ULF geomagnetic activity effects on tropospheric temperature, specific humidity, and cloud cover in Antarctica, during 2003-2010

Science.gov (United States)

Regi, Mauro; Redaelli, Gianluca; Francia, Patrizia; De Lauretis, Marcello

2017-06-01

In the present study we investigated the possible relationship between the ULF geomagnetic activity and the variations of several atmospheric parameters. In particular, we compared the ULF activity in the Pc1-2 frequency band (100 mHz-5 Hz), computed from geomagnetic field measurements at Terra Nova Bay in Antarctica, with the tropospheric temperature T, specific humidity Q, and cloud cover (high cloud cover, medium cloud cover, and low cloud cover) obtained from reanalysis data set. The statistical analysis was conducted during the years 2003-2010, using correlation and Superposed Epoch Analysis approaches. The results show that the atmospheric parameters significantly change following the increase of geomagnetic activity within 2 days. These changes are evident in particular when the interplanetary magnetic field Bz component is oriented southward (Bz0). We suggest that both the precipitation of electrons induced by Pc1-2 activity and the intensification of the polar cap potential difference, modulating the microphysical processes in the clouds, can affect the atmosphere conditions.

THE INFLUENCE OF NONUNIFORM CLOUD COVER ON TRANSIT TRANSMISSION SPECTRA

Energy Technology Data Exchange (ETDEWEB)

Line, Michael R. [NASA Ames Research Center, Moffet Field, CA 94035 (United States); Parmentier, Vivien, E-mail: mrline@ucsc.edu [Department of Astronomy and Astrophysics, University of California–Santa Cruz, 1156 High Street, Santa Cruz, CA 95064 (United States)

2016-03-20

We model the impact of nonuniform cloud cover on transit transmission spectra. Patchy clouds exist in nearly every solar system atmosphere, brown dwarfs, and transiting exoplanets. Our major findings suggest that fractional cloud coverage can exactly mimic high mean molecular weight atmospheres and vice versa over certain wavelength regions, in particular, over the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) bandpass (1.1–1.7 μm). We also find that patchy cloud coverage exhibits a signature that is different from uniform global clouds. Furthermore, we explain analytically why the “patchy cloud-high mean molecular weight” degeneracy exists. We also explore the degeneracy of nonuniform cloud coverage in atmospheric retrievals on both synthetic and real planets. We find from retrievals on a synthetic solar composition hot Jupiter with patchy clouds and a cloud-free high mean molecular weight warm Neptune that both cloud-free high mean molecular weight atmospheres and partially cloudy atmospheres can explain the data equally well. Another key finding is that the HST WFC3 transit transmission spectra of two well-observed objects, the hot Jupiter HD 189733b and the warm Neptune HAT-P-11b, can be explained well by solar composition atmospheres with patchy clouds without the need to invoke high mean molecular weight or global clouds. The degeneracy between high molecular weight and solar composition partially cloudy atmospheres can be broken by observing the molecular Rayleigh scattering differences between the two. Furthermore, the signature of partially cloudy limbs also appears as a ∼100 ppm residual in the ingress and egress of the transit light curves, provided that the transit timing is known to seconds.

Do clouds save the great barrier reef? satellite imagery elucidates the cloud-SST relationship at the local scale.

Directory of Open Access Journals (Sweden)

Susannah M Leahy

Full Text Available Evidence of global climate change and rising sea surface temperatures (SSTs is now well documented in the scientific literature. With corals already living close to their thermal maxima, increases in SSTs are of great concern for the survival of coral reefs. Cloud feedback processes may have the potential to constrain SSTs, serving to enforce an "ocean thermostat" and promoting the survival of coral reefs. In this study, it was hypothesized that cloud cover can affect summer SSTs in the tropics. Detailed direct and lagged relationships between cloud cover and SST across the central Great Barrier Reef (GBR shelf were investigated using data from satellite imagery and in situ temperature and light loggers during two relatively hot summers (2005 and 2006 and two relatively cool summers (2007 and 2008. Across all study summers and shelf positions, SSTs exhibited distinct drops during periods of high cloud cover, and conversely, SST increases during periods of low cloud cover, with a three-day temporal lag between a change in cloud cover and a subsequent change in SST. Cloud cover alone was responsible for up to 32.1% of the variation in SSTs three days later. The relationship was strongest in both El Niño (2005 and La Niña (2008 study summers and at the inner-shelf position in those summers. SST effects on subsequent cloud cover were weaker and more variable among study summers, with rising SSTs explaining up to 21.6% of the increase in cloud cover three days later. This work quantifies the often observed cloud cooling effect on coral reefs. It highlights the importance of incorporating local-scale processes into bleaching forecasting models, and encourages the use of remote sensing imagery to value-add to coral bleaching field studies and to more accurately predict risks to coral reefs.

Nimbus-3/HRIR Level 2 Earth's Cloud Cover and Temperature of Cloud Tops and Terrain Features V001

Data.gov (United States)

National Aeronautics and Space Administration — The Nimbus High Resolution Infrared Radiometer (HRIR) was originally designed to perform two major functions: First, to map the Earth's cloud cover at night to...

Estimating solar resources in Mexico using cloud cover data

Energy Technology Data Exchange (ETDEWEB)

Renne, David; George, Ray; Brady, Liz; Marion, Bill [National Renewable Energy Laboratory, Colorado (United States); Estrada Cajigal, Vicente [Cuernavaca, Morelos (Mexico)

2000-07-01

This paper presents the results of applying the National Renewable Energy Laboratory's (NREL) Climatological Solar Radiation (CSR) model to Mexico to develop solar resource data. A major input to the CSR model is a worldwide surface and satellite-derived cloud cover database, called the Real Time Nephanalysis (RTNEPH). The RTNEPH is developed by the U.S. Air Force and distributed by the U.S. National Climatic Data Center. The RTNEPH combines routine ground-based cloud cover observations made every three hours at national weather centers throughout the world with satellite-derived cloud cover information developed from polar orbiting weather satellites. The data are geospatially digitized so that multilayerd cloud cover information is available on a grid of approximately 40-km to a side. The development of this database is an ongoing project that now covers more than twenty years of observations. For the North America analysis (including Mexico) we used an 8-year summarized histogram of the RTNEPH that provides monthly average cloud cover information for the period 1985-1992. The CSR model also accounts for attenuation of the solar beam due to aerosols, atmospheric trace gases, and water vapor. The CSR model outputs monthly average direct normal, global horizontal and diffuse solar information for each of the 40-km grid cells. From this information it is also possible to produce solar resource estimates for various solar collector types and orientations, such as flat plate collectors oriented at latitude tilt, or concentrating solar power collectors. Model results are displayed using Geographic Information System software. CSR model results for Mexico are presented here, along with a discussion of earlier solar resource assessment studies for Mexico, where both modeling approaches and measurement analyses have been used. [Spanish] Este articulo presenta los resultados de aplicar el modelo Radiacion Solar Climatologica CSR del NREL (National Renewable Energy

A large catalog of accurate distances to molecular clouds from PS1 photometry

Energy Technology Data Exchange (ETDEWEB)

Schlafly, E. F.; Rix, H.-W.; Martin, N. F. [Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany); Green, G.; Finkbeiner, D. P. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Bell, E. F. [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI 48109 (United States); Burgett, W. S.; Chambers, K. C.; Hodapp, K. W.; Kaiser, N.; Magnier, E. A.; Tonry, J. L. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Draper, P. W.; Metcalfe, N. [Department of Physics, Durham University, South Road, Durham DH1 3LE (United Kingdom); Price, P. A. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

2014-05-01

Distance measurements to molecular clouds are important but are often made separately for each cloud of interest, employing very different data and techniques. We present a large, homogeneous catalog of distances to molecular clouds, most of which are of unprecedented accuracy. We determine distances using optical photometry of stars along lines of sight toward these clouds, obtained from PanSTARRS-1. We simultaneously infer the reddenings and distances to these stars, tracking the full probability distribution function using a technique presented in Green et al. We fit these star-by-star measurements using a simple dust screen model to find the distance to each cloud. We thus estimate the distances to almost all of the clouds in the Magnani et al. catalog, as well as many other well-studied clouds, including Orion, Perseus, Taurus, Cepheus, Polaris, California, and Monoceros R2, avoiding only the inner Galaxy. Typical statistical uncertainties in the distances are 5%, though the systematic uncertainty stemming from the quality of our stellar models is about 10%. The resulting catalog is the largest catalog of accurate, directly measured distances to molecular clouds. Our distance estimates are generally consistent with available distance estimates from the literature, though in some cases the literature estimates are off by a factor of more than two.

An Uneven Illumination Correction Algorithm for Optical Remote Sensing Images Covered with Thin Clouds

Directory of Open Access Journals (Sweden)

Xiaole Shen

2015-09-01

Full Text Available The uneven illumination phenomenon caused by thin clouds will reduce the quality of remote sensing images, and bring adverse effects to the image interpretation. To remove the effect of thin clouds on images, an uneven illumination correction can be applied. In this paper, an effective uneven illumination correction algorithm is proposed to remove the effect of thin clouds and to restore the ground information of the optical remote sensing image. The imaging model of remote sensing images covered by thin clouds is analyzed. Due to the transmission attenuation, reflection, and scattering, the thin cloud cover usually increases region brightness and reduces saturation and contrast of the image. As a result, a wavelet domain enhancement is performed for the image in Hue-Saturation-Value (HSV color space. We use images with thin clouds in Wuhan area captured by QuickBird and ZiYuan-3 (ZY-3 satellites for experiments. Three traditional uneven illumination correction algorithms, i.e., multi-scale Retinex (MSR algorithm, homomorphic filtering (HF-based algorithm, and wavelet transform-based MASK (WT-MASK algorithm are performed for comparison. Five indicators, i.e., mean value, standard deviation, information entropy, average gradient, and hue deviation index (HDI are used to analyze the effect of the algorithms. The experimental results show that the proposed algorithm can effectively eliminate the influences of thin clouds and restore the real color of ground objects under thin clouds.

Cloud Detection by Fusing Multi-Scale Convolutional Features

Science.gov (United States)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

A Comparison of MODIS/VIIRS Cloud Masks over Ice-Bearing River: On Achieving Consistent Cloud Masking and Improved River Ice Mapping

Directory of Open Access Journals (Sweden)

Simon Kraatz

2017-03-01

Full Text Available The capability of frequently and accurately monitoring ice on rivers is important, since it may be possible to timely identify ice accumulations corresponding to ice jams. Ice jams are dam-like structures formed from arrested ice floes, and may cause rapid flooding. To inform on this potential hazard, the CREST River Ice Observing System (CRIOS produces ice cover maps based on MODIS and VIIRS overpass data at several locations, including the Susquehanna River. CRIOS uses the respective platform’s automatically produced cloud masks to discriminate ice/snow covered grid cells from clouds. However, since cloud masks are produced using each instrument’s data, and owing to differences in detector performance, it is quite possible that identical algorithms applied to even nearly identical instruments may produce substantially different cloud masks. Besides detector performance, cloud identification can be biased due to local (e.g., land cover, viewing geometry, and transient conditions (snow and ice. Snow/cloud confusions and large view angles can result in substantial overestimates of clouds and ice. This impacts algorithms, such as CRIOS, since false cloud cover precludes the determination of whether an otherwise reasonably cloud free grid consists of water or ice. Especially for applications aiming to frequently classify or monitor a location it is important to evaluate cloud masking, including false cloud detections. We present an assessment of three cloud masks via the parameter of effective revisit time. A 100 km stretch of up to 1.6 km wide river was examined with daily data sampled at 500 m resolution, examined over 317 days during winter. Results show that there are substantial differences between each of the cloud mask products, especially while the river bears ice. A contrast-based cloud screening approach was found to provide improved and consistent cloud and ice identification within the reach (95%–99% correlations, and 3%–7% mean

Influence of cloud fraction and snow cover to the variation of surface UV radiation at King Sejong station, Antarctica

Science.gov (United States)

Lee, Yun Gon; Koo, Ja-Ho; Kim, Jhoon

2015-10-01

This study investigated how cloud fraction and snow cover affect the variation of surface ultraviolet (UV) radiation by using surface Erythemal UV (EUV) and Near UV (NUV) observed at the King Sejong Station, Antarctica. First the Radiative Amplification Factor (RAF), the relative change of surface EUV according to the total-column ozone amount, is compared for different cloud fractions and solar zenith angles (SZAs). Generally, all cloudy conditions show that the increase of RAF as SZA becomes larger, showing the larger effects of vertical columnar ozone. For given SZA cases, the EUV transmission through mean cloud layer gradually decreases as cloud fraction increases, but sometimes the maximum of surface EUV appears under partly cloudy conditions. The high surface EUV transmittance under broken cloud conditions seems due to the re-radiation of scattered EUV by cloud particles. NUV transmission through mean cloud layer also decreases as cloud amount increases but the sensitivity to the cloud fraction is larger than EUV. Both EUV and NUV radiations at the surface are also enhanced by the snow cover, and their enhancement becomes higher as SZA increases implying the diurnal variation of surface albedo. This effect of snow cover seems large under the overcast sky because of the stronger interaction between snow surface and cloudy sky.

Cloud Statistics and Discrimination in the Polar Regions

Science.gov (United States)

Chan, M.; Comiso, J. C.

2012-12-01

Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice

ASTER cloud coverage reassessment using MODIS cloud mask products

Science.gov (United States)

Tonooka, Hideyuki; Omagari, Kunjuro; Yamamoto, Hirokazu; Tachikawa, Tetsushi; Fujita, Masaru; Paitaer, Zaoreguli

2010-10-01

In the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) Project, two kinds of algorithms are used for cloud assessment in Level-1 processing. The first algorithm based on the LANDSAT-5 TM Automatic Cloud Cover Assessment (ACCA) algorithm is used for a part of daytime scenes observed with only VNIR bands and all nighttime scenes, and the second algorithm based on the LANDSAT-7 ETM+ ACCA algorithm is used for most of daytime scenes observed with all spectral bands. However, the first algorithm does not work well for lack of some spectral bands sensitive to cloud detection, and the two algorithms have been less accurate over snow/ice covered areas since April 2008 when the SWIR subsystem developed troubles. In addition, they perform less well for some combinations of surface type and sun elevation angle. We, therefore, have developed the ASTER cloud coverage reassessment system using MODIS cloud mask (MOD35) products, and have reassessed cloud coverage for all ASTER archived scenes (>1.7 million scenes). All of the new cloud coverage data are included in Image Management System (IMS) databases of the ASTER Ground Data System (GDS) and NASA's Land Process Data Active Archive Center (LP DAAC) and used for ASTER product search by users, and cloud mask images are distributed to users through Internet. Daily upcoming scenes (about 400 scenes per day) are reassessed and inserted into the IMS databases in 5 to 7 days after each scene observation date. Some validation studies for the new cloud coverage data and some mission-related analyses using those data are also demonstrated in the present paper.

The Impact of Time Difference between Satellite Overpass and Ground Observation on Cloud Cover Performance Statistics

Directory of Open Access Journals (Sweden)

Jędrzej S. Bojanowski

2014-12-01

Full Text Available Cloud property data sets derived from passive sensors onboard the polar orbiting satellites (such as the NOAA’s Advanced Very High Resolution Radiometer have global coverage and now span a climatological time period. Synoptic surface observations (SYNOP are often used to characterize the accuracy of satellite-based cloud cover. Infrequent overpasses of polar orbiting satellites combined with the 3- or 6-h SYNOP frequency lead to collocation time differences of up to 3 h. The associated collocation error degrades the cloud cover performance statistics such as the Hanssen-Kuiper’s discriminant (HK by up to 45%. Limiting the time difference to 10 min, on the other hand, introduces a sampling error due to a lower number of corresponding satellite and SYNOP observations. This error depends on both the length of the validated time series and the SYNOP frequency. The trade-off between collocation and sampling error call for an optimum collocation time difference. It however depends on cloud cover characteristics and SYNOP frequency, and cannot be generalized. Instead, a method is presented to reconstruct the unbiased (true HK from HK affected by the collocation differences, which significantly (t-test p < 0.01 improves the validation results.

Diurnal cycle and seasonal variation of cloud cover over the Tibetan Plateau as determined from Himawari-8 new-generation geostationary satellite data.

Science.gov (United States)

Shang, Huazhe; Letu, Husi; Nakajima, Takashi Y; Wang, Ziming; Ma, Run; Wang, Tianxing; Lei, Yonghui; Ji, Dabin; Li, Shenshen; Shi, Jiancheng

2018-01-18

Analysis of cloud cover and its diurnal variation over the Tibetan Plateau (TP) is highly reliant on satellite data; however, the accuracy of cloud detection from both polar-orbiting and geostationary satellites over this area remains unclear. The new-generation geostationary Himawari-8 satellites provide high-resolution spatial and temporal information about clouds over the Tibetan Plateau. In this study, the cloud detection of MODIS and AHI is investigated and validated against CALIPSO measurements. For AHI and MODIS, the false alarm rate of AHI and MODIS in cloud identification over the TP was 7.51% and 1.94%, respectively, and the cloud hit rate was 73.55% and 80.15%, respectively. Using hourly cloud-cover data from the Himawari-8 satellites, we found that at the monthly scale, the diurnal cycle in cloud cover over the TP tends to increase throughout the day, with the minimum and maximum cloud fractions occurring at 10:00 a.m. and 18:00 p.m. local time. Due to the limited time resolution of polar-orbiting satellites, the underestimation of MODIS daytime average cloud cover is approximately 4.00% at the annual scale, with larger biases during the spring (5.40%) and winter (5.90%).

Effects of Varying Cloud Cover on Springtime Runoff in California's Sierra Nevada

Science.gov (United States)

Sumargo, E.; Cayan, D. R.

2017-12-01

This study investigates how cloud cover modifies snowmelt-runoff processes in Sierra Nevada watersheds during dry and wet periods. We use two of the California Department of Water Resources' (DWR's) quasi-operational models of the Tuolumne and Merced River basins developed from the USGS Precipitation-Runoff Modeling System (PRMS) hydrologic modeling system. Model simulations are conducted after a validated optimization of model performance in simulating recent (1996-2014) historical variability in the Tuolumne and Merced basins using solar radiation (Qsi) derived from Geostationary Operational Environmental Satellite (GOES) remote sensing. Specifically, the questions we address are: 1) how sensitive are snowmelt and runoff in the Tuolumne and Merced River basins to Qsi variability associated with cloud cover variations?, and 2) does this sensitivity change in dry vs. wet years? To address these question, we conduct two experiments, where: E1) theoretical clear-sky Qsi is used as an input to PRMS, and E2) the annual harmonic cycle of Qsi is used as an input to PRMS. The resulting hydrographs from these experiments exhibit changes in peak streamflow timing by several days to a few weeks and smaller streamflow variability when compared to the actual flows and the original simulations. For E1, despite some variations, this pattern persists when the result is evaluated for dry-year and wet-year subsets, reflecting the consistently higher Qsi input available. For E2, the hydrograph shows a later spring-summer streamflow peak in the dry-year subset when compared to the original simulations, indicating the relative importance of the modulating effect of cloud cover on snowmelt-runoff in drier years.

Trapping in stochastic mechanics and applications to covers of clouds and radiation belts

International Nuclear Information System (INIS)

Albeverio, S.; Blanchard, P.; Combe, P.; Rodriguez, R.; Sirugue, M.; Sirugue-Collin, M.

1984-11-01

It is possible to assign a stochastic acceleration to conservative stochastic diffusion processes. As a basic assumption, this stochastic acceleration is set equal to the deterministic smooth component of the external force acting on the particle, whereas the influences of the remainder is modelled by a diffusion coefficient. In this paper, we shall try to see whether it can account for the observation in two cases: the cover of clouds of planets and the radiation belts in the planetary magnetic field. We describe the basic properties of Newtonian Diffusion Stochastic Processes and indicate their connection with Schroedinger-like equations. Furthermore we give a heuristic interpretation of the nodal surfaces as impenetrable barriers for Newtonian Stochastic Diffusion Processes. The possible applications to the observed average cloud covering in the planetary atmosphere are presented we discuss the radiation belts (Van Allen Belts) along the previous ideas

Seasonal and interannual variations of top-of-atmosphere irradiance and cloud cover over polar regions derived from the CERES data set

Science.gov (United States)

Kato, Seiji; Loeb, Norman G.; Minnis, Patrick; Francis, Jennifer A.; Charlock, Thomas P.; Rutan, David A.; Clothiaux, Eugene E.; Sun-Mack, Szedung

2006-10-01

The daytime cloud fraction derived by the Clouds and the Earth's Radiant Energy System (CERES) cloud algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) radiances over the Arctic from March 2000 through February 2004 increases at a rate of 0.047 per decade. The trend is significant at an 80% confidence level. The corresponding top-of-atmosphere (TOA) shortwave irradiances derived from CERES radiance measurements show less significant trend during this period. These results suggest that the influence of reduced Arctic sea ice cover on TOA reflected shortwave radiation is reduced by the presence of clouds and possibly compensated by the increase in cloud cover. The cloud fraction and TOA reflected shortwave irradiance over the Antarctic show no significant trend during the same period.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

Science.gov (United States)

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Assessing the performance of aerial image point cloud and spectral metrics in predicting boreal forest canopy cover

Science.gov (United States)

Melin, M.; Korhonen, L.; Kukkonen, M.; Packalen, P.

2017-07-01

Canopy cover (CC) is a variable used to describe the status of forests and forested habitats, but also the variable used primarily to define what counts as a forest. The estimation of CC has relied heavily on remote sensing with past studies focusing on satellite imagery as well as Airborne Laser Scanning (ALS) using light detection and ranging (lidar). Of these, ALS has been proven highly accurate, because the fraction of pulses penetrating the canopy represents a direct measurement of canopy gap percentage. However, the methods of photogrammetry can be applied to produce point clouds fairly similar to airborne lidar data from aerial images. Currently there is little information about how well such point clouds measure canopy density and gaps. The aim of this study was to assess the suitability of aerial image point clouds for CC estimation and compare the results with those obtained using spectral data from aerial images and Landsat 5. First, we modeled CC for n = 1149 lidar plots using field-measured CCs and lidar data. Next, this data was split into five subsets in north-south direction (y-coordinate). Finally, four CC models (AerialSpectral, AerialPointcloud, AerialCombi (spectral + pointcloud) and Landsat) were created and they were used to predict new CC values to the lidar plots, subset by subset, using five-fold cross validation. The Landsat and AerialSpectral models performed with RMSEs of 13.8% and 12.4%, respectively. AerialPointcloud model reached an RMSE of 10.3%, which was further improved by the inclusion of spectral data; RMSE of the AerialCombi model was 9.3%. We noticed that the aerial image point clouds managed to describe only the outermost layer of the canopy and missed the details in lower canopy, which was resulted in weak characterization of the total CC variation, especially in the tails of the data.

