. MADA allows one to approximate the contribution of photon tunneling to absorption relative to other optical processes, which reveals that part of the error regarding the D(sub e)-IWC assumption can be associated with tunneling. By relating the remaining error to the radiation penetration depth in bulk ice (DELTA L) due to absorption, the domain where the D(sub e)-IWC assumption is weakest was described in terms of D(sub e) and DELTA L.

Mitchell, D. L.↗

NASA NTRS2012

Applications for Near-Real Time Satellite Cloud and Radiation Products

At NASA Langley Research Center, a variety of cloud, clear-sky, and radiation products are being derived at different scales from regional to global using geostationary satellite (GEOSat) and lower Earth-orbiting (LEOSat) imager data. With growing availability, these products are becoming increasingly valuable for weather forecasting and nowcasting. These products include, but are not limited to, cloud-top and base heights, cloud water path and particle size, cloud temperature and phase, surface skin temperature and albedo, and top-of-atmosphere radiation budget. Some of these data products are currently assimilated operationally in a numerical weather prediction model. Others are used unofficially for nowcasting, while testing is underway for other applications. These applications include the use of cloud water path in an NWP model, cloud optical depth for detecting convective initiation in cirrus-filled skies, and aircraft icing condition diagnoses among others. This paper briefly describes a currently operating system that analyzes data from GEOSats around the globe (GOES, Meteosat, MTSAT, FY-2) and LEOSats (AVHRR and MODIS) and makes the products available in near-real time through a variety of media. Current potential future use of these products is discussed.

Minnis, Patrick↗

NASA NTRSDate not supplied

Cloud Climate Data Records from Geostationary Satellites to Support CERES: Challenges and Recent Progress

clouds↗

NASA NTRSDate not supplied

Development of a Consistent GEOsat Cloud Property Dataset for the CERES Climate Data Record

Cloud properties are critical for understanding the Earth’s radiation budget and cloud feedbacks. At NASA Langley Research Center, the Satellite ClOud and Radiative Property retrieval System (SatCORPS) provides real-time and historical analyses of clouds derived from Geostationary satellite (GEOsat) data for weather and climate applications. For the Clouds and the Earth’s Radiant Energy System (CERES) program, the global constellation of GEOsats has been analyzed since 2000 to help characterize and account for the diurnal cycle of clouds and their radiative impacts in the CERES climate data record. Obtaining consistent cloud properties over the GEOsat data record during the CERES era is a major objective but a significant challenge considering the diversity of imaging capabilities deployed during that time. The GEOsat data analysis approach for the current CERES Edition-4 (Ed4) data products was focused on accuracy and consistency with MODIS by employing as much spectral information as possible from each satellite. However, the inconsistent use of spectral information across GEOsats led to marked discontinuities in the spatial and temporal record of cloud properties that had to be accounted for post facto in downstream CERES processing. This paper reports progress in developing a new GEOsat analysis system for the next CERES edition (Ed5) that has potential to improve cross-platform consistency and continuity. In this approach, the spectral channel complement is limited to just 3-channels during daytime, ~0.65 µm (VIS), ~3.9 µm (NIR), and ~10.8 µm (IR), common to nearly all of the satellites in the record. At night, a 2-channel approach is taken with the NIR and IR, and ~6.7 µm bands that includes a machine learning approach for optically thick cloud properties. A tradeoff is the potential for reduced accuracy particularly using data from the more advanced satellites that have more spectral channels (e.g. SEVIRI, AHI and ABI) that are known to help improve thin cirrus detection, cloud-aerosol discrimination and estimates in other difficult conditions that challenge cloud remote sensing. The new continuity approach is applied to one month of global GEOSat data for each year of the CERES record since 2000 and compared with the Ed4 GEO and MODIS cloud property time series in order to evaluate the level of improved consistency in the GEOsat record and to assess the accuracy impacts. Cloud fraction will also be assessed with CALIPSO data. Outstanding issues and challenges will be discussed. The results are expected to guide future work needed to develop a more robust GEOsat cloud data record for CERES.

CERES CDR↗

NASA NTRS2017

Lessons Learned While Exploring Cloud-Native Architectures for NASA EOSDIS Applications and Systems

NASA's Earth Observing System (EOS) is a coordinated series of satellites for long term global observations. NASA's Earth Observing System Data and Information System (EOSDIS) is a multi-petabyte-scale archive of environmental data that supports global climate change research by providing end-to-end services from EOS instrument data collection to science data processing to full access to EOS and other earth science data. On a daily basis, the EOSDIS ingests, processes, archives and distributes over 3 terabytes of data from NASA's Earth Science missions representing over 6000 data products ranging from various types of science disciplines. EOSDIS has continually evolved to improve the discoverability, accessibility, and usability of high-impact NASA data spanning the multi-petabyte-scale archive of Earth science data products. Reviewed and approved by Chris Lynnes.

