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At least 523 records · Page 29

Covariability in the Monthly Mean Convective and Radiative Diurnal Cycles in the Amazon

The diurnal cycle of convective clouds greatly influences the radiative energy balance in convectively active regions of Earth, through both direct presence, and the production of anvil and stratiform clouds. Previous studies show that the frequency and properties of convective clouds can vary on monthly timescales as a result of variability in the monthly mean atmospheric state. Furthermore, the radiative budget in convectively active regions also varies by up to 7 Wm-2 in convectively active regions. These facts suggest that convective clouds connect atmospheric state variability and radiation variability beyond clear sky effects alone. Previous research has identified monthly covariability between the diurnal cycle of CERES-observed top-of-atmosphere radiative fluxes and multiple atmospheric state variables from reanalysis over the Amazon region. ASVs that enhance (reduce) deep convection, such as CAPE (LTS), tend to shift the daily OLR and cloud albedo maxima earlier (later) in the day by 2-3 hr. We first test the analysis method using multiple reanalysis products for both the dry and wet seasons to further investigate the robustness of the preliminary results. We then use CloudSat data as an independent cloud observing system to further evaluate the relationships of cloud properties to variability in radiation and atmospheric states. While CERES can decompose OLR variability into clear sky and cloud effects, it cannot determine what variability in cloud properties lead to variability in the radiative cloud effects. Cloud frequency, cloud top height, and cloud microphysics all contribute to the cloud radiative effect, all of which are observable by CloudSat. In addition, CloudSat can also observe the presence and variability of deep convective cores responsible for the production of anvil clouds. We use these capabilities to determine the covariability of convective cloud properties and the radiative diurnal cycle.

Dodson, Jason B.↗

Development of a Scalable Risk-informed Predictive Maintenance Cloud-based Strategy at Nuclear Power Plants

The fact that light-water reactor operation and maintenance costs are prohibitively expensive and contribute to the premature decommissioning of nuclear power plants is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology, as its low cost, computing and storage adaptability, and ability to host applications across numerous virtual infrastructures potentially make it a cost-effective alternative to onsite storage and diagnostics. In this paper, a technological assessment is carried out on a provisional cloud deployment architecture for a nuclear power plant predictive monitoring system. This cloud-based monitoring system would enable maintenance and diagnostic analysts and other authorized plant users to remotely monitor equipment functionality, thus enabling early fault detection and effective predictive maintenance practices. To provide data processing and storage, sensor device networking, and database management, the Microsoft Azure cloud platform is utilized as part of the proposed cloud architecture; however, this analysis could be extended to other cloud computing service providers as well. The focus of this paper is on application of cloud resources for enabling predictive maintenance, identification of technological hurdles associated with moving to a cloud-computing-based architecture, and potential benefits from moving to a centralized cloud system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Clouds and Water Vapor in the Climate System and Radiative Transfer in Clear Air and Cirrus Clouds in the Tropics

Research supported under this grant was aimed at attacking unanswered scientific questions that lie at the intersection of radiation, dynamics, chemistry, and climate. Considerable emphasis was placed on scientific collaboration and the innovative development of instruments required to address these issues. Specific questions include water vapor distribution in the tropical troposphere, atmospheric radiation, thin cirrus clouds, stratosphere-troposphere exchange, and correlative science with satellite observations.

Anderson, James G.↗

RECOVER: An Automated Cloud-Based Decision Support System for Post-fire Rehabilitation Planning

RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

cloud computing↗

Ultraviolet photometer observations of the Saturnian system

Several interesting cloud and atmospheric features of the Saturn system have been observed by the long-wavelength channel of the two-channel ultraviolet photometer aboard the Pioneer Saturn spacecraft. Reported are observations of the most obvious features, including a Titan-associated cloud, a ring cloud, and the variation of atmospheric emission across Saturn's disk. The long-wavelength data for Titan suggest that a cloud of atomic hydrogen extends at least 5 Saturn radii along its orbit and about 1.5 Saturn radii vertically. A ring cloud, thought to be atomic hydrogen, has also been observed by the long-wavelength channel of the photometer; it shows significant enhancement in the vicinity of the B ring. Finally, spatially resolved observations of Saturn's disk show significant latitudinal variation. Possible explanations of the variation include aurora or limb brightening.

Judge, D. L.↗

The Representation of Tropical Cyclones Within the Global William Putman Non-Hydrostatic Goddard Earth Observing System Model (GEOS-5) at Cloud-Permitting Resolutions

The Goddard Earth Observing System Model (GEOS-S), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-S from irs standard 72-level 27-km resolution (approx.5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (approx. 3.6 billion cells).