Development of the Landsat Data Continuity Mission Cloud Cover Assessment Algorithms

Science.gov (United States)

Scaramuzza, Pat; Bouchard, M.A.; Dwyer, John L.

2012-01-01

The upcoming launch of the Operational Land Imager (OLI) will start the next era of the Landsat program. However, the Automated Cloud-Cover Assessment (CCA) (ACCA) algorithm used on Landsat 7 requires a thermal band and is thus not suited for OLI. There will be a thermal instrument on the Landsat Data Continuity Mission (LDCM)-the Thermal Infrared Sensor-which may not be available during all OLI collections. This illustrates a need for CCA for LDCM in the absence of thermal data. To research possibilities for full-resolution OLI cloud assessment, a global data set of 207 Landsat 7 scenes with manually generated cloud masks was created. It was used to evaluate the ACCA algorithm, showing that the algorithm correctly classified 79.9% of a standard test subset of 3.95 109 pixels. The data set was also used to develop and validate two successor algorithms for use with OLI data-one derived from an off-the-shelf machine learning package and one based on ACCA but enhanced by a simple neural network. These comprehensive CCA algorithms were shown to correctly classify pixels as cloudy or clear 88.5% and 89.7% of the time, respectively.

Strategies for cloud-top phase determination: differentiation between thin cirrus clouds and snow in manual (ground truth) analyses

Science.gov (United States)

Hutchison, Keith D.; Etherton, Brian J.; Topping, Phillip C.

1996-12-01

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

Relationships between lower tropospheric stability, low cloud cover, and water vapor isotopic composition in the subtropical Pacific

Science.gov (United States)

Galewsky, J.

2017-12-01

Understanding the processes that govern the relationships between lower tropospheric stability and low-cloud cover is crucial for improved constraints on low-cloud feedbacks and for improving the parameterizations of low-cloud cover used in climate models. The stable isotopic composition of atmospheric water vapor is a sensitive recorder of the balance of moistening and drying processes that set the humidity of the lower troposphere and may thus provide a useful framework for improving our understanding low-cloud processes. In-situ measurements of water vapor isotopic composition collected at the NOAA Mauna Loa Observatory in Hawaii, along with twice-daily soundings from Hilo and remote sensing of cloud cover, show a clear inverse relationship between the estimated inversion strength (EIS) and the mixing ratios and water vapor δ -values, and a positive relationship between EIS, deuterium excess, and Δ δ D, defined as the difference between an observation and a reference Rayleigh distillation curve. These relationships are consistent with reduced moistening and an enhanced upper-tropospheric contribution above the trade inversion under high EIS conditions and stronger moistening under weaker EIS conditions. The cloud fraction, cloud liquid water path, and cloud-top pressure were all found to be higher under low EIS conditions. Inverse modeling of the isotopic data for the highest and lowest terciles of EIS conditions provide quantitative constraints on the cold-point temperatures and mixing fractions that govern the humidity above the trade inversion. The modeling shows the moistening fraction between moist boundary layer air and dry middle tropospheric air 24±1.5% under low EIS conditions is and 6±1.5% under high EIS conditions. A cold-point (last-saturation) temperature of -30C can match the observations for both low and high EIS conditions. The isotopic composition of the moistening source as derived from the inversion (-114±10‰ ) requires moderate

MUSE: An Efficient and Accurate Verifiable Privacy-Preserving Multikeyword Text Search over Encrypted Cloud Data

Directory of Open Access Journals (Sweden)

Zhu Xiangyang

2017-01-01

Full Text Available With the development of cloud computing, services outsourcing in clouds has become a popular business model. However, due to the fact that data storage and computing are completely outsourced to the cloud service provider, sensitive data of data owners is exposed, which could bring serious privacy disclosure. In addition, some unexpected events, such as software bugs and hardware failure, could cause incomplete or incorrect results returned from clouds. In this paper, we propose an efficient and accurate verifiable privacy-preserving multikeyword text search over encrypted cloud data based on hierarchical agglomerative clustering, which is named MUSE. In order to improve the efficiency of text searching, we proposed a novel index structure, HAC-tree, which is based on a hierarchical agglomerative clustering method and tends to gather the high-relevance documents in clusters. Based on the HAC-tree, a noncandidate pruning depth-first search algorithm is proposed, which can filter the unqualified subtrees and thus accelerate the search process. The secure inner product algorithm is used to encrypted the HAC-tree index and the query vector. Meanwhile, a completeness verification algorithm is given to verify search results. Experiment results demonstrate that the proposed method outperforms the existing works, DMRS and MRSE-HCI, in efficiency and accuracy, respectively.

Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery

Science.gov (United States)

Helmer, E.H.; Kennaway, T.A.; Pedreros, D.H.; Clark, M.L.; Marcano-Vega, H.; Tieszen, L.L.; Ruzycki, T.R.; Schill, S.R.; Carrington, C.M.S.

2008-01-01

Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius, testing a more detailed classification than earlier work in the latter three islands. Secondly, we estimate the extents of land cover and protected forest by formation for five islands and ask how land cover has changed over the second half of the 20th century. The image interpretation approach combines image mosaics and ancillary geographic data, classifying the resulting set of raster data with decision tree software. Cloud-free image mosaics for one or two seasons were created by applying regression tree normalization to scene dates that could fill cloudy areas in a base scene. Such mosaics are also known as cloud-filled, cloud-minimized or cloud-cleared imagery, mosaics, or composites. The approach accurately distinguished several classes that more standard methods would confuse; the seamless mosaics aided reference data collection; and the multiseason imagery allowed us to separate drought deciduous forests and woodlands from semi-deciduous ones. Cultivated land areas declined 60 to 100 percent from about 1945 to 2000 on several islands. Meanwhile, forest cover has increased 50 to 950%. This trend will likely continue where sugar cane cultivation has dominated. Like the island of Puerto Rico, most higher-elevation forest formations are protected in formal or informal reserves. Also similarly, lowland forests, which are drier forest types on these islands, are not well represented in reserves. Former cultivated lands in lowland areas could provide lands for new reserves of drier forest types. The land-use history of these islands may provide insight for planners in countries currently considering

Spatial and temporal patterns of cloud cover and fog inundation in coastal California: Ecological implications

Science.gov (United States)

Rastogi, Bharat; Williams, A. Park; Fischer, Douglas T.; Iacobellis, Sam F.; McEachern, A. Kathryn; Carvalho, Leila; Jones, Charles Leslie; Baguskas, Sara A.; Still, Christopher J.

2016-01-01

The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets, and often have different spatial and temporal patterns. Here we use remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. We found marine stratus to be persistent from May through September across the years 2001-2012. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening, and dissipated by the following early afternoon. We present a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to our ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve our understanding of cloud-ecosystem interactions, species distributions and coastal ecohydrology.

Accurate mobile malware detection and classification in the cloud.

Science.gov (United States)

Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

2015-01-01

As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service.

Changes in atmospheric circulation and the Arctic Oscillation preserved within a millennial length reconstruction of summer cloud cover from northern Fennoscandia

Energy Technology Data Exchange (ETDEWEB)

Young, Giles H.F.; McCarroll, Danny; Loader, Neil J.; Gagen, Mary H.; Demmler, Joanne C. [Swansea University, Department of Geography, Swansea (United Kingdom); Kirchhefer, Andreas J. [University of Tromsoe, Department of Arctic and Marine Biology, Tromsoe (Norway); Dendrooekologen, Tromsoe (Norway)

2012-07-15

Cloud cover currently represents the single greatest source of uncertainty in General Circulation Models. Stable carbon isotope ratios ({delta}{sup 13}C) from tree-rings, in areas of low moisture stress, are likely to be primarily controlled by photosynthetically active radiation (PAR), and therefore should provide a proxy record for cloud cover or sunshine; indeed this association has previously been demonstrated experimentally for Scots pine in Fennoscandia, with sunlight explaining ca 90% of the variance in photosynthesis and temperature only ca 4%. We present a statistically verifiable 1011-year reconstruction of cloud cover from a well replicated, annually-resolved {delta}{sup 13}C record from Forfjord in coastal northwestern Norway. This reconstruction exhibits considerable variability in cloud cover over the past millennium, including extended sunny periods during the cool seventeenth and eighteenth centuries and warm cloudy periods during the eleventh, early fifteenth and twentieth centuries. We find that while a generally positive relationship persists between sunshine and temperature at high-frequency, at lower (multi-decadal) frequencies the relationship is more often a negative one, with cool periods being sunny (most notably the Little Ice Age period from 1600 to 1750 CE) and warm periods more cloudy (e.g. the mediaeval and the twentieth century). We conclude that these long-term changes may be caused by changes in the dominant circulation mode, likely to be associated with the Arctic Oscillation. There is also strong circumstantial evidence that prolonged periods of high summer cloud cover, with low PAR and probably high precipitation, may be in part responsible for major European famines caused by crop failures. (orig.)

Mapping Urban Tree Canopy Cover Using Fused Airborne LIDAR and Satellite Imagery Data

Science.gov (United States)

Parmehr, Ebadat G.; Amati, Marco; Fraser, Clive S.

2016-06-01

Urban green spaces, particularly urban trees, play a key role in enhancing the liveability of cities. The availability of accurate and up-to-date maps of tree canopy cover is important for sustainable development of urban green spaces. LiDAR point clouds are widely used for the mapping of buildings and trees, and several LiDAR point cloud classification techniques have been proposed for automatic mapping. However, the effectiveness of point cloud classification techniques for automated tree extraction from LiDAR data can be impacted to the point of failure by the complexity of tree canopy shapes in urban areas. Multispectral imagery, which provides complementary information to LiDAR data, can improve point cloud classification quality. This paper proposes a reliable method for the extraction of tree canopy cover from fused LiDAR point cloud and multispectral satellite imagery data. The proposed method initially associates each LiDAR point with spectral information from the co-registered satellite imagery data. It calculates the normalised difference vegetation index (NDVI) value for each LiDAR point and corrects tree points which have been misclassified as buildings. Then, region growing of tree points, taking the NDVI value into account, is applied. Finally, the LiDAR points classified as tree points are utilised to generate a canopy cover map. The performance of the proposed tree canopy cover mapping method is experimentally evaluated on a data set of airborne LiDAR and WorldView 2 imagery covering a suburb in Melbourne, Australia.

Trends in Upper-Level Cloud Cover and Surface Divergence Over the Tropical Indo-Pacific Ocean Between 1952 And 1997

Science.gov (United States)

Norris, Joel R.

2005-01-01

This study investigated the spatial pattern of linear trends in surface-observed upper-level (combined mid-level and High-level) cloud cover, precipitation, and surface divergence over the tropical Indo-Pacific Ocean during 1952-1957. Cloud values were obtained from the Extended Edited Cloud Report Archive (EECRA), precipitation values were obtained from the Hulme/Climate Research Unit Data Set, and surface divergence was alternatively calculated from wind reported Comprehensive Ocean-Atmosphere Data Set and from Smith and Reynolds Extended Reconstructed sea level pressure data.

An energy balance model exploration of the impacts of interactions between surface albedo, cloud cover and water vapor on polar amplification

Science.gov (United States)

Södergren, A. Helena; McDonald, Adrian J.; Bodeker, Gregory E.

2017-11-01

We examine the effects of non-linear interactions between surface albedo, water vapor and cloud cover (referred to as climate variables) on amplified warming of the polar regions, using a new energy balance model. Our simulations show that the sum of the contributions to surface temperature changes due to any variable considered in isolation is smaller than the temperature changes from coupled feedback simulations. This non-linearity is strongest when all three climate variables are allowed to interact. Surface albedo appears to be the strongest driver of this non-linear behavior, followed by water vapor and clouds. This is because increases in longwave radiation absorbed by the surface, related to increases in water vapor and clouds, and increases in surface absorbed shortwave radiation caused by a decrease in surface albedo, amplify each other. Furthermore, our results corroborate previous findings that while increases in cloud cover and water vapor, along with the greenhouse effect itself, warm the polar regions, water vapor also significantly warms equatorial regions, which reduces polar amplification. Changes in surface albedo drive large changes in absorption of incoming shortwave radiation, thereby enhancing surface warming. Unlike high latitudes, surface albedo change at low latitudes are more constrained. Interactions between surface albedo, water vapor and clouds drive larger increases in temperatures in the polar regions compared to low latitudes. This is in spite of the fact that, due to a forcing, cloud cover increases at high latitudes and decreases in low latitudes, and that water vapor significantly enhances warming at low latitudes.

The cloud-radiative processes and its modulation by sea-ice cover and stability as derived from a merged C3M Data product.

Science.gov (United States)

Nag, B.

2016-12-01

The polar regions of the world constitute an important sector in the global energy balance. Among other effects responsible for the change in the sea-ice cover like ocean circulation and ice-albedo feedback, the cloud-radiation feedback also plays a vital role in modulation of the Arctic environment. However the annual cycle of the clouds is very poorly represented in current global circulation models. This study aims to take advantage of a merged C3M data (CALIPSO, CloudSat, CERES, and MODIS) product from the NASA's A-Train Series to explore the sea-ice and atmospheric conditions in the Arctic on a spatial coverage spanning 70N to 80N. This study is aimed at the interactions or the feedbacks processes among sea-ice, clouds and the atmosphere. Using a composite approach based on a classification due to surface type, it is found that limitation of the water vapour influx from the surface due to change in phase at the surface featuring open oceans or marginal sea-ice cover to complete sea-ice cover is a major determinant in the modulation of the atmospheric moisture and its impacts. The impact of the cloud-radiative effects in the Arctic is found to vary with sea-ice cover and seasonally. The effect of the marginal sea-ice cover becomes more and more pronounced in the winter. The seasonal variation of the dependence of the atmospheric moisture on the surface and the subsequent feedback effects is controlled by the atmospheric stability measured as a difference between the potential temperature at the surface and the 700hPa level. It is found that a stronger stability cover in the winter is responsible for the longwave cloud radiative feedback in winter which is missing during the summer. A regional analysis of the same suggests that most of the depiction of the variations observed is contributed from the North Atlantic region.

Global Distribution and Vertical Structure of Clouds Revealed by CALIPSO

Science.gov (United States)

Yi, Y.; Minnis, P.; Winker, D.; Huang, J.; Sun-Mack, S.; Ayers, K.

2007-12-01

Understanding the effects of clouds on Earth's radiation balance, especially on longwave fluxes within the atmosphere, depends on having accurate knowledge of cloud vertical location within the atmosphere. The Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite mission provides the opportunity to measure the vertical distribution of clouds at a greater detail than ever before possible. The CALIPSO cloud layer products from June 2006 to June 2007 are analyzed to determine the occurrence frequency and thickness of clouds as functions of time, latitude, and altitude. In particular, the latitude-longitude and vertical distributions of single- and multi-layer clouds and the latitudinal movement of cloud cover with the changing seasons are examined. The seasonal variablities of cloud frequency and geometric thickness are also analyzed and compared with similar quantities derived from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) using the Clouds and the Earth's Radiant Energy System (CERES) cloud retrieval algorithms. The comparisons provide an estimate of the errors in cloud fraction, top height, and thickness incurred by passive algorithms.

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

Science.gov (United States)

Logan, T. L.; Huning, J. R.; Glackin, D. L.

1983-01-01

The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

Cloud detection algorithm comparison and validation for operational Landsat data products

Science.gov (United States)

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Cover Layer (CCL) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality Environmental Data Record (EDR) of Cloud Cover Layers (CCL) from the Visible Infrared Imaging Radiometer Suite (VIIRS)...

Effects of an assumed cosmic ray-modulated low global cloud cover on the Earth's temperature

Energy Technology Data Exchange (ETDEWEB)

Ramirez, J.; Mendoza, B. [Instituto de Geofisica, Universidad Nacional Autonoma de Mexico, Mexico, D.F. (Mexico); Mendoza, V.; Adem, J. [Centro de Ciencias de la Atmosfera, Universidad Nacional Autonoma de Mexico, Mexico, D.F. (Mexico)]. E-mail: victor@atmosfera.unam.mx

2006-07-15

We have used the Thermodynamic Model of the Climate to estimate the effect of variations in the low cloud cover on the surface temperature of the Earth in the Northern Hemisphere during the period 1984-1994. We assume that the variations in the low cloud cover are proportional to the variation of the cosmic ray flux measured during the same period. The results indicate that the effect in the surface temperature is more significant in the continents, where for July of 1991, we have found anomalies of the order of 0.7 degrees Celsius for the southeastern of Asia and 0.5 degrees Celsius for the northeast of Mexico. For an increase of 0.75% in the low cloud cover, the surface temperature computed by the model in the North Hemisphere presents a decrease of {approx} 0.11 degrees Celsius; however, for a decrease of 0.90% in the low cloud cover, the model gives an increase in the surface temperature of {approx} 0.15 degrees Celsius, these two cases correspond to a climate sensitivity factor for the case of forcing by duplication of atmospheric CO{sub 2}. These decreases or increases in surface temperature by increases of decreases in low clouds cover are ten times greater than the overall variability of the non-forced model time series. [Spanish] Hemos usado el Modelo Termodinamico del Clima para estimar el efecto de variaciones en la cubierta de nubes bajas sobre la temperatura superficial de la Tierra en el Hemisferio Norte durante el periodo 1984 - 1994. Suponemos que las variaciones en la cubierta de nubes bajas son proporcionales a las variaciones del flujo de rayos cosmicos medido durante el mismo periodo. Los resultados indican que el efecto en la temperatura es mas significativo en los continentes, donde para julio de 1991, hemos encontrado anomalias del orden de 0.7 grados Celsius sobre el sureste de Asia y 0.5 grados Celsius al noreste de Mexico. Para un incremento de 0.75% en la cubierta de nubes bajas, la temperatura de la superficie calculada por el modelo en

A Study of the Role of Clouds in the Relationship Between Land Use/Land Cover and the Climate and Air Quality of the Atlanta Area

Science.gov (United States)

Kidder, Stanley Q.; Hafner, Jan

2001-01-01

The goal of Project ATLANTA is to derive a better scientific understanding of how land cover changes associated with urbanization affect climate and air quality. In this project the role that clouds play in this relationship was studied. Through GOES satellite observations and RAMS modeling of the Atlanta area, we found that in Atlanta (1) clouds are more frequent than in the surrounding rural areas; (2) clouds cool the surface by shading and thus tend to counteract the warming effect of urbanization; (3) clouds reflect sunlight, which might other wise be used to produce ozone; and (4) clouds decrease biogenic emission of ozone precursors, and they probably decrease ozone concentration. We also found that mesoscale modeling of clouds, especially of small, summertime clouds, needs to be improved and that coupled mesoscale and air quality models are needed to completely understand the mediating role that clouds play in the relationship between land use/land cover change and the climate and air quality of Atlanta. It is strongly recommended that more cities be studied to strengthen and extend these results.

A study on the relationship between incoming solar UV radiation and cloud cover

International Nuclear Information System (INIS)

Daoo, V.J.

1992-01-01

In this study an empirical relationship between the incoming solar UV radiation and concurrently measured cloud cover at Bombay (19 o 01'N, 72 o 55'E), based on data pertaining to two year (1986-1987) period is established. It is compared with a similar relationship used elsewhere and found to differ in its form as well as in the regression coefficients. Possible reasons for this discrepancy are discussed. Conditions under which the two relationships agree are also examined. (author)

Cloud Cover Assessment for Operational Crop Monitoring Systems in Tropical Areas

Directory of Open Access Journals (Sweden)

Isaque Daniel Rocha Eberhardt

2016-03-01

Full Text Available The potential of optical remote sensing data to identify, map and monitor croplands is well recognized. However, clouds strongly limit the usefulness of optical imagery for these applications. This paper aims at assessing cloud cover conditions over four states in the tropical and sub-tropical Center-South region of Brazil to guide the development of an appropriate agricultural monitoring system based on Landsat-like imagery. Cloudiness was assessed during overlapping four months periods to match the typical length of crop cycles in the study area. The percentage of clear sky occurrence was computed from the 1 km resolution MODIS Cloud Mask product (MOD35 considering 14 years of data between July 2000 and June 2014. Results showed high seasonality of cloud occurrence within the crop year with strong variations across the study area. The maximum seasonality was observed for the two states in the northern part of the study area (i.e., the ones closer to the Equator line, which also presented the lowest averaged values (15% of clear sky occurrence during the main (summer cropping period (November to February. In these locations, optical data faces severe constraints for mapping summer crops. On the other hand, relatively favorable conditions were found in the southern part of the study region. In the South, clear sky values of around 45% were found and no significant clear sky seasonality was observed. Results underpin the challenges to implement an operational crop monitoring system based solely on optical remote sensing imagery in tropical and sub-tropical regions, in particular if short-cycle crops have to be monitored during the cloudy summer months. To cope with cloudiness issues, we recommend the use of new systems with higher repetition rates such as Sentinel-2. For local studies, Unmanned Aircraft Vehicles (UAVs might be used to augment the observing capability. Multi-sensor approaches combining optical and microwave data can be another

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

Science.gov (United States)

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.

Cloud-Top Entrainment in Stratocumulus Clouds

Science.gov (United States)

Mellado, Juan Pedro

2017-01-01

Cloud entrainment, the mixing between cloudy and clear air at the boundary of clouds, constitutes one paradigm for the relevance of small scales in the Earth system: By regulating cloud lifetimes, meter- and submeter-scale processes at cloud boundaries can influence planetary-scale properties. Understanding cloud entrainment is difficult given the complexity and diversity of the associated phenomena, which include turbulence entrainment within a stratified medium, convective instabilities driven by radiative and evaporative cooling, shear instabilities, and cloud microphysics. Obtaining accurate data at the required small scales is also challenging, for both simulations and measurements. During the past few decades, however, high-resolution simulations and measurements have greatly advanced our understanding of the main mechanisms controlling cloud entrainment. This article reviews some of these advances, focusing on stratocumulus clouds, and indicates remaining challenges.

Physically-Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

Science.gov (United States)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Mango, Stephen A.; Huang, Hung-Lung

2007-01-01

A physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). NPOESS Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the Atlantic-THORPEX Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and the Hyperspectral Environmental Suite (HES). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on Polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project and the following NPOESS series of satellites.

Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks

Science.gov (United States)

Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.

2017-12-01

Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.

