Security-aware Virtual Machine Allocation in the Cloud: A Game Theoretic Approach

DTIC Science & Technology

2015-01-13

predecessor, however, this paper used empirical evidence and actual data from running experiments on the Amazon EC2 cloud . They began by running all 5...is through effective VM allocation management of the cloud provider to ensure delivery of maximum security for all cloud users. The negative... Cloud : A Game Theoretic Approach 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f

High resolution radiometric measurements of convective storms during the GATE experiment

NASA Technical Reports Server (NTRS)

Fowler, G.; Lisa, A. S.

1976-01-01

Using passive microwave data from the NASA CV-990 aircraft and radar data collected during the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), an empirical model was developed relating brightness temperatures sensed at 19.35 GHz to surface rainfall rates. This model agreed well with theoretical computations of the relationship between microwave radiation and precipitation in the tropics. The GATE aircraft microwave data was then used to determine the detailed structure of convective systems. The high spatial resolution of the data permitted identification of individual cells which retained unique identities throughout their lifetimes in larger cloud masses and allowed analysis of the effects of cloud merger.

Physical properties of CO-dark molecular gas traced by C+

NASA Astrophysics Data System (ADS)

Tang, Ningyu; Li, Di; Heiles, Carl; Wang, Shen; Pan, Zhichen; Wang, Jun-Jie

2016-09-01

Context. Neither Hi nor CO emission can reveal a significant quantity of so-called dark gas in the interstellar medium (ISM). It is considered that CO-dark molecular gas (DMG), the molecular gas with no or weak CO emission, dominates dark gas. Determination of physical properties of DMG is critical for understanding ISM evolution. Previous studies of DMG in the Galactic plane are based on assumptions of excitation temperature and volume density. Independent measurements of temperature and volume density are necessary. Aims: We intend to characterize physical properties of DMG in the Galactic plane based on C+ data from the Herschel open time key program, namely Galactic Observations of Terahertz C+ (GOT C+) and Hi narrow self-absorption (HINSA) data from international Hi 21 cm Galactic plane surveys. Methods: We identified DMG clouds with HINSA features by comparing Hi, C+, and CO spectra. We derived the Hi excitation temperature and Hi column density through spectral analysis of HINSA features. The Hi volume density was determined by utilizing the on-the-sky dimension of the cold foreground Hi cloud under the assumption of axial symmetry. The column and volume density of H2 were derived through excitation analysis of C+ emission. The derived parameters were then compared with a chemical evolutionary model. Results: We identified 36 DMG clouds with HINSA features. Based on uncertainty analysis, optical depth of HiτHi of 1 is a reasonable value for most clouds. With the assumption of τHi = 1, these clouds were characterized by excitation temperatures in a range of 20 K to 92 K with a median value of 55 K and volume densities in the range of 6.2 × 101 cm-3 to 1.2 × 103 cm-3 with a median value of 2.3 × 102 cm-3. The fraction of DMG column density in the cloud (fDMG) decreases with increasing excitation temperature following an empirical relation fDMG =-2.1 × 10-3Tex,(τHi = 1) + 1.0. The relation between fDMG and total hydrogen column density NH is given by fDMG = 1.0-3.7 × 1020/NH. We divided the clouds into a high extinction group and low extinction group with the dividing threshold being total hydrogen column density NH of 5.0 × 1021 cm-2 (AV = 2.7 mag). The values of fDMG in the low extinction group (AV ≤ 2.7 mag) are consistent with the results of the time-dependent, chemical evolutionary model at the age of ~10 Myr. Our empirical relation cannot be explained by the chemical evolutionary model for clouds in the high extinction group (AV > 2.7 mag). Compared to clouds in the low extinction group (AV ≤ 2.7 mag), clouds in the high extinction group (AV > 2.7 mag) have comparable volume densities but excitation temperatures that are 1.5 times lower. Moreover, CO abundances in clouds of the high extinction group (AV > 2.7 mag) are 6.6 × 102 times smaller than the canonical value in the Milky Way. Conclusions: The molecular gas seems to be the dominate component in these clouds. The high percentage of DMG in clouds of the high extinction group (AV > 2.7 mag) may support the idea that molecular clouds are forming from pre-existing molecular gas, I.e., a cold gas with a high H2 content but that contains a little or no CO content.

Temporal monitoring of vessels activity using day/night band in Suomi NPP on South China Sea

NASA Astrophysics Data System (ADS)

Yamaguchi, Takashi; Asanuma, Ichio; Park, Jong Geol; Mackin, Kenneth J.; Mittleman, John

2017-05-01

In this research, we focus on vessel detection using the satellite imagery of day/night band (DNB) on Suomi NPP in order to monitor the change of vessel activity on the region of South China Sea. In this paper, we consider the relation between the temporal change of vessel activities and the events on maritime environment based on the vessel traffic density estimation using DNB. DNB is a moderate resolution (350-700m) satellite imagery but can detect the fishing light of fishery boats in night time for every day. The advantage of DNB is the continuous monitoring on wide area compared to another vessel detection and locating system. However, DNB gave strong influence of cloud and lunar refection. Therefore, we additionally used Brightness Temperature at 3.7μm(BT3.7) for cloud information. In our previous research, we construct an empirical vessel detection model that based on the DNB contrast and the estimation of cloud condition using BT3.7. Moreover, we proposed a vessel traffic density estimation method based on empirical model. In this paper, we construct the time temporal density estimation map on South China Sea and East China Sea in order to extract the knowledge from vessel activities change.

Empirical orthogonal function analysis of cloud-containing coastal zone color scanner images of northeastern North American coastal waters

NASA Technical Reports Server (NTRS)

Eslinger, David L.; O'Brien, James J.; Iverson, Richard L.

1989-01-01

Empirical-orthogonal-function (EOF) analyses were carried out on 36 images of the Mid-Atlantic Bight and the Gulf of Maine, obtained by the CZCS aboard Nimbus 7 for the time period from February 28 through July 9, 1979, with the purpose of determining pigment concentrations in coastal waters. The EOF procedure was modified so as to include images with significant portions of data missing due to cloud obstruction, making it possible to estimate pigment values in areas beneath clouds. The results of image analyses explained observed variances in pigment concentrations and showed a south-to-north pattern corresponding to an April Mid-Atlantic Bight bloom and a June bloom over Nantucket Shoals and Platts Bank.

Modelling heterogeneous ice nucleation on mineral dust and soot with parameterizations based on laboratory experiments

NASA Astrophysics Data System (ADS)

Hoose, C.; Hande, L. B.; Mohler, O.; Niemand, M.; Paukert, M.; Reichardt, I.; Ullrich, R.

2016-12-01

Between 0 and -37°C, ice formation in clouds is triggered by aerosol particles acting as heterogeneous ice nuclei. At lower temperatures, heterogeneous ice nucleation on aerosols can occur at lower supersaturations than homogeneous freezing of solutes. In laboratory experiments, the ability of different aerosol species (e.g. desert dusts, soot, biological particles) has been studied in detail and quantified via various theoretical or empirical parameterization approaches. For experiments in the AIDA cloud chamber, we have quantified the ice nucleation efficiency via a temperature- and supersaturation dependent ice nucleation active site density. Here we present a new empirical parameterization scheme for immersion and deposition ice nucleation on desert dust and soot based on these experimental data. The application of this parameterization to the simulation of cirrus clouds, deep convective clouds and orographic clouds will be shown, including the extension of the scheme to the treatment of freezing of rain drops. The results are compared to other heterogeneous ice nucleation schemes. Furthermore, an aerosol-dependent parameterization of contact ice nucleation is presented.

The birth of the empirical turn in bioethics.

PubMed

Borry, Pascal; Schotsmans, Paul; Dierickx, Kris

2005-02-01

Since its origin, bioethics has attracted the collaboration of few social scientists, and social scientific methods of gathering empirical data have remained unfamiliar to ethicists. Recently, however, the clouded relations between the empirical and normative perspectives on bioethics appear to be changing. Three reasons explain why there was no easy and consistent input of empirical evidence in bioethics. Firstly, interdisciplinary dialogue runs the risk of communication problems and divergent objectives. Secondly, the social sciences were absent partners since the beginning of bioethics. Thirdly, the meta-ethical distinction between 'is' and 'ought' created a 'natural' border between the disciplines. Now, bioethics tends to accommodate more empirical research. Three hypotheses explain this emergence. Firstly, dissatisfaction with a foundationalist interpretation of applied ethics created a stimulus to incorporate empirical research in bioethics. Secondly, clinical ethicists became engaged in empirical research due to their strong integration in the medical setting. Thirdly, the rise of the evidence-based paradigm had an influence on the practice of bioethics. However, a problematic relationship cannot simply and easily evolve into a perfect interaction. A new and positive climate for empirical approaches has arisen, but the original difficulties have not disappeared.

Effects of turbulence on the collision rate of cloud droplets

NASA Astrophysics Data System (ADS)

Ayala, Orlando

This dissertation concerns effects of air turbulence on the collision rate of atmospheric cloud droplets. This research was motivated by the speculation that air turbulence could enhance the collision rate thereby help transform cloud droplets to rain droplets in a short time as observed in nature. The air turbulence within clouds is assumed to be homogeneous and isotropic, and its small-scale motion (1 mm to 10 cm scales) is computationally generated by direct numerical integration of the full Navier-Stokes equations. Typical droplet and turbulence parameters of convective warm clouds are used to determine the Stokes numbers (St) and the nondimensional terminal velocities (Sv) which characterize droplet relative inertia and gravitational settling, respectively. A novel and efficient methodology for conducting direct numerical simulations (DNS) of hydrodynamically-interacting droplets in the context of cloud microphysics has been developed. This numerical approach solves the turbulent flow by the pseudo-spectral method with a large-scale forcing, and utilizes an improved superposition method to embed analytically the local, small-scale (10 mum to 1 mm) disturbance flows induced by the droplets. This hybrid representation of background turbulent air motion and the induced disturbance flows is then used to study the combined effects of hydrodynamic interactions and airflow turbulence on the motion and collisions of cloud droplets. Hybrid DNS results show that turbulence can increase the geometric collision kernel relative to the gravitational geometric kernel by as much as 42% due to enhanced radial relative motion and preferential concentration of droplets. The exact level of enhancements depends on the Taylor-microscale Reynolds number, turbulent dissipation rate, and droplet pair size ratio. One important finding is that turbulence has a relatively dominant effect on the collision process between droplets close in size as the gravitational collision mechanism diminishes. A theory was developed to predict the radial relative velocity between droplets at contact. The theory agrees with our DNS results to within 5% for cloud droplets with strong settling. In addition, an empirical model is developed to quantify the radial distribution function. (Abstract shortened by UMI.)

Beyond multi-fractals: surrogate time series and fields

NASA Astrophysics Data System (ADS)

Venema, V.; Simmer, C.

2007-12-01

Most natural complex are characterised by variability on a large range of temporal and spatial scales. The two main methodologies to generate such structures are Fourier/FARIMA based algorithms and multifractal methods. The former is restricted to Gaussian data, whereas the latter requires the structure to be self-similar. This work will present so-called surrogate data as an alternative that works with any (empirical) distribution and power spectrum. The best-known surrogate algorithm is the iterative amplitude adjusted Fourier transform (IAAFT) algorithm. We have studied six different geophysical time series (two clouds, runoff of a small and a large river, temperature and rain) and their surrogates. The power spectra and consequently the 2nd order structure functions were replicated accurately. Even the fourth order structure function was more accurately reproduced by the surrogates as would be possible by a fractal method, because the measured structure deviated too strong from fractal scaling. Only in case of the daily rain sums a fractal method could have been more accurate. Just as Fourier and multifractal methods, the current surrogates are not able to model the asymmetric increment distributions observed for runoff, i.e., they cannot reproduce nonlinear dynamical processes that are asymmetric in time. Furthermore, we have found differences for the structure functions on small scales. Surrogate methods are especially valuable for empirical studies, because the time series and fields that are generated are able to mimic measured variables accurately. Our main application is radiative transfer through structured clouds. Like many geophysical fields, clouds can only be sampled sparsely, e.g. with in-situ airborne instruments. However, for radiative transfer calculations we need full 3-dimensional cloud fields. A first study relating the measured properties of the cloud droplets and the radiative properties of the cloud field by generating surrogate cloud fields yielded good results within the measurement error. A further test of the suitability of the surrogate clouds for radiative transfer is evaluated by comparing the radiative properties of model cloud fields of sparse cumulus and stratocumulus with their surrogate fields. The bias and root mean square error in various radiative properties is small and the deviations in the radiances and irradiances are not statistically significant, i.e. these deviations can be attributed to the Monte Carlo noise of the radiative transfer calculations. We compared these results with optical properties of synthetic clouds that have either the correct distribution (but no spatial correlations) or the correct power spectrum (but a Gaussian distribution). These clouds did show statistical significant deviations. For more information see: http://www.meteo.uni-bonn.de/venema/themes/surrogates/

Horizontal Variability of Water and Its Relationship to Cloud Fraction near the Tropical Tropopause: Using Aircraft Observations of Water Vapor to Improve the Representation of Grid-scale Cloud Formation in GEOS-5

NASA Technical Reports Server (NTRS)

Selkirk, Henry B.; Molod, Andrea M.

2014-01-01

Large-scale models such as GEOS-5 typically calculate grid-scale fractional cloudiness through a PDF parameterization of the sub-gridscale distribution of specific humidity. The GEOS-5 moisture routine uses a simple rectangular PDF varying in height that follows a tanh profile. While below 10 km this profile is informed by moisture information from the AIRS instrument, there is relatively little empirical basis for the profile above that level. ATTREX provides an opportunity to refine the profile using estimates of the horizontal variability of measurements of water vapor, total water and ice particles from the Global Hawk aircraft at or near the tropopause. These measurements will be compared with estimates of large-scale cloud fraction from CALIPSO and lidar retrievals from the CPL on the aircraft. We will use the variability measurements to perform studies of the sensitivity of the GEOS-5 cloud-fraction to various modifications to the PDF shape and to its vertical profile.

Effects of Raindrop Shape Parameter on the Simulation of Plum Rains

NASA Astrophysics Data System (ADS)

Mei, H.; Zhou, L.; Li, X.; Huang, X.; Guo, W.

2017-12-01

The raindrop shape parameter of particle distribution is generally set as constant in a Double-moment Bulk Microphysics Scheme (DBMS) using Gama distribution function though which suggest huge differences in time and space according to observations. Based on Milbrandt 2-mon(MY) DBMS, four cases during Plum Rains season are simulated coupled with four empirical relationships between shape parameter (μr) and slope parameter of raindrop which have been concluded from observations of raindrop distributions. The analysis of model results suggest that μr have some influences on rainfall. Introducing the diagnostic formulas of μr may have some improvement on systematic biases of 24h accumulated rainfall and show some correction ability on local characteristics of rainfall distribution. Besides,the tendency to improve strong rainfall could be sensitive to μr. With the improvement of the diagnosis of μr using the empirically diagnostic formulas, μr increases generally in the middle- and lower-troposphere and decreases with the stronger rainfall. Its conclued that, the decline in raindrop water content and the increased raindrop mass-weighted average terminal velocity directly related to μr are the direct reasons of variations in the precipitation.On the other side, the environmental conditions including relative humidity and dynamical parameters are the key indirectly causes which has close relationships with the changes in cloud particles and rainfall distributions.Furthermore,the differences in the scale of improvement between the weak and heavy rainfall mainly come from the distinctions of response features about their variable fields respectively. The extent of variation in the features of cloud particles in warm clouds of heavy rainfall differs greatly from that of weak rainfall, though they share the same trend of variation. On the conditions of weak rainfall, the response of physical characteristics to μr performed consistent trends and some linear features. However, environmental conditions of relative humidity and dynamical parameters perform strong and vertically deep adjustments in the heavy precipitation with vigorous cloud systems. In this case, the microphysical processes and environmental conditions experience complex interactions with each other and no significant laws could be concluded.

Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model.

