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At least 1,405 records · Page 78

Interpretation of the polarization of Venus

The linear polarization of sunlight reflected by Venus is analyzed by comparing observations with extensive multiple scattering computations. The analysis establishes that Venus is veiled by a cloud or haze layer of spherical particles. The refractive index of the particles is about 1.44 at 0.55 microns with a normal dispersion, the refractive index decreasing from about 1.46 at 0.365 microns to 1.43 at 0.99 microns. The cloud particles have a narrow size distribution with a mean radius of about 1 micron; specifically, the effective radius of the size distribution is approximately 1.05 microns and the effective variance is about 0.07. The particles exist at a high level in the atmosphere, with the optical thickness unity occurring where the pressure is about 50 mb. The particle properties deduced from the polarization eliminate all but one of the cloud compositions which have been proposed for Venus. A concentrated solution of sulfuric acid provides good agreement with the polarization data.

Hansen, J. E.↗

Planetary atmospheres program

Chemical and physical models of the Jovian subnebula are addressed. Halide cloud condensation and volatile element inventories on Venus and considered. Computation methods for isolated grain condensation behavior are examined.

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The role of earth radiation budget studies in climate and general circulation research

The use of earth radiation budget (ERB) data for climate and general circulation research is studied. ERB measurements obtained in the 1960's and 1970's have provided data on planetary brightness, planetary global energy balances, the greenhouse effect, solar insolation, meridional heat transport by oceans and atmospheres, regional forcing, climate feedback processes, and the computation of albedo values in low latitudes. The role of clouds in governing climate, in influencing the general circulation, and in determining the sensitivity of climate to external perturbations needs to be researched; a procedure for analyzing the ERB data, which will address these problems, is described. The approach involves estimating the clear-sky fluxes from the high spatial resolution scanner measurement and defining a cloud radiative forcing; the global average of the sum of the solar and long-wave cloud forcing yields the net radiative effect of clouds on the climate.

Ramanathan, V.↗

Spatial and temporal variability of global surface solar irradiance

Consideration is given to a fast scheme for computing surface solar irradiance using data from the International Satellite Cloud Climatology Project (ISCCP). Daily mean solar irradiances from the fast scheme reproduce the detailed global results from full radiative transfer model calculations to within 6 and 10 W/sq m over the ocean and land, respectively. Comparison of calculated monthly mean results using 5 m of ISCCP data (July 1983-July 1984) with climatology from the 1970s at six temperature-latitude ocean weather stations shows agreement within published estimates of interannual variability of monthly means at the individual stations. A further test against a 17-day time series at a continental site, where ground and satellite data were spatially and temporally coincident, showed an accuracy of better than 9 W/sq m on a daily basis and less than 4 percent bias in the 17-day mean. Frequently used bulk formulas for solar irradiance are also evaluated in each of these tests.

Bishop, James K. B.↗

Computerized reduction of airborne foil impactor data

A new technique for reducing data obtained from a foil impactor carried on the T-28 thunderstorm penetration aircraft is described. The technique employs a video-image processing system that was originally developed for satellite imagery and a computer-reduction program that was originally developed for determining cloud-size distributions to count and size particle impressions on the foil. This eliminates the tedious manual processing that has limited the usefulness of such devices, while at the same time improving objectivity. The technique has been applied to foil data acquired in thunderstorms in the southeastern United States during the Cooperative Huntsville Meteorological Experiment, where most of the particles were at least roughly spherical. Its usefulness for storms in which highly irregular or fragile ice particles predominate has yet to be established.

Peterson, Bret A.↗

Estimation of monthly rainfall over Japan and surrounding waters from a combination of low-orbit microwave and geosynchronous IR data

A method is described for estimating the mean monthly rainfall data for climate studies by combining the geosynchronous IR and low-orbit microwave data. The microwave technique uses the brightness temperature at 37 and 86 GHz from the Special Sensor Microwave/Imager instrument on board the DMSP satellite to define raining areas over water and land, and the 86-GHz scattering signal to assign rain rate based on cloud model-microwave calculations. The IR estimates are initially computed separately, using hourly data from the Japanese Geostationary Meteorological Satellite. Results show that, in areas where the microwave technique performs well, the combined microwave-IR monthly total estimates have better error statistics than either the microwave of the IR techniques individually.