A comparison of ground and satellite observations of cloud cover to saturation pressure differences during a cold air outbreak

Energy Technology Data Exchange (ETDEWEB)

Alliss, R.J.; Raman, S. [North Carolina State Univ., Raleigh, NC (United States)

1996-04-01

The role of clouds in the atmospheric general circulation and the global climate is twofold. First, clouds owe their origin to large-scale dynamical forcing, radiative cooling in the atmosphere, and turbulent transfer at the surface. In addition, they provide one of the most important mechanisms for the vertical redistribution of momentum and sensible and latent heat for the large scale, and they influence the coupling between the atmosphere and the surface as well as the radiative and dynamical-hydrological balance. In existing diagnostic cloudiness parameterization schemes, relative humidity is the most frequently used variable for estimating total cloud amount or stratiform cloud amount. However, the prediction of relative humidity in general circulation models (GCMs) is usually poor. Even for the most comprehensive GCMs, the predicted relative humidity may deviate greatly from that observed, as far as the frequency distribution of relative humidity is concerned. Recently, there has been an increased effort to improve the representation of clouds and cloud-radiation feedback in GCMs, but the verification of cloudiness parameterization schemes remains a severe problem because of the lack of observational data sets. In this study, saturation pressure differences (as opposed to relative humidity) and satellite-derived cloud heights and amounts are compared with ground determinations of cloud cover over the Gulf Stream Locale (GSL) during a cold air outbreak.

VMware private cloud computing with vCloud director

CERN Document Server

Gallagher, Simon

2013-01-01

It's All About Delivering Service with vCloud Director Empowered by virtualization, companies are not just moving into the cloud, they're moving into private clouds for greater security, flexibility, and cost savings. However, this move involves more than just infrastructure. It also represents a different business model and a new way to provide services. In this detailed book, VMware vExpert Simon Gallagher makes sense of private cloud computing for IT administrators. From basic cloud theory and strategies for adoption to practical implementation, he covers all the issues. You'll lea

Comparative analysis of cloud cover databases for CORDEX-AFRICA

Science.gov (United States)

Enríquez, A.; Taima-Hernández, D.; González, A.; Pérez, J. C.; Díaz, J. P.; Expósito, F. J.

2012-04-01

The main objective of the CORDEX program (COordinated Regional climate Downscaling Experiment) [1] is the production of regional climate change scenarios at a global scale, creating a contribution to the IPCC (Intergovernmental Panel on Climate Change) AR5 (5th Assessment Report). Inside this project, Africa is the key region due to the lack of data at this moment. In this study, the cloud cover information obtained through five well-known databases: ERA-40, ERA-Interim, ISCCP, NCEP and CRU, over the CORDEX-AFRICA domain, is analyzed for the period 1984-2000, in order to determine the similarity between them.To analyze the accuracy and consistency of the climate databases, some statistical techniques such as correlation coefficient (r), root mean square (RMS) differences and a defined skill score (SS), based on the difference between areas of the probability density functions (PDFs) associated to study parameters [2], were applied. Thus which databases are well-related in different regions and which not are determined, establishing an appropriate framework which could be used to validate the AR5 models in historical simulations.

Simultaneous colour visualizations of multiple ALS point cloud attributes for land cover and vegetation analysis

Science.gov (United States)

Zlinszky, András; Schroiff, Anke; Otepka, Johannes; Mandlburger, Gottfried; Pfeifer, Norbert

2014-05-01

LIDAR point clouds hold valuable information for land cover and vegetation analysis, not only in the spatial distribution of the points but also in their various attributes. However, LIDAR point clouds are rarely used for visual interpretation, since for most users, the point cloud is difficult to interpret compared to passive optical imagery. Meanwhile, point cloud viewing software is available allowing interactive 3D interpretation, but typically only one attribute at a time. This results in a large number of points with the same colour, crowding the scene and often obscuring detail. We developed a scheme for mapping information from multiple LIDAR point attributes to the Red, Green, and Blue channels of a widely used LIDAR data format, which are otherwise mostly used to add information from imagery to create "photorealistic" point clouds. The possible combinations of parameters are therefore represented in a wide range of colours, but relative differences in individual parameter values of points can be well understood. The visualization was implemented in OPALS software, using a simple and robust batch script, and is viewer independent since the information is stored in the point cloud data file itself. In our case, the following colour channel assignment delivered best results: Echo amplitude in the Red, echo width in the Green and normalized height above a Digital Terrain Model in the Blue channel. With correct parameter scaling (but completely without point classification), points belonging to asphalt and bare soil are dark red, low grassland and crop vegetation are bright red to yellow, shrubs and low trees are green and high trees are blue. Depending on roof material and DTM quality, buildings are shown from red through purple to dark blue. Erroneously high or low points, or points with incorrect amplitude or echo width usually have colours contrasting from terrain or vegetation. This allows efficient visual interpretation of the point cloud in planar

Considerations for Cloud Security Operations

OpenAIRE

Cusick, James

2016-01-01

Information Security in Cloud Computing environments is explored. Cloud Computing is presented, security needs are discussed, and mitigation approaches are listed. Topics covered include Information Security, Cloud Computing, Private Cloud, Public Cloud, SaaS, PaaS, IaaS, ISO 27001, OWASP, Secure SDLC.

Remote Sensing of Cloud Top Heights Using the Research Scanning Polarimeter

Science.gov (United States)

Sinclair, Kenneth; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej

2015-01-01

Clouds cover roughly two thirds of the globe and act as an important regulator of Earth's radiation budget. Of these, multilayered clouds occur about half of the time and are predominantly two-layered. Changes in cloud top height (CTH) have been predicted by models to have a globally averaged positive feedback, however observational changes in CTH have shown uncertain results. Additional CTH observations are necessary to better and quantify the effect. Improved CTH observations will also allow for improved sub-grid parameterizations in large-scale models and accurate CTH information is important when studying variations in freezing point and cloud microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. RSP scans along the aircraft track and obtains measurements at 152 viewing angles at any aircraft location. The approach presented here aggregates measurements from multiple scans to a single location at cloud altitude using a correlation function designed to identify the location-distinct features in each scan. During NASAs SEAC4RS air campaign, the RSP was mounted on the ER-2 aircraft along with the Cloud Physics Lidar (CPL), which made simultaneous measurements of CTH. The RSPs unique method of determining CTH is presented. The capabilities of using single and combinations of channels within the approach are investigated. A detailed comparison of RSP retrieved CTHs with those of CPL reveal the accuracy of the approach. Results indicate a strong ability for the RSP to accurately identify cloud heights. Interestingly, the analysis reveals an ability for the approach to identify multiple cloud layers in a single scene and estimate the CTH of each layer. Capabilities and limitations of identifying single and multiple cloud layers heights are explored. Special focus is given to sources of error in the method including optically thin clouds, physically thick clouds, multi

Encyclopedia of cloud computing

CERN Document Server

Bojanova, Irena

2016-01-01

The Encyclopedia of Cloud Computing provides IT professionals, educators, researchers and students with a compendium of cloud computing knowledge. Authored by a spectrum of subject matter experts in industry and academia, this unique publication, in a single volume, covers a wide range of cloud computing topics, including technological trends and developments, research opportunities, best practices, standards, and cloud adoption. Providing multiple perspectives, it also addresses questions that stakeholders might have in the context of development, operation, management, and use of clouds. Furthermore, it examines cloud computing's impact now and in the future. The encyclopedia presents 56 chapters logically organized into 10 sections. Each chapter covers a major topic/area with cross-references to other chapters and contains tables, illustrations, side-bars as appropriate. Furthermore, each chapter presents its summary at the beginning and backend material, references and additional resources for further i...

The CLOUD experiment

CERN Multimedia

Maximilien Brice

2006-01-01

The Cosmics Leaving Outdoor Droplets (CLOUD) experiment as shown by Jasper Kirkby (spokesperson). Kirkby shows a sketch to illustrate the possible link between galactic cosmic rays and cloud formations. The CLOUD experiment uses beams from the PS accelerator at CERN to simulate the effect of cosmic rays on cloud formations in the Earth's atmosphere. It is thought that cosmic ray intensity is linked to the amount of low cloud cover due to the formation of aerosols, which induce condensation.

Raster Vs. Point Cloud LiDAR Data Classification

Science.gov (United States)

El-Ashmawy, N.; Shaker, A.

2014-09-01

Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the

Clouds and the Near-Earth Environment: Possible Links

Directory of Open Access Journals (Sweden)

Condurache-Bota Simona

2015-12-01

Full Text Available Climate variability is a hot topic not only for scientists and policy-makers, but also for each and every one of us. The anthropogenic activities are considered to be responsible for most climate change, however there are large uncertainties about the magnitude of effects of solar variability and other extraterrestrial influences, such as galactic cosmic rays on terrestrial climate. Clouds play an important role due to feedbacks of the radiation budget: variation of cloud cover/composition affects climate, which, in turn, affects cloud cover via atmospheric dynamics and sea temperature variations. Cloud formation and evolution are still under scientific scrutiny, since their microphysics is still not understood. Besides atmospheric dynamics and other internal climatic parameters, extraterrestrial sources of cloud cover variation are considered. One of these is the solar wind, whose effect on cloud cover might be modulated by the global atmospheric electrical circuit. Clouds height and composition, their seasonal variation and latitudinal distribution should be considered when trying to identify possible mechanisms by which solar energy is transferred to clouds. The influence of the solar wind on cloud formation can be assessed also through the ap index - the geomagnetic storm index, which can be readily connected with interplanetary magnetic field, IMF structure. This paper proposes to assess the possible relationship between both cloud cover and solar wind proxies, as the ap index, function of cloud height and composition and also through seasonal studies. The data covers almost three solar cycles (1984-2009. Mechanisms are looked for by investigating observed trends or correlation at local/seasonal scale

Accurate single-scattering simulation of ice cloud using the invariant-imbedding T-matrix method and the physical-geometric optics method

Science.gov (United States)

Sun, B.; Yang, P.; Kattawar, G. W.; Zhang, X.

2017-12-01

The ice cloud single-scattering properties can be accurately simulated using the invariant-imbedding T-matrix method (IITM) and the physical-geometric optics method (PGOM). The IITM has been parallelized using the Message Passing Interface (MPI) method to remove the memory limitation so that the IITM can be used to obtain the single-scattering properties of ice clouds for sizes in the geometric optics regime. Furthermore, the results associated with random orientations can be analytically achieved once the T-matrix is given. The PGOM is also parallelized in conjunction with random orientations. The single-scattering properties of a hexagonal prism with height 400 (in units of lambda/2*pi, where lambda is the incident wavelength) and an aspect ratio of 1 (defined as the height over two times of bottom side length) are given by using the parallelized IITM and compared to the counterparts using the parallelized PGOM. The two results are in close agreement. Furthermore, the integrated single-scattering properties, including the asymmetry factor, the extinction cross-section, and the scattering cross-section, are given in a completed size range. The present results show a smooth transition from the exact IITM solution to the approximate PGOM result. Because the calculation of the IITM method has reached the geometric regime, the IITM and the PGOM can be efficiently employed to accurately compute the single-scattering properties of ice cloud in a wide spectral range.

A Study on the Motif Pattern of Dark-Cloud Cover in the Securities

Directory of Open Access Journals (Sweden)

Long Jing

2017-01-01

Full Text Available Morphological analysis is the analysis and mining of the graphics formed of the securities price changes. Investors need to forecast the trend of future before buying and selling points, which can avoid great loss. Therefore, the analysis of motif pattern of K-line in the form of futures investment technology analysis is very significant. Based on the thoughts of short-term trend clustering, this paper proposes a method of detecting the motif pattern of Dark-Cloud Cover in stock time series by analysing stock historic data and K-line shape, in order to predict the stock market trends. And we prove the effectiveness and practicality of the method by a series of experimental analysis.

Monitoring Areal Snow Cover Using NASA Satellite Imagery

Science.gov (United States)

Harshburger, Brian J.; Blandford, Troy; Moore, Brandon

2011-01-01

The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data

On the existence of tropical anvil clouds

Science.gov (United States)

Seeley, J.; Jeevanjee, N.; Langhans, W.; Romps, D.

2017-12-01

In the deep tropics, extensive anvil clouds produce a peak in cloud cover below the tropopause. The dominant paradigm for cloud cover attributes this anvil peak to a layer of enhanced mass convergence in the clear-sky upper-troposphere, which is presumed to force frequent detrainment of convective anvils. However, cloud cover also depends on the lifetime of cloudy air after it detrains, which raises the possibility that anvil clouds may be the signature of slow cloud decay rather than enhanced detrainment. Here we measure the cloud decay timescale in cloud-resolving simulations, and find that cloudy updrafts that detrain in the upper troposphere take much longer to dissipate than their shallower counterparts. We show that cloud lifetimes are long in the upper troposphere because the saturation specific humidity becomes orders of magnitude smaller than the typical condensed water loading of cloudy updrafts. This causes evaporative cloud decay to act extremely slowly, thereby prolonging cloud lifetimes in the upper troposphere. As a consequence, extensive anvil clouds still occur in a convecting atmosphere that is forced to have no preferential clear-sky convergence layer. On the other hand, when cloud lifetimes are fixed at a characteristic lower-tropospheric value, extensive anvil clouds do not form. Our results support a revised understanding of tropical anvil clouds, which attributes their existence to the microphysics of slow cloud decay rather than a peak in clear-sky convergence.

Electronic measurement equipment for determining the cloud cover of the sky. Elektronisches Messgeraet zur Bestimmung des Bedeckungsgrades des Himmels

Energy Technology Data Exchange (ETDEWEB)

Siebrasse, R

1990-01-18

The invention is used for the automatic determination of the degree of cloud cover of the sky. Compared to the state of the art, the invention has the advantage that it manages without mechanical controls, like those of 'sky scanners' for example, and that the measuring head has a very simple, cheap and robust construction. In order to do without any mechanics, a group of 24 photo-transistors of type BPX 43 was mounted on a hemispherical support, which screens the individual elements from one another, so that a certain section of the sky is allocated to each transistor. The optical axes of the individual axes are distributed completely evenly, so that there is an even and beam-shaped alignment to the sky above the measurement head. The individual measurements of the 24 transistors together give a certain optical impression, a 'picture' or a brightness distribution of the sky hemisphere, which can be read by a suitable program via a normal commercial adaptor into a personal computer, where this distribution is compared with given distributions which have degrees of cover of 0-8 or 0-10 as heading. The given 'picture' which comes closest to the current distribution is ejected as the result, and the heading of this picture gives the current degree of cloud cover.

Hybrid cloud for dummies

CERN Document Server

Hurwitz, Judith; Halper, Fern; Kirsch, Dan

2012-01-01

Understand the cloud and implement a cloud strategy for your business Cloud computing enables companies to save money by leasing storage space and accessing technology services through the Internet instead of buying and maintaining equipment and support services. Because it has its own unique set of challenges, cloud computing requires careful explanation. This easy-to-follow guide shows IT managers and support staff just what cloud computing is, how to deliver and manage cloud computing services, how to choose a service provider, and how to go about implementation. It also covers security and

Separating Real and Apparent Effects of Cloud, Humidity, and Dynamics on Aerosol Optical Thickness near Cloud Edges

Science.gov (United States)

Jeong, Myeong-Jae; Li, Zhanqing

2010-01-01

Aerosol optical thickness (AOT) is one of aerosol parameters that can be measured on a routine basis with reasonable accuracy from Sun-photometric observations at the surface. However, AOT-derived near clouds is fraught with various real effects and artifacts, posing a big challenge for studying aerosol and cloud interactions. Recently, several studies have reported correlations between AOT and cloud cover, pointing to potential cloud contamination and the aerosol humidification effect; however, not many quantitative assessments have been made. In this study, various potential causes of apparent correlations are investigated in order to separate the real effects from the artifacts, using well-maintained observations from the Aerosol Robotic Network, Total Sky Imager, airborne nephelometer, etc., over the Southern Great Plains site operated by the U.S. Department of Energy's Atmospheric Radiation Measurement Program. It was found that aerosol humidification effects can explain about one fourth of the correlation between the cloud cover and AOT. New particle genesis, cloud-processed particles, atmospheric dynamics, and aerosol indirect effects are likely to be contributing to as much as the remaining three fourth of the relationship between cloud cover and AOT.

Tracking Land Use/Land Cover Dynamics in Cloud Prone Areas Using Moderate Resolution Satellite Data: A Case Study in Central Africa

Directory of Open Access Journals (Sweden)

Bikash Basnet

2015-05-01

Full Text Available Tracking land surface dynamics over cloud prone areas with complex mountainous terrain is an important challenge facing the Earth Science community. One such region is the Lake Kivu region in Central Africa. We developed a processing chain to systematically monitor the spatio-temporal land use/land cover dynamics of this region over the years 1988, 2001, and 2011 using Landsat data, complemented by ancillary data. Topographic compensation was performed on Landsat reflectances to avoid the strong illumination angle impacts and image compositing was used to compensate for frequent cloud cover and thus incomplete annual data availability in the archive. A systematic supervised classification was applied to the composite Landsat imagery to obtain land cover thematic maps with overall accuracies of 90% and higher. Subsequent change analysis between these years found extensive conversions of the natural environment as a result of human related activities. The gross forest cover loss for 1988–2001 and 2001–2011 period was 216.4 and 130.5 thousand hectares, respectively, signifying significant deforestation in the period of civil war and a relatively stable and lower deforestation rate later, possibly due to conservation and reforestation efforts in the region. The other dominant land cover changes in the region were aggressive subsistence farming and urban expansion displacing natural vegetation and arable lands. Despite limited data availability, this study fills the gap of much needed detailed and updated land cover change information for this biologically important region of Central Africa. These multi-temporal datasets will be a valuable baseline for land use managers in the region interested in developing ecologically sustainable land management strategies and measuring the impacts of biodiversity conservation efforts.

Cloud vertical profiles derived from CALIPSO and CloudSat and a comparison with MODIS derived clouds

Science.gov (United States)

Kato, S.; Sun-Mack, S.; Miller, W. F.; Rose, F. G.; Minnis, P.; Wielicki, B. A.; Winker, D. M.; Stephens, G. L.; Charlock, T. P.; Collins, W. D.; Loeb, N. G.; Stackhouse, P. W.; Xu, K.

2008-05-01

CALIPSO and CloudSat from the a-train provide detailed information of vertical distribution of clouds and aerosols. The vertical distribution of cloud occurrence is derived from one month of CALIPSO and CloudSat data as a part of the effort of merging CALIPSO, CloudSat and MODIS with CERES data. This newly derived cloud profile is compared with the distribution of cloud top height derived from MODIS on Aqua from cloud algorithms used in the CERES project. The cloud base from MODIS is also estimated using an empirical formula based on the cloud top height and optical thickness, which is used in CERES processes. While MODIS detects mid and low level clouds over the Arctic in April fairly well when they are the topmost cloud layer, it underestimates high- level clouds. In addition, because the CERES-MODIS cloud algorithm is not able to detect multi-layer clouds and the empirical formula significantly underestimates the depth of high clouds, the occurrence of mid and low-level clouds is underestimated. This comparison does not consider sensitivity difference to thin clouds but we will impose an optical thickness threshold to CALIPSO derived clouds for a further comparison. The effect of such differences in the cloud profile to flux computations will also be discussed. In addition, the effect of cloud cover to the top-of-atmosphere flux over the Arctic using CERES SSF and FLASHFLUX products will be discussed.

Sensor Data Fusion for Accurate Cloud Presence Prediction Using Dempster-Shafer Evidence Theory

Directory of Open Access Journals (Sweden)

Jesse S. Jin

2010-10-01

Full Text Available Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent.

Quantifying Structural and Compositional Changes in Forest Cover in NW Yunnan, China

Science.gov (United States)

Hakkenberg, C.

2012-12-01

NW Yunnan, China is a region renowned for high levels of biodiversity, endemism and genetically distinct refugial plant populations. It is also a focal area for China's national reforestation efforts like the Natural Forest Protection Program (NFPP), intended to control erosion in the Upper Yangtze watershed. As part of a larger project to investigate the role of reforestation programs in facilitating the emergence of increasingly species-rich forest communities on a previously degraded and depauperate land mosaic in montane SW China, this study uses a series of Landsat TM images to quantify the spatial pattern and rate of structural and compositional change in forests recovering from medium to large-scale disturbances in the area over the past 25 years. Beyond the fundamental need to assess the outcomes of one of the world's largest reforestation programs, this research offers approaches to confronting two critical methodological issues: (1) techniques for characterizing subtle changes in the nature of vegetation cover, and (2) reducing change detection uncertainty due to persistent cloud cover and shadow. To address difficulties in accurately assessing the structure and composition of vegetative regrowth, a biophysical model was parameterized with over 300 ground-truthed canopy cover assessment points to determine pattern and rate of long-term vegetation changes. To combat pervasive shadow and cloud cover, an interactive generalized additive model (GAM) model based on topographic and spatial predictors was used to overcome some of the constraints of satellite image analysis in Himalayan regions characterized by extreme topography and extensive cloud cover during the summer monsoon. The change detection is assessed for accuracy using ground-truthed observations in a variety of forest cover types and topographic positions. Results indicate effectiveness in reducing the areal extent of unclassified regions and increasing total change detection accuracy. In addition

Deriving Snow Cover Metrics for Alaska from MODIS

Directory of Open Access Journals (Sweden)

Chuck Lindsay

2015-09-01

Full Text Available Moderate Resolution Imaging Spectroradiometer (MODIS daily snow cover products provide an opportunity for determining snow onset and melt dates across broad geographic regions; however, cloud cover and polar darkness are limiting factors at higher latitudes. This study presents snow onset and melt dates for Alaska, portions of western Canada and the Russian Far East derived from Terra MODIS snow cover daily 500 m grid data (MOD10A1 and evaluates our method for filling data gaps caused by clouds or polar darkness. Pixels classified as cloud or no data were reclassified by: spatial filtering using neighboring pixel values; temporal filtering using pixel values for days before/after cloud cover; and snow-cycle filtering based on a time series assessment of a pixel’s position within snow accumulation, cover or melt periods. During the 2012 snow year, these gap-filling methods reduced cloud pixels from 27.7% to 3.1%. A total of 12 metrics (e.g., date of first and last snow, date of persistent snow cover and periods of intermittence for each pixel were calculated by snow year. A comparison of MODIS-derived snow onset and melt dates with in situ observations from 244 weather stations generally showed an early bias in MODIS-derived dates and an effect of increasing cloudiness exacerbating bias. Our results show that mean regional duration of seasonal snow cover is 179–311 days/year and that snow cover is often intermittent, with 41% of the area experiencing ≥2 snow-covered periods during a snow season. Other regional-scale patterns in the timing of snow onset and melt are evident in the yearly 500 m gridded products publically available at http://static.gina.alaska.edu/NPS_products/MODIS_snow/.