PubMed

Sato, Yousuke; Goto, Daisuke; Michibata, Takuro; Suzuki, Kentaroh; Takemura, Toshihiko; Tomita, Hirofumi; Nakajima, Teruyuki

2018-03-07

Aerosols affect climate by modifying cloud properties through their role as cloud condensation nuclei or ice nuclei, called aerosol-cloud interactions. In most global climate models (GCMs), the aerosol-cloud interactions are represented by empirical parameterisations, in which the mass of cloud liquid water (LWP) is assumed to increase monotonically with increasing aerosol loading. Recent satellite observations, however, have yielded contradictory results: LWP can decrease with increasing aerosol loading. This difference implies that GCMs overestimate the aerosol effect, but the reasons for the difference are not obvious. Here, we reproduce satellite-observed LWP responses using a global simulation with explicit representations of cloud microphysics, instead of the parameterisations. Our analyses reveal that the decrease in LWP originates from the response of evaporation and condensation processes to aerosol perturbations, which are not represented in GCMs. The explicit representation of cloud microphysics in global scale modelling reduces the uncertainty of climate prediction.

Students' Attitude to Cloud-Based Learning in University Diverse Environment: A Case of Russia

ERIC Educational Resources Information Center

Atabekova, Anastasia; Gorbatenko, Rimma; Chilingaryan, Kamo

2015-01-01

The paper explores the ways how Russian students with different social background view the cloud- based foreign language learning. The empirical data was collected through questionnaires and in-depth interviews of students from metropolitan and regional universities, taking into account the students' family incomes, ethnic and religious…

Predicting Daily Insolation with Hourly Cloud Height and Coverage.

NASA Astrophysics Data System (ADS)

Meyers, T. P.; Dale, R. F.

1983-04-01

Solar radiation information is used in crop growth, boundary layer, entomological and plant pathological models, and in determining the potential use of active and passive solar energy systems. Yet solar radiation is among the least measured meteorological variables.A semi-physical model based on standard meteorological data was developed to estimate solar radiation received at the earth's surface. The radiation model includes the effects of Rayleigh scattering, absorption by water vapor and permanent gases, and absorption and scattering by aerosols and clouds. Cloud attenuation is accounted for by assigning transmission coefficients based on cloud height and amount. The cloud transmission coefficients for various heights and coverages were derived empirically from hourly observations of solar radiation in conjunction with corresponding cloud observations at West Lafayette, Indiana. The model was tested with independent data from West Lafayette and Indianapolis, Madison, WI, Omaha, NE, Columbia, MO, Nashville, TN, Seattle, WA, Los Angeles, CA, Phoenix, AZ, Lake Charles, LA, Miami, FL, and Sterling, VA. For each of these locations a 16% random sample of days was drawn within each of the 12 months in a year for testing the model. Excellent agreement between predicted and observed radiation values was obtained for all stations tested. Mean absolute errors ranged from 1.05 to 1.80 MJ m2 day1 and root-mean-square errors ranged from 1.31 to 2.32 MJ m2 day1. The model's performance judged by relative error was found to be independent of season and cloud amount for all locations tested.

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and validated with icing PIREPS. The initial validation is encouraging for single-layer cloud conditions. More work is needed to test and refine the method for global application in a wider range of cloud conditions. A brief overview of our current method, applications, verification, and plans for future work will be presented.

Cloud Front

NASA Technical Reports Server (NTRS)

2006-01-01

[figure removed for brevity, see original site] Context image for PIA02171 Cloud Front

These clouds formed in the south polar region. The faintness of the cloud system likely indicates that these are mainly ice clouds, with relatively little dust content.

Image information: VIS instrument. Latitude -86.7N, Longitude 212.3E. 17 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Determine precipitation rates from visible and infrared satellite images of clouds by pattern recognition technique. Progress Report, 1 Jul. 1985 - 31 Mar. 1987 Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Weinman, James A.; Garan, Louis

1987-01-01

A more advanced cloud pattern analysis algorithm was subsequently developed to take the shape and brightness of the various clouds into account in a manner that is more consistent with the human analyst's perception of GOES cloud imagery. The results of that classification scheme were compared with precipitation probabilities observed from ships of opportunity off the U.S. east coast to derive empirical regressions between cloud types and precipitation probability. The cloud morphology was then quantitatively and objectively used to map precipitation probabilities during two winter months during which severe cold air outbreaks were observed over the northwest Atlantic. Precipitation probabilities associated with various cloud types are summarized. Maps of precipitation probability derived from the cloud morphology analysis program for two months and the precipitation probability derived from thirty years of ship observation were observed.

Operational implications of a cloud model simulation of space shuttle exhaust clouds in different atmospheric conditions

NASA Technical Reports Server (NTRS)

Zak, J. A.

1989-01-01

A three-dimensional cloud model was used to characterize the dominant influence of the environment on the Space Shuttle exhaust cloud. The model was modified to accept the actual heat and moisture from rocket exhausts and deluge water as initial conditions. An upper-air sounding determined the ambient atmosphere in which the cloud would grow. The model was validated by comparing simulated clouds with observed clouds from four actual Shuttle launches. Results are discussed with operational weather forecasters in mind. The model successfully produced clouds with dimensions, rise, decay, liquid water contents, and vertical motion fields very similar to observed clouds whose dimensions were calculated from 16 mm film frames. Once validated, the model was used in a number of different atmospheric conditions ranging from very unstable to very stable. Wind shear strongly affected the appearance of both the ground cloud and vertical column cloud. The ambient low-level atmospheric moisture governed the amount of cloud water in model clouds. Some dry atmospheres produced little or no cloud water. An empirical forecast technique for Shuttle cloud rise is presented and differences between natural atmospheric convection and exhaust clouds are discussed.

Scale dependence of entrainment-mixing mechanisms in cumulus clouds

DOE PAGES

Lu, Chunsong; Liu, Yangang; Niu, Shengjie; ...

2014-12-17

This work empirically examines the dependence of entrainment-mixing mechanisms on the averaging scale in cumulus clouds using in situ aircraft observations during the Routine Atmospheric Radiation Measurement Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) field campaign. A new measure of homogeneous mixing degree is defined that can encompass all types of mixing mechanisms. Analysis of the dependence of the homogenous mixing degree on the averaging scale shows that, on average, the homogenous mixing degree decreases with increasing averaging scales, suggesting that apparent mixing mechanisms gradually approach from homogeneous mixing to extreme inhomogeneous mixing with increasingmore » scales. The scale dependence can be well quantified by an exponential function, providing first attempt at developing a scale-dependent parameterization for the entrainment-mixing mechanism. The influences of three factors on the scale dependence are further examined: droplet-free filament properties (size and fraction), microphysical properties (mean volume radius and liquid water content of cloud droplet size distributions adjacent to droplet-free filaments), and relative humidity of entrained dry air. It is found that the decreasing rate of homogeneous mixing degree with increasing averaging scales becomes larger with larger droplet-free filament size and fraction, larger mean volume radius and liquid water content, or higher relative humidity. The results underscore the necessity and possibility of considering averaging scale in representation of entrainment-mixing processes in atmospheric models.« less

Explicit prediction of ice clouds in general circulation models

NASA Astrophysics Data System (ADS)

Kohler, Martin

1999-11-01

Although clouds play extremely important roles in the radiation budget and hydrological cycle of the Earth, there are large quantitative uncertainties in our understanding of their generation, maintenance and decay mechanisms, representing major obstacles in the development of reliable prognostic cloud water schemes for General Circulation Models (GCMs). Recognizing their relative neglect in the past, both observationally and theoretically, this work places special focus on ice clouds. A recent version of the UCLA - University of Utah Cloud Resolving Model (CRM) that includes interactive radiation is used to perform idealized experiments to study ice cloud maintenance and decay mechanisms under various conditions in term of: (1) background static stability, (2) background relative humidity, (3) rate of cloud ice addition over a fixed initial time-period and (4) radiation: daytime, nighttime and no-radiation. Radiation is found to have major effects on the life-time of layer-clouds. Optically thick ice clouds decay significantly slower than expected from pure microphysical crystal fall-out (taucld = 0.9--1.4 h as opposed to no-motion taumicro = 0.5--0.7 h). This is explained by the upward turbulent fluxes of water induced by IR destabilization, which partially balance the downward transport of water by snowfall. Solar radiation further slows the ice-water decay by destruction of the inversion above cloud-top and the resulting upward transport of water. Optically thin ice clouds, on the other hand, may exhibit even longer life-times (>1 day) in the presence of radiational cooling. The resulting saturation mixing ratio reduction provides for a constant cloud ice source. These CRM results are used to develop a prognostic cloud water scheme for the UCLA-GCM. The framework is based on the bulk water phase model of Ose (1993). The model predicts cloud liquid water and cloud ice separately, and which is extended to split the ice phase into suspended cloud ice (predicted) and falling snow (diagnosed) components. An empirical parameterization of the effect of upward turbulent water fluxes in cloud layers is obtained from the CRM simulations by (1) identifying the time-scale of conversion of cloud ice to snow as the key parameter, and (2) regressing it onto cloud differential IR heating and environmental static stability. The updated UCLA-GCM achieves close agreement with observations in global mean top of atmosphere fluxes (within 1--4 W/m2). Artificially suppressing the impact of cloud turbulent fluxes reduces the global mean ice water path by a factor of 3 and produces errors in each of solar and IR fluxes at the top of atmosphere of about 5--6 W/m2.

Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.

Observed reflectivities and liquid water content for marine stratocumulus

NASA Technical Reports Server (NTRS)

Coakley, J. A., Jr.; Snider, J. B.

1989-01-01

Simultaneous observations of cloud liquid water content and cloud reflectivity are used to verify their parametric relationship in a manner consistent with simple parameterizations often used in general-circulation climate models. The column amount of cloud liquid water was measured with a microwave radiometer on San Nicolas Island as described by Hogg et al., (1983). Cloud reflectivity was obtained through spatial coherence analysis of AVHRR imagery data as per Coakley and Baldwin (1984) and Coakley and Beckner (1988). The dependence of the observed reflectivity on the observed liquid water is discussed, and this empirical relationship is compared with the parameterization proposed by Stephens (1978).

Empirical and modeled synoptic cloud climatology of the Arctic Ocean

NASA Technical Reports Server (NTRS)

Barry, R. G.; Newell, J. P.; Schweiger, A.; Crane, R. G.

1986-01-01

A set of cloud cover data were developed for the Arctic during the climatically important spring/early summer transition months. Parallel with the determination of mean monthly cloud conditions, data for different synoptic pressure patterns were also composited as a means of evaluating the role of synoptic variability on Arctic cloud regimes. In order to carry out this analysis, a synoptic classification scheme was developed for the Arctic using an objective typing procedure. A second major objective was to analyze model output of pressure fields and cloud parameters from a control run of the Goddard Institue for Space Studies climate model for the same area and to intercompare the synoptic climatatology of the model with that based on the observational data.

Evaluation of sea-surface photosynthetically available radiation algorithms under various sky conditions and solar elevations.

PubMed

Somayajula, Srikanth Ayyala; Devred, Emmanuel; Bélanger, Simon; Antoine, David; Vellucci, V; Babin, Marcel

2018-04-20

In this study, we report on the performance of satellite-based photosynthetically available radiation (PAR) algorithms used in published oceanic primary production models. The performance of these algorithms was evaluated using buoy observations under clear and cloudy skies, and for the particular case of low sun angles typically encountered at high latitudes or at moderate latitudes in winter. The PAR models consisted of (i) the standard one from the NASA-Ocean Biology Processing Group (OBPG), (ii) the Gregg and Carder (GC) semi-analytical clear-sky model, and (iii) look-up-tables based on the Santa Barbara DISORT atmospheric radiative transfer (SBDART) model. Various combinations of atmospheric inputs, empirical cloud corrections, and semi-analytical irradiance models yielded a total of 13 (11 + 2 developed in this study) different PAR products, which were compared with in situ measurements collected at high frequency (15 min) at a buoy site in the Mediterranean Sea (the "BOUée pour l'acquiSition d'une Série Optique à Long termE," or, "BOUSSOLE" site). An objective ranking method applied to the algorithm results indicated that seven PAR products out of 13 were well in agreement with the in situ measurements. Specifically, the OBPG method showed the best overall performance with a root mean square difference (RMSD) (bias) of 19.7% (6.6%) and 10% (6.3%) followed by the look-up-table method with a RMSD (bias) of 25.5% (6.8%) and 9.6% (2.6%) at daily and monthly scales, respectively. Among the four methods based on clear-sky PAR empirically corrected for cloud cover, the Dobson and Smith method consistently underestimated daily PAR while the Budyko formulation overestimated daily PAR. Empirically cloud-corrected methods using cloud fraction (CF) performed better under quasi-clear skies (CF<0.3) with an RMSD (bias) of 9.7%-14.8% (3.6%-11.3%) than under partially clear to cloudy skies (0.30.7), however, all methods showed larger RMSD differences (biases) ranging between 32% and 80.6% (-54.5%-8.7%). Finally, three methods tested for low sun elevations revealed systematic overestimation, and one method showed a systematic underestimation of daily PAR, with relative RMSDs as large as 50% under all sky conditions. Under partially clear to overcast conditions all the methods underestimated PAR. Model uncertainties predominantly depend on which cloud products were used.

Predicting Cloud Computing Technology Adoption by Organizations: An Empirical Integration of Technology Acceptance Model and Theory of Planned Behavior

ERIC Educational Resources Information Center

Ekufu, ThankGod K.

2012-01-01

Organizations are finding it difficult in today's economy to implement the vast information technology infrastructure required to effectively conduct their business operations. Despite the fact that some of these organizations are leveraging on the computational powers and the cost-saving benefits of computing on the Internet cloud, others…

Altitude-dependent Drift of a Chemical Release Cloud at Middle Latitudes

NASA Astrophysics Data System (ADS)

Pedersen, T.; Holmes, J. M.; Sutton, E. K.

2017-12-01

A chemical release experiment conducted at the White Sands Missile Range in February 2015 consisted of firing of three identical canisters at different altitudes along a near-vertical trajectory, creating a large structured cloud after diffusion and expansion of the three initial dispersals. Dedicated optical observations from near the launch site and a remote site allow determination of the position and motion of the extended optical cloud as a function of time, while photographs captured and posted by members of the general public provide additional look angles to constrain the cloud shape in more detail. We compare the observed drift and evolution of the cloud with empirical and theoretical models of the neutral winds to examine the altitudinal shear in the neutral winds and their effects on the motion and shape of the extended optical cloud.

Polarization models of filamentary molecular clouds.

NASA Astrophysics Data System (ADS)

Carlqvist, P.; Kristen, H.

1997-08-01

We study numerically the linear polarization and extinction of light from background stars in three types of models of elongated molecular clouds by following the development of the Stokes parameters. The clouds are assumed to be of cylindrical shape and penetrated by a helical magnetic field {vec}(B). In the first two models we study only the relative magnitude of the polarization assuming that the polarization is proportional to Bmu^, where primarily μ=2. Provided there is no background/foreground polarization present we find from the cylindrically symmetric Model I that the angle of polarization has a bimodal character with the polarization being either parallel with or perpendicular to the axis of the filament. For some magnetic-field geometries both angles may exist in one and the same filament. It is concluded that it is not a straightforward task to find the magnetic-field-line pattern from the polarization pattern. If a background/foreground polarization exists or, as in Model II, the filament is not cylindrically symmetric, the bimodal character of the angle of polarization is lost. By means of Model III we have, using semi-empirical methods based on the Davis-Greenstein mechanism, estimated the absolute degree of polarization in the filamentary molecular cloud L204. It is found that the polarization produced by the model is much less than the polarization observed. We therefore conclude that most of the polarization measured in the L204 cloud is not produced in the cloud itself but is constituted by a large-scale background/foreground polarization.

Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications

NASA Astrophysics Data System (ADS)

Minnis, P.; Bedka, K. M.; Smith, W., Jr.; Yost, C. R.; Bedka, S. T.; Palikonda, R.; Spangenberg, D.; Sun-Mack, S.; Trepte, Q.; Dong, X.; Xi, B.