Adler, Robert F.↗

A versatile system for processing geostationary satellite data with run-time visualization capability

To better predict global climate change, scientists are developing climate models that require interdisciplinary and collaborative efforts in their building. We are currently involved in several such projects but will briefly discuss activities in support of two such complementary projects: the Atmospheric Radiation Measurement (ARM) program of the Department of Energy and Sequoia 2000, a joint venture of the University of California, the private sector, and government agencies. Our contribution to the ARM program is to investigate the role of clouds on the top of the atmosphere and on surface radiance fields through the data analysis of surface and satellite observations and complex modeling of the interaction of radiation with clouds. One of our first ARM research activities involves the computation of the broadband shortwave surface irradiance from satellite observations. Geostationary satellite images centered over the first ARM observation site are received hourly over the Internet network and processed in real time to compute hourly and daily composite shortwave irradiance fields. The images and the results are transferred via a high-speed network to the Sequoia 2000 storage facility in Berkeley, where they are archived These satellite-derived results are compared with the surface observations to evaluate the accuracy of the satellite estimate and the spatial representation of the surface observations. In developing the software involved in calculating the surface shortwave irradiance, we have produced an environment whereby we can easily modify and monitor the data processing as required. Through the principles of modular programming, we have developed software that is easily modified as new algorithms for computation are developed or input data availability changes. In addition, the software was designed so that it could be run from an interactive, icon-driven, graphical interface, TCL-TK, developed by Sequoia 2000 participants. In this way, the data flow can be interactively assessed and altered as needed. In this environment, the intermediate data processing 'images' can be viewed, enabling the investigator to easily monitor the various data processing steps as they progress. Additionally, this environment allows the rapid testing of new processing modules and allows their effects to be visually compared with previous results.

Landsfeld, M.↗

Distribution of Dust from Kuiper Belt Objects

Using an efficient computational approach, we have reconstructed the structure of the dust cloud in the Solar system between 0.5 and 100 AU produced by the Kuiper belt objects. Our simulations offer a 3-D physical model of the 'kuiperoidal' dust cloud based on the distribution of 280 dust particle trajectories produced by 100 known Kuiper belt objects; the resulting 3-D grid consists of 1.9 x 10' cells containing 1.2 x 10" particle positions. The following processes that influence the dust particle dynamics are taken into account: 1) gravitational scattering on the eight planets (neglecting Pluto); 2) planetary resonances; 3) radiation pressure; and 4) the Poynting-Robertson (P-R) and solar wind drags. We find the dust distribution highly non-uniform: there is a minimum in the kuiperoidal dust between Mars and Jupiter, after which both the column and number densities of kuiperoidal dust sharply increase with heliocentric distance between 5 and 10 AU, and then form a plateau between 10 and 50 AU. Between 25 and 45 AU, there is an appreciable concentration of kuiperoidal dust in the form of a broad belt of mostly resonant particles associated with Neptune. In fact, each giant planet possesses its own circumsolar dust belt consisting of both resonant and gravitationally scattered particles. As with the cometary belts simulated in our related papers, we reveal a rich and sophisticated resonant structure of the dust belts containing families of resonant peaks and gaps. An important result is that both the column and number dust density are more or less flat between 10 and 50 AU, which might explain the surprising data obtained by Pioneers 10 & 11 and Voyager that the dust number density remains approximately distance-independent in this region. The simulated kuiperoidal dust, in addition to asteroidal and cometary dust, might represent a third possible source of the zodiacal light in the Solar system.