Putman, William M.↗

Dimensionless parameters for cloudy Rayleigh-Bénard convection: Supersaturation, Damköhler, and Nusselt numbers

In steady-state Rayleigh-Bénard convection, heat is transported by turbulent thermal convection from the bottom, hot surface to the top, cold surface, leading to a height-independent sensible heat flux. When water vapor is present and cloud formation occurs, there is also an additional latent heat flux. Heat transport in cloudy Rayleigh-Bénard convection depends on turbulent flow as well as the microphysical state of the clouds: specifically, whether substantial supersaturations exist and whether cloud liquid water is removed through sedimentation/precipitation. In this article we bridge between the Rayleigh-Bénard convection literature and the atmospheric literature. We express the governing equations for cloudy convection in dimensionless form, thereby explicitly identifying the governing parameters relevant to the cloudy case, including Schmidt, Damköhler, supersaturation, and sedimentation numbers. We further connect to the atmospheric literature by obtaining a Nusselt number (dimensionless heat flux) for a cloud-convection system, directly from the conservation equations for temperature and water vapor. This flux has the same form as that identified by Zhang et al. [L. Zhang, K. L. Chong, and K.-Q. Xia, J. Fluid Mech. 874, 1041 (2019)] for convection with water vapor, but is extended to the cloudy case. For equal thermal and water vapor diffusivities, the flux corresponds to the widely used atmospheric quantities equivalent temperature and moist static energy. Using large eddy simulation (LES) of an idealized cloudy Rayleigh-Bénard convection system with fixed boundary conditions, we find that the equivalent heat flux (Nusselt number) is only weakly dependent on the microphysical details of the system, such as liquid water mixing ratio and cloud droplet number concentration. Finally, from the results, we show the vertical profiles of sensible and latent heat fluxes depend on the liquid water content, whereas the equivalent heat flux remains a constant throughout the height of the chamber.

54 ENVIRONMENTAL SCIENCES↗

Glaciation of mixed-phase clouds: insights from bulk model and bin-microphysics large-eddy simulation informed by laboratory experiment

Abstract. Mixed-phase clouds affect precipitation and radiation differently from liquid and ice clouds, posing greater challenges to their representation in numerical simulations. Recent laboratory experiments using the Pi Cloud Chamber explored cloud glaciation conditions based on increased injection of ice-nucleating particles. In this study, we use two approaches to reproduce the results of the laboratory experiments: a bulk scalar mixing model and large-eddy simulation (LES) with bin microphysics. The first approach assumes a well-mixed domain to provide an efficient assessment of the mean cloud properties for a wide range of conditions. The second approach resolves the energy-carrying turbulence, the particle size distribution, and their spatial distribution to provide more details. These modeling approaches enable a separate and detailed examination of liquid and ice properties, which is challenging in the laboratory. Both approaches demonstrate that, with an increased ice number concentration, the flow and microphysical properties exhibit the same changes in trends. Additionally, both approaches show that the ice integral radius reaches the theoretical glaciation threshold when the cloud is subsaturated with respect to liquid water. The main difference between the results of the two approaches is that the bulk model allows for the complete glaciation of the cloud. However, LES reveals that, in a dynamic system, the cloud is not completely glaciated as liquid water droplets are continuously produced near the warm lower boundary and subsequently mixed into the chamber interior. These results highlight the importance of the ice mass fraction in distinguishing the mixed-phase clouds and ice clouds.

54 ENVIRONMENTAL SCIENCES↗

A system for recording physical properties of clouds

Characterization of the physical properties of clouds is an important objective of the FIRE Project intensive field operations (IFO) planned for 1990 thru 1992. Physical properties observed from satellites will be directly compared to ground based observations during this period. The technical information is provided which is required to record local cloud parameters such as type of clouds, direction of travel, layering, and cloud fraction data. Such information should be very useful in analyzing other cloud and meteorological data. A system of the type described was deployed as part of the First Global Surface Radiation Budget Experiment in April 1989.

Purgold, G. C.↗

High-resolution measurements of microphysics and entrainment in marine stratocumulus clouds

High-resolution measurements from the Airborne Cloud-Turbulence Observation System (ACTOS) during the Azores Stratocumulus Measurements of Radiation, Turbulence and Aerosols (ACORES) campaign are analysed for an investigation of the vertical profiles of microphysical properties and entrainment velocity ( W e ) in marine stratocumulus clouds. Here, the vertical profiles show the transition from the cloudy layer to free troposphere with nearly linear profiles of total water mixing ratio, liquid water potential temperature and virtual potential temperature, but the thickness of entrainment interfacial layer varies significantly. Sharp transitions of cloud microphysical and optical properties within a single horizontal flight leg are found in one stratocumulus cloud system. They seem to be related to the local environmental conditions, such as the wind shear and turbulent dissipation rate. W e values estimated by three methods show consistent tendencies in general and are clearly related to the local environmental conditions, such as vertical shear of the horizontal wind and turbulence intensity. However, the magnitudes of W e values differ by up to two orders of magnitude depending on the methods, which suggests that the estimation of W e from in situ measurements is still a challenge. Analysis of the microphysical response to entrainment suggests that inhomogeneous mixing occurs dominantly. On the other hand, the analysis results for the clouds under more humid conditions indicate a higher likelihood of homogeneous mixing.