2014-12-01

Cloud properties determined from satellite imager radiances are increasingly used in weather and climate applications, particularly in nowcasting, model assimilation and validation, trend monitoring, and precipitation and radiation analyses. The value of using the satellite-derived cloud parameters is determined by the accuracy of the particular parameter for a given set of conditions, such as viewing and illumination angles, surface background, and cloud type and structure. Because of the great variety of those conditions and of the sensors used to monitor clouds, determining the accuracy or uncertainties in the retrieved cloud parameters is a daunting task. Sensitivity studies of the retrieved parameters to the various inputs for a particular cloud type are helpful for understanding the errors associated with the retrieval algorithm relative to the plane-parallel world assumed in most of the model clouds that serve as the basis for the retrievals. Real world clouds, however, rarely fit the plane-parallel mold and generate radiances that likely produce much greater errors in the retrieved parameter than can be inferred from sensitivity analyses. Thus, independent, empirical methods are used to provide a more reliable uncertainty analysis. At NASA Langley, cloud properties are being retrieved from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for climate monitoring and model validation as part of the NASA CERES project since 2000 and from AVHRR data since 1978 as part of the NOAA CDR program. Cloud properties are also being retrieved in near-real time globally from both GEO and LEO satellites for weather model assimilation and nowcasting for hazards such as aircraft icing. This paper discusses the various independent datasets and approaches that are used to assessing the imager-based satellite cloud retrievals. These include, but are not limited to data from ARM sites, CloudSat, and CALIPSO. This paper discusses the use of the various datasets available, the methods employed to utilize them in the cloud property retrieval validation process, and the results and how they aid future development of the retrieval algorithms. Future needs are also discussed.

Moisture status during a strong El Niño explains a tropical montane cloud forest's upper limit.

PubMed

Crausbay, Shelley D; Frazier, Abby G; Giambelluca, Thomas W; Longman, Ryan J; Hotchkiss, Sara C

2014-05-01

Growing evidence suggests short-duration climate events may drive community structure and composition more directly than long-term climate means, particularly at ecotones where taxa are close to their physiological limits. Here we use an empirical habitat model to evaluate the role of microclimate during a strong El Niño in structuring a tropical montane cloud forest's upper limit and composition in Hawai'i. We interpolate climate surfaces, derived from a high-density network of climate stations, to permanent vegetation plots. Climatic predictor variables include (1) total rainfall, (2) mean relative humidity, and (3) mean temperature representing non-El Niño periods and a strong El Niño drought. Habitat models explained species composition within the cloud forest with non-El Niño rainfall; however, the ecotone at the cloud forest's upper limit was modeled with relative humidity during a strong El Niño drought and secondarily with non-El Niño rainfall. This forest ecotone may be particularly responsive to strong, short-duration climate variability because taxa here, particularly the isohydric dominant Metrosideros polymorpha, are near their physiological limits. Overall, this study demonstrates moisture's overarching influence on a tropical montane ecosystem, and suggests that short-term climate events affecting moisture status are particularly relevant at tropical ecotones. This study further suggests that predicting the consequences of climate change here, and perhaps in other tropical montane settings, will rely on the skill and certainty around future climate models of regional rainfall, relative humidity, and El Niño.

The great Indian haze revisited: aerosol distribution effects on microphysical and optical properties of warm clouds over peninsular India

NASA Astrophysics Data System (ADS)

Ghanti, R.; Ghosh, S.

2010-03-01

The Indian subcontinent is undergoing a phase of rapid urbanisation. Inevitable fallout of this process is a concomitant increase in air pollution much of which can be attributed to the infamous great Indian haze phenomena. One observes that the aerosol size distributions vary considerably along the Bay of Bengal (BOB), Arabian Sea (AS) and the Indian Ocean (IO), although, the dynamical attributes are very similar, particularly over the BOB and the AS during this season. Unlike major European studies (e.g. Aerosol Characterization Experiment-2, Ghosh et al., 2005), there are no cloud microphysical modelling studies to complement these observational results for the Indian sub-continent. Ours is the first modelling study over this important region where a time-tested model (O'Dowd et al., 1999a; Ghosh et al., 2007; Rap et al., 2009) is used to obtain cloud microphysical and optical properties from observed aerosol size distributions. Un-activated aerosol particles and very small cloud droplets have to be treated specially to account for non-ideal effects-our model does this effectively yielding realistic estimate of cloud droplet number concentrations (Nc). Empirical relationships linking aerosol concentration to (Nc) yield a disproportionately higher Nc suggesting that such empirical formulations should be used with caution. Our modelling study reveals that the cloud's microphysical and optical properties are very similar along the AS and the BOB despite them having disparate dry aerosol spectral distributions. This is non-intuitive, as one would expect changes in microphysical development with widely different aerosol distributions. There is some increase in cloud droplet numbers with increased haze concentrations but much less than a simple proportion would indicate.

Implementing a warm cloud microphysics parameterization for convective clouds in NCAR CESM

NASA Astrophysics Data System (ADS)

Shiu, C.; Chen, Y.; Chen, W.; Li, J. F.; Tsai, I.; Chen, J.; Hsu, H.

2013-12-01

Most of cumulus convection schemes use simple empirical approaches to convert cloud liquid mass to rain water or cloud ice to snow e.g. using a constant autoconversion rate and dividing cloud liquid mass into cloud water and ice as function of air temperature (e.g. Zhang and McFarlane scheme in NCAR CAM model). There are few studies trying to use cloud microphysical schemes to better simulate such precipitation processes in the convective schemes of global models (e.g. Lohmann [2008] and Song, Zhang, and Li [2012]). A two-moment warm cloud parameterization (i.e. Chen and Liu [2004]) is implemented into the deep convection scheme of CAM5.2 of CESM model for treatment of conversion of cloud liquid water to rain water. Short-term AMIP type global simulations are conducted to evaluate the possible impacts from the modification of this physical parameterization. Simulated results are further compared to observational results from AMWG diagnostic package and CloudSAT data sets. Several sensitivity tests regarding to changes in cloud top droplet concentration (here as a rough testing for aerosol indirect effects) and changes in detrained cloud size of convective cloud ice are also carried out to understand their possible impacts on the cloud and precipitation simulations.

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

NASA Technical Reports Server (NTRS)

Shiffman, Smadar; Nemani, Ramakrishna

2005-01-01

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

No breakdown of the radiatively driven wind theory in low-metallicity environments

NASA Astrophysics Data System (ADS)

Bouret, J.-C.; Lanz, T.; Hillier, D. J.; Martins, F.; Marcolino, W. L. F.; Depagne, E.

2015-05-01

We present a spectroscopic analysis of Hubble Space Telescope/Cosmic Origins Spectrograph observations of three massive stars in the low metallicity dwarf galaxies IC 1613 and WLM. These stars, were previously observed with Very Large Telescope (VLT)/X-shooter by Tramper et al., who claimed that their mass-loss rates are higher than expected from theoretical predictions for the underlying metallicity. A comparison of the far ultraviolet (FUV) spectra with those of stars of similar spectral types/luminosity classes in the Galaxy, and the Magellanic Clouds provides a direct, model-independent check of the mass-loss-metallicity relation. Then, a quantitative spectroscopic analysis is carried out using the non-LTE (NLTE) stellar atmosphere code CMFGEN. We derive the photospheric and wind characteristics, benefiting from a much better sensitivity of the FUV lines to wind properties than Hα. Iron and CNO abundances are measured, providing an independent check of the stellar metallicity. The spectroscopic analysis indicates that Z/Z⊙ = 1/5, similar to a Small Magellanic Cloud-type environment, and higher than usually quoted for IC 1613 and WLM. The mass-loss rates are smaller than the empirical ones by Tramper et al., and those predicted by the widely used theoretical recipe by Vink et al. On the other hand, we show that the empirical, FUV-based, mass-loss rates are in good agreement with those derived from mass fluxes computed by Lucy. We do not concur with Tramper et al. that there is a breakdown in the mass-loss-metallicity relation.

Daytime turbulent exchange between the Amazon forest and the atmosphere

NASA Technical Reports Server (NTRS)

Fitzjarrald, David R.; Moore, Kathleen E.; Cabral, Osvaldo M. R.; Scolar, Jose; Manzi, Antonio O.; Deabreusa, Leonardo D.

1989-01-01

Detailed observations of turbulence just above and below the crown of the Amazon rain forest during the wet season are presented. The forest canopy is shown to remove high frequency turbulent fluctuations while passing lower frequencies. Filter characteristics of turbulent transfer into the Amazon rain forest canopy are quantified. Simple empirical relations that relate observed turbulent heat fluxes to horizontal wind variance are presented. Changes in the amount of turbulent coupling between the forest and the boundary layer associated with deep convective clouds are presented both as statistical averages and as a series of case studies. These convective processes during the rainy season are shown to alter the diurnal course of turbulent fluxes. In wake of giant coastal systems, no significant heat or moisture fluxes occur for up to a day after the event. Radar data is used to demonstrate that even small raining clouds are capable of evacuating the canopy of substances normally trapped by persistent static stability near the forest floor. Recovery from these events can take more than an hour, even during mid-day. In spite of the ubiquitous presence of clouds and frequent rain during this season, the average horizontal wind speed spectrum is well described by dry CBL similarity hypotheses originally found to apply in flat terrain.

Daytime turbulent exchange between the Amazon forest and the atmosphere

NASA Technical Reports Server (NTRS)

Fitzjarrald, David R.; Moore, Kathleen E.; Cabral, Osvaldo M. R.; Scolar, Jose; Manzi, Antonio

1990-01-01

Detailed observations of turbulence just above and below the crown of the Amazon rain forest during the wet season are presented. The forest canopy is shown to remove high frequency turbulent fluctuations while passing lower frequencies. Filter characteristics of turbulent transfer into the Amazon rain forest canopy are quantified. Simple empirical relations that relate observed turbulent heat fluxes to horizontal wind variance are presented. Changes in the amount of turbulent coupling between the forest and the boundary layer associated with deep convective clouds are presented both as statistical averages and as a series of case studies. These convective processes during the rainy season are shown to alter the diurnal course of turbulent fluxes. In wake of giant coastal systems, no significant heat or moisture fluxes occur for up to a day after the event. Radar data is used to demonstrate that even small raining clouds are capable of evacuating the canopy of substances normally trapped by persistent static stability near the forest floor. Recovery from these events can take more than an hour, even during mid-day. In spite of the ubiquitous presence of clouds and frequent rain during this season, the average horizontal wind speed spectrum is well described by dry CBL similarity hypotheses originally found to apply in flat terrain.

Global validation of empirically corrected EP-Total Ozone Mapping Spectrometer (TOMS) total ozone columns using Brewer and Dobson ground-based measurements

NASA Astrophysics Data System (ADS)

Antón, M.; Koukouli, M. E.; Kroon, M.; McPeters, R. D.; Labow, G. J.; Balis, D.; Serrano, A.

2010-10-01

This article focuses on the global-scale validation of the empirically corrected Version 8 total ozone column data set acquired by the NASA Total Ozone Mapping Spectrometer (TOMS) during the period 1996-2004 when this instrument was flying aboard the Earth Probe (EP) satellite platform. This analysis is based on the use of spatially co-located, ground-based measurements from Dobson and Brewer spectrophotometers. The original EP-TOMS V8 total ozone column data set was also validated with these ground-based measurements to quantify the improvements made by the empirical correction that was necessary as a result of instrumental degradation issues occurring from the year 2000 onward that were uncorrectable by normal calibration techniques. EP-TOMS V8-corrected total ozone data present a remarkable improvement concerning the significant negative bias of around ˜3% detected in the original EP-TOMS V8 observations after the year 2000. Neither the original nor the corrected EP-TOMS satellite total ozone data sets show a significant dependence on latitude. In addition, both EP-TOMS satellite data sets overestimate the Brewer measurements for small solar zenith angles (SZA) and underestimate for large SZA, explaining a significant seasonality (˜1.5%) for cloud-free and cloudy conditions. Conversely, relative differences between EP-TOMS and Dobson present almost no dependence on SZA for cloud-free conditions and a strong dependence for cloudy conditions (from +2% for small SZA to -1% for high SZA). The dependence of the satellite ground-based relative differences on total ozone shows good agreement for column values above 250 Dobson units. Our main conclusion is that the upgrade to TOMS V8-corrected total ozone data presents a remarkable improvement. Nevertheless, despite its quality, the EP-TOMS data for the period 2000-2004 should not be used as a source for trend analysis since EP-TOMS ozone trends are empirically corrected using NOAA-16 and NOAA-17 solar backscatter ultraviolet/2 data as external references, and therefore, they are no longer considered as independent observations.

A Global, Multi-Waveband Model for the Zodiacal Cloud

NASA Technical Reports Server (NTRS)

Grogan, Keith; Dermott, Stanley F.; Kehoe, Thomas J. J.

2003-01-01

This recently completed three-year project was undertaken by the PI at the University of Florida, NASA Goddard and JPL, and by the Co-I and Collaborator at the University of Florida. The funding was used to support a continuation of research conducted at the University of Florida over the last decade which focuses on the dynamics of dust particles in the interplanetary environment. The main objectives of this proposal were: To produce improved dynamical models of the zodiacal cloud by performing numerical simulations of the orbital evolution of asteroidal and cometary dust particles. To provide visualizations of the results using our visualization software package, SIMUL, simulating the viewing geometries of IRAS and COBE and comparing the model results with archived data. To use the results to provide a more accurate model of the brightness distribution of the zodiacal cloud than existing empirical models. In addition, our dynamical approach can provide insight into fundamental properties of the cloud, including but not limited to the total mass and surface area of dust, the size-frequency distribution of dust, and the relative contributions of asteroidal and cometary material. The model can also be used to provide constraints on trace signals from other sources, such as dust associated with the "Plutinos" , objects captured in the 2:3 resonance with Neptune.

Shallow cumuli ensemble statistics for development of a stochastic parameterization

NASA Astrophysics Data System (ADS)

Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

2014-05-01

According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a Poisson distribution, and cloud properties sub-sampled from a generalized ensemble distribution. We study the role of the different cloud subtypes in a shallow convective ensemble and how the diverse cloud properties and cloud lifetimes affect the system macro-state. To what extent does the cloud-base mass flux distribution deviate from the simple Boltzmann distribution and how does it affect the results from the stochastic model? Is the memory, provided by the finite lifetime of individual clouds, of importance for the ensemble statistics? We also test for the minimal information given as an input to the stochastic model, able to reproduce the ensemble mean statistics and the variability in a convective ensemble. An important property of the resulting distribution of the sub-grid convective states is its scale-adaptivity - the smaller the grid-size, the broader the compound distribution of the sub-grid states.

An Architecture for Cross-Cloud System Management

NASA Astrophysics Data System (ADS)

Dodda, Ravi Teja; Smith, Chris; van Moorsel, Aad

The emergence of the cloud computing paradigm promises flexibility and adaptability through on-demand provisioning of compute resources. As the utilization of cloud resources extends beyond a single provider, for business as well as technical reasons, the issue of effectively managing such resources comes to the fore. Different providers expose different interfaces to their compute resources utilizing varied architectures and implementation technologies. This heterogeneity poses a significant system management problem, and can limit the extent to which the benefits of cross-cloud resource utilization can be realized. We address this problem through the definition of an architecture to facilitate the management of compute resources from different cloud providers in an homogenous manner. This preserves the flexibility and adaptability promised by the cloud computing paradigm, whilst enabling the benefits of cross-cloud resource utilization to be realized. The practical efficacy of the architecture is demonstrated through an implementation utilizing compute resources managed through different interfaces on the Amazon Elastic Compute Cloud (EC2) service. Additionally, we provide empirical results highlighting the performance differential of these different interfaces, and discuss the impact of this performance differential on efficiency and profitability.

Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

DOE PAGES

Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; ...

2014-11-06

In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice numbermore » is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.« less

A New Cloud and Aerosol Layer Detection Method Based on Micropulse Lidar Measurements

NASA Astrophysics Data System (ADS)

Wang, Q.; Zhao, C.; Wang, Y.; Li, Z.; Wang, Z.; Liu, D.

2014-12-01

A new algorithm is developed to detect aerosols and clouds based on micropulse lidar (MPL) measurements. In this method, a semi-discretization processing (SDP) technique is first used to inhibit the impact of increasing noise with distance, then a value distribution equalization (VDE) method is introduced to reduce the magnitude of signal variations with distance. Combined with empirical threshold values, clouds and aerosols are detected and separated. This method can detect clouds and aerosols with high accuracy, although classification of aerosols and clouds is sensitive to the thresholds selected. Compared with the existing Atmospheric Radiation Measurement (ARM) program lidar-based cloud product, the new method detects more high clouds. The algorithm was applied to a year of observations at both the U.S. Southern Great Plains (SGP) and China Taihu site. At SGP, the cloud frequency shows a clear seasonal variation with maximum values in winter and spring, and shows bi-modal vertical distributions with maximum frequency at around 3-6 km and 8-12 km. The annual averaged cloud frequency is about 50%. By contrast, the cloud frequency at Taihu shows no clear seasonal variation and the maximum frequency is at around 1 km. The annual averaged cloud frequency is about 15% higher than that at SGP.