Cumulus↗

DOE OSTI2014

A Monte Carlo investigation of low-Z target image quality generated in a linear accelerator using Varian's VirtuaLinac

Purpose: The focus of this work was the demonstration and validation of VirtuaLinac with clinical photon beams and to investigate the implementation of low-Z targets in a TrueBeam linear accelerator (Linac) using Monte Carlo modeling. Methods: VirtuaLinac, a cloud based web application utilizing Geant4 Monte Carlo code, was used to model the Linac treatment head components. Particles were propagated through the lower portion of the treatment head using BEAMnrc. Dose distributions and spectral distributions were calculated using DOSXYZnrc and BEAMdp, respectively. For validation, 6 MV flattened and flattening filter free (FFF) photon beams were generated and compared to measurement for square fields, 10 and 40 cm wide and at d{sub max} for diagonal profiles. Two low-Z targets were investigated: a 2.35 MeV carbon target and the proposed 2.50 MeV commercial imaging target for the TrueBeam platform. A 2.35 MeV carbon target was also simulated in a 2100EX Clinac using BEAMnrc. Contrast simulations were made by scoring the dose in the phosphor layer of an IDU20 aSi detector after propagating through a 4 or 20 cm thick phantom composed of water and ICRP bone. Results: Measured and modeled depth dose curves for 6 MV flattened and FFF beams agree within 1% for 98.3% of points at depths greater than 0.85 cm. Ninety three percent or greater of points analyzed for the diagonal profiles had a gamma value less than one for the criteria of 1.5 mm and 1.5%. The two low-Z target photon spectra produced in TrueBeam are harder than that from the carbon target in the Clinac. Percent dose at depth 10 cm is greater by 3.6% and 8.9%; the fraction of photons in the diagnostic energy range (25–150 keV) is lower by 10% and 28%; and contrasts are lower by factors of 1.1 and 1.4 (4 cm thick phantom) and 1.03 and 1.4 (20 cm thick phantom), for the TrueBeam 2.35 MV/carbon and commercial imaging beams, respectively. Conclusions: VirtuaLinac is a promising new tool for Monte Carlo modeling of novel target designs. A significant spectral difference is observed between the low-Z target beam on the Clinac platform and the proposed imaging beam line on TrueBeam, with the former providing greater diagnostic energy content.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS1966

Properties of the clouds of Venus

Method for calculating properties of monochromatic radiation through layer of dispersed particles and its application to Venus clouds

CLOUD PHYSICS↗

NASA NTRS1994

General analytic results for nonlinear waves and solitons in molecular clouds

We study nonlinear wave phenomena in self-gravitating fluid systems, with a particular emphasis on applications to molecular clouds. This paper presents analytical results for one spatial dimension. We show that a large class of physical systems can be described by theories with a 'charge density' q(rho); this quantity replaces the density on the right-hand side of the Poisson equation for the gravitational potential. We use this formulation to prove general results about nonlinear wave motions in self-gravitating systems. We show that in order for stationary waves to exist, the total charge (the integral of the charge density over the wave profile) must vanish. This 'no-charge' property for solitary waves is related to the capability of a system to be stable to gravitational perturbations for arbitrarily long wavelengths. We find necessary and sufficient conditions on the charge density for the existence of solitary waves and stationary waves. We study nonlinear wave motions for Jeans-type theories (where q(rho) = rho-rho(sub 0)) and find that nonlinear waves of large amplitude are confined to a rather narrow range of wavelengths. We also study wave motions for molecular clouds threaded by magnetic fields and show how the allowed range of wavelengths is affected by the field strength. Since the gravitational force in one spatial dimension does not fall off with distance, we consider two classes of models with more realistic gravity: Yukawa potentials and a pseudo two-dimensional treatment. We study the allowed types of wave behavior for these models. Finally, we discuss the implications of this work for molecular cloud structure. We argue that molecular clouds can support a wide variety of wave motions and suggest that stationary waves (such as those considered in this paper) may have already been observed.

Adams, Fred C.↗

NASA NTRS1970

Definition of experimental studies for determining gaseous and particulate cloud environment of manned spacecraft and applications to cometary physics Final report

Cosmic gas environment surrounding manned spacecraft

Lilienfeld, P.↗

NASA NTRS1977

Cloud physics laboratory project science and applications working group

The conditions of the expansion chamber under zero gravity environment were simulated. The following three branches of fluid mechanics simulation under low gravity environment were accomplished: (1) oscillation of the water droplet which characterizes the nuclear oscillation in nuclear physics, bubble oscillation of two phase flow in chemical engineering, and water drop oscillation in meteorology; (2) rotation of the droplet which characterizes nuclear fission in nuclear physics, formation of binary stars and rotating stars in astrophysics, and breakup of the water droplet in meteorology; and (3) collision and coalescence of the water droplets which characterizes nuclear fusion in nuclear physics and processes of rain formation in meteorology.