54 ENVIRONMENTAL SCIENCES↗

Automated cloud classification with a fuzzy logic expert system

An unresolved problem in current cloud retrieval algorithms concerns the analysis of scenes containing overlapping cloud layers. Cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget. Most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. One promising method uses fuzzy logic to determine whether mixed cloud and/or surface types exist within a group of pixels, such as cirrus, land, and water, or cirrus and stratus. When two or more class types are present, fuzzy logic uses membership values to assign the group of pixels partially to the different class types. The strength of fuzzy logic lies in its ability to work with patterns that may include more than one class, facilitating greater information extraction from satellite radiometric data. The development of the fuzzy logic rule-based expert system involves training the fuzzy classifier with spectral and textural features calculated from accurately labeled 32x32 regions of Advanced Very High Resolution Radiometer (AVHRR) 1.1-km data. The spectral data consists of AVHRR channels 1 (0.55-0.68 mu m), 2 (0.725-1.1 mu m), 3 (3.55-3.93 mu m), 4 (10.5-11.5 mu m), and 5 (11.5-12.5 mu m), which include visible, near-infrared, and infrared window regions. The textural features are based on the gray level difference vector (GLDV) method. A sophisticated new interactive visual image Classification System (IVICS) is used to label samples chosen from scenes collected during the FIRE IFO II. The training samples are chosen from predefined classes, chosen to be ocean, land, unbroken stratiform, broken stratiform, and cirrus. The November 28, 1991 NOAA overpasses contain complex multilevel cloud situations ideal for training and validating the fuzzy logic expert system.

Tovinkere, Vasanth↗

The Ice, Cloud, and Land Elevation Satellite-2 Mission: A Global Geolocated Photon Product Derived from the Advanced Topographic Laser Altimeter System

The Ice, Cloud, and land Elevation Satellite – 2 (ICESat-2) observatory was launched on 15 September 2018 to measure ice sheet and glacier elevation change, sea ice freeboard, and enable the determination of the heights of Earth’s forests. ICESat-2’s laser altimeter, the Advanced Topographic Laser Altimeter System (ATLAS) uses green (532 nm) laser light and single-photon sensitive detection to measure time of flight and subsequently surface height along each of its six beams. In this paper, we describe the major components of ATLAS, including the transmitter, the receiver and the components of the timing system. We present the major components of the ICESat-2 observatory, including the Global Positioning System, star trackers and inertial measurement unit. The ICESat-2 Level 1B data product (ATL02) provides the precise photon round-trip time of flight, among other data. The ICESat-2 Level 2A data product (ATL03) combines the photon times of flight with the observatory position and attitude to determine the geodetic location (i.e. the latitude, longitude and height) of the ground bounce point of photons detected by ATLAS. The ATL03 data product is used by higher-level (Level 3A) surface-specific data products to determine glacier and ice sheet height, sea ice freeboard, vegetation canopy height, ocean surface topography, and inland water body height.

ICESat-2↗

A Theoretical Approach for Reliability Within Information Supply Chains With Cycles and Negations

Complex networks of information processing systems, or information supply chains, present challenges for performance analysis. Here, we establish a mathematical setting, in which a process within an information supply chain can be analyzed in terms of the functionality of the system’s components. Principles of this methodology are rigorously defended and induce a model for determining the reliability for the various products in these networks. Our model does not limit us from having cycles in the network, as long as the cycles do not contain negation. It is shown that our approach to reliability resolves the nonuniqueness caused by cycles in a probabilistic Boolean network. An iterative algorithm is given to find the reliability values of the model, using a process that can be fully automated. This automated method of discerning reliability is beneficial for systems managers. As a systems manager considers systems modification, such as the replacement of owned and maintained hardware systems with cloud computing resources, the need for comparative analysis of system reliability is paramount. The model is extended to handle conditional knowledge about the network, allowing one to make predictions of weaknesses in the system. Finally, to illustrate the model’s flexibility over different forms, it is demonstrated on a system of components and subcomponents.

97 MATHEMATICS AND COMPUTING↗