Comparative study of internet cloud and cloudlet over wireless mesh networks for real-time applications

NASA Astrophysics Data System (ADS)

Khan, Kashif A.; Wang, Qi; Luo, Chunbo; Wang, Xinheng; Grecos, Christos

2014-05-01

Mobile cloud computing is receiving world-wide momentum for ubiquitous on-demand cloud services for mobile users provided by Amazon, Google etc. with low capital cost. However, Internet-centric clouds introduce wide area network (WAN) delays that are often intolerable for real-time applications such as video streaming. One promising approach to addressing this challenge is to deploy decentralized mini-cloud facility known as cloudlets to enable localized cloud services. When supported by local wireless connectivity, a wireless cloudlet is expected to offer low cost and high performance cloud services for the users. In this work, we implement a realistic framework that comprises both a popular Internet cloud (Amazon Cloud) and a real-world cloudlet (based on Ubuntu Enterprise Cloud (UEC)) for mobile cloud users in a wireless mesh network. We focus on real-time video streaming over the HTTP standard and implement a typical application. We further perform a comprehensive comparative analysis and empirical evaluation of the application's performance when it is delivered over the Internet cloud and the cloudlet respectively. The study quantifies the influence of the two different cloud networking architectures on supporting real-time video streaming. We also enable movement of the users in the wireless mesh network and investigate the effect of user's mobility on mobile cloud computing over the cloudlet and Amazon cloud respectively. Our experimental results demonstrate the advantages of the cloudlet paradigm over its Internet cloud counterpart in supporting the quality of service of real-time applications.

Evidence for climate change in the satellite cloud record.

PubMed

Norris, Joel R; Allen, Robert J; Evan, Amato T; Zelinka, Mark D; O'Dell, Christopher W; Klein, Stephen A

2016-08-04

Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Evidence for climate change in the satellite cloud record

NASA Astrophysics Data System (ADS)

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; Zelinka, Mark D.; O'Dell, Christopher W.; Klein, Stephen A.

2016-08-01

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Longitudinal Control for Mengshi Autonomous Vehicle via Cloud Model

NASA Astrophysics Data System (ADS)

Gao, H. B.; Zhang, X. Y.; Li, D. Y.; Liu, Y. C.

2018-03-01

Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control method of autonomous is a key technique which has drawn the attention of industry and academe. In this paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. An experiments is applied to test the implementation of the longitudinal control algorithm. Empirical results show that if the longitudinal control algorithm based Gauss cloud model are applied to calculate the acceleration, and the vehicles drive at different speeds, a stable longitudinal control effect is achieved.

Performance Evaluation of sUAS Equipped with Velodyne HDL-32E LiDAR Sensor

NASA Astrophysics Data System (ADS)

Jozkow, G.; Wieczorek, P.; Karpina, M.; Walicka, A.; Borkowski, A.

2017-08-01

The Velodyne HDL-32E laser scanner is used more frequently as main mapping sensor in small commercial UASs. However, there is still little information about the actual accuracy of point clouds collected with such UASs. This work evaluates empirically the accuracy of the point cloud collected with such UAS. Accuracy assessment was conducted in four aspects: impact of sensors on theoretical point cloud accuracy, trajectory reconstruction quality, and internal and absolute point cloud accuracies. Theoretical point cloud accuracy was evaluated by calculating 3D position error knowing errors of used sensors. The quality of trajectory reconstruction was assessed by comparing position and attitude differences from forward and reverse EKF solution. Internal and absolute accuracies were evaluated by fitting planes to 8 point cloud samples extracted for planar surfaces. In addition, the absolute accuracy was also determined by calculating point 3D distances between LiDAR UAS and reference TLS point clouds. Test data consisted of point clouds collected in two separate flights performed over the same area. Executed experiments showed that in tested UAS, the trajectory reconstruction, especially attitude, has significant impact on point cloud accuracy. Estimated absolute accuracy of point clouds collected during both test flights was better than 10 cm, thus investigated UAS fits mapping-grade category.

A new cloud and aerosol layer detection method based on micropulse lidar measurements

NASA Astrophysics Data System (ADS)

Zhao, Chuanfeng; Wang, Yuzhao; Wang, Qianqian; Li, Zhanqing; Wang, Zhien; Liu, Dong

2014-06-01

This paper introduces a new algorithm to detect aerosols and clouds based on micropulse lidar measurements. A semidiscretization processing technique is first used to inhibit the impact of increasing noise with distance. The value distribution equalization method which reduces the magnitude of signal variations with distance is then introduced. Combined with empirical threshold values, we determine if the signal waves indicate clouds or aerosols. This method can separate clouds and aerosols with high accuracy, although differentiation between aerosols and clouds are subject to more uncertainties depending on the thresholds selected. Compared with the existing Atmospheric Radiation Measurement program lidar-based cloud product, the new method appears more reliable and detects more clouds with high bases. The algorithm is applied to a year of observations at both the U.S. Southern Great Plains (SGP) and China Taihu sites. At the SGP site, the cloud frequency shows a clear seasonal variation with maximum values in winter and spring and shows bimodal vertical distributions with maximum occurrences at around 3-6 km and 8-12 km. The annual averaged cloud frequency is about 50%. The dominant clouds are stratiform in winter and convective in summer. By contrast, the cloud frequency at the Taihu site shows no clear seasonal variation and the maximum occurrence is at around 1 km. The annual averaged cloud frequency is about 15% higher than that at the SGP site. A seasonal analysis of cloud base occurrence frequency suggests that stratiform clouds dominate at the Taihu site.

Empirical Evaluation of Conservative and Optimistic Discrete Event Execution on Cloud and VM Platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoginath, Srikanth B; Perumalla, Kalyan S

2013-01-01

Virtual machine (VM) technologies, especially those offered via Cloud platforms, present new dimensions with respect to performance and cost in executing parallel discrete event simulation (PDES) applications. Due to the introduction of overall cost as a metric, the choice of the highest-end computing configuration is no longer the most economical one. Moreover, runtime dynamics unique to VM platforms introduce new performance characteristics, and the variety of possible VM configurations give rise to a range of choices for hosting a PDES run. Here, an empirical study of these issues is undertaken to guide an understanding of the dynamics, trends and trade-offsmore » in executing PDES on VM/Cloud platforms. Performance results and cost measures are obtained from actual execution of a range of scenarios in two PDES benchmark applications on the Amazon Cloud offerings and on a high-end VM host machine. The data reveals interesting insights into the new VM-PDES dynamics that come into play and also leads to counter-intuitive guidelines with respect to choosing the best and second-best configurations when overall cost of execution is considered. In particular, it is found that choosing the highest-end VM configuration guarantees neither the best runtime nor the least cost. Interestingly, choosing a (suitably scaled) low-end VM configuration provides the least overall cost without adversely affecting the total runtime.« less

An uncertainty principle for star formation - II. A new method for characterising the cloud-scale physics of star formation and feedback across cosmic history

NASA Astrophysics Data System (ADS)

Kruijssen, J. M. Diederik; Schruba, Andreas; Hygate, Alexander P. S.; Hu, Chia-Yu; Haydon, Daniel T.; Longmore, Steven N.

2018-05-01

The cloud-scale physics of star formation and feedback represent the main uncertainty in galaxy formation studies. Progress is hampered by the limited empirical constraints outside the restricted environment of the Local Group. In particular, the poorly-quantified time evolution of the molecular cloud lifecycle, star formation, and feedback obstructs robust predictions on the scales smaller than the disc scale height that are resolved in modern galaxy formation simulations. We present a new statistical method to derive the evolutionary timeline of molecular clouds and star-forming regions. By quantifying the excess or deficit of the gas-to-stellar flux ratio around peaks of gas or star formation tracer emission, we directly measure the relative rarity of these peaks, which allows us to derive their lifetimes. We present a step-by-step, quantitative description of the method and demonstrate its practical application. The method's accuracy is tested in nearly 300 experiments using simulated galaxy maps, showing that it is capable of constraining the molecular cloud lifetime and feedback time-scale to <0.1 dex precision. Access to the evolutionary timeline provides a variety of additional physical quantities, such as the cloud-scale star formation efficiency, the feedback outflow velocity, the mass loading factor, and the feedback energy or momentum coupling efficiencies to the ambient medium. We show that the results are robust for a wide variety of gas and star formation tracers, spatial resolutions, galaxy inclinations, and galaxy sizes. Finally, we demonstrate that our method can be applied out to high redshift (z≲ 4) with a feasible time investment on current large-scale observatories. This is a major shift from previous studies that constrained the physics of star formation and feedback in the immediate vicinity of the Sun.

A Multilateral Negotiation Model for Cloud Service Market

NASA Astrophysics Data System (ADS)

Yoo, Dongjin; Sim, Kwang Mong

Trading cloud services between consumers and providers is a complicated issue of cloud computing. Since a consumer can negotiate with multiple providers to acquire the same service and each provider can receive many requests from multiple consumers, to facilitate the trading of cloud services among multiple consumers and providers, a multilateral negotiation model for cloud market is necessary. The contribution of this work is the proposal of a business model supporting a multilateral price negotiation for trading cloud services. The design of proposed systems for cloud service market includes considering a many-to-many negotiation protocol, and price determining factor from service level feature. Two negotiation strategies are implemented: 1) MDA (Market Driven Agent); and 2) adaptive concession making responding to changes of bargaining position are proposed for cloud service market. Empirical results shows that MDA achieved better performance in some cases that the adaptive concession making strategy, it is noted that unlike the MDA, the adaptive concession making strategy does not assume that an agent has information of the number of competitors (e.g., a consumer agent adopting the adaptive concession making strategy need not know the number of consumer agents competing for the same service).

Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

NASA Technical Reports Server (NTRS)

Shiffman, Smadar

2004-01-01

Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Hao; Ren, Shangping; Garzoglio, Gabriele

Cloud bursting is one of the key research topics in the cloud computing communities. A well designed cloud bursting module enables private clouds to automatically launch virtual machines (VMs) to public clouds when more resources are needed. One of the main challenges in developing a cloud bursting module is to decide when and where to launch a VM so that all resources are most effectively and efficiently utilized and the system performance is optimized. However, based on system operational data obtained from FermiCloud, a private cloud developed by the Fermi National Accelerator Laboratory for scientific workflows, the VM launching overheadmore » is not a constant. It varies with physical resource utilization, such as CPU and I/O device utilizations, at the time when a VM is launched. Hence, to make judicious decisions as to when and where a VM should be launched, a VM launching overhead reference model is needed. In this paper, we first develop a VM launching overhead reference model based on operational data we have obtained on FermiCloud. Second, we apply the developed reference model on FermiCloud and compare calculated VM launching overhead values based on the model with measured overhead values on FermiCloud. Our empirical results on FermiCloud indicate that the developed reference model is accurate. We believe, with the guidance of the developed reference model, efficient resource allocation algorithms can be developed for cloud bursting process to minimize the operational cost and resource waste.« less

Evidence for climate change in the satellite cloud record

DOE PAGES

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; ...

2016-07-11

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space 1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming 2, 3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts 4, 5. Here we show that several independent,more » empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. Here, these results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.« less

Improving Individual Acceptance of Health Clouds through Confidentiality Assurance.

PubMed

Ermakova, Tatiana; Fabian, Benjamin; Zarnekow, Rüdiger

2016-10-26

Cloud computing promises to essentially improve healthcare delivery performance. However, shifting sensitive medical records to third-party cloud providers could create an adoption hurdle because of security and privacy concerns. This study examines the effect of confidentiality assurance in a cloud-computing environment on individuals' willingness to accept the infrastructure for inter-organizational sharing of medical data. We empirically investigate our research question by a survey with over 260 full responses. For the setting with a high confidentiality assurance, we base on a recent multi-cloud architecture which provides very high confidentiality assurance through a secret-sharing mechanism: Health information is cryptographically encoded and distributed in a way that no single and no small group of cloud providers is able to decode it. Our results indicate the importance of confidentiality assurance in individuals' acceptance of health clouds for sensitive medical data. Specifically, this finding holds for a variety of practically relevant circumstances, i.e., in the absence and despite the presence of conventional offline alternatives and along with pseudonymization. On the other hand, we do not find support for the effect of confidentiality assurance in individuals' acceptance of health clouds for non-sensitive medical data. These results could support the process of privacy engineering for health-cloud solutions.

Improving Individual Acceptance of Health Clouds through Confidentiality Assurance

PubMed Central

Fabian, Benjamin; Zarnekow, Rüdiger

2016-01-01

Summary Background Cloud computing promises to essentially improve healthcare delivery performance. However, shifting sensitive medical records to third-party cloud providers could create an adoption hurdle because of security and privacy concerns. Objectives This study examines the effect of confidentiality assurance in a cloud-computing environment on individuals’ willingness to accept the infrastructure for inter-organizational sharing of medical data. Methods We empirically investigate our research question by a survey with over 260 full responses. For the setting with a high confidentiality assurance, we base on a recent multi-cloud architecture which provides very high confidentiality assurance through a secret-sharing mechanism: Health information is cryptographically encoded and distributed in a way that no single and no small group of cloud providers is able to decode it. Results Our results indicate the importance of confidentiality assurance in individuals’ acceptance of health clouds for sensitive medical data. Specifically, this finding holds for a variety of practically relevant circumstances, i.e., in the absence and despite the presence of conventional offline alternatives and along with pseudonymization. On the other hand, we do not find support for the effect of confidentiality assurance in individuals’ acceptance of health clouds for non-sensitive medical data. These results could support the process of privacy engineering for health-cloud solutions. PMID:27781238

Evidence for climate change in the satellite cloud record

DOE Office of Scientific and Technical Information (OSTI.GOV)

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space 1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming 2, 3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts 4, 5. Here we show that several independent,more » empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. Here, these results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.« less

Surface Downward Longwave Radiation Retrieval Algorithm for GEO-KOMPSAT-2A/AMI

NASA Astrophysics Data System (ADS)

Ahn, Seo-Hee; Lee, Kyu-Tae; Rim, Se-Hun; Zo, Il-Sung; Kim, Bu-Yo

2018-05-01

This study contributes to the development of an algorithm to retrieve the Earth's surface downward longwave radiation (DLR) for 2nd Geostationary Earth Orbit KOrea Multi-Purpose SATellite (GEO-KOMPSAT-2A; GK-2A)/Advanced Meteorological Imager (AMI). Regarding simulation data for algorithm development, we referred to Clouds and the Earth's Radiant Energy System (CERES), and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-interim reanalysis data. The clear sky DLR calculations were in good agreement with the Gangneung-Wonju National University (GWNU) Line-By-Line (LBL) model. Compared with CERES data, the Root Mean Square Error (RMSE) was 10.14Wm-2. In the case of cloudy sky DLR, we estimated the cloud base temperature empirically by utilizing cloud liquid water content (LWC) according to the cloud type. As a result, the correlation coefficients with CERES all sky DLRs were greater than 0.99. However, the RMSE between calculated DLR and CERES data was about 16.67Wm-2, due to ice clouds and problems of mismatched spatial and temporal resolutions for input data. This error may be reduced when GK-2A is launched and its products can be used as input data. Accordingly, further study is needed to improve the accuracy of DLR calculation by using high-resolution input data. In addition, when compared with BSRN surface-based observational data and retrieved DLR for all sky, the correlation coefficient was 0.86 and the RMSE was 31.55 Wm-2, which indicates relatively high accuracy. It is expected that increasing the number of experimental Cases will reduce the error.

Support for the Harvard University Water Vapor and Total Water Instruments for the 2004 NASA WB57 Middle Latitude Cirrus Experiment

NASA Technical Reports Server (NTRS)

Anderson, James G.