Characterization of Cloud Water-Content Distribution

Science.gov (United States)

Lee, Seungwon

2010-01-01

The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.

A new NDVI measure that overcomes data sparsity in cloud-covered regions predicts annual variation in ground-based estimates of high arctic plant productivity

Science.gov (United States)

Rune Karlsen, Stein; Anderson, Helen B.; van der Wal, René; Bremset Hansen, Brage

2018-02-01

Efforts to estimate plant productivity using satellite data can be frustrated by the presence of cloud cover. We developed a new method to overcome this problem, focussing on the high-arctic archipelago of Svalbard where extensive cloud cover during the growing season can prevent plant productivity from being estimated over large areas. We used a field-based time-series (2000-2009) of live aboveground vascular plant biomass data and a recently processed cloud-free MODIS-Normalised Difference Vegetation Index (NDVI) data set (2000-2014) to estimate, on a pixel-by-pixel basis, the onset of plant growth. We then summed NDVI values from onset of spring to the average time of peak NDVI to give an estimate of annual plant productivity. This remotely sensed productivity measure was then compared, at two different spatial scales, with the peak plant biomass field data. At both the local scale, surrounding the field data site, and the larger regional scale, our NDVI measure was found to predict plant biomass (adjusted R 2 = 0.51 and 0.44, respectively). The commonly used ‘maximum NDVI’ plant productivity index showed no relationship with plant biomass, likely due to some years having very few cloud-free images available during the peak plant growing season. Thus, we propose this new summed NDVI from onset of spring to time of peak NDVI as a proxy of large-scale plant productivity for regions such as the Arctic where climatic conditions restrict the availability of cloud-free images.

Quantitative Measures of Immersion in Cloud and the Biogeography of Cloud Forests

Science.gov (United States)

Lawton, R. O.; Nair, U. S.; Ray, D.; Regmi, A.; Pounds, J. A.; Welch, R. M.

2010-01-01

Sites described as tropical montane cloud forests differ greatly, in part because observers tend to differ in their opinion as to what constitutes frequent and prolonged immersion in cloud. This definitional difficulty interferes with hydrologic analyses, assessments of environmental impacts on ecosystems, and biogeographical analyses of cloud forest communities and species. Quantitative measurements of cloud immersion can be obtained on site, but the observations are necessarily spatially limited, although well-placed observers can examine 10 50 km of a mountain range under rainless conditions. Regional analyses, however, require observations at a broader scale. This chapter discusses remote sensing and modeling approaches that can provide quantitative measures of the spatiotemporal patterns of cloud cover and cloud immersion in tropical mountain ranges. These approaches integrate remote sensing tools of various spatial resolutions and frequencies of observation, digital elevation models, regional atmospheric models, and ground-based observations to provide measures of cloud cover, cloud base height, and the intersection of cloud and terrain. This combined approach was applied to the Monteverde region of northern Costa Rica to illustrate how the proportion of time the forest is immersed in cloud may vary spatially and temporally. The observed spatial variation was largely due to patterns of airflow over the mountains. The temporal variation reflected the diurnal rise and fall of the orographic cloud base, which was influenced in turn by synoptic weather conditions, the seasonal movement of the Intertropical Convergence Zone and the north-easterly trade winds. Knowledge of the proportion of the time that sites are immersed in clouds should facilitate ecological comparisons and biogeographical analyses, as well as land use planning and hydrologic assessments in areas where intensive on-site work is not feasible.

Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

Science.gov (United States)

Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

2016-10-01

Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

Cloud computing basics

CERN Document Server

Srinivasan, S

2014-01-01

Cloud Computing Basics covers the main aspects of this fast moving technology so that both practitioners and students will be able to understand cloud computing. The author highlights the key aspects of this technology that a potential user might want to investigate before deciding to adopt this service. This book explains how cloud services can be used to augment existing services such as storage, backup and recovery. Addressing the details on how cloud security works and what the users must be prepared for when they move their data to the cloud. Also this book discusses how businesses could prepare for compliance with the laws as well as industry standards such as the Payment Card Industry.

Analysis On Land Cover In Municipality Of Malang With Landsat 8 Image Through Unsupervised Classification

Science.gov (United States)

Nahari, R. V.; Alfita, R.

2018-01-01

Remote sensing technology has been widely used in the geographic information system in order to obtain data more quickly, accurately and affordably. One of the advantages of using remote sensing imagery (satellite imagery) is to analyze land cover and land use. Satellite image data used in this study were images from the Landsat 8 satellite combined with the data from the Municipality of Malang government. The satellite image was taken in July 2016. Furthermore, the method used in this study was unsupervised classification. Based on the analysis towards the satellite images and field observations, 29% of the land in the Municipality of Malang was plantation, 22% of the area was rice field, 12% was residential area, 10% was land with shrubs, and the remaining 2% was water (lake/reservoir). The shortcoming of the methods was 25% of the land in the area was unidentified because it was covered by cloud. It is expected that future researchers involve cloud removal processing to minimize unidentified area.

Cloud essentials CompTIA authorized courseware for exam CLO-001

CERN Document Server

Hausman, Kirk; Sampaio, Telmo

2013-01-01

CompTIA-Authorized courseware for the Cloud Essentials Exam (CLO-001) What better way to get up to speed on cloud computing than with this new book in the popular Sybex Essentials series? Cloud Essentials covers the basics of cloud computing and its place in the modern enterprise. Explore public and private clouds; contrast the ""as a service"" models for PaaS, SaaS, IaaS, or XaaS platforms; plan security; and more. In addition, the book covers the exam objectives for the both the CompTIA Cloud Essentials (Exam CLO-001) exam and the EXIN Cloud Computing Foundation (EX0-1

Hidden in the Clouds: New Ideas in Cloud Computing

CERN Multimedia

CERN. Geneva

2013-01-01

Abstract: Cloud computing has become a hot topic. But 'cloud' is no newer in 2013 than MapReduce was in 2005: We've been doing both for years. So why is cloud more relevant today than it ever has been? In this presentation, we will introduce the (current) central thesis of cloud computing, and explore how and why (or even whether) the concept has evolved. While we will cover a little light background, our primary focus will be on the consequences, corollaries and techniques introduced by some of the leading cloud developers and organizations. We each have a different deployment model, different applications and workloads, and many of us are still learning to efficiently exploit the platform services offered by a modern implementation. The discussion will offer the opportunity to share these experiences and help us all to realize the benefits of cloud computing to the fullest degree. Please bring questions and opinions, and be ready to share both!   Bio: S...

Cloud database development and management

CERN Document Server

Chao, Lee

2013-01-01

Nowadays, cloud computing is almost everywhere. However, one can hardly find a textbook that utilizes cloud computing for teaching database and application development. This cloud-based database development book teaches both the theory and practice with step-by-step instructions and examples. This book helps readers to set up a cloud computing environment for teaching and learning database systems. The book will cover adequate conceptual content for students and IT professionals to gain necessary knowledge and hands-on skills to set up cloud based database systems.

Trusted cloud computing

CERN Document Server

Krcmar, Helmut; Rumpe, Bernhard

2014-01-01

This book documents the scientific results of the projects related to the Trusted Cloud Program, covering fundamental aspects of trust, security, and quality of service for cloud-based services and applications. These results aim to allow trustworthy IT applications in the cloud by providing a reliable and secure technical and legal framework. In this domain, business models, legislative circumstances, technical possibilities, and realizable security are closely interwoven and thus are addressed jointly. The book is organized in four parts on "Security and Privacy", "Software Engineering and

Accurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information

Science.gov (United States)

Wang, Yongzhi; Ma, Yuqing; Zhu, A.-xing; Zhao, Hui; Liao, Lixia

2018-05-01

Facade features represent segmentations of building surfaces and can serve as a building framework. Extracting facade features from three-dimensional (3D) point cloud data (3D PCD) is an efficient method for 3D building modeling. By combining the advantages of 3D PCD and two-dimensional optical images, this study describes the creation of a highly accurate building facade feature extraction method from 3D PCD with a focus on structural information. The new extraction method involves three major steps: image feature extraction, exploration of the mapping method between the image features and 3D PCD, and optimization of the initial 3D PCD facade features considering structural information. Results show that the new method can extract the 3D PCD facade features of buildings more accurately and continuously. The new method is validated using a case study. In addition, the effectiveness of the new method is demonstrated by comparing it with the range image-extraction method and the optical image-extraction method in the absence of structural information. The 3D PCD facade features extracted by the new method can be applied in many fields, such as 3D building modeling and building information modeling.

Cloud ERP and Cloud Accounting Software in Romania

Directory of Open Access Journals (Sweden)

Gianina MIHAI

2015-05-01

Full Text Available Nowadays, Cloud Computing becomes a more and more fashionable concept in the IT environment. There is no unanimous opinion on the definition of this concept, as it covers several versions of the newly emerged stage in the IT. But in fact, Cloud Computing should not suggest anything else than simplicity. Thus, in short, simple terms, Cloud Computing can be defined as a solution to use external IT resources (servers, storage media, applications and services, via Internet. Cloud computing is nothing more than the promise of an easy accessible technology. If the promise will eventually turn into something certain yet remains to be seen. In our opinion it is too early to make an assertion. In this article, our purpose is to find out what is the Romanian offer of ERP and Accounting software applications in Cloud and / or as services in SaaS version. Thus, we conducted an extensive study whose results we’ll present in the following.

350 Year Cloud Reconstruction Deduced from Northeast Caribbean Coral Proxies

Science.gov (United States)

Winter, A.; Sammarco, P. W.; Mikolajewicz, U.; Jury, M.; Zanchettin, D.

2014-12-01

Clouds are a major factor influencing the global climate and its response to external forcing through their implications for the global hydrological cycle, and hence for the planetary radiative budget. Clouds also contribute to regional climates and their variability through, e.g., the changes they induce in regional precipitation patterns. There have been very few studies of decadal and longer-term changes in cloud cover in the tropics and sub-tropics, both over land and the ocean. In the tropics, there is great uncertainty regarding how global warming will affect cloud cover. Observational satellite data are too short to unambiguously discern any temporal trends in cloud cover. Corals generally live in well-mixed coastal regions and can often record environmental conditions of large areas of the upper ocean. This is particularly the case at low latitudes. Scleractinian corals are sessile, epibenthic fauna, and the type of environmental information recorded at the location where the coral has been living is dependent upon the species of coral considered and proxy index of interest. Skeletons of scleractinian corals are considered to provide among the best records of high-resolution (sub-annual) environmental variability in the tropical and sub-tropical oceans. Zooxanthellate hermatypic corals in tropical and sub-tropical seas precipitate CaCO3 skeletons as they grow. This growth is made possible through the manufacture of CaCO3crystals, facilitated by the zooxanthellae. During the process of crystallization, the holobiont binds carbon of different isotopes into the crystals. Stable carbon isotope concentrations vary with a variety of environmental conditions. In the Caribbean, d13C in corals of the species Montastraea faveolata can be used as a proxy for changes in cloud cover. In this contribution, we will demonstrate that the stable isotope 13C varies concomitantly with cloud cover for the northeastern Caribbean region. Using this proxy we have been able to

Thermodynamic and cloud parameter retrieval using infrared spectral data

Science.gov (United States)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Huang, Hung-Lung A.; Li, Jun; McGill, Matthew J.; Mango, Stephen A.

2005-01-01

High-resolution infrared radiance spectra obtained from near nadir observations provide atmospheric, surface, and cloud property information. A fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The retrieval algorithm is presented along with its application to recent field experiment data from the NPOESS Airborne Sounding Testbed - Interferometer (NAST-I). The retrieval accuracy dependence on cloud properties is discussed. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with an accuracy of approximately 1.0 km. Preliminary NAST-I retrieval results from the recent Atlantic-THORPEX Regional Campaign (ATReC) are presented and compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL).

Alpine cloud climatology using long-term NOAA-AVHRR satellite data

Energy Technology Data Exchange (ETDEWEB)

Kaestner, M.; Kriebel, K.T.

2000-07-01

Three different climates have been identified by our evaluation of AVHRR (advanced very high resolution radiometer) data using APOLLO (AVHRR processing scheme over land, clouds and ocean) for a five-years cloud climatology of the Alpine region. The cloud cover data from four layers were spatially averaged in boxes of 15 km by 14 km. The study area only comprises 540 km by 560 km, but contains regions with moderate, Alpine and Mediterranean climate. Data from the period July 1989 until December 1996 have been considered. The temporal resolution is one scene per day, the early afternoon pass, yielding monthly means of satellite derived cloud coverages 5% to 10% above the daily mean compared to conventional surface observation. At nonvegetated sites the cloudiness is sometimes significantly overestimated. Averaging high resolution cloud data seems to be superior to low resolution measurements of cloud properties and averaging is favourable in topographical homogeneous regions only. The annual course of cloud cover reveals typical regional features as foehn or temporal singularities as the so-called Christmas thaw. The cloud cover maps in spatially high resolution show local luff/lee features which outline the orography. Less cloud cover is found over the Alps than over the forelands in winter, an accumulation of thick cirrus is found over the High Alps and an accumulation of thin cirrus north of the Alps. (orig.)

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

Science.gov (United States)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

Spatial and Temporal Inter-Relationship between Anomalies and Trends of Temperature, Moisture, Cloud Cover and OLR as Observed by AIRS/AMSU on Aqua

Science.gov (United States)

Susskind, Joel; Molnar, Gyula

2009-01-01

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiled; atmospheric humidity profiles, fractional cloud clover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2006 - November 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extra-tropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear Sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to evaluate the anomalies and trends of temperature profiles and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 1/3 year time period are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.

The role of cloud-scale resolution on radiative properties of oceanic cumulus clouds

International Nuclear Information System (INIS)

Kassianov, Evgueni; Ackerman, Thomas; Kollias, Pavlos

2005-01-01

Both individual and combined effects of the horizontal and vertical variability of cumulus clouds on solar radiative transfer are investigated using a two-dimensional (x- and z-directions) cloud radar dataset. This high-resolution dataset of typical fair-weather marine cumulus is derived from ground-based 94GHz cloud radar observations. The domain-averaged (along x-direction) radiative properties are computed by a Monte Carlo method. It is shown that (i) different cloud-scale resolutions can be used for accurate calculations of the mean absorption, upward and downward fluxes; (ii) the resolution effects can depend strongly on the solar zenith angle; and (iii) a few cloud statistics can be successfully applied for calculating the averaged radiative properties

Trends and variability of cloud fraction cover in the Arctic, 1982-2009

Science.gov (United States)

Boccolari, Mauro; Parmiggiani, Flavio

2018-05-01

Climatology, trends and variability of cloud fraction cover (CFC) data over the Arctic (north of 70°N), were analysed over the 1982-2009 period. Data, available from the Climate Monitoring Satellite Application Facility (CM SAF), are derived from satellite measurements by AVHRR. Climatological means confirm permanent high CFC values over the Atlantic sector during all the year and during summer over the eastern Arctic Ocean. Lower values are found in the rest of the analysed area especially over Greenland and the Canadian Archipelago, nearly continuously during all the months. These results are confirmed by CFC trends and variability. Statistically significant trends were found during all the months over the Greenland Sea, particularly during the winter season (negative, less than -5 % dec -1) and over the Beaufort Sea in spring (positive, more than +5 % dec -1). CFC variability, investigated by the Empirical Orthogonal Functions, shows a substantial "non-variability" in the Northern Atlantic Ocean. Statistically significant correlations between CFC principal components elements and both the Pacific Decadal Oscillation index and Pacific North America patterns are found.

How accurately can the instantaneous aerosol effect on cloud albedo be constrained?

Science.gov (United States)

Gryspeerdt, E.; Quaas, J.; Ferrachat, S.; Gettelman, A.; Ghan, S. J.; Lohmann, U.; Neubauer, D.; Morrison, H.; Partridge, D.; Stier, P.; Takemura, T.; Wang, H.; Wang, M.; Zhang, K.

2017-12-01

Aerosol-cloud interactions are the most uncertain component of the anthropogenic radiative forcing, with a significant fraction of this uncertainty coming from uncertainty in the radiative forcing due to instantaneous changes in cloud albedo (the RFaci). Aerosols can have a strong influence on the cloud droplet number concentration (CDNC), so previous studies have used the sensitivity of CDNC to aerosol properties as a method of estimating the RFaci. However, recent studies have suggested that this sensitivity is unsuitable as a constraint on the RFaci, as it differs in the present day and pre-industrial atmosphere. This would place significant limits on our ability to constrain the RFaci from satellite observations. In this study, a selection of global aerosol-climate models are used to investigate the suitability of various aerosol proxies and methods for calculating the RFaci from present day data. A linear-regression based sensitivity of CDNC to aerosol perturbations can lead to large errors in the diagnosed RFaci, as can the use of the aerosol optical depth (AOD) as an aerosol proxy. However, we show that if suitable choices of aerosol proxy are made and the anthropogenic aerosol contribution is known, it is possible to diagnose the anthropogenic change in CDNC, and so the RFaci, using present day aerosol-cloud relationships.

Spectral Dependence of MODIS Cloud Droplet Effective Radius Retrievals for Marine Boundary Layer Clouds

Science.gov (United States)

Zhang, Zhibo; Platnick, Steven E.; Ackerman, Andrew S.; Cho, Hyoun-Myoung

2014-01-01

Low-level warm marine boundary layer (MBL) clouds cover large regions of Earth's surface. They have a significant role in Earth's radiative energy balance and hydrological cycle. Despite the fundamental role of low-level warm water clouds in climate, our understanding of these clouds is still limited. In particular, connections between their properties (e.g. cloud fraction, cloud water path, and cloud droplet size) and environmental factors such as aerosol loading and meteorological conditions continue to be uncertain or unknown. Modeling these clouds in climate models remains a challenging problem. As a result, the influence of aerosols on these clouds in the past and future, and the potential impacts of these clouds on global warming remain open questions leading to substantial uncertainty in climate projections. To improve our understanding of these clouds, we need continuous observations of cloud properties on both a global scale and over a long enough timescale for climate studies. At present, satellite-based remote sensing is the only means of providing such observations.

Solar variability and clouds

CERN Document Server

Kirkby, Jasper

2000-01-01

Satellite observations have revealed a surprising imprint of the 11- year solar cycle on global low cloud cover. The cloud data suggest a correlation with the intensity of Galactic cosmic rays. If this apparent connection between cosmic rays and clouds is real, variations of the cosmic ray flux caused by long-term changes in the solar wind could have a significant influence on the global energy radiation budget and the climate. However a direct link between cosmic rays and clouds has not been unambiguously established and, moreover, the microphysical mechanism is poorly understood. New experiments are being planned to find out whether cosmic rays can affect cloud formation, and if so how. (37 refs).

Clouds and snowmelt on the north slope of Alaska

Energy Technology Data Exchange (ETDEWEB)

Zhang, T.; Stamnes, K.; Bowling, S.A. [Univ. of Alaska, Fairbanks, AK (United States)

1996-04-01

Clouds have a large effect on the radiation field. Consequently, possible changes in cloud properties may have a very substantial impact on climate. Of all natural surfaces, seasonal snow cover has the highest surface albedo, which is one of the most important components of the climatic system. Interactions between clouds and seasonal snow cover are expected to have a significant effect on climate and its change at high latitudes. The purpose of this paper is to investigate the sensitivity of the surface cloud-radiative forcing during the period of snowmelt at high latitudes. The primary variables investigated are cloud liquid path (LWP) and droplet equivalent radius (r{sub e}). We will also examine the sensitivity of the surface radiative fluxes to cloud base height and cloud base temperature.

MUSE: An Efficient and Accurate Verifiable Privacy-Preserving Multikeyword Text Search over Encrypted Cloud Data

OpenAIRE

Xiangyang, Zhu; Hua, Dai; Xun, Yi; Geng, Yang; Xiao, Li

2017-01-01

With the development of cloud computing, services outsourcing in clouds has become a popular business model. However, due to the fact that data storage and computing are completely outsourced to the cloud service provider, sensitive data of data owners is exposed, which could bring serious privacy disclosure. In addition, some unexpected events, such as software bugs and hardware failure, could cause incomplete or incorrect results returned from clouds. In this paper, we propose an efficient ...

Remote Sensing Based Two-Stage Sampling for Accuracy Assessment and Area Estimation of Land Cover Changes

Directory of Open Access Journals (Sweden)

Heinz Gallaun

2015-09-01

Full Text Available Land cover change processes are accelerating at the regional to global level. The remote sensing community has developed reliable and robust methods for wall-to-wall mapping of land cover changes; however, land cover changes often occur at rates below the mapping errors. In the current publication, we propose a cost-effective approach to complement wall-to-wall land cover change maps with a sampling approach, which is used for accuracy assessment and accurate estimation of areas undergoing land cover changes, including provision of confidence intervals. We propose a two-stage sampling approach in order to keep accuracy, efficiency, and effort of the estimations in balance. Stratification is applied in both stages in order to gain control over the sample size allocated to rare land cover change classes on the one hand and the cost constraints for very high resolution reference imagery on the other. Bootstrapping is used to complement the accuracy measures and the area estimates with confidence intervals. The area estimates and verification estimations rely on a high quality visual interpretation of the sampling units based on time series of satellite imagery. To demonstrate the cost-effective operational applicability of the approach we applied it for assessment of deforestation in an area characterized by frequent cloud cover and very low change rate in the Republic of Congo, which makes accurate deforestation monitoring particularly challenging.