Gorkavyi, Nick N.↗

GMS-based"Future Time" Rainfall Data Assimilation for Mesoscale Weather Prediction over Korean Peninsula and Future Prospects with GPM Satellite Measurements

This study examines the use of satellite-derived nowcasted (short-term forecasted) rainfall over 3-hour time periods to gain an equivalent time increment in initializing a nonhydrostatic mesoscale model used for predicting convective rainfall events over the Korean peninsula. Infrared (IR) window measurements from the Japanese Geostationary Meteorological Satellite (GMS) are used to specify latent heating for a spinup period of the model - but in future time -- thus initializing in advance of actual time in the framework of a prediction scenario. The main scientific objective of the study is to investigate the strengths and weaknesses of this approach insofar as data assimilation, in which the nowcasted assimilation data are derived independently of the prognostic model itself. Although there have been various recent improvements in formulating the dynamics, thermodynamics, and microphysics of mesoscale models, as well as computer advances which allow the use of high resolution cloud-resolving grids and explicit latent heating over regional domains, spinup remains at the forefront of unresolved mesoscale modeling problems. In general, non-realistic spinup limits the skill in predicting the spatial-temporal distribution of convection and precipitation, primarily in the early hours of a. forecast, stemming from standard prognostic variables not representing the initial diabatic heating field produced by the ambient convection and cloud fields. The long-term goal of this research is to improve short-range (12-hour) quantitative precipitation forecasting (QPF) over the Korean peninsula through the use of innovative data assimilation methods based on geosynchronous satellite measurements. As a step in th~s direction, a non-standard data assimilation experiment in conjunction with GMS-retrieved nowcasted rainfall information introduced to the mesoscale model is conducted. The 3-hourly precipitation forecast information is assimilated through nudging the associated diabatic heating during the early stages of a forecast period. This procedure is expected to enhance details in the moisture field during model integration, and thus improve spinup performance, assuming the errors in the future time latent heating data ate less than intrinsic model background errors.

Smith, Eric A.↗

NASA Tech Briefs, June 2013

Topics include: Cloud Absorption Radiometer Autonomous Navigation System - CANS, Software Method for Computed Tomography Cylinder Data Unwrapping, Re-slicing, and Analysis, Discrete Data Qualification System and Method Comprising Noise Series Fault Detection, Simple Laser Communications Terminal for Downlink from Earth Orbit at Rates Exceeding 10 Gb/s, Application Program Interface for the Orion Aerodynamics Database, Hyperspectral Imager-Tracker, Web Application Software for Ground Operations Planning Database (GOPDb) Management, Software Defined Radio with Parallelized Software Architecture, Compact Radar Transceiver with Included Calibration, Software Defined Radio with Parallelized Software Architecture, Phase Change Material Thermal Power Generator, The Thermal Hogan - A Means of Surviving the Lunar Night, Micromachined Active Magnetic Regenerator for Low-Temperature Magnetic Coolers, Nano-Ceramic Coated Plastics, Preparation of a Bimetal Using Mechanical Alloying for Environmental or Industrial Use, Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO, Dual-Compartment Inflatable Suitlock, Modular Connector Keying Concept, Genesis Ultrapure Water Megasonic Wafer Spin Cleaner, Piezoelectrically Initiated Pyrotechnic Igniter, Folding Elastic Thermal Surface - FETS, Multi-Pass Quadrupole Mass Analyzer, Lunar Sulfur Capture System, Environmental Qualification of a Single-Crystal Silicon Mirror for Spaceflight Use, Planar Superconducting Millimeter-Wave/Terahertz Channelizing Filter, Qualification of UHF Antenna for Extreme Martian Thermal Environments, Ensemble Eclipse: A Process for Prefab Development Environment for the Ensemble Project, ISS Live!, Space Operations Learning Center (SOLC) iPhone/iPad Application, Software to Compare NPP HDF5 Data Files, Planetary Data Systems (PDS) Imaging Node Atlas II, Automatic Calibration of an Airborne Imaging System to an Inertial Navigation Unit, Translating MAPGEN to ASPEN for MER, Support Routines for In Situ Image Processing, and Semi-Supervised Eigenbasis Novelty Detection.