2005-01-01

In order to improve our understanding of the role clouds play in the climate system, NASA is investing considerable effort in characterizing clouds with instruments ranging from passive remote sensors on board the EOS platforms, to the forthcoming active remote sensors on Cloudsat and Calipso. These missions, when taken together, have the capacity to advance our understanding of the coupling between various components of the hydrologic cycle and the atmospheric circulation, and hold the additional potential of leading to significant improvements in the characterization of cloud feedbacks in global models. This is especially true considering that several of these platforms will be flown in an identical orbit within several minutes of one another-a constellation of satellites known as the A-Train. The algorithms that are being implemented and developed to convert these new data streams from radiance and reflectivity measurements into geophysical parameters invariably rely on some set of simplifymg assumptions and empirical constants. Uncertainties in these relationships lead to poorly understood random and systematic errors in the retrieved properties. This lack of understanding introduces ambiguity in interpreting the data and in using the global data sets for their intended purposes. In light of this, a series of flights with the W57F was proposed to address certain specific issues related to the basic properties of mid latitude cirrus clouds: the NASA WE357 Middle Latitude Cirrus Experiment ("MidCiX"). The science questions addressed are: 1) Can cloud property retrieval algorithms developed for A-Train active and passive remote sensing measurements accurately characterize the microphysical properties of synoptic and convectively generated cirrus cloud systems? 2) What are the relationships between the cirrus particle mass, projected area, and particle size spectrum in various genre of cirrus clouds? 3) Does the present compliment of state of the art in situ cloud probes provide the level of precision and accuracy needed to develop and validate algorithms and to contribute to our understanding of the characteristics and microphysical processes operating in cirrus clouds?

Empirical relationships between gas abundances and UV selective extinction

NASA Technical Reports Server (NTRS)

Joseph, Charles L.

1990-01-01

Several studies of gas-phase abundances in lines of sight through the outer edges of dense clouds are summarized. These lines of sight have 0.4 less than E(B-V) less than 1.1 and have inferred spatial densities of a few hundred cm(-3). The primary thrust of these studies has been to compare gaseous abundances in interstellar clouds that have various types of peculiar selective extinction. To date, the most notable result has been an empirical relationship between the CN/Fe I abundance ratio and the depth of the 2200 A extinction bump. It is not clear at the present time, however, whether these two parameters are linearly correlated or the data are organized into two discrete ensembles. Based on 19 samples and assuming the clouds form discrete ensembles, lines of sight that have a CN/Fe I abundance ratio greater than 0.3 (dex) appear to have a shallow 2.57 plus or minus 0.55 bump compared to 3.60 plus or minus 0.36 for other dense clouds and compared to the 3.6 Seaton (1979) average. The difference in the strength of the extinction bump between these two ensembles is 1.03 plus or minus 0.23. Although a high-resolution IUE survey of dense clouds is far from complete, the few lines of sight with shallow extinction bumps all show preferential depletion of certain elements, while those lines of sight with normal 2200 A bumps do not. Ca II, Cr II, and Mn II appear to exhibit the strongest preferential depletion compared to S II, P II, and Mg II. Fe II and Si II depletions also appear to be enhanced somewhat in the shallow-bump lines of sight. It should be noted that Copernicus data suggest all elements, including the so-called nondepletors, deplete in diffuse clouds (Snow and Jenkins 1980, Joseph 1988). Those lines of sight through dense clouds that have normal 2200 A extinction bumps appear to be extensions of the depletions found in the diffuse interstellar medium. That is, the overall level of depletion is enhanced, but the element-to-element abundances are similar to those in diffuse clouds. In a separate study, the abundances of neutral atoms were studied in a dense cloud having a shallow 2200 A bump and in one with a normal strength bump.

Small-Scale Drop-Size Variability: Empirical Models for Drop-Size-Dependent Clustering in Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Knyazikhin, Yuri; Larsen, Michael L.; Wiscombe, Warren J.

2005-01-01

By analyzing aircraft measurements of individual drop sizes in clouds, it has been shown in a companion paper that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)), where 0 less than or equals D(r) less than or equals 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and a Poisson distribution of cloud drops, these models illustrate strong drop clustering, especially with larger drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics, including how fast rain can form. For radiative transfer theory, clustering of large drops enhances their impact on the cloud optical path. The clustering phenomenon also helps explain why remotely sensed cloud drop size is generally larger than that measured in situ.

The 27-28 October 1986 FIRE IFO cirrus case study: Cirrus parameter relationships derived from satellite and lidar data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Young, David F.; Sassen, Kenneth; Alvarez, Joseph M.; Grund, Christian J.

1989-01-01

Cirrus cloud radiative and physical characteristics are determined using a combination of ground-based, aircraft, and satellite measurements taken as part of the First ISCCP Regional Experiment (FIRE) Cirrus Intensive Field Observations (IFO) during October and November 1986. Lidar backscatter data are used to define cloud base, center, and top heights and the corresponding temperatures. Coincident GOES 4 km visible (0.65 microns) and 8 km infrared window (11.5 microns) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance mode. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8 km for the 71 scenes. An average visible scattering efficiency of 2.1 was found for this data set. The results reveal a significant dependence of scattering efficiency on cloud temperature.

Cloud cover and horizontal plane eye damaging solar UV exposures.

PubMed

Parisi, A V; Downs, N

2004-11-01

The spectral UV and the cloud cover were measured at intervals of 5 min with an integrated cloud and spectral UV measurement system at a sub-tropical Southern Hemisphere site for a 6-month period and solar zenith angle (SZA) range of 4.7 degrees to approximately 80 degrees . The solar UV spectra were recorded between 280 nm and 400 nm in 0.5 nm increments and weighted with the action spectra for photokeratitis and cataracts in order to investigate the effect of cloud cover on the horizontal plane biologically damaging UV irradiances for cataracts (UVBE(cat)) and photokeratitis (UVBE(pker)). Eighty five percent of the recorded spectra produced a measured irradiance to a cloud free irradiance ratio of 0.6 and higher while 76% produced a ratio of 0.8 and higher. Empirical non-linear expressions as a function of SZA have been developed for all sky conditions to allow the evaluation of the biologically damaging UV irradiances for photokeratitis and cataracts from a knowledge of the unweighted UV irradiances.

Star formation in massive Milky Way molecular clouds: Building a bridge to distant galaxies

NASA Astrophysics Data System (ADS)

Willis, Sarah Elizabeth

The Kennicutt-Schmidt relation is an empirical power-law linking the surface density of the star formation rate (SigmaSFR) to the surface density of gas (Sigmagas ) averaged over the observed face of a starforming galaxy Kennicutt (1998). The original presentation used observations of CO to measure gas density and H alpha emission to measure the population of hot, massive young stars (and infer the star formation rate). Observations of Sigma SFR from a census of young stellar objects in nearby molecular clouds in our Galaxy are up to 17 times higher than the extragalactic relation would predict given their Sigmagas. These clouds primarily form low-mass stars that are essentially invisible to star formation rate tracers. A sample of six giant molecular cloud (GMC) complexes with signposts of massive star formation was identified in our galaxy. The regions selected have a range of total luminosity and morphology. Deep ground-based observations in the near-infrared with NEWFIRM and IRAC observations with the Spitzer Space Telescope were used to conduct a census of the young stellar content associated with each of these clouds. The star formation rates from the stellar census in each of these regions was compared with the star formation rates measured by extragalactic star formation rate tracers based on monochromatic mid-infrared luminosities. Far-infrared Herschel observations from 160 through 500 mum were used to determine the column density and temperature in each region. The region NGC 6334 served as a test case to compare the Herschel column density measurements with the measurements for near-infrared extinction. The combination of the column density maps and the stellar census lets us examine SigmaSFR vs. Sigma gas for the massive GMCs. These regions are consistent with the results for the low-mass molecular clouds, indicating Sigma SFR levels that are higher than predicted based on Sigma gas. The overall Sigmagas levels are higher for the massive star forming regions, indicating that they have a higher fraction of dense gas than the clouds that are forming primarily low mass stars. There is still significant spread at a given average gas density, indicating that the star formation history and dense gas fraction play important roles in determining an individual molecular cloud's place in a Sigma SFR vs. Sigmagas diagram. Zooming in, SigmaSFR vs. Sigma gas was examined within the individual clouds, revealing a decrease relative to the spread that is observed for the average over whole clouds. The dependence of SigmaSFR on Sigma gas increases significantly above AV ˜ 5 - 10 which is consistent with previous measurements of a threshold for star formation around AV = 8 or Sigma gas = 0.04 g cm-2. NGC 6334 was found to be consistent with a threshold for massive star formation at Sigmagas = 1 g cm-2.

Estimating Longwave Atmospheric Emissivity in the Canadian Rocky Mountains

NASA Astrophysics Data System (ADS)

Ebrahimi, S.; Marshall, S. J.

2014-12-01

Incoming longwave radiation is an important source of energy contributing to snow and glacier melt. However, estimating the incoming longwave radiation from the atmosphere is challenging due to the highly varying conditions of the atmosphere, especially cloudiness. We analyze the performance of some existing models included a physically-based clear-sky model by Brutsaert (1987) and two different empirical models for all-sky conditions (Lhomme and others, 2007; Herrero and Polo, 2012) at Haig Glacier in the Canadian Rocky Mountains. Models are based on relations between readily observed near-surface meteorological data, including temperature, vapor pressure, relative humidity, and estimates of shortwave radiation transmissivity (i.e., clear-sky or cloud-cover indices). This class of models generally requires solar radiation data in order to obtain a proxy for cloud conditions. This is not always available for distributed models of glacier melt, and can have high spatial variations in regions of complex topography, which likely do not reflect the more homogeneous atmospheric longwave emissions. We therefore test longwave radiation parameterizations as a function of near-surface humidity and temperature variables, based on automatic weather station data (half-hourly and mean daily values) from 2004 to 2012. Results from comparative analysis of different incoming longwave radiation parameterizations showed that the locally-calibrated model based on relative humidity and vapour pressure performs better than other published models. Performance is degraded but still better than standard cloud-index based models when we transfer the model to another site, roughly 900 km away, Kwadacha Glacier in the northern Canadian Rockies.

New Concepts for Refinement of Cumulus Parameterization in GCM's the Arakawa-Schubert Framework

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.; Lau, William (Technical Monitor)

2002-01-01

Several state-of-the-art models including the one employed in this study use the Arakawa-Schubert framework for moist convection, and Sundqvist formulation of stratiform. clouds, for moist physics, in-cloud condensation, and precipitation. Despite a variety of cloud parameterization methodologies developed by several modelers including the authors, most of the parameterized cloud-models have similar deficiencies. These consist of: (a) not enough shallow clouds, (b) too many deep clouds; (c) several layers of clouds in a vertically demoralized model as opposed to only a few levels of observed clouds, and (d) higher than normal incidence of double ITCZ (Inter-tropical Convergence Zone). Even after several upgrades consisting of a sophisticated cloud-microphysics and sub-grid scale orographic precipitation into the Data Assimilation Office (DAO)'s atmospheric model (called GEOS-2 GCM) at two different resolutions, we found that the above deficiencies remained persistent. The two empirical solutions often used to counter the aforestated deficiencies consist of a) diffusion of moisture and heat within the lower troposphere to artificially force the shallow clouds; and b) arbitrarily invoke evaporation of in-cloud water for low-level clouds. Even though helpful, these implementations lack a strong physical rationale. Our research shows that two missing physical conditions can ameliorate the aforestated cloud-parameterization deficiencies. First, requiring an ascending cloud airmass to be saturated at its starting point will not only make the cloud instantly buoyant all through its ascent, but also provide the essential work function (buoyancy energy) that would promote more shallow clouds. Second, we argue that training clouds that are unstable to a finite vertical displacement, even if neutrally buoyant in their ambient environment, must continue to rise and entrain causing evaporation of in-cloud water. These concepts have not been invoked in any of the cloud parameterization schemes so far. We introduced them into the DAO-GEOS-2 GCM with McRAS (Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme).

Lightning and Other Influences On Tropical Tropospheric Ozone: Empirical Studies of Covariation

NASA Technical Reports Server (NTRS)

Chatfield, Robert B.; Guan, Hong; Hudson, Robert D.; Witte, Jacquelyne C.

2003-01-01

Tropical and subtropical tropospheric ozone are important radiatively active species, with particularly large effects in the upper third of the troposphere. Temporal variability of O3 has proved difficult to simulate day by day in process models. Thus, individual roles of lightning, biomass burning, and other pollution in providing precursor NO(x), radicals, and chain carriers (CO, hydrocarbons) remain unquantified by simulation, and it is theoretically reasonable that individual roles are magnified by a joint synergy. We use wavelet analysis and Burg-algorithm maximum entropy spectral analyses to describe time-scales and correlation of ozone with proxies for processes controlling its concentration. Our empirical studies link time variations apparent in several datasets: the SHADOZ (Southern Hemisphere Additional Ozonesondes) network stations (Nairobi, Fiji), and auxiliary series with power to explain ozone-determining processes, with some interpretation based on the TTO (Tropical Tropospheric Ozone) product derived from TOMS (the Total Ozone Mapping Spectrometer). The auxiliary series are The OTD/LIS(Optical Transient Detector/Lightning Imaging Sensor) measurements of the lightning NO(x) source, the OLR (Outgoing Longwave Radiation)measurement of high-topped clouds, and standard meteorological variables from the United States NCEP (National Centers for Environmental Prediction) and Data Assimilation Office analyses. Concentrating on equatorial ozone, we compare the statistical evidence on the variability of tropospheric ozone. Important variations occur on approximately two-week, two-month (Madden-Julian Oscillation) and annual scales, and relations with OLR suggest controls associated with continental clouds. Hence we are now using the Lightning Imaging Sensor data set to indicate NO(x) sources. We report initial results defining relative roles of the process mentioned affecting O3 using their covariance properties.

Constructing a Merged Cloud-Precipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Zhe; McFarlane, Sally A.; Schumacher, Courtney

2014-05-16

To improve understanding of the convective processes key to the Madden-Julian-Oscillation (MJO) initiation, the Dynamics of the MJO (DYNAMO) and Atmospheric Radiation Measurement MJO Investigation Experiment (AMIE) collected four months of observations from three radars, the S-band Polarization Radar (S-Pol), the C-band Shared Mobile Atmospheric Research & Teaching Radar (SMART-R), and Ka-band Zenith Radar (KAZR) on Addu Atoll in the tropical Indian Ocean. This study compares the measurements from the S-Pol and SMART-R to those from the more sensitive KAZR in order to characterize the hydrometeor detection capabilities of the two scanning precipitation radars. Frequency comparisons for precipitating convective cloudsmore » and non-precipitating high clouds agree much better than non-precipitating low clouds for both scanning radars due to issues in ground clutter. On average, SMART-R underestimates convective and high cloud tops by 0.3 to 1.1 km, while S-Pol underestimates cloud tops by less than 0.4 km for these cloud types. S-Pol shows excellent dynamic range in detecting various types of clouds and therefore its data are well suited for characterizing the evolution of the 3D cloud structures, complementing the profiling KAZR measurements. For detecting non-precipitating low clouds and thin cirrus clouds, KAZR remains the most reliable instrument. However, KAZR is attenuated in heavy precipitation and underestimates cloud top height due to rainfall attenuation 4.3% of the time during DYNAMO/AMIE. An empirical method to correct the KAZR cloud top heights is described, and a merged radar dataset is produced to provide improved cloud boundary estimates, microphysics and radiative heating retrievals.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bae, Soo Ya; Jeong, Jaein I.; Park, R.

We examine the effect of anthropogenic aerosols on the weekly variability of precipitation in Korea in summer 2004 by using Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models. We con-duct two WRF simulations including a baseline simulation with empirically based cloud condensation nuclei (CCN) number concentrations and a sensitivity simulation with our implementation to account for the effect of aerosols on CCN number concentrations. The first simulation underestimates observed precipitation amounts, particularly in northeastern coastal areas of Korea, whereas the latter shows higher precipitation amounts that are in better agree-ment with the observations. In addition, themore » sensitivity model with the aerosol effects reproduces the observed weekly variability, particularly for precipitation frequency with a high R at 0.85, showing 20% increase of precipita-tion events during the weekend than those during weekdays. We find that the aerosol effect results in higher CCN number concentrations during the weekdays and a three-fold increase of the cloud water mixing ratio through en-hanced condensation. As a result, the amount of warm rain is generally suppressed because of the low auto-conversion process from cloud water to rain water under high aerosol conditions. The inefficient conversion, how-ever, leads to higher vertical development of clouds in the mid-atmosphere with stronger updrafts in the sensitivity model, which increases by 21% cold-phase hydrometeors including ice, snow, and graupel relative to the baseline model and ultimately results in higher precipitation amounts in summer.« less

Validating an operational physical method to compute surface radiation from geostationary satellites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Manajit; Dhere, Neelkanth G.; Wohlgemuth, John H.