Tropical Montane Cloud Forests: Hydrometeorological variability in three neighbouring catchments with different forest cover

Science.gov (United States)

Ramírez, Beatriz H.; Teuling, Adriaan J.; Ganzeveld, Laurens; Hegger, Zita; Leemans, Rik

2017-09-01

Mountain areas are characterized by a large heterogeneity in hydrological and meteorological conditions. This heterogeneity is currently poorly represented by gauging networks and by the coarse scale of global and regional climate and hydrological models. Tropical Montane Cloud Forests (TMCFs) are found in a narrow elevation range and are characterized by persistent fog. Their water balance depends on local and upwind temperatures and moisture, therefore, changes in these parameters will alter TMCF hydrology. Until recently the hydrological functioning of TMCFs was mainly studied in coastal regions, while continental TMCFs were largely ignored. This study contributes to fill this gap by focusing on a TMCF which is located on the northern eastern Andes at an elevation of 1550-2300 m asl, in the Orinoco river basin highlands. In this study, we describe the spatial and seasonal meteorological variability, analyse the corresponding catchment hydrological response to different land cover, and perform a sensitivity analysis on uncertainties related to rainfall interpolation, catchment area estimation and streamflow measurements. Hydro-meteorological measurements, including hourly solar radiation, temperature, relative humidity, wind speed, precipitation, soil moisture and streamflow, were collected from June 2013 to May 2014 at three gauged neighbouring catchments with contrasting TMCF/grassland cover and less than 250 m elevation difference. We found wetter and less seasonally contrasting conditions at higher elevations, indicating a positive relation between elevation and fog or rainfall persistence. This pattern is similar to that of other eastern Andean TMCFs, however, the study site had higher wet season rainfall and lower dry season rainfall suggesting that upwind contrasts in land cover and moisture can influence the meteorological conditions at eastern Andean TMCFs. Contrasting streamflow dynamics between the studied catchments reflect the overall system response

Modeled Impact of Cirrus Cloud Increases Along Aircraft Flight Paths

Science.gov (United States)

Rind, David; Lonergan, P.; Shah, K.

1999-01-01

The potential impact of contrails and alterations in the lifetime of background cirrus due to subsonic airplane water and aerosol emissions has been investigated in a set of experiments using the GISS GCM connected to a q-flux ocean. Cirrus clouds at a height of 12-15km, with an optical thickness of 0.33, were input to the model "x" percentage of clear-sky occasions along subsonic aircraft flight paths, where x is varied from .05% to 6%. Two types of experiments were performed: one with the percentage cirrus cloud increase independent of flight density, as long as a certain minimum density was exceeded; the other with the percentage related to the density of fuel expenditure. The overall climate impact was similar with the two approaches, due to the feedbacks of the climate system. Fifty years were run for eight such experiments, with the following conclusions based on the stable results from years 30-50 for each. The experiments show that adding cirrus to the upper troposphere results in a stabilization of the atmosphere, which leads to some decrease in cloud cover at levels below the insertion altitude. Considering then the total effect on upper level cloud cover (above 5 km altitude), the equilibrium global mean temperature response shows that altering high level clouds by 1% changes the global mean temperature by 0.43C. The response is highly linear (linear correlation coefficient of 0.996) for high cloud cover changes between 0. 1% and 5%. The effect is amplified in the Northern Hemisphere, more so with greater cloud cover change. The temperature effect maximizes around 10 km (at greater than 40C warming with a 4.8% increase in upper level clouds), again more so with greater warming. The high cloud cover change shows the flight path influence most clearly with the smallest warming magnitudes; with greater warming, the model feedbacks introduce a strong tropical response. Similarly, the surface temperature response is dominated by the feedbacks, and shows

StackInsights: Cognitive Learning for Hybrid Cloud Readiness

OpenAIRE

Qiao, Mu; Bathen, Luis; Génot, Simon-Pierre; Lee, Sunhwan; Routray, Ramani

2017-01-01

Hybrid cloud is an integrated cloud computing environment utilizing a mix of public cloud, private cloud, and on-premise traditional IT infrastructures. Workload awareness, defined as a detailed full range understanding of each individual workload, is essential in implementing the hybrid cloud. While it is critical to perform an accurate analysis to determine which workloads are appropriate for on-premise deployment versus which workloads can be migrated to a cloud off-premise, the assessment...

Cloud-Scale Numerical Modeling of the Arctic Boundary Layer

Science.gov (United States)

Krueger, Steven K.

1998-01-01

The interactions between sea ice, open ocean, atmospheric radiation, and clouds over the Arctic Ocean exert a strong influence on global climate. Uncertainties in the formulation of interactive air-sea-ice processes in global climate models (GCMs) result in large differences between the Arctic, and global, climates simulated by different models. Arctic stratus clouds are not well-simulated by GCMs, yet exert a strong influence on the surface energy budget of the Arctic. Leads (channels of open water in sea ice) have significant impacts on the large-scale budgets during the Arctic winter, when they contribute about 50 percent of the surface fluxes over the Arctic Ocean, but cover only 1 to 2 percent of its area. Convective plumes generated by wide leads may penetrate the surface inversion and produce condensate that spreads up to 250 km downwind of the lead, and may significantly affect the longwave radiative fluxes at the surface and thereby the sea ice thickness. The effects of leads and boundary layer clouds must be accurately represented in climate models to allow possible feedbacks between them and the sea ice thickness. The FIRE III Arctic boundary layer clouds field program, in conjunction with the SHEBA ice camp and the ARM North Slope of Alaska and Adjacent Arctic Ocean site, will offer an unprecedented opportunity to greatly improve our ability to parameterize the important effects of leads and boundary layer clouds in GCMs.

Verification of cloud cover forecast with INSAT observation over ...

Indian Academy of Sciences (India)

and recent trends in forecast quality, improving ... general framework for forecast verification based on the joint ... clouds is given by POD, and FAR offers a metric for how often the .... Kain J S and Fritsch J M 1993 Convective parameterizations.

Reassessing the effect of cloud type on Earth's energy balance

Science.gov (United States)

Hang, A.; L'Ecuyer, T.

2017-12-01

Cloud feedbacks depend critically on the characteristics of the clouds that change, their location and their environment. As a result, accurately predicting the impact of clouds on future climate requires a better understanding of individual cloud types and their spatial and temporal variability. This work revisits the problem of documenting the effects of distinct cloud regimes on Earth's radiation budget distinguishing cloud types according to their signatures in spaceborne active observations. Using CloudSat's multi-sensor radiative fluxes product that leverages high-resolution vertical cloud information from CloudSat, CALIPSO, and MODIS observations to provide the most accurate estimates of vertically-resolved radiative fluxes available to date, we estimate the global annual mean net cloud radiative effect at the top of the atmosphere to be -17.1 W m-2 (-44.2 W m-2 in the shortwave and 27.1 W m-2 in the longwave), slightly weaker than previous estimates from passive sensor observations. Multi-layered cloud systems, that are often misclassified using passive techniques but are ubiquitous in both hemispheres, contribute about -6.2 W m-2 of the net cooling effect, particularly at ITCZ and higher latitudes. Another unique aspect of this work is the ability of CloudSat and CALIPSO to detect cloud boundary information providing an improved capability to accurately discern the impact of cloud-type variations on surface radiation balance, a critical factor in modulating the disposition of excess energy in the climate system. The global annual net cloud radiative effect at the surface is estimated to be -24.8 W m-2 (-51.1 W m-2 in the shortwave and 26.3 W m-2 in the longwave), dominated by shortwave heating in multi-layered and stratocumulus clouds. Corresponding estimates of the effects of clouds on atmospheric heating suggest that clouds redistribute heat from poles to equator enhancing the general circulation.

Three-dimensional transfer of solar radiation in clouds

International Nuclear Information System (INIS)

Davies, R.

1976-01-01

The results of a theoretical study of the effects of cloud geometry on the transfer of incident solar radiation is presented. These results indicate that a three-dimensional description of cloud geometry is a necessary prerequisite to the accurate determination of the emerging radiation field. Models which make the plane parallel assumption are therefore frequently inadequate. Both a Monte Carlo method and an analytic method were used to model the three-dimensional transfer of radiation. At the expense of considerable computation time the Monte Carlo model provides accurate values of the fluxes and intensities (averages over π/30 steradians) emerging from clouds which can be described as a set of connected cuboidal cells, each cell being homogeneous with respect to extinction coefficient, single scatter albedo and phase function. The analytic model, based on an extension of Eddington's approximation to three dimensions and to anisotropic scattering, is efficient to use, but is restricted to clouds made up of a single cuboidal cell and is more accurate for large clouds than small ones. By an iterated approach, involving integration of the source function along line of sight, the analytic model provides both fluxes and intensities of the emerging radiation at any specified point on the cloud's surface. These models were both applied to a systematic study of the transfer of solar radiation in isolated cuboidal clouds of arbitraty dimensions, the results of which illustrate the importance of considering the total cloud geometry in any attempt at realistic modelling. A study of the transfer of radiation in stratiform clouds with turretted top surfaces also indicated that even for these clouds the plane parallel assumption was often not tenable

Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas: Atmospheric Observations and Modeling as Part of the Seasonal Ice Zone Reconnaissance Surveys

Science.gov (United States)

2017-06-04

further, changes in lower atmospheric temperature, humidity, winds , and clouds are likely to result from changed sea ice concentrations and ocean...affect changes in cloud properties and cover, • develop novel instrumentation including low cost, expendable, air-deployed micro -aircraft to obtain...from June through October to obtain atmospheric profiles of temperature, humidity, and winds from the time of ice edge retreat in spring to advance

Cloud and surface textural features in polar regions

Science.gov (United States)

Welch, Ronald M.; Kuo, Kwo-Sen; Sengupta, Sailes K.

1990-01-01

The study examines the textural signatures of clouds, ice-covered mountains, solid and broken sea ice and floes, and open water. The textural features are computed from sum and difference histogram and gray-level difference vector statistics defined at various pixel displacement distances derived from Landsat multispectral scanner data. Polar cloudiness, snow-covered mountainous regions, solid sea ice, glaciers, and open water have distinguishable texture features. This suggests that textural measures can be successfully applied to the detection of clouds over snow-covered mountains, an ability of considerable importance for the modeling of snow-melt runoff. However, broken stratocumulus cloud decks and thin cirrus over broken sea ice remain difficult to distinguish texturally. It is concluded that even with high spatial resolution imagery, it may not be possible to distinguish broken stratocumulus and thin clouds from sea ice in the marginal ice zone using the visible channel textural features alone.

CloudMonitor: Profiling Power Usage

OpenAIRE

Smith, James William; Khajeh-Hosseini, Ali; Ward, Jonathan Stuart; Sommerville, Ian

2012-01-01

In Cloud Computing platforms the addition of hardware monitoring devices to gather power usage data can be impractical or uneconomical due to the large number of machines to be metered. CloudMonitor, a monitoring tool that can generate power models for software-based power estimation, can provide insights to the energy costs of deployments without additional hardware. Accurate power usage data leads to the possibility of Cloud providers creating a separate tariff for power and therefore incen...

Teaching cloud computing: a software engineering perspective

OpenAIRE

Sommerville, Ian

2012-01-01

This short papers discusses the issues of teaching cloud computing from a software engineering rather than a business perspective. It discusses what topics might be covered in a senior course on cloud software engineering.

Military clouds: utilization of cloud computing systems at the battlefield

Science.gov (United States)

Süleyman, Sarıkürk; Volkan, Karaca; İbrahim, Kocaman; Ahmet, Şirzai

2012-05-01

Cloud computing is known as a novel information technology (IT) concept, which involves facilitated and rapid access to networks, servers, data saving media, applications and services via Internet with minimum hardware requirements. Use of information systems and technologies at the battlefield is not new. Information superiority is a force multiplier and is crucial to mission success. Recent advances in information systems and technologies provide new means to decision makers and users in order to gain information superiority. These developments in information technologies lead to a new term, which is known as network centric capability. Similar to network centric capable systems, cloud computing systems are operational today. In the near future extensive use of military clouds at the battlefield is predicted. Integrating cloud computing logic to network centric applications will increase the flexibility, cost-effectiveness, efficiency and accessibility of network-centric capabilities. In this paper, cloud computing and network centric capability concepts are defined. Some commercial cloud computing products and applications are mentioned. Network centric capable applications are covered. Cloud computing supported battlefield applications are analyzed. The effects of cloud computing systems on network centric capability and on the information domain in future warfare are discussed. Battlefield opportunities and novelties which might be introduced to network centric capability by cloud computing systems are researched. The role of military clouds in future warfare is proposed in this paper. It was concluded that military clouds will be indispensible components of the future battlefield. Military clouds have the potential of improving network centric capabilities, increasing situational awareness at the battlefield and facilitating the settlement of information superiority.

Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas: Atmospheric Observations and Modeling as Part of the Seasonal Ice Zone Reconnaissance Surveys

Science.gov (United States)

2017-06-04

conditions in the SIZ affeCt changes in cloud properties and cover, • develop novel instrumentation including low cost , expendable, air-deployed micro...hour per response, induding the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and...From- To) 04 - 06 - 2017 Final Technical 0/1/01/2012 - 12/31/2016 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER Atmospheric Profiles , Clouds and the

Cloud Services from Consumer Standpoint

OpenAIRE

Koski, Jori

2016-01-01

The objective of this thesis is to clarify the use of cloud services and how they are used in practice. This thesis will first cover the history of cloud computing. At the early days of computing, services have been stored on servers locally and could be accessed through direct connections. After this, services have been on the users’ personal computers. Nowadays, services are stored in the cloud. This research paper focuses on four sub topics: communication services, healthcare se...

Cloud shading and fog drip influence the metabolism of a coastal pine ecosystem.

Science.gov (United States)

Carbone, Mariah S; Park Williams, A; Ambrose, Anthony R; Boot, Claudia M; Bradley, Eliza S; Dawson, Todd E; Schaeffer, Sean M; Schimel, Joshua P; Still, Christopher J

2013-02-01

Assessing the ecological importance of clouds has substantial implications for our basic understanding of ecosystems and for predicting how they will respond to a changing climate. This study was conducted in a coastal Bishop pine forest ecosystem that experiences regular cycles of stratus cloud cover and inundation in summer. Our objective was to understand how these clouds impact ecosystem metabolism by contrasting two sites along a gradient of summer stratus cover. The site that was under cloud cover ~15% more of the summer daytime hours had lower air temperatures and evaporation rates, higher soil moisture content, and received more frequent fog drip inputs than the site with less cloud cover. These cloud-driven differences in environmental conditions translated into large differences in plant and microbial activity. Pine trees at the site with greater cloud cover exhibited less water stress in summer, larger basal area growth, and greater rates of sap velocity. The difference in basal area growth between the two sites was largely due to summer growth. Microbial metabolism was highly responsive to fog drip, illustrated by an observed ~3-fold increase in microbial biomass C with increasing summer fog drip. In addition, the site with more cloud cover had greater total soil respiration and a larger fractional contribution from heterotrophic sources. We conclude that clouds are important to the ecological functioning of these coastal forests, providing summer shading and cooling that relieve pine and microbial drought stress as well as regular moisture inputs that elevate plant and microbial metabolism. These findings are important for understanding how these and other seasonally dry coastal ecosystems will respond to predicted changes in stratus cover, rainfall, and temperature. © 2012 Blackwell Publishing Ltd.

Cloud fraction and cloud base measurements from scanning Doppler lidar during WFIP-2

Science.gov (United States)

Bonin, T.; Long, C.; Lantz, K. O.; Choukulkar, A.; Pichugina, Y. L.; McCarty, B.; Banta, R. M.; Brewer, A.; Marquis, M.

2017-12-01

The second Wind Forecast Improvement Project (WFIP-2) consisted of an 18-month field deployment of a variety of instrumentation with the principle objective of validating and improving NWP forecasts for wind energy applications in complex terrain. As a part of the set of instrumentation, several scanning Doppler lidars were installed across the study domain to primarily measure profiles of the mean wind and turbulence at high-resolution within the planetary boundary layer. In addition to these measurements, Doppler lidar observations can be used to directly quantify the cloud fraction and cloud base, since clouds appear as a high backscatter return. These supplementary measurements of clouds can then be used to validate cloud cover and other properties in NWP output. Herein, statistics of the cloud fraction and cloud base height from the duration of WFIP-2 are presented. Additionally, these cloud fraction estimates from Doppler lidar are compared with similar measurements from a Total Sky Imager and Radiative Flux Analysis (RadFlux) retrievals at the Wasco site. During mostly cloudy to overcast conditions, estimates of the cloud radiating temperature from the RadFlux methodology are also compared with Doppler lidar measured cloud base height.

Parameterization of clouds and radiation in climate models

Energy Technology Data Exchange (ETDEWEB)

Roeckner, E. [Max Planck Institute for Meterology, Hamburg (Germany)

1995-09-01

Clouds are a very important, yet poorly modeled element in the climate system. There are many potential cloud feedbacks, including those related to cloud cover, height, water content, phase change, and droplet concentration and size distribution. As a prerequisite to studying the cloud feedback issue, this research reports on the simulation and validation of cloud radiative forcing under present climate conditions using the ECHAM general circulation model and ERBE top-of-atmosphere radiative fluxes.

CloudAligner: A fast and full-featured MapReduce based tool for sequence mapping

Directory of Open Access Journals (Sweden)

Shi Weisong

2011-06-01

Full Text Available Abstract Background Research in genetics has developed rapidly recently due to the aid of next generation sequencing (NGS. However, massively-parallel NGS produces enormous amounts of data, which leads to storage, compatibility, scalability, and performance issues. The Cloud Computing and MapReduce framework, which utilizes hundreds or thousands of shared computers to map sequencing reads quickly and efficiently to reference genome sequences, appears to be a very promising solution for these issues. Consequently, it has been adopted by many organizations recently, and the initial results are very promising. However, since these are only initial steps toward this trend, the developed software does not provide adequate primary functions like bisulfite, pair-end mapping, etc., in on-site software such as RMAP or BS Seeker. In addition, existing MapReduce-based applications were not designed to process the long reads produced by the most recent second-generation and third-generation NGS instruments and, therefore, are inefficient. Last, it is difficult for a majority of biologists untrained in programming skills to use these tools because most were developed on Linux with a command line interface. Results To urge the trend of using Cloud technologies in genomics and prepare for advances in second- and third-generation DNA sequencing, we have built a Hadoop MapReduce-based application, CloudAligner, which achieves higher performance, covers most primary features, is more accurate, and has a user-friendly interface. It was also designed to be able to deal with long sequences. The performance gain of CloudAligner over Cloud-based counterparts (35 to 80% mainly comes from the omission of the reduce phase. In comparison to local-based approaches, the performance gain of CloudAligner is from the partition and parallel processing of the huge reference genome as well as the reads. The source code of CloudAligner is available at http

CloudAligner: A fast and full-featured MapReduce based tool for sequence mapping.

Science.gov (United States)

Nguyen, Tung; Shi, Weisong; Ruden, Douglas

2011-06-06

Research in genetics has developed rapidly recently due to the aid of next generation sequencing (NGS). However, massively-parallel NGS produces enormous amounts of data, which leads to storage, compatibility, scalability, and performance issues. The Cloud Computing and MapReduce framework, which utilizes hundreds or thousands of shared computers to map sequencing reads quickly and efficiently to reference genome sequences, appears to be a very promising solution for these issues. Consequently, it has been adopted by many organizations recently, and the initial results are very promising. However, since these are only initial steps toward this trend, the developed software does not provide adequate primary functions like bisulfite, pair-end mapping, etc., in on-site software such as RMAP or BS Seeker. In addition, existing MapReduce-based applications were not designed to process the long reads produced by the most recent second-generation and third-generation NGS instruments and, therefore, are inefficient. Last, it is difficult for a majority of biologists untrained in programming skills to use these tools because most were developed on Linux with a command line interface. To urge the trend of using Cloud technologies in genomics and prepare for advances in second- and third-generation DNA sequencing, we have built a Hadoop MapReduce-based application, CloudAligner, which achieves higher performance, covers most primary features, is more accurate, and has a user-friendly interface. It was also designed to be able to deal with long sequences. The performance gain of CloudAligner over Cloud-based counterparts (35 to 80%) mainly comes from the omission of the reduce phase. In comparison to local-based approaches, the performance gain of CloudAligner is from the partition and parallel processing of the huge reference genome as well as the reads. The source code of CloudAligner is available at http://cloudaligner.sourceforge.net/ and its web version is at http

Robust non-local effects of ocean heat uptake on radiative feedback and subtropical cloud cover

Science.gov (United States)

Rose, B. E. J.

2016-02-01

Much recent work has pointed to the limitations of the global mean planetary energy budget as a useful diagnostic tool for understanding transient climate response, because the climate sensitivity (or radiative feedback) governing the relationships between ocean heat content, surface temperature and top-of-atmosphere energy imbalance depends sensitively on timescale, spatial pattern and nature of the climate forcing. Progress has been made by treating the slowly-evolving (and spatially complex) pattern of ocean heat uptake as a quasi-equilibrium forcing on the "fast" components of the climate system: the atmospheric radiative-dynamical processes that link air-sea heat exchange to the top-of-atmosphere energy budget. Differences between these feedbacks and those on CO2 radiative forcing can be expressed as an "efficacy" of ocean heat uptake. We use idealized slab ocean GCMs forced by prescribed steady energy sinks limited to specific latitude bands (representing heat exchange with the deep ocean) to quantify how (and why) the efficacy depends on the spatial pattern of ocean heat uptake. By repeating the experiment across several independent GCMs we identify robust and non-robust aspects of the response. We find that the efficacy of sub-polar heat uptake is 3 to 4 times larger than the efficacy of tropical heat uptake. Radiative kernel analysis allows an accurate partition into feedbacks due to temperature, water vapor and clouds. We find large and robust differences in clear-sky lapse rate feedbacks, associated with robust differences in large-scale atmospheric circulation and stratification driven by ocean heat uptake. A more novel and surprising result is the robustness across several independent GCMs of the differences in subtropical low cloud feedback (positive under high-latitude uptake, strongly negative under tropical uptake). We trace these robust differences to thermodynamic constraints associated with lower-tropospheric stability and boundary layer

Evaluation of the MiKlip decadal prediction system using satellite based cloud products

Directory of Open Access Journals (Sweden)

Thomas Spangehl

2016-12-01

Full Text Available The decadal hindcast simulations performed for the Mittelfristige Klimaprognosen (MiKlip project are evaluated using satellite-retrieved cloud parameters from the CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data (CLARA-A1 provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF and from the International Satellite Cloud Climatology Project (ISCCP. The forecast quality of two sets of hindcasts, Baseline-1-LR and Baseline-0, which use differing initialisations, is assessed. Basic evaluation focuses on multi-year ensemble mean fields and cloud-type histograms utilizing satellite simulator output. Additionally, ensemble evaluation employing analysis of variance (ANOVA, analysis rank histograms (ARH and a deterministic correlation score is performed. Satellite simulator output is available for a subset of the full hindcast ensembles only. Therefore, the raw model cloud cover is complementary used. The new Baseline-1-LR hindcasts are closer to satellite data with respect to the simulated tropical/subtropical mean cloud cover pattern than the reference hindcasts (Baseline-0 emphasizing improvements of the new MiKlip initialisation procedure. A slightly overestimated occurrence rate of optically thick cloud-types is analysed for different experiments including hindcasts and simulations using realistic sea surface boundaries according to the Atmospheric Model Intercomparison Project (AMIP. By contrast, the evaluation of cirrus and cirrostratus clouds is complicated by observational based uncertainties. Time series of the 3-year mean total cloud cover averaged over the tropical warm pool (TWP region show some correlation with the CLARA-A1 cloud fractional cover. Moreover, ensemble evaluation of the Baseline-1-LR hindcasts reveals potential predictability of the 2–5 lead year averaged total cloud cover for a large part of this region when regarding the full observational period. However, the hindcasts show only

Bigdata Driven Cloud Security: A Survey

Science.gov (United States)

Raja, K.; Hanifa, Sabibullah Mohamed

2017-08-01

Cloud Computing (CC) is a fast-growing technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Recently, it has been observed that massive growth in the scale of data or big data generated through cloud computing. CC consists of a front-end, includes the users’ computers and software required to access the cloud network, and back-end consists of various computers, servers and database systems that create the cloud. In SaaS (Software as-a-Service - end users to utilize outsourced software), PaaS (Platform as-a-Service-platform is provided) and IaaS (Infrastructure as-a-Service-physical environment is outsourced), and DaaS (Database as-a-Service-data can be housed within a cloud), where leading / traditional cloud ecosystem delivers the cloud services become a powerful and popular architecture. Many challenges and issues are in security or threats, most vital barrier for cloud computing environment. The main barrier to the adoption of CC in health care relates to Data security. When placing and transmitting data using public networks, cyber attacks in any form are anticipated in CC. Hence, cloud service users need to understand the risk of data breaches and adoption of service delivery model during deployment. This survey deeply covers the CC security issues (covering Data Security in Health care) so as to researchers can develop the robust security application models using Big Data (BD) on CC (can be created / deployed easily). Since, BD evaluation is driven by fast-growing cloud-based applications developed using virtualized technologies. In this purview, MapReduce [12] is a good example of big data processing in a cloud environment, and a model for Cloud providers.