Hung, R. J.↗

NASA NTRS1987

The application of time series models to cloud field morphology analysis

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Chin, Roland T.↗

NASA NTRS1994

The deformation of flux tubes in the solar wind with applications to the structure of magnetic clouds and CMEs

Two dimensional magnetohydrodynamic simulations of the distortion of a magnetic flux tube, accelerated through ambient solar wind plasma, are presented. Vortices form on the trailing edge of the flux tube, and couple strongly to its interior. If the flux tube azimuthal field is weak, it deforms into an elongated banana-like shape after a few Alfven transit times. A significant azimuthal field component inhibits this distortion. In the case of magnetic clouds in the solar wind, it is suggested that the shape observed at 1 AU was determined by distortion of the cloud in the inner heliosphere. Distortion of the cloud beyond 1 AU takes many days. It is estimated that effective drag coefficients slightly greater than unity are appropriate for modeling flux tube propagation. Synthetic magnetic field profiles as would be seen by a spacecraft traversing the cloud are presented.

Cargill, Peter J.↗

NASA NTRS2018

The SPECTRAL Ice Chamber: Application to Titan's Stratospheric Ice Clouds

An ice chamber for obtaining thin-film transmission spectra of Titan-relevant organic ices between 50 and 11,700 cm−1 (200–0.85 μm) is described in detail in this work. The ice chamber, called the SPECtroscopy of Titan-Related ice AnaLogs chamber, is located in the Spectroscopy for Planetary ICes Environments laboratory at NASA Goddard Space Flight Center. Organic vapors are typically deposited between 30 and 150 K via a variable leak valve onto a chemical vapor deposition diamond substrate, where condensation directly into the solid state occurs. Quantitative thin-film infrared transmission spectra of the given ice or ice mixture are then measured, from which optical constants (complex indices of refraction) are computed. These optical constants in turn provide the necessary input for interpreting radiative transfer analyses of Cassini’s Composite InfraRed Spectrometer observations of Titan’s organic stratospheric ice clouds to determine their chemical compositions, abundances, and vertical distributions as functions of Titan latitude and season.

Anderson, C. M.↗

NASA NTRS2018

The SPECTRAL Ice Chamber: Application to Titan's Stratospheric Ice Clouds

An ice chamber for obtaining thin-film transmission spectra of Titan-relevant organic ices between 50 and 11,700 cm(exp −1) (200–0.85 μm) is described in detail in this work. The ice chamber, called the SPECtroscopy of Titan-Related ice AnaLogs chamber, is located in the Spectroscopy for Planetary ICes Environments laboratory at NASA Goddard Space Flight Center. Organic vapors are typically deposited between 30 and 150 K via a variable leak valve onto a chemical vapor deposition diamond substrate, where condensation directly into the solid state occurs. Quantitative thin-film infrared transmission spectra of the given ice or ice mixture are then measured, from which optical constants (complex indices of refraction) are computed. These optical constants in turn provide the necessary input for interpreting radiative transfer analyses of Cassini’s Composite InfraRed Spectrometer observations of Titan’s organic stratospheric ice clouds to determine their chemical compositions, abundances, and vertical distributions as functions of Titan latitude and season.

C. M. Anderson↗

NASA NTRS2018

The SPECTRAL Ice Chamber: Application to Titan's Stratospheric Ice Clouds

An ice chamber for obtaining thin-film transmission spectra of Titan-relevant organic ices between 50 and 11,700 cm−1 (200 to 0.85 µm) is described in detail in this work. The ice chamber, called the SPECtroscopy of Titan-Related ice AnaLogs (SPECTRAL) chamber, is located in the Spectroscopy for Planetary ICes Environments (SPICE) laboratory at NASA Goddard Space Flight Center (GSFC). Organic vapors are typically deposited between 30 K and 150 K via a variable leak valve onto a chemical vapor deposition (CVD) diamond substrate, where condensation directly into the solid state occurs. Quantitative thin-film infrared transmission spectra of the given ice or ice mixture are then measured, from which optical constants (complex indices of refraction) are computed. These optical constants in turn provide the necessary input for interpreting radiative transfer analyses of Cassini’s Composite InfraRed Spectrometer (CIRS) observations of Titan’s organic stratospheric ice clouds to determine their chemical compositions, abundances, and vertical distributions as functions of Titan latitude and season.

C. M. Anderson↗