We developed models to compute global horizontal irradiance (GHI) and direct normal irradiance (DNI) over the last three decades. These models can be classified as empirical or physical based on the approach. Empirical models relate ground-based observations with satellite measurements and use these relations to compute surface radiation. Physical models consider the physics behind the radiation received at the satellite and create retrievals to estimate surface radiation. Furthermore, while empirical methods have been traditionally used for computing surface radiation for the solar energy industry, the advent of faster computing has made operational physical models viable. The Global Solar Insolation Projectmore » (GSIP) is a physical model that computes DNI and GHI using the visible and infrared channel measurements from a weather satellite. GSIP uses a two-stage scheme that first retrieves cloud properties and uses those properties in a radiative transfer model to calculate GHI and DNI. Developed for polar orbiting satellites, GSIP has been adapted to NOAA's Geostationary Operation Environmental Satellite series and can run operationally at high spatial resolutions. Our method holds the possibility of creating high quality datasets of GHI and DNI for use by the solar energy industry. We present an outline of the methodology and results from running the model as well as a validation study using ground-based instruments.« less

Development of GK-2A cloud optical and microphysical properties retrieval algorithm

NASA Astrophysics Data System (ADS)

Yang, Y.; Yum, S. S.; Um, J.

2017-12-01

Cloud and aerosol radiative forcing is known to be one of the the largest uncertainties in climate change prediction. To reduce this uncertainty, remote sensing observation of cloud radiative and microphysical properties have been used since 1970s and the corresponding remote sensing techniques and instruments have been developed. As a part of such effort, Geo-KOMPSAT-2A (Geostationary Korea Multi-Purpose Satellite-2A, GK-2A) will be launched in 2018. On the GK-2A, the Advanced Meteorological Imager (AMI) is primary instrument which have 3 visible, 3 near-infrared, and 10 infrared channels. To retrieve optical and microphysical properties of clouds using AMI measurements, the preliminary version of new cloud retrieval algorithm for GK-2A was developed and several validation tests were conducted. This algorithm retrieves cloud optical thickness (COT), cloud effective radius (CER), liquid water path (LWP), and ice water path (IWP), so we named this algorithm as Daytime Cloud Optical thickness, Effective radius and liquid and ice Water path (DCOEW). The DCOEW uses cloud reflectance at visible and near-infrared channels as input data. An optimal estimation (OE) approach that requires appropriate a-priori values and measurement error information is used to retrieve COT and CER. LWP and IWP are calculated using empirical relationships between COT/CER and cloud water path that were determined previously. To validate retrieved cloud properties, we compared DCOEW output data with other operational satellite data. For COT and CER validation, we used two different data sets. To compare algorithms that use cloud reflectance at visible and near-IR channels as input data, MODIS MYD06 cloud product was selected. For the validation with cloud products that are based on microwave measurements, COT(2B-TAU)/CER(2C-ICE) data retrieved from CloudSat cloud profiling radar (W-band, 94 GHz) was used. For cloud water path validation, AMSR-2 Level-3 Cloud liquid water data was used. Detailed results will be shown at the conference.

Analytical Modeling of Pressure Wall Hole Size and Maximum Tip-to-Tip Crack Length for Perforating Normal and Oblique Orbital Debris Impacts

NASA Technical Reports Server (NTRS)

Schonberg, William P.; Mohamed, Essam

1997-01-01

This report presents the results of a study whose objective was to develop first-principles-based models of hole size and maximum tip-to-tip crack length for a spacecraft module pressure wall that has been perforated in an orbital debris particle impact. The hole size and crack length models are developed by sequentially characterizing the phenomena comprising the orbital debris impact event, including the initial impact, the creation and motion of a debris cloud within the dual-wall system, the impact of the debris cloud on the pressure wall, the deformation of the pressure wall due to debris cloud impact loading prior to crack formation, pressure wall crack initiation, propagation, and arrest, and finally pressure wall deformation following crack initiation and growth. The model development has been accomplished through the application of elementary shock physics and thermodynamic theory, as well as the principles of mass, momentum, and energy conservation. The predictions of the model developed herein are compared against the predictions of empirically-based equations for hole diameters and maximum tip-to-tip crack length for three International Space Station wall configurations. The ISS wall systems considered are the baseline U.S. Lab Cylinder, the enhanced U.S. Lab Cylinder, and the U.S. Lab Endcone. The empirical predictor equations were derived from experimentally obtained hole diameters and crack length data. The original model predictions did not compare favorably with the experimental data, especially for cases in which pressure wall petalling did not occur. Several modifications were made to the original model to bring its predictions closer in line with the experimental results. Following the adjustment of several empirical constants, the predictions of the modified analytical model were in much closer agreement with the experimental results.

Empirical evaluation of global vitamin D effective ultraviolet irradiances under cloudy conditions for a subtropical southern hemisphere site.

PubMed

Turnbull, David J; Parisi, Alfio V; Schouten, Peter W

2010-05-01

This paper evaluates the global vitamin D effective UV (UV(vitd)) irradiances under cloudy conditions at a subtropical, southern hemisphere site. The UV(vitd) irradiances were analyzed on a horizontal plane and sampled at 5-min intervals over 18 months so that a wide range of parameters including cloud conditions, solar zenith angles (SZA) and ozone levels were taken into account. Cloud modification factors were determined from the influence of clouds on the global broadband solar radiation, and these were applied to the cloud-free vitamin D effective UV irradiance to evaluate the UV(vitd) irradiances on a horizontal plane for cloudy conditions. For vitamin D effective UV irradiance, cloud modification factors were found to range from 0.9 to 1.0 for no cloud and 0.4 to 0.5 for 8 octa of cloud cover. SZA played a minimal role in this variation. A comparison of the measured and calculated UV(vitd) irradiances for the 2004 data set in the range of SZA of 70 degrees or less provided an R(2) value of 0.90. The output of the model was compared to data measured during the first 6 months of 2005 for an SZA of 70 degrees or less and provided an R(2) value of approximately 0.82.

a 33GHZ and 95GHZ Cloud Profiling Radar System (cprs): Preliminary Estimates of Particle Size in Precipitation and Clouds.

NASA Astrophysics Data System (ADS)

Sekelsky, Stephen Michael

1995-11-01

The Microwave Remote Sensing Laboratory (MIRSL) st the University of Massachusetts has developed a unique single antenna, dual-frequency polarimetric Cloud Profiling Radar System (CPRS). This project was funded by the Department of Energy's Atmospheric Radiation Measurement (ARM) program, and was intended to help fill the void of ground-based remote sensors capable of characterizing cloud microphysical properties. CPRS is unique in that it can simultaneously measure the complex power backscattered from clouds at 33 GHz and 95 GHz through the same aperture. Both the 33 GHz and 95 GHz channels can transmit pulse-to-pulse selectable vertical or horizontal polarization, and simultaneously record both the copolarized and crosspolarized backscatter. CPRS Doppler, polarimetric and dual-wavelength reflectivity measurements combined with in situ cloud measurements should lead to the development of empirical models that can more accurately classify cloud-particle phase and habit, and make better quantitative estimates of particle size distribution parameters. This dissertation describes the CPRS hardware, and presents colocated 33 GHz and 95 GHz measurements that illustrate the use of dual-frequency measurements to estimate particle size when Mie scattering, is observed in backscatter from rain and ice-phase clouds. Polarimetric measurements are presented as a means of discriminating cloud phase (ice-water) and estimating crystal shape in cirrus clouds. Polarimetric and dual-wavelength observations of insects are also presented with a brief discussion of their impact on the interpretation of precipitation and liquid cloud measurements. In precipitation, Diermendjian's equations for Mie backscatter (1) and the Marshal-Palmer drop-size distribution are used to develop models relating differences in the reflectivity and mean velocity at 33 GHz and 95 GHz to the microphysical parameters of rain. These models are then used to estimate mean droplet size from CPRS measurements of drizzle, which were collected in July, 1993 during the system's first field test in Lincoln, NE. The dissertation also presents cirrus cloud and other measurements collected during the DOE-sponsored Remote Cloud Sensing Intensive Operations Period (RCS-IOP) experiment in April, 1994. Zenith-pointing cirrus measurements show small differences in 33 GHz and 95 GHz reflectivity, as models have predicted (2). Depolarization was also detected in a few cases when ice crystals precipitated from the base of a cloud. On May 29, 1994 CPRS observed a convective storm that produced a cirrus anvil cloud and hail. These storms are one 'engine' producing cirrus clouds and are currently a topic of intensive research by climatologists. Both zenith-pointing and range-height data formats are presented. Measurements of depolarization above the melting/layer are compared to in situ observations of particle size and shape. The RCS-IOP experiment also provided a first opportunity to verify our calibration with aircraft in situ measurements, and to compare our cloud measurements to those collected by other remote sensors. (Abstract shortened by UMI.).

Secure Skyline Queries on Cloud Platform.

PubMed

Liu, Jinfei; Yang, Juncheng; Xiong, Li; Pei, Jian

2017-04-01

Outsourcing data and computation to cloud server provides a cost-effective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data (e.g., medical records) need to be protected from the cloud server and other unauthorized users. One approach is to outsource encrypted data to the cloud server and have the cloud server perform query processing on the encrypted data only. It remains a challenging task to support various queries over encrypted data in a secure and efficient way such that the cloud server does not gain any knowledge about the data, query, and query result. In this paper, we study the problem of secure skyline queries over encrypted data. The skyline query is particularly important for multi-criteria decision making but also presents significant challenges due to its complex computations. We propose a fully secure skyline query protocol on data encrypted using semantically-secure encryption. As a key subroutine, we present a new secure dominance protocol, which can be also used as a building block for other queries. Finally, we provide both serial and parallelized implementations and empirically study the protocols in terms of efficiency and scalability under different parameter settings, verifying the feasibility of our proposed solutions.

Cloud rise model for radiological dispersal devices events

NASA Astrophysics Data System (ADS)

Sharon, Avi; Halevy, Itzhak; Sattinger, Daniel; Yaar, Ilan

2012-07-01

As a part of the preparedness and response to possible radiological terror events, it is important to model the evolution of the radioactive cloud immediately after its formation, as a function of time, explosive quantity and local meteorological conditions. One of the major outputs of a cloud rise models is the evaluation of cloud top height, which is an essential input for most of the succeeding atmospheric dispersion models. This parameter strongly affects the radiological consequences of the event. Most of the cloud rise models used today, have been developed according to experiments were large quantities of explosives were used, within the range of hundreds of kilograms of TNT. The majority of these models, however, fail to address Radiological Dispersion Devices (RDD) events, which are typically characterized by smaller amounts of TNT. In this paper, a new, semi-empirical model that describes the vertical evolution of the cloud up to its effective height as a function of time, explosive quantity, atmospheric stability and horizontal wind speed, is presented. The database for this model is taken from five sets of experiments done in Israel during 2006-2009 under the "Green Field" (GF) project, using 0.25-100 kg of TNT.

Cloud Feedbacks in the Climate System: A Critical Review.

NASA Astrophysics Data System (ADS)

Stephens, Graeme L.

2005-01-01

This paper offers a critical review of the topic of cloud-climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet's hydrological cycle to climate radiative forcings.The paper provides a brief overview of the effects of clouds on the radiation budget of the earth-atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative-convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global-time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis.It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model's credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress.Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future.

3D micro-mapping: Towards assessing the quality of crowdsourcing to support 3D point cloud analysis

NASA Astrophysics Data System (ADS)

Herfort, Benjamin; Höfle, Bernhard; Klonner, Carolin

2018-03-01

In this paper, we propose a method to crowdsource the task of complex three-dimensional information extraction from 3D point clouds. We design web-based 3D micro tasks tailored to assess segmented LiDAR point clouds of urban trees and investigate the quality of the approach in an empirical user study. Our results for three different experiments with increasing complexity indicate that a single crowdsourcing task can be solved in a very short time of less than five seconds on average. Furthermore, the results of our empirical case study reveal that the accuracy, sensitivity and precision of 3D crowdsourcing are high for most information extraction problems. For our first experiment (binary classification with single answer) we obtain an accuracy of 91%, a sensitivity of 95% and a precision of 92%. For the more complex tasks of the second Experiment 2 (multiple answer classification) the accuracy ranges from 65% to 99% depending on the label class. Regarding the third experiment - the determination of the crown base height of individual trees - our study highlights that crowdsourcing can be a tool to obtain values with even higher accuracy in comparison to an automated computer-based approach. Finally, we found out that the accuracy of the crowdsourced results for all experiments is hardly influenced by characteristics of the input point cloud data and of the users. Importantly, the results' accuracy can be estimated using agreement among volunteers as an intrinsic indicator, which makes a broad application of 3D micro-mapping very promising.

Top-of-the-Atmosphere Shortwave Flux Estimation from UV Observations: An Empirical Approach

NASA Technical Reports Server (NTRS)

Gupta, P.; Joiner, Joanna; Vasilkov, A.; Bhartia, P. K.; da Silva, Arlindo

2012-01-01

Measurements of top of the atmosphere (TOA) radiation are essential to the understanding of Earth's climate. Clouds, aerosols, and ozone (0,) are among the most important agents impacting the Earth's short-wave (SW) radiation budget. There are several sensors in orbit that provide independent information related to the Earth's SW radiation budget. Having coincident information from these sensors is important for understanding their potential contributions. The A-train constellation of satellites provides a unique opportunity to analyze near-simultaneous data from several of these sensors. They include the Ozone Monitoring Instrument (OMI), on the NASA Aura satellite, that makes TOA hyper-spectral measurements from ultraviolet (UV) to visible wavelengths, and Clouds and the Earth's Radiant Energy System (CERES) instrument, on the NASA Aqua satellite, that makes broadband measurements in both the long- and short-wave. OMI measurements have been successfully utilized to derive the information on trace gases (e.g., 0 1, NO" and SO,), clouds, and absorbing aerosols. TOA SW fluxes are estimated using a combination of data from CERES and the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS). In this paper, OMI retrievals of cloud/aerosol parameters and 0 1 have been collocated with CERES TOA SW flux retrievals. We use this collocated data to develop a neural network that estimates TOA shortwave flux globally over ocean using data from OMI and meteorological analyses. This input data include the effective cloud fraction, cloud optical centroid pressure (OCP), total-column 0" and sun-satellite viewing geometry from OMI as well as wind speed and water vapor from the Goddard Earth Observing System 5 Modern Era Retrospective-analysis for Research and Applications (GEOS-5 MERRA) along with a climatology of chlorophyll content. We train the neural network using a subset of CERES retrievals of TOA SW flux as the target output (truth) and withhold a different subset of the CERES data to be used for validation.

Rain estimation from satellites: An examination of the Griffith-Woodley technique

NASA Technical Reports Server (NTRS)

Negri, A. J.; Adler, R. F.; Wetzel, P. J.

1983-01-01

The Griffith-Woodley Technique (GWT) is an approach to estimating precipitation using infrared observations of clouds from geosynchronous satellites. It is examined in three ways: an analysis of the terms in the GWT equations; a case study of infrared imagery portraying convective development over Florida; and the comparison of a simplified equation set and resultant rain map to results using the GWT. The objective is to determine the dominant factors in the calculation of GWT rain estimates. Analysis of a single day's convection over Florida produced a number of significant insights into various terms in the GWT rainfall equations. Due to the definition of clouds by a threshold isotherm the majority of clouds on this day did not go through an idealized life cycle before losing their identity through merger, splitting, etc. As a result, 85% of the clouds had a defined life of 0.5 or 1 h. For these clouds the terms in the GWT which are dependent on cloud life history become essentially constant. The empirically derived ratio of radar echo area to cloud area is given a singular value (0.02) for 43% of the sample, while the rainrate term is 20.7 mmh-1 for 61% of the sample. For 55% of the sampled clouds the temperature weighting term is identically 1.0. Cloud area itself is highly correlated (r=0.88) with GWT computed rain volume. An important, discriminating parameter in the GWT is the temperature defining the coldest 10% cloud area. The analysis further shows that the two dominant parameters in rainfall estimation are the existence of cold cloud and the duration of cloud over a point.