Providing Diurnal Sky Cover Data at ARM Sites

Energy Technology Data Exchange (ETDEWEB)

Klebe, Dimitri I. [Solmirus Corporation, Colorado Springs, CO (United States)

2015-03-06

The Solmirus Corporation was awarded two-year funding to perform a comprehensive data analysis of observations made during Solmirus’ 2009 field campaign (conducted from May 21 to July 27, 2009 at the ARM SGP site) using their All Sky Infrared Visible Analyzer (ASIVA) instrument. The objective was to develop a suite of cloud property data products for the ASIVA instrument that could be implemented in real time and tailored for cloud modelers. This final report describes Solmirus’ research and findings enabled by this grant. The primary objective of this award was to develop a diurnal sky cover (SC) data product utilizing the ASIVA’s infrared (IR) radiometrically-calibrated data and is described in detail. Other data products discussed in this report include the sky cover derived from ASIVA’s visible channel and precipitable water vapor, cloud temperature (both brightness and color), and cloud height inferred from ASIVA’s IR channels.

Improved cloud parameterization for Arctic climate simulations based on satellite data

Science.gov (United States)

Klaus, Daniel; Dethloff, Klaus; Dorn, Wolfgang; Rinke, Annette

2015-04-01

The defective representation of Arctic cloud processes and properties remains a crucial problem in climate modelling and in reanalysis products. Satellite-based cloud observations (MODIS and CPR/CALIOP) and single-column model simulations (HIRHAM5-SCM) were exploited to evaluate and improve the simulated Arctic cloud cover of the atmospheric regional climate model HIRHAM5. The ECMWF reanalysis dataset 'ERA-Interim' (ERAint) was used for the model initialization, the lateral boundary forcing as well as the dynamical relaxation inside the pan-Arctic domain. HIRHAM5 has a horizontal resolution of 0.25° and uses 40 pressure-based and terrain-following vertical levels. In comparison with the satellite observations, the HIRHAM5 control run (HH5ctrl) systematically overestimates total cloud cover, but to a lesser extent than ERAint. The underestimation of high- and mid-level clouds is strongly outweighed by the overestimation of low-level clouds. Numerous sensitivity studies with HIRHAM5-SCM suggest (1) the parameter tuning, enabling a more efficient Bergeron-Findeisen process, combined with (2) an extension of the prognostic-statistical (PS) cloud scheme, enabling the use of negatively skewed beta distributions. This improved model setup was then used in a corresponding HIRHAM5 sensitivity run (HH5sens). While the simulated high- and mid-level cloud cover is improved only to a limited extent, the large overestimation of low-level clouds can be systematically and significantly reduced, especially over sea ice. Consequently, the multi-year annual mean area average of total cloud cover with respect to sea ice is almost 14% lower than in HH5ctrl. Overall, HH5sens slightly underestimates the observed total cloud cover but shows a halved multi-year annual mean bias of 2.2% relative to CPR/CALIOP at all latitudes north of 60° N. Importantly, HH5sens produces a more realistic ratio between the cloud water and ice content. The considerably improved cloud simulation manifests in

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility. Part II; Cloud Fraction and Radiative Forcing

Science.gov (United States)

Dong, Xiquan; Xi, Baike; Minnis, Patrick

2006-01-01

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) central facility are analyzed for determining the variability of cloud fraction and radiative forcing at several temporal scales between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layer low (0-3 km), middle (3-6 km), and high clouds (greater than 6 km) using ARM SGP ground-based paired lidar-radar measurements. Shortwave (SW), longwave (LW), and net cloud radiative forcings (CRF) are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements. The annual averages of total, and single-layer, nonoverlapped low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Total and low cloud amounts were greatest from December through March and least during July and August. The monthly variation of high cloud amount is relatively small with a broad maximum from May to August. During winter, total cloud cover varies diurnally with a small amplitude, mid-morning maximum and early evening minimum, and during summer it changes by more than 0.14 over the daily cycle with a pronounced early evening minimum. The diurnal variations of mean single-layer cloud cover change with season and cloud height. Annual averages of all-sky, total, and single-layer high, middle, and low LW CRFs are 21.4, 40.2, 16.7, 27.2, and 55.0 Wm(sup -2), respectively; and their SW CRFs are -41.5, -77.2, -37.0, -47.0, and -90.5 Wm(sup -2). Their net CRFs range from -20 to -37 Wm(sup -2). For all-sky, total, and low clouds, the maximum negative net CRFs of -40.1, -70, and -69.5 Wm(sup -2), occur during April; while the respective minimum values of -3.9, -5.7, and -4.6 Wm(sup -2), are found during December. July is the month having maximum negative net CRF of -46.2 Wm(sup -2) for middle clouds, and May has the maximum value of -45.9 Wm(sup -2) for high clouds. An

An Economic Model for Self-tuned Cloud Caching

OpenAIRE

Dash, Debabrata; Kantere, Verena; Ailamaki, Anastasia

2009-01-01

Cloud computing, the new trend for service infrastructures requires user multi-tenancy as well as minimal capital expenditure. In a cloud that services large amounts of data that are massively collected and queried, such as scientific data, users typically pay for query services. The cloud supports caching of data in order to provide quality query services. User payments cover query execution costs and maintenance of cloud infrastructure, and incur cloud profit. The challenge resides in provi...

Modelling the Effects of Temperature and Cloud Cover Change on Mountain Permafrost Distribution, Northwest Canada

Science.gov (United States)

Bonnaventure, P. P.; Lewkowicz, A. G.

2008-12-01

Spatial models of permafrost probability for three study areas in northwest Canada between 59°N and 61°N were perturbed to investigate climate change impacts. The models are empirical-statistical in nature, based on basal temperature of snow (BTS) measurements in winter, and summer ground-truthing of the presence or absence of frozen ground. Predictions of BTS values are made using independent variables of elevation and potential incoming solar radiation (PISR), both derived from a 30 m DEM. These are then transformed into the probability of the presence or absence of permafrost through logistic regression. Under present climate conditions, permafrost percentages in the study areas are 44% for Haines Summit, British Columbia, 38% for Wolf Creek, Yukon, and 69% for part of the Ruby Range, Yukon (Bonnaventure and Lewkowicz, 2008; Lewkowicz and Bonaventure, 2008). Scenarios of air temperature change from -2K (approximating Neoglacial conditions) to +5K (possible within the next century according to the IPCC) were examined for the three sites. Manipulations were carried out by lowering or raising the terrain within the DEM assuming a mean environmental lapse rate of 6.5K/km. Under a -2K scenario, permafrost extent increased by 22-43% in the three study areas. Under a +5K warming, permafrost essentially disappeared in Haines Summit and Wolf Creek, while in the Ruby Range less than 12% of the area remained perennially frozen. It should be emphasized that these model predictions are for equilibrium conditions which might not be attained for several decades or longer in areas of cold permafrost. Cloud cover changes of -10% to +10% were examined through adjusting the partitioning of direct beam and diffuse radiation in the PISR input field. Changes to permafrost extent were small, ranging from -2% to -4% for greater cloudiness with changes of the opposite magnitude for less cloud. The results show that air temperature change has a much greater potential to affect mountain

Implementing and developing cloud computing applications

CERN Document Server

Sarna, David E Y

2010-01-01

From small start-ups to major corporations, companies of all sizes have embraced cloud computing for the scalability, reliability, and cost benefits it can provide. It has even been said that cloud computing may have a greater effect on our lives than the PC and dot-com revolutions combined.Filled with comparative charts and decision trees, Implementing and Developing Cloud Computing Applications explains exactly what it takes to build robust and highly scalable cloud computing applications in any organization. Covering the major commercial offerings available, it provides authoritative guidan

Collaborative Research: Cloudiness transitions within shallow marine clouds near the Azores

Energy Technology Data Exchange (ETDEWEB)

Mechem, David B. [Univ. of Kansas, Lawrence, KS (United States). Atmospheric Science Program. Dept. of Geography and Atmospheric Science; de Szoeke, Simon P. [Oregon State Univ., Corvallis, OR (United States). College of Earth, Ocean, and Atmospheric Sciences; Yuter, Sandra E. [North Carolina State Univ., Raleigh, NC (United States). Dept. of Marine, Earth, and Atmospheric Sciences

2017-01-15

Marine stratocumulus clouds are low, persistent, liquid phase clouds that cover large areas and play a significant role in moderating the climate by reflecting large quantities of incoming solar radiation. The deficiencies in simulating these clouds in global climate models are widely recognized. Much of the uncertainty arises from sub-grid scale variability in the cloud albedo that is not accurately parameterized in climate models. The Clouds, Aerosol and Precipitation in the Marine Boundary Layer (CAP–MBL) observational campaign and the ongoing ARM site measurements on Graciosa Island in the Azores aim to sample the Northeast Atlantic low cloud regime. These data represent, the longest continuous research quality cloud radar/lidar/radiometer/aerosol data set of open-ocean shallow marine clouds in existence. Data coverage from CAP–MBL and the series of cruises to the southeast Pacific culminating in VOCALS will both be of sufficient length to contrast the two low cloud regimes and explore the joint variability of clouds in response to several environmental factors implicated in cloudiness transitions. Our research seeks to better understand cloud system processes in an underexplored but climatologically important maritime region. Our primary goal is an improved physical understanding of low marine clouds on temporal scales of hours to days. It is well understood that aerosols, synoptic-scale forcing, surface fluxes, mesoscale dynamics, and cloud microphysics all play a role in cloudiness transitions. However, the relative importance of each mechanism as a function of different environmental conditions is unknown. To better understand cloud forcing and response, we are documenting the joint variability of observed environmental factors and associated cloud characteristics. In order to narrow the realm of likely parameter ranges, we assess the relative importance of parameter conditions based primarily on two criteria: how often the condition occurs (frequency

Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

Science.gov (United States)

Uttal, Taneil; Frisch, Shelby; Wang, Xuan-Ji; Key, Jeff; Schweiger, Axel; Sun-Mack, Sunny; Minnis, Patrick

2005-01-01

A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

Cloud a particle beam facility to investigate the influence of cosmic rays on clouds

CERN Document Server

Kirkby, Jasper

2001-01-01

Palaeoclimatic data provide extensive evidence for solar forcing of the climate during the Holocene and the last ice age, but the underlying mechanism remains a mystery. However recent observations suggest that cosmic rays may play a key role. Satellite data have revealed a surprising correlation between cosmic ray intensity and the fraction of the Earth covered by low clouds \\cite{svensmark97,marsh}. Since the cosmic ray intensity is modulated by the solar wind, this may be an important clue to the long-sought mechanism for solar-climate variability. In order to test whether cosmic rays and clouds are causally linked and, if so, to understand the microphysical mechanisms, a novel experiment known as CLOUD\\footnotemark\\ has been proposed \\cite{cloud_proposal}--\\cite{cloud_addendum_2}. CLOUD proposes to investigate ion-aerosol-cloud microphysics under controlled laboratory conditions using a beam from a particle accelerator, which provides a precisely adjustable and measurable artificial source of cosmic rays....

Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

Directory of Open Access Journals (Sweden)

Adam M Wilson

2016-03-01

Full Text Available Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

Science.gov (United States)

Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan;

Low cloud properties influenced by cosmic rays

Science.gov (United States)

Marsh; Svensmark

2000-12-04

The influence of solar variability on climate is currently uncertain. Recent observations have indicated a possible mechanism via the influence of solar modulated cosmic rays on global cloud cover. Surprisingly the influence of solar variability is strongest in low clouds (climate on Earth.

CloudSat-Constrained Cloud Ice Water Path and Cloud Top Height Retrievals from MHS 157 and 183.3 GHz Radiances

Science.gov (United States)

Gong, J.; Wu, D. L.

2014-01-01

Ice water path (IWP) and cloud top height (ht) are two of the key variables in determining cloud radiative and thermodynamical properties in climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3+/-3 and 190.3 GHz radiances of the Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining the empirical forward models between collocated and coincident measurements of CloudSat IWP and MHS cloud-induced radiance depression (Tcir) at these channels. The empirical forward model is represented by a lookup table (LUT) of Tcir-IWP relationships as a function of ht and the frequency channel.With ht simultaneously retrieved, the IWP is found to be more accurate. The useful range of the MHS IWP retrieval is between 0.5 and 10 kg/sq m, and agrees well with CloudSat in terms of the normalized probability density function (PDF). Compared to the empirical model, current operational radiative transfer models (RTMs) still have significant uncertainties in characterizing the observed Tcir-IWP relationships. Therefore, the empirical LUT method developed here remains an effective approach to retrieving ice cloud properties from the MHS-like microwave channels.

Looking for the rainbow on exoplanets covered by liquid and icy water clouds

NARCIS (Netherlands)

Karalidi, T.; Stam, D.M.; Hovenier, J.W.

2012-01-01

Aims. Looking for the primary rainbow in starlight that is reflected by exoplanets appears to be a promising method to search for liquid water clouds in exoplanetary atmospheres. Ice water clouds, that consist of water crystals instead of water droplets, could potentially mask the rainbow feature in

Fractal properties and denoising of lidar signals from cirrus clouds

NARCIS (Netherlands)

Heuvel, J.C. van den; Driesenaar, M.L.; Lerou, R.J.L.

2000-01-01

Airborne lidar signals of cirrus clouds are analyzed to determine the cloud structure. Climate modeling and numerical weather prediction benefit from accurate modeling of cirrus clouds. Airborne lidar measurements of the European Lidar in Space Technology Experiment (ELITE) campaign were analyzed by

Detecting Forest Cover and Ecosystem Service Change Using ...

African Journals Online (AJOL)

user

Mpigi, than in Butambala by 5.99%, disturbed forest was 3%, farm land ... climate change impacts on ecosystem services requires more attention and ... While these conceptual models usually assume relatively a causal-effect ... images with relatively low cloud cover or free-cloud imagery during the time period of interest.

High performance cloud auditing and applications

CERN Document Server

Choi, Baek-Young; Song, Sejun

2014-01-01

This book mainly focuses on cloud security and high performance computing for cloud auditing. The book discusses emerging challenges and techniques developed for high performance semantic cloud auditing, and presents the state of the art in cloud auditing, computing and security techniques with focus on technical aspects and feasibility of auditing issues in federated cloud computing environments.   In summer 2011, the United States Air Force Research Laboratory (AFRL) CyberBAT Cloud Security and Auditing Team initiated the exploration of the cloud security challenges and future cloud auditing research directions that are covered in this book. This work was supported by the United States government funds from the Air Force Office of Scientific Research (AFOSR), the AFOSR Summer Faculty Fellowship Program (SFFP), the Air Force Research Laboratory (AFRL) Visiting Faculty Research Program (VFRP), the National Science Foundation (NSF) and the National Institute of Health (NIH). All chapters were partially suppor...

Security of Data Stored in the Cloud

OpenAIRE

Vrhovec, Andraž

2016-01-01

The goal of this diploma thesis is to give an overview of data security in cloud systems. The first part covers basics of cloud and security. Additionally it identifies some risks arising from the use of cloud computing. The second part focuses on cryptography, especially on ciphers, as a tool for mitigation of those risks. We try to convey some recent ideas (especially those interesting in the context of cloud computing) from the cryptographic world to the reader in an easy manner. We conclu...

CLOUD DETECTION OF OPTICAL SATELLITE IMAGES USING SUPPORT VECTOR MACHINE

Directory of Open Access Journals (Sweden)

K.-Y. Lee

2016-06-01

Full Text Available Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012 uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+ and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate

Cloud Detection of Optical Satellite Images Using Support Vector Machine

Science.gov (United States)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection

Accurate simulation of the electron cloud in the Fermilab Main Injector with VORPAL

Energy Technology Data Exchange (ETDEWEB)

Lebrun, Paul L.G.; Spentzouris, Panagiotis; /Fermilab; Cary, John R.; Stoltz, Peter; Veitzer, Seth A.; /Tech-X, Boulder

2010-05-01

Precision simulations of the electron cloud at the Fermilab Main Injector have been studied using the plasma simulation code VORPAL. Fully 3D and self consistent solutions that includes E.M. field maps generated by the cloud and the proton bunches have been obtained, as well detailed distributions of the electron's 6D phase space. We plan to include such maps in the ongoing simulation of the space charge effects in the Main Injector. Simulations of the response of beam position monitors, retarding field analyzers and microwave transmission experiments are ongoing.

Life in the clouds: are tropical montane cloud forests responding to changes in climate?

Science.gov (United States)

Hu, Jia; Riveros-Iregui, Diego A

2016-04-01

The humid tropics represent only one example of the many places worldwide where anthropogenic disturbance and climate change are quickly affecting the feedbacks between water and trees. In this article, we address the need for a more long-term perspective on the effects of climate change on tropical montane cloud forests (TMCF) in order to fully assess the combined vulnerability and long-term response of tropical trees to changes in precipitation regimes, including cloud immersion. We first review the ecophysiological benefits that cloud water interception offers to trees in TMCF and then examine current climatological evidence that suggests changes in cloud base height and impending changes in cloud immersion for TMCF. Finally, we propose an experimental approach to examine the long-term dynamics of tropical trees in TMCF in response to environmental conditions on decade-to-century time scales. This information is important to assess the vulnerability and long-term response of TMCF to changes in cloud cover and fog frequency and duration.

An evaluation of Arctic cloud and radiation processes during the SHEBA year: simulation results from eight Arctic regional climate models

Energy Technology Data Exchange (ETDEWEB)

Wyser, K.; Willen, U. [Rossby Centre, SMHI, Norrkoeping (Sweden); Jones, C.G.; Du, P.; Girard, E.; Laprise, R. [Universite du Quebec a Montreal, Canadian Regional Climate Modelling and Diagnostics Network, Montreal (Canada); Cassano, J.; Serreze, M.; Shaw, M.J. [University of Colorado, Cooperative Institute for Research in Environmental Sciences and Department of Atmospheric and Oceanic Sciences, Boulder, CO (United States); Christensen, J.H. [Danish Meteorological Institute, Copenhagen (Denmark); Curry, J.A. [School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA (United States); Dethloff, K.; Rinke, A. [Alfred Wegener Institute for Polar and Marine Research, Research Unit, Potsdam (Germany); Haugen, J.-E.; Koeltzow, M. [Norwegian Meteorological Institute, Oslo (Norway); Jacob, D.; Pfeifer, S. [Max Planck Institute for Meteorology, Hamburg (Germany); Lynch, A. [Monash University, School of Geography and Environmental Science, Melbourne (Australia); Tjernstroem, M.; Zagar, M. [Stockholm University, Department of Meteorology, Stockholm (Sweden)

2008-02-15

Eight atmospheric regional climate models (RCMs) were run for the period September 1997 to October 1998 over the western Arctic Ocean. This period was coincident with the observational campaign of the Surface Heat Budget of the Arctic Ocean (SHEBA) project. The RCMs shared common domains, centred on the SHEBA observation camp, along with a common model horizontal resolution, but differed in their vertical structure and physical parameterizations. All RCMs used the same lateral and surface boundary conditions. Surface downwelling solar and terrestrial radiation, surface albedo, vertically integrated water vapour, liquid water path and cloud cover from each model are evaluated against the SHEBA observation data. Downwelling surface radiation, vertically integrated water vapour and liquid water path are reasonably well simulated at monthly and daily timescales in the model ensemble mean, but with considerable differences among individual models. Simulated surface albedos are relatively accurate in the winter season, but become increasingly inaccurate and variable in the melt season, thereby compromising the net surface radiation budget. Simulated cloud cover is more or less uncorrelated with observed values at the daily timescale. Even for monthly averages, many models do not reproduce the annual cycle correctly. The inter-model spread of simulated cloud-cover is very large, with no model appearing systematically superior. Analysis of the co-variability of terms controlling the surface radiation budget reveal some of the key processes requiring improved treatment in Arctic RCMs. Improvements in the parameterization of cloud amounts and surface albedo are most urgently needed to improve the overall performance of RCMs in the Arctic. (orig.)