Source record↗

Cloud Simulations in Response to Turbulence Parameterizations in the GISS Model E GCM

The response of cloud simulations to turbulence parameterizations is studied systematically using the GISS general circulation model (GCM) E2 employed in the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5).Without the turbulence parameterization, the relative humidity (RH) and the low cloud cover peak unrealistically close to the surface; with the dry convection or with only the local turbulence parameterization, these two quantities improve their vertical structures, but the vertical transport of water vapor is still weak in the planetary boundary layers (PBLs); with both local and nonlocal turbulence parameterizations, the RH and low cloud cover have better vertical structures in all latitudes due to more significant vertical transport of water vapor in the PBL. The study also compares the cloud and radiation climatologies obtained from an experiment using a newer version of turbulence parameterization being developed at GISS with those obtained from the AR5 version. This newer scheme differs from the AR5 version in computing nonlocal transports, turbulent length scale, and PBL height and shows significant improvements in cloud and radiation simulations, especially over the subtropical eastern oceans and the southern oceans. The diagnosed PBL heights appear to correlate well with the low cloud distribution over oceans. This suggests that a cloud-producing scheme needs to be constructed in a framework that also takes the turbulence into consideration.

Yao, Mao-Sung↗

ML/AI Applications to the Atmosphere Science Data and Simulations (Demonstration and Vision)

Artificial Intelligence has been recognized as one of the most powerful tools for scientific research. It has a wide range of applications in atmospheric science and plays a significant role in advancing our understanding of the Earth-Atmosphere system, as well as improving our ability to monitor, predict, and respond to atmospheric observations and simulations. Different AI architectures can help us handle various problems according to our research goals. In this presentation, we will introduce several use cases and models for applying computer vision to active remote sensing data from CALIOP, analyzing cloud dynamical relationships for climate model parameterizations, and building surrogate models for lidar simulations. The presentation will highlight the advantages that AI offers compared to traditional analytical methods. By assembling pieces of the multidimensional atmospheric science puzzle, we can integrate our knowledge from observations to simulations.

Shan Zeng↗

Applications of Deep Learning to physics workflows

Modern large-scale physics experiments create datasets with sizes and streaming rates that can exceed those from industry leaders such as Google Cloud and Netflix. Fully processing these datasets requires both sufficient compute power and efficient workflows. Recent advances in Machine Learning (ML) and Artificial Intelligence (AI) can either improve or replace existing domain-specific algorithms to increase workflow efficiency. Not only can these algorithms improve the physics performance of current algorithms, but they can often be executed more quickly, especially when run on coprocessors such as GPUs or FPGAs. In the winter of 2023, MIT hosted the Accelerating Physics with ML at MIT workshop, which brought together researchers from gravitational-wave physics, multi-messenger astrophysics, and particle physics to discuss and share current efforts to integrate ML tools into their workflows. The following white paper highlights examples of algorithms and computing frameworks discussed during this workshop and summarizes the expected computing needs for the immediate future of the involved fields.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A model predicting the evolution of ice particle size spectra and radiative properties of cirrus clouds. Part 2: Dependence of absorption and extinction on ice crystal morphology

This study builds upon the microphysical modeling described in Part 1 by deriving formulations for the extinction and absorption coefficients in terms of the size distribution parameters predicted from the micro-physical model. The optical depth and single scatter albedo of a cirrus cloud can then be determined, which, along with the asymmetry parameter, are the input parameters needed by cloud radiation models. Through the use of anomalous diffraction theory, analytical expressions were developed describing the absorption and extinction coefficients and the single scatter albedo as functions of size distribution parameters, ice crystal shapes (or habits), wavelength, and refractive index. The extinction coefficient was formulated in terms of the projected area of the size distribution, while the absorption coefficient was formulated in terms of both the projected area and mass of the size distribution. These properties were formulated as explicit functions of ice crystal geometry and were not based on an 'effective radius.' Based on simulations of the second cirrus case study described in Part 1, absorption coefficients predicted in the near infrared for hexagonal columns and rosettes were up to 47% and 71% lower, respectively, than absorption coefficients predicted by using equivalent area spheres. This resulted in single scatter albedos in the near-infrared that were considerably greater than those predicted by the equivalent area sphere method. Reflectances in this region should therefore be underestimated using the equivalent area sphere approach. Cloud optical depth was found to depend on ice crystal habit. When the simulated cirrus cloud contained only bullet rosettes, the optical depth was 142% greater than when the cloud contained only hexagonal columns. This increase produced a doubling in cloud albedo. In the near-infrared (IR), the single scatter albedo also exhibited a significant dependence on ice crystal habit. More research is needed on the geometrical properties of ice crystals before the influence of ice crystal shape on cirrus radiative properties can be adequately understood. This study provides a way of coupling the radiative properties of absorption, extinction, and single scatter albedo to the microphysical properties of cirrus clouds. The dependence of extinction and absorption on ice crystal shape was not just due to geometrical differences between crystal types, but was also due to the effect these differences had on the evolution of ice particle size spectra. The ice particle growth model in Part 1 and the radiative properties treated here are based on analytical formulations, and thus represent a computationally efficient means of modeling the microphysical and radiative properties of cirrus clouds.