Cryptonite: A Secure and Performant Data Repository on Public Clouds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumbhare, Alok; Simmhan, Yogesh; Prasanna, Viktor

2012-06-29

Cloud storage has become immensely popular for maintaining synchronized copies of files and for sharing documents with collaborators. However, there is heightened concern about the security and privacy of Cloud-hosted data due to the shared infrastructure model and an implicit trust in the service providers. Emerging needs of secure data storage and sharing for domains like Smart Power Grids, which deal with sensitive consumer data, require the persistence and availability of Cloud storage but with client-controlled security and encryption, low key management overhead, and minimal performance costs. Cryptonite is a secure Cloud storage repository that addresses these requirements using amore » StrongBox model for shared key management.We describe the Cryptonite service and desktop client, discuss performance optimizations, and provide an empirical analysis of the improvements. Our experiments shows that Cryptonite clients achieve a 40% improvement in file upload bandwidth over plaintext storage using the Azure Storage Client API despite the added security benefits, while our file download performance is 5 times faster than the baseline for files greater than 100MB.« less

Quantifying the uncertainties of aerosol indirect effects and impacts on decadal-scale climate variability in NCAR CAM5 and CESM1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Sungsu

2014-12-12

The main goal of this project is to systematically quantify the major uncertainties of aerosol indirect effects due to the treatment of moist turbulent processes that drive aerosol activation, cloud macrophysics and microphysics in response to anthropogenic aerosol perturbations using the CAM5/CESM1. To achieve this goal, the P.I. hired a postdoctoral research scientist (Dr. Anna Fitch) who started her work from the Nov.1st.2012. In order to achieve the project goal, the first task that the Postdoc. and the P.I. did was to quantify the role of subgrid vertical velocity variance on the activation and nucleation of cloud liquid droplets andmore » ice crystals and its impact on the aerosol indirect effect in CAM5. First, we analyzed various LES cases (from dry stable to cloud-topped PBL) to check whether this isotropic turbulence assumption used in CAM5 is really valid. It turned out that this isotropic turbulence assumption is not universally valid. Consequently, from the analysis of LES, we derived an empirical formulation relaxing the isotropic turbulence assumption used for the CAM5 aerosol activation and ice nucleation, and implemented the empirical formulation into CAM5/CESM1, and tested in the single-column and global simulation modes, and examined how it changed aerosol indirect effects in the CAM5/CESM1. These results were reported in the poster section in the 18th Annual CESM workshop held in Breckenridge, CO during Jun.17-20.2013. While we derived an empirical formulation from the analysis of couple of LES from the first task, the general applicability of that empirical formulation was questionable, because it was obtained from the limited number of LES simulations. The second task we did was to derive a more fundamental analytical formulation relating vertical velocity variance to TKE using other information starting from basic physical principles. This was a somewhat challenging subject, but if this could be done in a successful way, it could be directly implemented into the CAM5 as a practical parameterization, and substantially contributes to achieving the project goal. Through an intensive research for about one year, we found appropriate mathematical formulation and tried to implement it into the CAM5 PBL and activation routine as a practical parameterized numerical code. During these processes, however, the Postdoc applied for another position in Sweden, Europe, and accepted a job offer there, and left NCAR in August 2014. In Sweden, Dr. Anna Fitch is still working on this subject in a part time, planning to finalize the research and to write the paper in a near future.« less

Geoeffectiveness of three Wind magnetic clouds: A comparative study

NASA Astrophysics Data System (ADS)

Farrugia, C. J.; Scudder, J. D.; Freeman, M. P.; Janoo, L.; Lu, G.; Quinn, J. M.; Arnoldy, R. L.; Torbert, R. B.; Burlaga, L. F.; Ogilvie, K. W.; Lepping, R. P.; Lazarus, A. J.; Steinberg, J. T.; Gratton, F. T.; Rostoker, G.

1998-08-01

We compare the large-scale geomagnetic response to the three magnetic clouds observed by Wind in October 1995 (OCT95), May 1996 (MAY96), and January 1997 (JAN97), studying specifically storm and substorm activity, and other global effects due to untypically large and variable solar wind dynamic pressures. Since the temporal profiles of the interplanetary parameters of the three clouds resemble one another closely, the comparison is meaningful. Using the integrated Poynting flux into the magnetosphere as a rough measure of energy input into the magnetosphere, we find relative energy inputs to be OCT95:JAN97:MAY96=22:11:4, with most of the accumulation in the 3-day periods occurring during passage of the Bz<0 cloud phase. The peak Dst ring current indices, corrected for magnetopause currents, were in the ratio -138:-87:-38, and hence OCT95 caused a major, JAN97 a moderate, and MAY96 a weak storm. The empirical criterion derived from studies near solar maximum that a solar wind dawn-dusk electric field >=5 mVm-1 lasting for at least 3 hours is necessary and sufficient to generate major storms does not hold for JAN97. Storm main phase onset coincides with cloud arrival in all three cases. The number of substorm onsets during the cloud periods were OCT95:JAN97:MAY96=5:3:2, with peak AL values in the ratio -1180:-1750:-570. The dayside magnetosphere was variably compressed, the largest amplitude of variation being on JAN97, where the dynamic pressure change spanned 2 orders of magnitude. MAY96 showed the least variation. The interaction of the individual clouds with the faster trailing flows had two major effects on the magnetosphere: (1) a compression of the cavity during passage of the Bz>0 cloud phase and the leading edge of the fast stream; and (2) a weakening of the control of the cloud field on magnetosheath flow during the Bz>0 cloud phase. In summary we find that under most of the aspects considered, OCT95 is the most geoeffective. The buffetting of the magnetospheric cavity by dynamic pressure changes was, however, strongest on JAN97. The profound differences in the magnetospheric response elicited by the clouds is found to be due to the amplitude, duration and rapidity of change of the relevant interplanetary parameters. At present, interplanetary monitors are indispensable for understanding the geomagnetic response to interplanetary structures.

OCRA radiometric cloud fractions for GOME-2 on MetOp-A/B

NASA Astrophysics Data System (ADS)

Lutz, R.; Loyola, D.; Gimeno García, S.; Romahn, F.

2015-12-01

This paper describes an approach for cloud parameter retrieval (radiometric cloud fraction estimation) using the polarization measurements of the Global Ozone Monitoring Experiment-2 (GOME-2) on-board the MetOp-A/B satellites. The core component of the Optical Cloud Recognition Algorithm (OCRA) is the calculation of monthly cloud-free reflectances for a global grid (resolution of 0.2° in longitude and 0.2° in latitude) and to derive radiometric cloud fractions. These cloud fractions will serve as a priori information for the retrieval of cloud top height (CTH), cloud top pressure (CTP), cloud top albedo (CTA) and cloud optical thickness (COT) with the Retrieval Of Cloud Information using Neural Networks (ROCINN) algorithm. This approach is already being implemented operationally for the GOME/ERS-2 and SCIAMACHY/ENVISAT sensors and here we present version 3.0 of the OCRA algorithm applied to the GOME-2 sensors. Based on more than six years of GOME-2A data (February 2007-June 2013), reflectances are calculated for ≈ 35 000 orbits. For each measurement a degradation correction as well as a viewing angle dependent and latitude dependent correction is applied. In addition, an empirical correction scheme is introduced in order to remove the effect of oceanic sun glint. A comparison of the GOME-2A/B OCRA cloud fractions with co-located AVHRR geometrical cloud fractions shows a general good agreement with a mean difference of -0.15±0.20. From operational point of view, an advantage of the OCRA algorithm is its extremely fast computational time and its straightforward transferability to similar sensors like OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument) on Sentinel 5 Precursor, as well as Sentinel 4 and Sentinel 5. In conclusion, it is shown that a robust, accurate and fast radiometric cloud fraction estimation for GOME-2 can be achieved with OCRA by using the polarization measurement devices (PMDs).

OCRA radiometric cloud fractions for GOME-2 on MetOp-A/B

NASA Astrophysics Data System (ADS)

Lutz, Ronny; Loyola, Diego; Gimeno García, Sebastián; Romahn, Fabian

2016-05-01

This paper describes an approach for cloud parameter retrieval (radiometric cloud-fraction estimation) using the polarization measurements of the Global Ozone Monitoring Experiment-2 (GOME-2) onboard the MetOp-A/B satellites. The core component of the Optical Cloud Recognition Algorithm (OCRA) is the calculation of monthly cloud-free reflectances for a global grid (resolution of 0.2° in longitude and 0.2° in latitude) to derive radiometric cloud fractions. These cloud fractions will serve as a priori information for the retrieval of cloud-top height (CTH), cloud-top pressure (CTP), cloud-top albedo (CTA) and cloud optical thickness (COT) with the Retrieval Of Cloud Information using Neural Networks (ROCINN) algorithm. This approach is already being implemented operationally for the GOME/ERS-2 and SCIAMACHY/ENVISAT sensors and here we present version 3.0 of the OCRA algorithm applied to the GOME-2 sensors. Based on more than five years of GOME-2A data (April 2008 to June 2013), reflectances are calculated for ≈ 35 000 orbits. For each measurement a degradation correction as well as a viewing-angle-dependent and latitude-dependent correction is applied. In addition, an empirical correction scheme is introduced in order to remove the effect of oceanic sun glint. A comparison of the GOME-2A/B OCRA cloud fractions with colocated AVHRR (Advanced Very High Resolution Radiometer) geometrical cloud fractions shows a general good agreement with a mean difference of -0.15 ± 0.20. From an operational point of view, an advantage of the OCRA algorithm is its very fast computational time and its straightforward transferability to similar sensors like OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument) on Sentinel 5 Precursor, as well as Sentinel 4 and Sentinel 5. In conclusion, it is shown that a robust, accurate and fast radiometric cloud-fraction estimation for GOME-2 can be achieved with OCRA using polarization measurement devices (PMDs).

About Jupiter's Reflectance Function in JunoCam Images

NASA Astrophysics Data System (ADS)

Eichstaedt, G.; Orton, G. S.; Momary, T.; Hansen, C. J.; Caplinger, M.

2017-09-01

NASA's Juno spacecraft has successfully completed several perijove passes. JunoCam is Juno's visible light and infrared camera. It was added to the instrument complement to investigate Jupiter's polar regions, and for education and public outreach purposes. Images of Jupiter taken by JunoCam have been revealing effects that can be interpreted as caused by a haze layer. This presumed haze layer appears to be structured, and it partially obscures Jupiter's cloud top. With empirical investigation of Jupiter's reflectance function we intend to separate light contributed by haze from light reflected off Jupiter's cloud tops, enabling both layers to be investigated separately.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J.

1989-01-01

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

Airborne observations of cloud condensation nuclei spectra and aerosols over East Inner Mongolia

NASA Astrophysics Data System (ADS)

Yang, Jiefan; Lei, Hengchi; Lü, Yuhuan

2017-08-01

A set of vertical profiles of aerosol number concentrations, size distributions and cloud condensation nuclei (CCN) spectra was observed using a passive cloud and aerosol spectrometer (PCASP) and cloud condensation nuclei counter, over the Tongliao area, East Inner Mongolia, China. The results showed that the average aerosol number concentration in this region was much lower than that in heavily polluted areas. Monthly average aerosol number concentrations within the boundary layer reached a maximum in May and a minimum in September, and the variations in CCN number concentrations at different supersaturations showed the same trend. The parameters c and k of the empirical function N = cS k were 539 and 1.477 under clean conditions, and their counterparts under polluted conditions were 1615 and 1.42. Measurements from the airborne probe mounted on a Yun-12 (Y12) aircraft, together with Hybrid Single-Particle Lagrangian Integrated Trajectory model backward trajectories indicated that the air mass from the south of Tongliao contained a high concentration of aerosol particles (1000-2500 cm-3) in the middle and lower parts of the troposphere. Moreover, detailed intercomparison of data obtained on two days in 2010 indicated that the activation efficiency in terms of the ratio of N CCN to N a (aerosols measured from PCASP) was 0.74 (0.4 supersaturations) when the air mass mainly came from south of Tongliao, and this value increased to 0.83 on the relatively cleaner day. Thus, long-range transport of anthropogenic pollutants from heavily polluted mega cities, such as Beijing and Tianjin, may result in slightly decreasing activation efficiencies.

Dense gas and star formation in individual Giant Molecular Clouds in M31

NASA Astrophysics Data System (ADS)

Viaene, S.; Forbrich, J.; Fritz, J.

2018-04-01

Studies both of entire galaxies and of local Galactic star formation indicate a dependency of a molecular cloud's star formation rate (SFR) on its dense gas mass. In external galaxies, such measurements are derived from HCN(1-0) observations, usually encompassing many Giant Molecular Clouds (GMCs) at once. The Andromeda galaxy (M31) is a unique laboratory to study the relation of the SFR and HCN emission down to GMC scales at solar-like metallicities. In this work, we correlate our composite SFR determinations with archival HCN, HCO+, and CO observations, resulting in a sample of nine reasonably representative GMCs. We find that, at the scale of individual clouds, it is important to take into account both obscured and unobscured star formation to determine the SFR. When correlated against the dense-gas mass from HCN, we find that the SFR is low, in spite of these refinements. We nevertheless retrieve an SFR-dense-gas mass correlation, confirming that these SFR tracers are still meaningful on GMC scales. The correlation improves markedly when we consider the HCN/CO ratio instead of HCN by itself. This nominally indicates a dependency of the SFR on the dense-gas fraction, in contradiction to local studies. However, we hypothesize that this partly reflects the limited dynamic range in dense-gas mass, and partly that the ratio of single-pointing HCN and CO measurements may be less prone to systematics like sidelobes. In this case, the HCN/CO ratio would importantly be a better empirical measure of the dense-gas content itself.

Importance of including ammonium sulfate ((NH4)2SO4) aerosols for ice cloud parameterization in GCMs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhattacharjee, P. S.; Sud, Yogesh C.; Liu, Xiaohong

2010-02-22

A common deficiency of many cloud-physics parameterizations including the NASA’s microphysics of clouds with aerosol- cloud interactions (hereafter called McRAS-AC) is that they simulate less (larger) than the observed ice cloud particle number (size). A single column model (SCM) of McRAS-AC and Global Circulation Model (GCM) physics together with an adiabatic parcel model (APM) for ice-cloud nucleation (IN) of aerosols were used to systematically examine the influence of ammonium sulfate ((NH4)2SO4) aerosols, not included in the present formulations of McRAS-AC. Specifically, the influence of (NH4)2SO4 aerosols on the optical properties of both liquid and ice clouds were analyzed. First anmore » (NH4)2SO4 parameterization was included in the APM to assess its effect vis-à-vis that of the other aerosols. Subsequently, several evaluation tests were conducted over the ARM-SGP and thirteen other locations (sorted into pristine and polluted conditions) distributed over marine and continental sites with the SCM. The statistics of the simulated cloud climatology were evaluated against the available ground and satellite data. The results showed that inclusion of (NH4)2SO4 in the SCM made a remarkable improvement in the simulated effective radius of ice clouds. However, the corresponding ice-cloud optical thickness increased more than is observed. This can be caused by lack of cloud advection and evaporation. We argue that this deficiency can be mitigated by adjusting the other tunable parameters of McRAS-AC such as precipitation efficiency. Inclusion of ice cloud particle splintering introduced through well- established empirical equations is found to further improve the results. Preliminary tests show that these changes make a substantial improvement in simulating the cloud optical properties in the GCM, particularly by simulating a far more realistic cloud distribution over the ITCZ.« less

4-D cloud properties from passive satellite data and applications to resolve the flight icing threat to aircraft

NASA Astrophysics Data System (ADS)

Smith, William L., Jr.

The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This thesis develops new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft in a wide range of cloud conditions. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS, the satellite icing detection and intensity accuracies are found to be about 90% and 70%, respectively. Mean differences between the imager IWC retrievals with those from CloudSat and Calipso are less than 30%. This level of closure in the cloud water budget can only be achieved by correcting for errors in the imager retrievals due to the simplifying but poor assumption that deep optically thick clouds are single-phase and vertically homogeneous. When applied to geostationary satellite data, the profiling method provides a real-time characterization of clouds in 4-D. This research should improve the utility of satellite imager data for quantitatively diagnosing and predicting clouds and their effects in weather and climate applications.