Cloud computing for data-intensive applications

CERN Document Server

Li, Xiaolin

2014-01-01

This book presents a range of cloud computing platforms for data-intensive scientific applications. It covers systems that deliver infrastructure as a service, including: HPC as a service; virtual networks as a service; scalable and reliable storage; algorithms that manage vast cloud resources and applications runtime; and programming models that enable pragmatic programming and implementation toolkits for eScience applications. Many scientific applications in clouds are also introduced, such as bioinformatics, biology, weather forecasting and social networks. Most chapters include case studie

Cloudonomics the business value of cloud computing

CERN Document Server

Weinman, Joe

2012-01-01

The ultimate guide to assessing and exploiting the customer value and revenue potential of the Cloud A new business model is sweeping the world—the Cloud. And, as with any new technology, there is a great deal of fear, uncertainty, and doubt surrounding cloud computing. Cloudonomics radically upends the conventional wisdom, clearly explains the underlying principles and illustrates through understandable examples how Cloud computing can create compelling value—whether you are a customer, a provider, a strategist, or an investor. Cloudonomics covers everything you need to consider f

Microphysical and radiative effects of aerosols on warm clouds during the Amazon biomass burning season as observed by MODIS: impacts of water vapor and land cover

Directory of Open Access Journals (Sweden)

J. E. Ten Hoeve

2011-04-01

aerosols and both CWV and clouds over varying land surface types is also analyzed. The study finds that the difference in CWV between forested and deforested land is not correlated with aerosol loading, supporting the assumption that temporal variation of CWV is primarily a function of the larger-scale meteorology. However, a difference in the response of CF to increasing AOD is observed between forested and deforested land. This suggests that dissimilarities between other meteorological factors, such as atmospheric stability, may have an impact on aerosol-cloud correlations between different land cover types.

ISR-1 Seminar: Nuclear Cloud Lofting

International Nuclear Information System (INIS)

Walker, Andrew Charles

2016-01-01

This report goes into detail about motivation, background, lofting methodologies (empirical, parcel methods, Navier-Stokes), DELFIC Model, validation, DIORAMA integration, and has the following conclusions: A parcel methodology was applied to develop the DIORAMA cloud lofting module. It is based on the DELFIC model and treats the cloud as a homogenous unit. It solves the set of 8 ODEs for cloud properties. It outputs the time history of the cloud height, radius, and other parameters. The cloud lofting module was tuned with 54 test cases. An iterative brute force search was carried out to find the best fit tuning parameters. The best fit parameters yielded average cloud height errors of 12.9% and 10.3% for the bottom and top, respectively. This all allows for more accurate modeling of the propagation of delayed gamma rays in DIORAMA.

Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds

Science.gov (United States)

Fan, Jiwen; Leung, L. Ruby; Rosenfeld, Daniel; Chen, Qian; Li, Zhanqing; Zhang, Jinqiang; Yan, Hongru

2013-11-01

Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol's thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ∼27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3-5 Wṡm-2) and a surface cooling (-5 to -8 Wṡm-2). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments.

Microphysical effects determine macrophysical response for aerosol impacts on deep convective clouds.

Science.gov (United States)

Fan, Jiwen; Leung, L Ruby; Rosenfeld, Daniel; Chen, Qian; Li, Zhanqing; Zhang, Jinqiang; Yan, Hongru

2013-11-26

Deep convective clouds (DCCs) play a crucial role in the general circulation, energy, and hydrological cycle of our climate system. Aerosol particles can influence DCCs by altering cloud properties, precipitation regimes, and radiation balance. Previous studies reported both invigoration and suppression of DCCs by aerosols, but few were concerned with the whole life cycle of DCC. By conducting multiple monthlong cloud-resolving simulations with spectral-bin cloud microphysics that capture the observed macrophysical and microphysical properties of summer convective clouds and precipitation in the tropics and midlatitudes, this study provides a comprehensive view of how aerosols affect cloud cover, cloud top height, and radiative forcing. We found that although the widely accepted theory of DCC invigoration due to aerosol's thermodynamic effect (additional latent heat release from freezing of greater amount of cloud water) may work during the growing stage, it is microphysical effect influenced by aerosols that drives the dramatic increase in cloud cover, cloud top height, and cloud thickness at the mature and dissipation stages by inducing larger amounts of smaller but longer-lasting ice particles in the stratiform/anvils of DCCs, even when thermodynamic invigoration of convection is absent. The thermodynamic invigoration effect contributes up to ~27% of total increase in cloud cover. The overall aerosol indirect effect is an atmospheric radiative warming (3-5 W m(-2)) and a surface cooling (-5 to -8 W m(-2)). The modeling findings are confirmed by the analyses of ample measurements made at three sites of distinctly different environments.

Beam Measurements of a CLOUD (Cosmics Leaving OUtdoor Droplets) Chamber

CERN Document Server

Kirkby, Jasper

2001-01-01

A striking correlation has recently been observed between global cloud cover and the flux of incident cosmic rays. The effect of natural variations in the cosmic ray flux is large, causing estimated changes in the Earth's energy radiation balance that are comparable to those attributed to greenhouse gases from the burning of fossil fuels since the Industrial Revolution. However a direct link between cosmic rays and cloud formation has not been unambiguously established. We therefore propose to experimentally measure cloud (water droplet) formation under controlled conditions in a test beam at CERN with a CLOUD chamber, duplicating the conditions prevailing in the troposphere. These data, which have never been previously obtained, will allow a detailed understanding of the possible effects of cosmic rays on clouds and confirm, or otherwise, a direct link between cosmic rays, global cloud cover and the Earth's climate. The measurements will, in turn, allow more reliable calculations to be made of the residual e...

The stepwise discriminant algorithm for snow cover mapping based on FY-3/MERSI data

Science.gov (United States)

Han, Tao; Wang, Dawei; Jiang, Youyan; Wang, Xiaowei

2013-10-01

Medium Resolution Spectral Imager (MERSI) on board China's new generation polar orbit meteorological satellite FY- 3A provides a new data source for snow monitoring in large area. As a case study, the typical snow cover of Qilian Mountains in northwest China was selected in this paper to develop the algorithm to map snow cover using FY- 3A/MERSI. By analyzing the spectral response characteristics of snow and other surface elements, as well as each channel image quality on FY-3A/MERSI, the widely used Normalized Difference Snow Index (NDSI) was defined to be computed from channel 2 and channel 7 for this satellite data. Basing on NDSI, a tree-structure prototype version of snow identification model was proposed, including five newly-built multi-spectral indexes to remove those pixels such as forest, cloud shadow, water, lake ice, sand (salty land), or cloud that are usually confused with snow step by step, especially, a snow/cloud discrimination index was proposed to eliminate cloud, apart from use of cloud mask product in advance. Furthermore, land cover land use (LULC) image has been adopted as auxiliary dataset to adjust the corresponding LULC NDSI threshold constraints for snow final determination and optimization. This model is composed as the core of FY-3A/MERSI snow cover mapping flowchart, to produce daily snow map at 250m spatial resolution, and statistics can be generated on the extent and persistence of snow cover in each pixel for time series maps. Preliminary validation activities of our snow identification model have been undertaken. Comparisons of the 104 FY- 3A/MERSI snow cover maps in 2010-2011 snow season with snow depth records from 16 meteorological stations in Qilian Mountains region, the sunny snow cover had an absolute accuracy of 92.8%. Results of the comparison with the snow cover identified from 6 Terra/MODIS scenes showed that they had consistent pixels about 85%. When the two satellite resultant snow cover maps compared with the 6

Quantifying the impact of cloud cover on ground radiation flux measurements using hemispherical images

NARCIS (Netherlands)

Roupioz, L.; Colin, J.; Jia, L.; Nerry, F.; Menenti, M.

2015-01-01

Linking observed or estimated ground incoming solar radiation with cloud coverage is difficult since the latter is usually poorly described in standard meteorological observation protocols. To investigate the benefits of detailed observation and characterization of cloud coverage and

Atmospheric Correction Performance of Hyperspectral Airborne Imagery over a Small Eutrophic Lake under Changing Cloud Cover

Directory of Open Access Journals (Sweden)

Lauri Markelin

2016-12-01

Full Text Available Atmospheric correction of remotely sensed imagery of inland water bodies is essential to interpret water-leaving radiance signals and for the accurate retrieval of water quality variables. Atmospheric correction is particularly challenging over inhomogeneous water bodies surrounded by comparatively bright land surface. We present results of AisaFENIX airborne hyperspectral imagery collected over a small inland water body under changing cloud cover, presenting challenging but common conditions for atmospheric correction. This is the first evaluation of the performance of the FENIX sensor over water bodies. ATCOR4, which is not specifically designed for atmospheric correction over water and does not make any assumptions on water type, was used to obtain atmospherically corrected reflectance values, which were compared to in situ water-leaving reflectance collected at six stations. Three different atmospheric correction strategies in ATCOR4 was tested. The strategy using fully image-derived and spatially varying atmospheric parameters produced a reflectance accuracy of ±0.002, i.e., a difference of less than 15% compared to the in situ reference reflectance. Amplitude and shape of the remotely sensed reflectance spectra were in general accordance with the in situ data. The spectral angle was better than 4.1° for the best cases, in the spectral range of 450–750 nm. The retrieval of chlorophyll-a (Chl-a concentration using a popular semi-analytical band ratio algorithm for turbid inland waters gave an accuracy of ~16% or 4.4 mg/m3 compared to retrieval of Chl-a from reflectance measured in situ. Using fixed ATCOR4 processing parameters for whole images improved Chl-a retrieval results from ~6 mg/m3 difference to reference to approximately 2 mg/m3. We conclude that the AisaFENIX sensor, in combination with ATCOR4 in image-driven parametrization, can be successfully used for inland water quality observations. This implies that the need for in situ

Cloud cover over the equatorial eastern Pacific derived from July 1983 International Satellite Cloud Climatology Project data using a hybrid bispectral threshold method

Science.gov (United States)

Minnis, Patrick; Harrison, Edwin F.; Gibson, Gary G.

1987-01-01

A set of visible and IR data obtained with GOES from July 17-31, 1983 is analyzed using a modified version of the hybrid bispectral threshold method developed by Minnis and Harrison (1984). This methodology can be divided into a set of procedures or optional techniques to determine the proper contaminate clear-sky temperature or IR threshold. The various optional techniques are described; the options are: standard, low-temperature limit, high-reflectance limit, low-reflectance limit, coldest pixel and thermal adjustment limit, IR-only low-cloud temperature limit, IR clear-sky limit, and IR overcast limit. Variations in the cloud parameters and the characteristics and diurnal cycles of trade cumulus and stratocumulus clouds over the eastern equatorial Pacific are examined. It is noted that the new method produces substantial changes in about one third of the cloud amount retrieval; and low cloud retrievals are affected most by the new constraints.

Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas

Science.gov (United States)

2014-09-30

developed by incorporating the proposed IR sensors and ground-sky temperature difference algorithm into a tethered balloon borne payload (Figure 3...into the cloud base. RESULTS FROM FY 2014 • A second flight of the tethered balloon -borne IR cloud margin sensor was conducted in Colorado on...Figure 3: Tethered balloon -borne IR sensing payload IR Cloud Margin Sensor Figure 4: First successful flight validation of the IR cloud

CERN Computing Colloquium | Hidden in the Clouds: New Ideas in Cloud Computing | 30 May

CERN Multimedia

2013-01-01

by Dr. Shevek (NEBULA) Thursday 30 May 2013 from 2 p.m. to 4 p.m. at CERN ( 40-S2-D01 - Salle Dirac ) Abstract: Cloud computing has become a hot topic. But 'cloud' is no newer in 2013 than MapReduce was in 2005: We've been doing both for years. So why is cloud more relevant today than it ever has been? In this presentation, we will introduce the (current) central thesis of cloud computing, and explore how and why (or even whether) the concept has evolved. While we will cover a little light background, our primary focus will be on the consequences, corollaries and techniques introduced by some of the leading cloud developers and organizations. We each have a different deployment model, different applications and workloads, and many of us are still learning to efficiently exploit the platform services offered by a modern implementation. The discussion will offer the opportunity to share these experiences and help us all to realize the benefits of cloud computing to the ful...

Technology Trends in Cloud Infrastructure

CERN Multimedia

CERN. Geneva

2018-01-01

Cloud computing is growing at an exponential pace with an increasing number of workloads being hosted in mega-scale public clouds such as Microsoft Azure. Designing and operating such large infrastructures requires not only a significant capital spend for provisioning datacenters, servers, networking and operating systems, but also R&D investments to capitalize on disruptive technology trends and emerging workloads such as AI/ML. This talk will cover the various infrastructure innovations being implemented in large scale public clouds and opportunities/challenges ahead to deliver the next generation of scale computing. About the speaker Kushagra Vaid is the general manager and distinguished engineer for Hardware Infrastructure in the Microsoft Azure division. He is accountable for the architecture and design of compute and storage platforms, which are the foundation for Microsoft’s global cloud-scale services. He and his team have successfully delivered four generations of hyperscale cloud hardwar...

In search of the best match: probing a multi-dimensional cloud microphysical parameter space to better understand what controls cloud thermodynamic phase

Science.gov (United States)

Tan, Ivy; Storelvmo, Trude

2015-04-01

Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters, which are also notoriously fraught with uncertainties. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has neglected to focus on improving the ability of GCMs to accurately simulate the present-day global distribution of thermodynamic phase partitioning in mixed-phase clouds. Liquid droplets and ice crystals not only influence the Earth's radiative budget and hence climate sensitivity via their contrasting optical properties, but also through the effects of their lifetimes in the atmosphere. The current study employs NCAR's CAM5.1, and uses observations of cloud phase obtained by NASA's CALIOP lidar over a 79-month period (November 2007 to June 2014) guide the accurate simulation of the global distribution of mixed-phase clouds in 20∘ latitudinal bands at the -10∘ C, -20∘C and -30∘C isotherms, by adjusting six relevant cloud microphysical tuning parameters in the CAM5.1 via Quasi-Monte Carlo sampling. Among the parameters include those that control the Wegener-Bergeron-Findeisen (WBF) timescale for the conversion of supercooled liquid droplets to ice and snow in mixed-phase clouds, the fraction of ice nuclei that nucleate ice in the atmosphere, ice crystal sedimentation speed, and wet scavenging in stratiform and convective clouds. Using a Generalized Linear Model as a variance-based sensitivity analysis, the relative contributions of each of the six parameters are quantified to gain a better understanding of the importance of their individual and two-way interaction effects on the liquid to ice proportion in mixed-phase clouds. Thus, the methodology implemented in the current study aims to search for the combination of cloud microphysical parameters in a GCM that

Retrieval of liquid water cloud properties from ground-based remote sensing observations

NARCIS (Netherlands)

Knist, C.L.

2014-01-01

Accurate ground-based remotely sensed microphysical and optical properties of liquid water clouds are essential references to validate satellite-observed cloud properties and to improve cloud parameterizations in weather and climate models. This requires the evaluation of algorithms for retrieval of

Cloud Type Classification (cldtype) Value-Added Product

Energy Technology Data Exchange (ETDEWEB)

Flynn, Donna [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Shi, Yan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lim, K-S [Korean Atomic Energy Research Inst., Daejeon (South Korea); Riihimaki, Laura [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2017-08-15

The Cloud Type (cldtype) value-added product (VAP) provides an automated cloud type classification based on macrophysical quantities derived from vertically pointing lidar and radar. Up to 10 layers of clouds are classified into seven cloud types based on predetermined and site-specific thresholds of cloud top, base and thickness. Examples of thresholds for selected U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility sites are provided in Tables 1 and 2. Inputs for the cldtype VAP include lidar and radar cloud boundaries obtained from the Active Remotely Sensed Cloud Location (ARSCL) and Surface Meteorological Systems (MET) data. Rain rates from MET are used to determine when radar signal attenuation precludes accurate cloud detection. Temporal resolution and vertical resolution for cldtype are 1 minute and 30 m respectively and match the resolution of ARSCL. The cldtype classification is an initial step for further categorization of clouds. It was developed for use by the Shallow Cumulus VAP to identify potential periods of interest to the LASSO model and is intended to find clouds of interest for a variety of users.

GEWEX cloud assessment: A review

Science.gov (United States)

Stubenrauch, Claudia; Rossow, William B.; Kinne, Stefan; Ackerman, Steve; Cesana, Gregory; Chepfer, Hélène; Di Girolamo, Larry; Getzewich, Brian; Guignard, Anthony; Heidinger, Andy; Maddux, Brent; Menzel, Paul; Minnis, Patrick; Pearl, Cindy; Platnick, Steven; Poulsen, Caroline; Riedi, Jérôme; Sayer, Andrew; Sun-Mack, Sunny; Walther, Andi; Winker, Dave; Zeng, Shen; Zhao, Guangyu

2013-05-01

Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provides the first coordinated intercomparison of publicly available, global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multi-angle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. The monthly, gridded database presented here facilitates further assessments, climate studies, and the evaluation of climate models.

Services Recommendation System based on Heterogeneous Network Analysis in Cloud Computing

OpenAIRE

Junping Dong; Qingyu Xiong; Junhao Wen; Peng Li

2014-01-01

Resources are provided mainly in the form of services in cloud computing. In the distribute environment of cloud computing, how to find the needed services efficiently and accurately is the most urgent problem in cloud computing. In cloud computing, services are the intermediary of cloud platform, services are connected by lots of service providers and requesters and construct the complex heterogeneous network. The traditional recommendation systems only consider the functional and non-functi...

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies

Science.gov (United States)

Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O`Halloran, John

2015-01-01

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting. PMID:26262681

Selective cooling on land supports cloud formation by cosmic ray during geomagnetic reversals

Science.gov (United States)

Kitaba, I.; Hyodo, M.; Nakagawa, T.; Katoh, S.; Dettman, D. L.; Sato, H.

2017-12-01

On geological time scales, the galactic cosmic ray (GCR) flux at the Earth's surface has increased significantly during many short time intervals. There is a growing body of evidence that suggests that climatic cooling occurred during these episodes. Cloud formation by GCR has been claimed as the most likely cause of the linkage. However, the mechanism is not fully understood due to the difficulty of accurately estimating the amount of cloud cover in the geologic past. Our study focused on the geomagnetic field and climate in East Asia. The Earth's magnetic field provides a shield against GCR. The East Asian climate reflects the temperature balance between the Eurasian landmass and the Pacific Ocean that drives monsoon circulation.Two geomagnetic polarity reversals occurred at 780 ka and 1,070 ka. At these times the geomagnetic field decreased to about 10% of its present level causing a near doubling of the GCR flux. Temperature and rainfall amounts during these episodes were reconstructed using pollen in sediment cores from Osaka Bay, Japan. The results show a more significant temperature drop on the Eurasian continent than over the Pacific, and a decrease of summer rainfall in East Asia (i.e. a weakening of East Asian summer monsoon). These observed climate changes can be accounted for if the landmasses were more strongly cooled than the oceans. The simplest mechanism behind such asymmetric cooling is the so-called `umbrella effect' (increased cloud cover blocking solar radiation) that induces greater cooling of objects with smaller heat capacities.

Advancing the quantification of humid tropical forest cover loss with multi-resolution optical remote sensing data: Sampling & wall-to-wall mapping

Science.gov (United States)

Broich, Mark

best Landsat images. Such an approach does not provide timely results, and cloud cover reduces the utility of map outputs. In a second study, I develop a method to exhaustively mine the recently opened Landsat archive for cloud-free observations and automatically map forest cover loss for Sumatra and Kalimantan for the 2000-2005 interval. In a comparison with a reference dataset consisting of 64 Landsat sample blocks, I show that my method, using per pixel time-series, provides more accurate forest cover loss maps for multiyear intervals than approaches using image composites. In a third study, I disaggregate Landsat-mapped forest cover loss, mapped over a multiyear interval, by year using annual forest cover loss maps generated from coarse spatial, high temporal resolution MODIS imagery. I further disaggregate and analyze forest cover loss by forest land use, and provinces. Forest cover loss trends show high spatial and temporal variability. These results underline the importance of annual mapping for the quantification of forest cover loss in Indonesia, specifically in the light of the developing Reducing Emissions from Deforestation and Forest Degradation in Developing Countries policy framework (REDD). All three studies highlight the advances in quantifying forest cover loss in the humid tropics made by integrating coarse spatial, high temporal resolution data with moderate spatial, low temporal resolution data. The three methods presented can be combined into an integrated monitoring strategy.

Impact of deforestation in the Amazon basin on cloud climatology.

Science.gov (United States)

Wang, Jingfeng; Chagnon, Frédéric J F; Williams, Earle R; Betts, Alan K; Renno, Nilton O; Machado, Luiz A T; Bisht, Gautam; Knox, Ryan; Bras, Rafael L

2009-03-10

Shallow clouds are prone to appear over deforested surfaces whereas deep clouds, much less frequent than shallow clouds, favor forested surfaces. Simultaneous atmospheric soundings at forest and pasture sites during the Rondonian Boundary Layer Experiment (RBLE-3) elucidate the physical mechanisms responsible for the observed correlation between clouds and land cover. We demonstrate that the atmospheric boundary layer over the forested areas is more unstable and characterized by larger values of the convective available potential energy (CAPE) due to greater humidity than that which is found over the deforested area. The shallow convection over the deforested areas is relatively more active than the deep convection over the forested areas. This greater activity results from a stronger lifting mechanism caused by mesoscale circulations driven by deforestation-induced heterogeneities in land cover.

Unveiling aerosol-cloud interactions - Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate

Science.gov (United States)

Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.; Thomas, Gareth E.; McGarragh, Gregory R.; Povey, Adam C.; Proud, Simon R.; Grainger, Roy G.

2017-11-01

Increased concentrations of aerosol can enhance the albedo of warm low-level cloud. Accurately quantifying this relationship from space is challenging due in part to contamination of aerosol statistics near clouds. Aerosol retrievals near clouds can be influenced by stray cloud particles in areas assumed to be cloud-free, particle swelling by humidification, shadows and enhanced scattering into the aerosol field from (3-D radiative transfer) clouds. To screen for this contamination we have developed a new cloud-aerosol pairing algorithm (CAPA) to link cloud observations to the nearest aerosol retrieval within the satellite image. The distance between each aerosol retrieval and nearest cloud is also computed in CAPA. Results from two independent satellite imagers, the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS), show a marked reduction in the strength of the intrinsic aerosol indirect radiative forcing when selecting aerosol pairs that are located farther away from the clouds (-0.28±0.26 W m-2) compared to those including pairs that are within 15 km of the nearest cloud (-0.49±0.18 W m-2). The larger aerosol optical depths in closer proximity to cloud artificially enhance the relationship between aerosol-loading, cloud albedo, and cloud fraction. These results suggest that previous satellite-based radiative forcing estimates represented in key climate reports may be exaggerated due to the inclusion of retrieval artefacts in the aerosol located near clouds.

Optical Instruments Synergy in Determination of Optical Depth of Thin Clouds

Energy Technology Data Exchange (ETDEWEB)

Vladutescu, Daniela V.; Schwartz, Stephen E.