Mitchell, David L.↗

Load‐Balancing Intense Physics Calculations to Embed Regionalized High‐Resolution Cloud Resolving Models in the E3SM and CESM Climate Models

Abstract We design a new strategy to load‐balance high‐intensity sub‐grid atmospheric physics calculations restricted to a small fraction of a global climate simulation's domain. We show why the current parallel load balancing infrastructure of Community Earth System Model (CESM) and Energy Exascale Earth Model (E3SM) cannot efficiently handle this scenario at large core counts. As an example, we study an unusual configuration of the E3SM Multiscale Modeling Framework (MMF) that embeds a binary mixture of two separate cloud‐resolving model grid structures that is attractive for low cloud feedback studies. Less than a third of the planet uses high‐resolution (MMF‐HR; sub‐km horizontal grid spacing) relative to standard low‐resolution (MMF‐LR) cloud superparameterization elsewhere. To enable MMF runs with Multi‐Domain cloud resolving models (CRMs), our load balancing theory predicts the most efficient computational scale as a function of the high‐intensity work's relative overhead and its fractional coverage. The scheme successfully maximizes model throughput and minimizes model cost relative to precursor infrastructure, effectively by devoting the vast majority of the processor pool to operate on the few high‐intensity (and rate‐limiting) high‐resolution (HR) grid columns. Two examples prove the concept, showing that minor artifacts can be introduced near the HR/low‐resolution CRM grid transition boundary on idealized aquaplanets, but are minimal in operationally relevant real‐geography settings. As intended, within the high (low) resolution area, our Multi‐Domain CRM simulations exhibit cloud fraction and shortwave reflection convergent to standard baseline tests that use globally homogenous MMF‐LR and MMF‐HR. We suggest this approach can open up a range of creative multi‐resolution climate experiments without requiring unduly large allocations of computational resources.

54 ENVIRONMENTAL SCIENCES↗

Bounding Methods for Heterogeneous Lidar-derived Navigational Geofences

Safe Unmanned Aerial Vehicle (UAV) operations near the ground require navigation methods that avoid fixed obstacles such as buildings, power lines and trees. Aerial lidar surveys of ground structures are available with the precision and accuracy to geolocate obstacles, but the high volume of raw survey data can exceed the compute power of onboard processors and the rendering ability of ground-based flight planning maps. Representing ground structures with bounding polyhedra instead of point clouds greatly reduces the data size and can enable effective obstacle avoidance, as long as the bounding geometry envelopes the structures with high spatial fidelity. This report describes in detail four methods to compute bounding geometries of ground obstacles from lidar point clouds. The four methods are: 1) 2.5D Maximum Elevation Box, 2) 2.5D Ground Map Extrusion, 3) 3D Bounding Cylinder, and 4) 3D Bounding Box. The methods are applied to five point cloud datasets from lidar surveys of UAV flight research sites in Georgia and Virginia with an average point spacing that ranges from 0.1m to 0.6m. The methods are assessed using survey areas with geometrically heterogeneous ground structures: buildings, vegetation, power lines, and sub-meter structures such as road signs and guy wires. The 2.5D Maximum Elevation Box method is useful for simple structures. The 2.5D Ground Map Extrusion method efficiently encloses vegetation, but requires handdrawn ground footprints. The 3D Bounding Cylinder method excels at enclosing linear structures such as power lines and fences. The 3D Bounding Box method excels at enclosing planar structures such as buildings. The methods are compared on the basis of data compression and boundary fidelity on selected areas. The 2.5D methods yield the highest data compression but the polyhedra produced by them enclose significant amounts of empty space. Boundary fidelity is superior for the 3D methods, though this fidelity comes at the cost of a roughly thirtyfold lower data compression ratio than the 2.5D Maximum Elevation Box method. A mix of these output geometries is proposed for autonomous UAV navigation with limited on-board computing. Both the accuracy and spatial detail of emerging satellite-based survey technology lower than that of aerial lidar scanning survey technology. Sub-meter structures and thin linear structures are not reliably mapped at present by satellite-based surveys.