Cloud Radiation Forcings and Feedbacks: General Circulation Model Tests and Observational Validation

NASA Technical Reports Server (NTRS)

Lee,Wan-Ho; Iacobellis, Sam F.; Somerville, Richard C. J.

1997-01-01

Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model. together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.

US Policies toward Tehran: Redefining Counterproliferation for the Twenty-First Century

DTIC Science & Technology

2011-01-01

latent weapons power, purposefully not constructing an explicit, fully weaponized arsenal, but rather cultivating and maintaining a hedged nuclear...decisively dropping the popular but empirically dubious assump­ tion that Iran’s primary intent is to put mushroom clouds over Tel Aviv and Washington as

Do Open Educational Resources and Cloud Classroom Really Improve Students' Learning?

ERIC Educational Resources Information Center

Tsai, Chia-Wen; Shen, Pei-Di

2014-01-01

More and more educational institutions are using educational technologies and online learning materials to help students achieve satisfactory learning effects. However, not all teachers are able to prepare and design digital learning materials for students. This research attempted to empirically demonstrate the effects of applying open educational…

Understanding Ice Supersaturation, Particle Growth, and Number Concentration in Cirrus Clouds

NASA Technical Reports Server (NTRS)

Comstock, Jennifer M.; Lin, Ruei-Fong; Starr, David O'C.; Yang, Ping

2008-01-01

Many factors control the ice supersaturation and microphysical properties in cirrus clouds. We explore the effects of dynamic forcing, ice nucleation mechanisms, and ice crystal growth rate on the evolution and distribution of water vapor and cloud properties in nighttime cirrus clouds using a one-dimensional cloud model with bin microphysics and remote sensing measurements obtained at the Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility located near Lamont, OK. We forced the model using both large-scale vertical ascent and, for the first time, mean mesoscale velocity derived from radar Doppler velocity measurements. Both heterogeneous and homogeneous nucleation processes are explored, where a classical theory heterogeneous scheme is compared with empirical representations. We evaluated model simulations by examining both bulk cloud properties and distributions of measured radar reflectivity, lidar extinction, and water vapor profiles, as well as retrieved cloud microphysical properties. Our results suggest that mesoscale variability is the primary mechanism needed to reproduce observed quantities. Model sensitivity to the ice growth rate is also investigated. The most realistic simulations as compared with observations are forced using mesoscale waves, include fast ice crystal growth, and initiate ice by either homogeneous or heterogeneous nucleation. Simulated ice crystal number concentrations (tens to hundreds particles per liter) are typically two orders of magnitude smaller than previously published results based on aircraft measurements in cirrus clouds, although higher concentrations are possible in isolated pockets within the nucleation zone.

Evaluation on penetration rate of cloud for incoming solar radiation using geostationary satellite data

NASA Astrophysics Data System (ADS)

Yeom, Jong-Min; Han, Kyung-Soo; Kim, Jae-Jin

2012-05-01

Solar surface insolation (SSI) represents how much solar radiance reaches the Earth's surface in a specified area and is an important parameter in various fields such as surface energy research, meteorology, and climate change. This study calculates insolation using Multi-functional Transport Satellite (MTSAT-1R) data with a simplified cloud factor over Northeast Asia. For SSI retrieval from the geostationary satellite data, the physical model of Kawamura is modified to improve insolation estimation by considering various atmospheric constituents, such as Rayleigh scattering, water vapor, ozone, aerosols, and clouds. For more accurate atmospheric parameterization, satellite-based atmospheric constituents are used instead of constant values when estimating insolation. Cloud effects are a key problem in insolation estimation because of their complicated optical characteristics and high temporal and spatial variation. The accuracy of insolation data from satellites depends on how well cloud attenuation as a function of geostationary channels and angle can be inferred. This study uses a simplified cloud factor that depends on the reflectance and solar zenith angle. Empirical criteria to select reference data for fitting to the ground station data are applied to suggest simplified cloud factor methods. Insolation estimated using the cloud factor is compared with results of the unmodified physical model and with observations by ground-based pyranometers located in the Korean peninsula. The modified model results show far better agreement with ground truth data compared to estimates using the conventional method under overcast conditions.

A Global Classification of Contemporary Fire Regimes

NASA Astrophysics Data System (ADS)

Norman, S. P.; Kumar, J.; Hargrove, W. W.; Hoffman, F. M.

2014-12-01

Fire regimes provide a sensitive indicator of changes in climate and human use as the concept includes fire extent, season, frequency, and intensity. Fires that occur outside the distribution of one or more aspects of a fire regime may affect ecosystem resilience. However, global scale data related to these varied aspects of fire regimes are highly inconsistent due to incomplete or inconsistent reporting. In this study, we derive a globally applicable approach to characterizing similar fire regimes using long geophysical time series, namely MODIS hotspots since 2000. K-means non-hierarchical clustering was used to generate empirically based groups that minimized within-cluster variability. Satellite-based fire detections are known to have shortcomings, including under-detection from obscuring smoke, clouds or dense canopy cover and rapid spread rates, as often occurs with flashy fuels or during extreme weather. Such regions are free from preconceptions, and the empirical, data-mining approach used on this relatively uniform data source allows the region structures to emerge from the data themselves. Comparing such an empirical classification to expectations from climate, phenology, land use or development-based models can help us interpret the similarities and differences among places and how they provide different indicators of changes of concern. Classifications can help identify where large infrequent mega-fires are likely to occur ahead of time such as in the boreal forest and portions of the Interior US West, and where fire reports are incomplete such as in less industrial countries.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Habte, A.; Sengupta, M.; Wilcox, S.

Models to compute Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) have been in development over the last 3 decades. These models can be classified as empirical or physical, based on the approach. Empirical models relate ground based observations with satellite measurements and use these relations to compute surface radiation. Physical models consider the radiation received from the earth at the satellite and create retrievals to estimate surface radiation. While empirical methods have been traditionally used for computing surface radiation for the solar energy industry the advent of faster computing has made operational physical models viable. The Global Solarmore » Insolation Project (GSIP) is an operational physical model from NOAA that computes GHI using the visible and infrared channel measurements from the GOES satellites. GSIP uses a two-stage scheme that first retrieves cloud properties and uses those properties in a radiative transfer model to calculate surface radiation. NREL, University of Wisconsin and NOAA have recently collaborated to adapt GSIP to create a 4 km GHI and DNI product every 30 minutes. This paper presents an outline of the methodology and a comprehensive validation using high quality ground based solar data from the National Oceanic and Atmospheric Administration (NOAA) Surface Radiation (SURFRAD) (http://www.srrb.noaa.gov/surfrad/sitepage.html) and Integrated Surface Insolation Study (ISIS) http://www.srrb.noaa.gov/isis/isissites.html), the Solar Radiation Research Laboratory (SRRL) at National Renewable Energy Laboratory (NREL), and Sun Spot One (SS1) stations.« less

Impact of different cloud deployments on real-time video applications for mobile video cloud users

NASA Astrophysics Data System (ADS)

Khan, Kashif A.; Wang, Qi; Luo, Chunbo; Wang, Xinheng; Grecos, Christos

2015-02-01

The latest trend to access mobile cloud services through wireless network connectivity has amplified globally among both entrepreneurs and home end users. Although existing public cloud service vendors such as Google, Microsoft Azure etc. are providing on-demand cloud services with affordable cost for mobile users, there are still a number of challenges to achieve high-quality mobile cloud based video applications, especially due to the bandwidth-constrained and errorprone mobile network connectivity, which is the communication bottleneck for end-to-end video delivery. In addition, existing accessible clouds networking architectures are different in term of their implementation, services, resources, storage, pricing, support and so on, and these differences have varied impact on the performance of cloud-based real-time video applications. Nevertheless, these challenges and impacts have not been thoroughly investigated in the literature. In our previous work, we have implemented a mobile cloud network model that integrates localized and decentralized cloudlets (mini-clouds) and wireless mesh networks. In this paper, we deploy a real-time framework consisting of various existing Internet cloud networking architectures (Google Cloud, Microsoft Azure and Eucalyptus Cloud) and a cloudlet based on Ubuntu Enterprise Cloud over wireless mesh networking technology for mobile cloud end users. It is noted that the increasing trend to access real-time video streaming over HTTP/HTTPS is gaining popularity among both research and industrial communities to leverage the existing web services and HTTP infrastructure in the Internet. To study the performance under different deployments using different public and private cloud service providers, we employ real-time video streaming over the HTTP/HTTPS standard, and conduct experimental evaluation and in-depth comparative analysis of the impact of different deployments on the quality of service for mobile video cloud users. Empirical results are presented and discussed to quantify and explain the different impacts resulted from various cloud deployments, video application and wireless/mobile network setting, and user mobility. Additionally, this paper analyses the advantages, disadvantages, limitations and optimization techniques in various cloud networking deployments, in particular the cloudlet approach compared with the Internet cloud approach, with recommendations of optimized deployments highlighted. Finally, federated clouds and inter-cloud collaboration challenges and opportunities are discussed in the context of supporting real-time video applications for mobile users.

Secure Skyline Queries on Cloud Platform

PubMed Central

Liu, Jinfei; Yang, Juncheng; Xiong, Li; Pei, Jian

2017-01-01

Outsourcing data and computation to cloud server provides a cost-effective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data (e.g., medical records) need to be protected from the cloud server and other unauthorized users. One approach is to outsource encrypted data to the cloud server and have the cloud server perform query processing on the encrypted data only. It remains a challenging task to support various queries over encrypted data in a secure and efficient way such that the cloud server does not gain any knowledge about the data, query, and query result. In this paper, we study the problem of secure skyline queries over encrypted data. The skyline query is particularly important for multi-criteria decision making but also presents significant challenges due to its complex computations. We propose a fully secure skyline query protocol on data encrypted using semantically-secure encryption. As a key subroutine, we present a new secure dominance protocol, which can be also used as a building block for other queries. Finally, we provide both serial and parallelized implementations and empirically study the protocols in terms of efficiency and scalability under different parameter settings, verifying the feasibility of our proposed solutions. PMID:28883710

Improved Thin Cirrus and Terminator Cloud Detection in CERES Cloud Mask

NASA Technical Reports Server (NTRS)

Trepte, Qing; Minnis, Patrick; Palikonda, Rabindra; Spangenberg, Doug; Haeffelin, Martial

2006-01-01

Thin cirrus clouds account for about 20-30% of the total cloud coverage and affect the global radiation budget by increasing the Earth's albedo and reducing infrared emissions. Thin cirrus, however, are often underestimated by traditional satellite cloud detection algorithms. This difficulty is caused by the lack of spectral contrast between optically thin cirrus and the surface in techniques that use visible (0.65 micron ) and infrared (11 micron ) channels. In the Clouds and the Earth s Radiant Energy System (CERES) Aqua Edition 1 (AEd1) and Terra Edition 3 (TEd3) Cloud Masks, thin cirrus detection is significantly improved over both land and ocean using a technique that combines MODIS high-resolution measurements from the 1.38 and 11 micron channels and brightness temperature differences (BTDs) of 11-12, 8.5-11, and 3.7-11 micron channels. To account for humidity and view angle dependencies, empirical relationships were derived with observations from the 1.38 micron reflectance and the 11-12 and 8.5-11 micron BTDs using 70 granules of MODIS data in 2002 and 2003. Another challenge in global cloud detection algorithms occurs near the day/night terminator where information from the visible 0.65 micron channel and the estimated solar component of 3.7 micron channel becomes less reliable. As a result, clouds are often underestimated or misidentified near the terminator over land and ocean. Comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 N indicate significant amounts of missing clouds from CLAVR-x because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products (MOD06) and GLAS in the same region also show similar difficulties with MODIS cloud retrievals. The consistent detection of clouds through out the day is needed to provide reliable cloud and radiation products for CERES and other research efforts involving the modeling of clouds and their interaction with the radiation budget.

Improving Pixel Level Cloud Optical Property Retrieval using Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Marshak, Alexander; Cahalan, Robert F.

1999-01-01

The accurate pixel-by-pixel retrieval of cloud optical properties from space is influenced by radiative smoothing due to high order photon scattering and radiative roughening due to low order scattering events. Both are caused by cloud heterogeneity and the three-dimensional nature of radiative transfer and can be studied with the aid of computer simulations. We use Monte Carlo simulations on variable 1-D and 2-D model cloud fields to seek for dependencies of smoothing and roughening phenomena on single scattering albedo, solar zenith angle, and cloud characteristics. The results are discussed in the context of high resolution satellite (such as Landsat) retrieval applications. The current work extends the investigation on the inverse NIPA (Non-local Independent Pixel Approximation) as a tool for removing smoothing and improving retrievals of cloud optical depth. This is accomplished by: (1) Delineating the limits of NIPA applicability; (2) Exploring NIPA parameter dependences on cloud macrostructural features, such as mean cloud optical depth and geometrical thickness, degree of extinction and cloud top height variability. We also compare parameter values from empirical and theoretical considerations; (3) Examining the differences between applying NIPA on radiation quantities vs direct application on optical properties; (4) Studying the radiation budget importance of the NIPA corrections as a function of scale. Finally, we discuss fundamental adjustments that need to be considered for successful radiance inversion at non-conservative wavelengths and oblique Sun angles. These adjustments are necessary to remove roughening signatures which become more prominent with increasing absorption and solar zenith angle.

Chemistry of riming: the retention of organic and inorganic atmospheric trace constituents

NASA Astrophysics Data System (ADS)

Jost, Alexander; Szakáll, Miklós; Diehl, Karoline; Mitra, Subir K.; Borrmann, Stephan

2017-08-01

During free fall in clouds, ice hydrometeors such as snowflakes and ice particles grow effectively by riming, i.e., the accretion of supercooled droplets. Volatile atmospheric trace constituents dissolved in the supercooled droplets may remain in ice during freezing or may be released back to the gas phase. This process is quantified by retention coefficients. Once in the ice phase the trace constituents may be vertically redistributed by scavenging and subsequent precipitation or by evaporation of these ice hydrometeors at high altitudes. Retention coefficients of the most dominant carboxylic acids and aldehydes found in cloud water were investigated in the Mainz vertical wind tunnel under dry-growth (surface temperature less than 0 °C) riming conditions which are typically prevailing in the mixed-phase zone of convective clouds (i.e., temperatures from -16 to -7 °C and a liquid water content (LWC) of 0. 9 ± 0. 2 g m-3). The mean retention coefficients of formic and acetic acids are found to be 0. 68 ± 0. 09 and 0. 63 ± 0. 19. Oxalic and malonic acids as well as formaldehyde show mean retention coefficients of 0. 97 ± 0. 06, 0. 98 ± 0. 08, and 0. 97 ± 0. 11, respectively. Application of a semi-empirical model on the present and earlier wind tunnel measurements reveals that retention coefficients can be well interpreted by the effective Henry's law constant accounting for solubility and dissociation. A parameterization for the retention coefficients has been derived for substances whose aqueous-phase kinetics are fast compared to mass transport timescales. For other cases, the semi-empirical model in combination with a kinetic approach is suited to determine the retention coefficients. These may be implemented in high-resolution cloud models.

Testing the sensitivity of past climates to the indirect effects of dust

NASA Astrophysics Data System (ADS)

Sagoo, Navjit; Storelvmo, Trude

2017-06-01

Mineral dust particles are important ice nuclei (IN) and as such indirectly impact Earth's radiative balance via the properties of cold clouds. Using the Community Earth System Model version 1.0.6, and Community Atmosphere Model version 5.1, and a new empirical parameterization for ice nucleation on dust particles, we investigate the radiative forcing induced by dust IN for different dust loadings. Dust emissions are representative of global conditions for the Last Glacial Maximum and the mid-Pliocene Warm Period. Increased dust leads to smaller and more numerous ice crystals in mixed phase clouds, impacting cloud opacity, lifetime, and precipitation. This increases the shortwave cloud radiative forcing, resulting in significant surface temperature cooling and polar amplification—which is underestimated in existing studies relative to paleoclimate archives. Large hydrological changes occur and are linked to an enhanced dynamical response. We conclude that dust indirect effects could potentially have a significant impact on the model-data mismatch that exists for paleoclimates.