Moore, Andrew J.↗

Influence of Aerosol Embedded in Shallow Cumulus Cloud Fields on the Surface Solar Irradiance

Ubiquitous shallow cumulus clouds are associated with complex variability in surface solar irradiance (SSI). Aerosol embedded in the cloud field typically has a much smaller overall radiative effect, but can significantly perturb the shape of the SSI probability density function (PDF). These perturbations have important implications for several applications that utilize SSI, but are poorly quantified and are the subject of this study. Multiple cases of shallow cumulus cloud fields with embedded aerosol are simulated at the Southern Great Plains Atmospheric Observatory using large eddy simulation (LES). The LES-derived cloud and aerosol fields are then ingested into Monte Carlo three-dimensional (3D) radiative transfer to simulate SSI. We find a variety of perturbations to the SSI PDF that depend on aerosol presence and optical properties. The processes leading to these perturbations include extinction of the direct beam that often increases from the clear-sky region toward cloud edge due to aerosol hygroscopic growth, and scattering of radiation by aerosol into cloud shadows. The ability to predict the SSI PDF in the presence of aerosol is assessed by adding three representative aerosol optical properties into an existing machine learning framework. We show that machine learning accurately predicts the SSI PDF across a wide range of conditions with negligible computational expense. Importance metrics reveal the relatively high influence of aerosol optical properties in making the predictions. These new findings highlight the important role that aerosol plays in SSI variability for highly 3D cloud-aerosol environments and provides a computationally efficient route forward for its simulation.

3D radiative transfer↗

The properties and fate of the galactic center G2 cloud

The object G2 was recently discovered descending into the gravitational potential of the supermassive black hole (BH) Sgr A*. We test the photoionized cloud scenario, determine the cloud properties, and estimate the emission during the pericenter passage. The incident radiation is computed starting from the individual stars at the locations of G2. The radiative transfer calculations are conducted with CLOUDY code and 2011 broadband and line luminosities are fitted. The spherically symmetric, tidally distorted, and magnetically arrested cloud shapes are tested with both the interstellar medium dust and 10 nm graphite dust. The best-fitting magnetically arrested model has the initial density n {sub init} = 1.8 × 10{sup 5} cm{sup –3}, initial radius R {sub init} = 2.2 × 10{sup 15} cm = 17 mas, mass m {sub cloud} = 4 M {sub Earth}, and dust relative abundance A = 0.072. It provides a good fit to 2011 data, is consistent with the luminosities in 2004 and 2008, and reaches an agreement with the observed size. We revise down the predicted radio and X-ray bow shock luminosities to be below the quiescent level of Sgr A*, which readily leads to non-detection in agreement to observations. The magnetic energy dissipation in the cloud at the pericenter coupled with more powerful irradiation may lead to an infrared source with an apparent magnitude m{sub L{sup ′}}≈13.0. No shock into the cloud and no X-rays are expected from cloud squeezing by the ambient gas pressure. Larger than previously estimated cloud mass m {sub cloud} = (4-20) M {sub Earth} may produce a higher accretion rate and a brighter state of Sgr A* as the debris descend onto the BH.

79 ASTRONOMY AND ASTROPHYSICS↗