2017-06-25

Optically thin clouds have a strong radiative effect and need to be represented accurately in climate models. Cloud optical depth of thin clouds was retrieved using high resolution digital photography, lidar, and a radiative transfer model. The Doppler Lidar was operated at 1.5 μm, minimizing return from Rayleigh scattering, emphasizing return from aerosols and clouds. This approach examined cloud structure on scales 3 to 5 orders of magnitude finer than satellite products, opening new avenues for examination of cloud structure and evolution.

An A-Train Climatology of Extratropical Cyclone Clouds

Science.gov (United States)

Posselt, Derek J.; van den Heever, Susan C.; Booth, James F.; Del Genio, Anthony D.; Kahn, Brian; Bauer, Mike

2016-01-01

Extratropical cyclones (ETCs) are the main purveyors of precipitation in the mid-latitudes, especially in winter, and have a significant radiative impact through the clouds they generate. However, general circulation models (GCMs) have trouble representing precipitation and clouds in ETCs, and this might partly explain why current GCMs disagree on to the evolution of these systems in a warming climate. Collectively, the A-train observations of MODIS, CloudSat, CALIPSO, AIRS and AMSR-E have given us a unique perspective on ETCs: over the past 10 years these observations have allowed us to construct a climatology of clouds and precipitation associated with these storms. This has proved very useful for model evaluation as well in studies aimed at improving understanding of moist processes in these dynamically active conditions. Using the A-train observational suite and an objective cyclone and front identification algorithm we have constructed cyclone centric datasets that consist of an observation-based characterization of clouds and precipitation in ETCs and their sensitivity to large scale environments. In this presentation, we will summarize the advances in our knowledge of the climatological properties of cloud and precipitation in ETCs acquired with this unique dataset. In particular, we will present what we have learned about southern ocean ETCs, for which the A-train observations have filled a gap in this data sparse region. In addition, CloudSat and CALIPSO have for the first time provided information on the vertical distribution of clouds in ETCs and across warm and cold fronts. We will also discuss how these observations have helped identify key areas for improvement in moist processes in recent GCMs. Recently, we have begun to explore the interaction between aerosol and cloud cover in ETCs using MODIS, CloudSat and CALIPSO. We will show how aerosols are climatologically distributed within northern hemisphere ETCs, and how this relates to cloud cover.

On the regional climatic impact of contrails: microphysical and radiative properties of contrails and natural cirrus clouds

Directory of Open Access Journals (Sweden)

B. Strauss

Full Text Available The impact of contrail-induced cirrus clouds on regional climate is estimated for mean atmospheric conditions of southern Germany in the months of July and October. This is done by use of a regionalized one-dimensional radiative convective model (RCM. The influence of an increased ice cloud cover is studied by comparing RCM results representing climatological values with a modified case. In order to study the sensitivity of this effect on the radiative characteristics of the ice cloud, two types of additional ice clouds were modelled: cirrus and contrails, the latter cloud type containing a higher number of smaller and less of the larger cloud particles. Ice cloud parameters are calculated on the basis of a particle size distribution which covers the range from 2 to 2000 µm, taking into consideration recent measurements which show a remarkable amount of particles smaller than 20 µm. It turns out that a 10% increase in ice cloud cover leads to a surface temperature increase in the order of 1K, ranging from 1.1 to 1.2K in July and from 0.8 to 0.9K in October depending on the radiative characteristics of the air-traffic-induced ice clouds. Modelling the current contrail cloud cover which is near 0.5% over Europe yields a surface temperature increase in the order of 0.05K.

On the regional climatic impact of contrails: microphysical and radiative properties of contrails and natural cirrus clouds

Directory of Open Access Journals (Sweden)

B. Strauss

1997-11-01

Full Text Available The impact of contrail-induced cirrus clouds on regional climate is estimated for mean atmospheric conditions of southern Germany in the months of July and October. This is done by use of a regionalized one-dimensional radiative convective model (RCM. The influence of an increased ice cloud cover is studied by comparing RCM results representing climatological values with a modified case. In order to study the sensitivity of this effect on the radiative characteristics of the ice cloud, two types of additional ice clouds were modelled: cirrus and contrails, the latter cloud type containing a higher number of smaller and less of the larger cloud particles. Ice cloud parameters are calculated on the basis of a particle size distribution which covers the range from 2 to 2000 µm, taking into consideration recent measurements which show a remarkable amount of particles smaller than 20 µm. It turns out that a 10% increase in ice cloud cover leads to a surface temperature increase in the order of 1K, ranging from 1.1 to 1.2K in July and from 0.8 to 0.9K in October depending on the radiative characteristics of the air-traffic-induced ice clouds. Modelling the current contrail cloud cover which is near 0.5% over Europe yields a surface temperature increase in the order of 0.05K.

Thermal structure of intense convective clouds derived from GPS radio occultations

DEFF Research Database (Denmark)

Biondi, Riccardo; Randel, W. J.; Ho, S. -P.

2012-01-01

Thermal structure associated with deep convective clouds is investigated using Global Positioning System (GPS) radio occultation measurements. GPS data are insensitive to the presence of clouds, and provide high vertical resolution and high accuracy measurements to identify associated temperature...... behavior. Deep convective systems are identified using International Satellite Cloud Climatology Project (ISCCP) satellite data, and cloud tops are accurately measured using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) lidar observations; we focus on 53 cases of near-coincident GPS...

Thermal structure of intense convective clouds derived from GPS radio occultations

DEFF Research Database (Denmark)

Biondi, Riccardo; Randel, W. J.; Ho, S.-P.

2011-01-01

Thermal structure associated with deep convective clouds is investigated using Global Positioning System (GPS) radio occultation measurements. GPS data are insensitive to the presence of clouds, and provide high vertical resolution and high accuracy measurements to identify associated temperature...... behavior. Deep convective systems are identified using International Satellite Cloud Climatology Project (ISCCP) satellite data, and cloud tops are accurately measured using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) lidar observations; we focus on 53 cases of near-coincident GPS...

Cloud computing and digital media fundamentals, techniques, and applications

CERN Document Server

Li, Kuan-Ching; Shih, Timothy K

2014-01-01

Cloud Computing and Digital Media: Fundamentals, Techniques, and Applications presents the fundamentals of cloud and media infrastructure, novel technologies that integrate digital media with cloud computing, and real-world applications that exemplify the potential of cloud computing for next-generation digital media. It brings together technologies for media/data communication, elastic media/data storage, security, authentication, cross-network media/data fusion, interdevice media interaction/reaction, data centers, PaaS, SaaS, and more.The book covers resource optimization for multimedia clo

Sensitivity of PARASOL multi-angle photopolarimetric aerosol retrievals to cloud contamination

NARCIS (Netherlands)

Stap, F. A.; Hasekamp, O. P.; Roeckmann, Thomas

2015-01-01

An important problem in satellite remote sensing of aerosols is related to the need to perform an adequate cloud screening. If a cloud screening is applied that is not strict enough, the ground scene has the probability of residual cloud cover which causes large errors on the retrieved aerosol

Influence on the radiation regime and climate of dust aerosols and extensive cloud cover

Energy Technology Data Exchange (ETDEWEB)

Kondratev, K Ya; Binenko, V I; Zhavalev, V F; Ivonav, V A; Ter-Markaryants, N E

1983-04-01

The Global Aerosol/Radiation Experiment (GAREX) research programs, carried out in the Kara-Kum desert and in the Arctic and Kamchatka peninsula, has yielded the following conclusions: In the presence of liquid or particulate aerosols, the albedo of the underlying surface/atmosphere system increase over a weakly reflecting surface (water) and decreases over a highly reflecting surface (snow, ice). The albedo of ice of varying concentration and type ranges from 0.4 to 0.8 according to observations from an altitude of 200 m, reaching a maximum in the visible range of the spectrum. The albedo of clouds over the Arctic is noticeably greater than that of similar clouds over a city, over dry land, or over water in the European part of the USSR. The presence of particulates from volcanoes increases the albedo of clouds, but their influence is small in comparison with anthropogenic aerosols (mostly soot). The emissivity of clouds in the Arctic is less than unity, due to the predominance of ice crystals. In the Arctic, underlying surfaces typically have a large anisotropic reflection. 8 references, 3 figures, 2 tables.

AP-Cloud: Adaptive Particle-in-Cloud method for optimal solutions to Vlasov–Poisson equation

International Nuclear Information System (INIS)

Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin; Yu, Kwangmin

2016-01-01

We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes of computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.

Cloud Tolerance of Remote-Sensing Technologies to Measure Land Surface Temperature

Science.gov (United States)

Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

2016-01-01

Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared(TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave(MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product. This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

Retrieval of effective cloud field parameters from radiometric data

Science.gov (United States)

Paulescu, Marius; Badescu, Viorel; Brabec, Marek

2017-06-01

Clouds play a key role in establishing the Earth's climate. Real cloud fields are very different and very complex in both morphological and microphysical senses. Consequently, the numerical description of the cloud field is a critical task for accurate climate modeling. This study explores the feasibility of retrieving the effective cloud field parameters (namely the cloud aspect ratio and cloud factor) from systematic radiometric measurements at high frequency (measurement is taken every 15 s). Two different procedures are proposed, evaluated, and discussed with respect to both physical and numerical restrictions. None of the procedures is classified as best; therefore, the specific advantages and weaknesses are discussed. It is shown that the relationship between the cloud shade and point cloudiness computed using the estimated cloud field parameters recovers the typical relationship derived from measurements.

Comparison of cloud optical depth and cloud mask applying BRDF model-based background surface reflectance

Science.gov (United States)

Kim, H. W.; Yeom, J. M.; Woo, S. H.

2017-12-01

Over the thin cloud region, satellite can simultaneously detect the reflectance from thin clouds and land surface. Since the mixed reflectance is not the exact cloud information, the background surface reflectance should be eliminated to accurately distinguish thin cloud such as cirrus. In the previous research, Kim et al (2017) was developed the cloud masking algorithm using the Geostationary Ocean Color Imager (GOCI), which is one of significant instruments for Communication, Ocean, and Meteorology Satellite (COMS). Although GOCI has 8 spectral channels including visible and near infra-red spectral ranges, the cloud masking has quantitatively reasonable result when comparing with MODIS cloud mask (Collection 6 MYD35). Especially, we noticed that this cloud masking algorithm is more specialized in thin cloud detections through the validation with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data. Because this cloud masking method was concentrated on eliminating background surface effects from the top-of-atmosphere (TOA) reflectance. Applying the difference between TOA reflectance and the bi-directional reflectance distribution function (BRDF) model-based background surface reflectance, cloud areas both thick cloud and thin cloud can be discriminated without infra-red channels which were mostly used for detecting clouds. Moreover, when the cloud mask result was utilized as the input data when simulating BRDF model and the optimized BRDF model-based surface reflectance was used for the optimized cloud masking, the probability of detection (POD) has higher value than POD of the original cloud mask. In this study, we examine the correlation between cloud optical depth (COD) and its cloud mask result. Cloud optical depths mostly depend on the cloud thickness, the characteristic of contents, and the size of cloud contents. COD ranges from less than 0.1 for thin clouds to over 1000 for the huge cumulus due to scattering by droplets. With

Evaluation of stratocumulus cloud prediction in the Met Office forecast model during VOCALS-REx

Directory of Open Access Journals (Sweden)

S. J. Abel

2010-11-01

Full Text Available Observations in the subtropical southeast Pacific obtained during the VOCALS-REx field experiment are used to evaluate the representation of stratocumulus cloud in the Met Office forecast model and to identify key areas where model biases exist. Marked variations in the large scale structure of the cloud field were observed during the experiment on both day-to-day and on diurnal timescales. In the remote maritime region the model is shown to have a good representation of synoptically induced variability in both cloud cover and marine boundary layer depth. Satellite observations show a strong diurnal cycle in cloud fraction and liquid water path in the stratocumulus with enhanced clearances of the cloud deck along the Chilean and Peruvian coasts on certain days. The model accurately simulates the phase of the diurnal cycle but is unable to capture the coastal clearing of cloud. Observations along the 20° S latitude line show a gradual increase in the depth of the boundary layer away from the coast. This trend is well captured by the model (typical low bias of 200 m although significant errors exist at the coast where the model marine boundary layer is too shallow and moist. Drizzle in the model responds to changes in liquid water path in a manner that is consistent with previous ship-borne observations in the region although the intensity of this drizzle is likely to be too high, particularly in the more polluted coastal region where higher cloud droplet number concentrations are typical. Another mode of variability in the cloud field that the model is unable to capture are regions of pockets of open cellular convection embedded in the overcast stratocumulus deck and an example of such a feature that was sampled during VOCALS-REx is shown.

NH4SH and cloud cover in the atmospheres of the giant planets

Science.gov (United States)

Ibragimov, K. Iu.; Solodovnik, A. A.

1991-02-01

The probability of the formation of NH4SH and (NH4)2S is examined on the basis of the Le Chatelier principle. It is shown that it is very doubtful if NH4SH can be created in the atmospheres of the giant planets in quantities sufficient for cloud formation. Thus (NH4)2S is considered as a more likely candidate for cloud formation in the atmospheres of these planets, inasmuch as the conditions for its production there are more favorable.

Validation of MODIS snow cover images over Austria

Directory of Open Access Journals (Sweden)

J. Parajka

2006-01-01

Full Text Available This study evaluates the Moderate Resolution Imaging Spectroradiometer (MODIS snow cover product over the territory of Austria. The aims are (a to analyse the spatial and temporal variability of the MODIS snow product classes, (b to examine the accuracy of the MODIS snow product against in situ snow depth data, and (c to identify the main factors that may influence the MODIS classification accuracy. We use daily MODIS grid maps (version 4 and daily snow depth measurements at 754 climate stations in the period from February 2000 to December 2005. The results indicate that, on average, clouds obscured 63% of Austria, which may significantly restrict the applicability of the MODIS snow cover images to hydrological modelling. On cloud-free days, however, the classification accuracy is very good with an average of 95%. There is no consistent relationship between the classification errors and dominant land cover type and local topographical variability but there are clear seasonal patterns to the errors. In December and January the errors are around 15% while in summer they are less than 1%. This seasonal pattern is related to the overall percentage of snow cover in Austria, although in spring, when there is a well developed snow pack, errors tend to be smaller than they are in early winter for the same overall percent snow cover. Overestimation and underestimation errors balance during most of the year which indicates little bias. In November and December, however, there appears to exist a tendency for overestimation. Part of the errors may be related to the temporal shift between the in situ snow depth measurements (07:00 a.m. and the MODIS acquisition time (early afternoon. The comparison of daily air temperature maps with MODIS snow cover images indicates that almost all MODIS overestimation errors are caused by the misclassification of cirrus clouds as snow.

On the retrieval of ice cloud particle shapes from POLDER measurements

International Nuclear Information System (INIS)

Sun Wenbo; Loeb, Norman G.; Yang Ping

2006-01-01

Shapes of ice crystals can significantly affect the radiative transfer in ice clouds. The angular distribution of the polarized reflectance over ice clouds strongly depends on ice crystal shapes. Although the angular-distribution features of the total or polarized reflectance over ice clouds imply a possibility of retrieving ice cloud particle shapes by use of remote sensing data, the accuracy of the retrieval must be evaluated. In this study, a technique that applies single ice crystal habit and multidirectional polarized radiance to retrieve ice cloud particle shapes is assessed. Our sensitivity studies show that the retrieved particle shapes from this algorithm can be considered good approximations to those in actual clouds in calculation of the phase matrix elements. However, this algorithm can only work well under the following conditions: (1) the retrievable must be overcast and thick ice cloud pixels, (2) the particles in the cloud must be randomly oriented, (3) the particle shapes and size distributions used in the lookup tables must be representative, and (4) the multi-angle polarized measurements must be accurate and sufficient to identify ice cloud pixels of randomly oriented particles. In practice, these conditions will exclude most of the measured cloud pixels. Additionally, because the polarized measurements are only sensitive to the upper cloud part not deeper than an optical thickness of 4, the retrieved particle shapes with the polarized radiance may only approximate those in the upper parts of the clouds. In other words, for thicker clouds with vertical inhomogeneity in particle shapes, these retrieved particle shapes cannot represent those of whole clouds. More robust algorithm is needed in accurate retrieval of ice cloud particle shapes

Cosmic rays linked to rapid mid-latitude cloud changes

Directory of Open Access Journals (Sweden)

B. A. Laken

2010-11-01

Full Text Available The effect of the Galactic Cosmic Ray (GCR flux on Earth's climate is highly uncertain. Using a novel sampling approach based around observing periods of significant cloud changes, a statistically robust relationship is identified between short-term GCR flux changes and the most rapid mid-latitude (60°–30° N/S cloud decreases operating over daily timescales; this signal is verified in surface level air temperature (SLAT reanalysis data. A General Circulation Model (GCM experiment is used to test the causal relationship of the observed cloud changes to the detected SLAT anomalies. Results indicate that the anomalous cloud changes were responsible for producing the observed SLAT changes, implying that if there is a causal relationship between significant decreases in the rate of GCR flux (~0.79 GU, where GU denotes a change of 1% of the 11-year solar cycle amplitude in four days and decreases in cloud cover (~1.9 CU, where CU denotes a change of 1% cloud cover in four days, an increase in SLAT (~0.05 KU, where KU denotes a temperature change of 1 K in four days can be expected. The influence of GCRs is clearly distinguishable from changes in solar irradiance and the interplanetary magnetic field. However, the results of the GCM experiment are found to be somewhat limited by the ability of the model to successfully reproduce observed cloud cover. These results provide perhaps the most compelling evidence presented thus far of a GCR-climate relationship. From this analysis we conclude that a GCR-climate relationship is governed by both short-term GCR changes and internal atmospheric precursor conditions.

Cloud classification using whole-sky imager data

Energy Technology Data Exchange (ETDEWEB)

Buch, K.A. Jr.; Sun, C.H.; Thorne, L.R. [Sandia National Labs., Livermore, CA (United States)

1996-04-01

Clouds are one of the most important moderators of the earth radiation budget and one of the least understood. The effect that clouds have on the reflection and absorption of solar and terrestrial radiation is strongly influenced by their shape, size, and composition. Physically accurate parameterization of clouds is necessary for any general circulation model (GCM) to yield meaningful results. The work presented here is part of a larger project that is aimed at producing realistic three-dimensional (3D) volume renderings of cloud scenes based on measured data from real cloud scenes. These renderings will provide the important shape information for parameterizing GCMs. The specific goal of the current study is to develop an algorithm that automatically classifies (by cloud type) the clouds observed in the scene. This information will assist the volume rendering program in determining the shape of the cloud. Much work has been done on cloud classification using multispectral satellite images. Most of these references use some kind of texture measure to distinguish the different cloud types and some also use topological features (such as cloud/sky connectivity or total number of clouds). A wide variety of classification methods has been used, including neural networks, various types of clustering, and thresholding. The work presented here uses binary decision trees to distinguish the different cloud types based on cloud features vectors.

Monitoring and evaluation of seasonal snow cover in Kashmir valley ...

Indian Academy of Sciences (India)

89 to 2007–08) climatic conditions prevailed in both ranges of Kashmir valley. Region-wise ... effective use of snowmelt runoff models (Rango and Martinec ... J. Earth Syst. Sci. 118, No. ... of cloud cover can affect delineation of snow cover,.

A model of the microphysical evolution of a cloud

International Nuclear Information System (INIS)

Zinn, J.

1994-01-01

The earth's weather and climate are influenced strongly by phenomena associated with clouds. Therefore, a general circulation model (GCM) that models the evolution of weather and climate must include an accurate physical model of the clouds. This paper describes efforts to develop a suitable cloud model. It concentrates on the microphysical processes that determine the evolution of droplet and ice crystal size distributions, precipitation rates, total and condensed water content, and radiative extinction coefficients

A study of Monte Carlo radiative transfer through fractal clouds

Energy Technology Data Exchange (ETDEWEB)

Gautier, C.; Lavallec, D.; O`Hirok, W.; Ricchiazzi, P. [Univ. of California, Santa Barbara, CA (United States)] [and others

1996-04-01

An understanding of radiation transport (RT) through clouds is fundamental to studies of the earth`s radiation budget and climate dynamics. The transmission through horizontally homogeneous clouds has been studied thoroughly using accurate, discreet ordinates radiative transfer models. However, the applicability of these results to general problems of global radiation budget is limited by the plane parallel assumption and the fact that real clouds fields show variability, both vertically and horizontally, on all size scales. To understand how radiation interacts with realistic clouds, we have used a Monte Carlo radiative transfer model to compute the details of the photon-cloud interaction on synthetic cloud fields. Synthetic cloud fields, generated by a cascade model, reproduce the scaling behavior, as well as the cloud variability observed and estimated from cloud satellite data.

Observational evidence for the aerosol impact on ice cloud properties regulated by cloud/aerosol types

Science.gov (United States)

Zhao, B.; Gu, Y.; Liou, K. N.; Jiang, J. H.; Li, Q.; Liu, X.; Huang, L.; Wang, Y.; Su, H.

2017-12-01

The interactions between aerosols and ice clouds (consisting only of ice) represent one of the largest uncertainties in global radiative forcing from pre-industrial time to the present. The observational evidence for the aerosol impact on ice cloud properties has been quite limited and showed conflicting results, partly because previous observational studies did not consider the distinct features of different ice cloud and aerosol types. Using 9-year satellite observations, we find that, for ice clouds generated from deep convection, cloud thickness, cloud optical thickness (COT), and ice cloud fraction increase and decrease with small-to-moderate and high aerosol loadings, respectively. For in-situ formed ice clouds, however, the preceding cloud properties increase monotonically and more sharply with aerosol loadings. The case is more complicated for ice crystal effective radius (Rei). For both convection-generated and in-situ ice clouds, the responses of Rei to aerosol loadings are modulated by water vapor amount in conjunction with several other meteorological parameters, but the sensitivities of Rei to aerosols under the same water vapor amount differ remarkably between the two ice cloud types. As a result, overall Rei slightly increases with aerosol loading for convection-generated ice clouds, but decreases for in-situ ice clouds. When aerosols are decomposed into different types, an increase in the loading of smoke aerosols generally leads to a decrease in COT of convection-generated ice clouds, while the reverse is true for dust and anthropogenic pollution. In contrast, an increase in the loading of any aerosol type can significantly enhance COT of in-situ ice clouds. The modulation of the aerosol impacts by cloud/aerosol types is demonstrated and reproduced by simulations using the Weather Research and Forecasting (WRF) model. Adequate and accurate representations of the impact of different cloud/aerosol types in climate models are crucial for reducing the

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

Science.gov (United States)

Yost, Christopher R.; Minnis, Patrick; Trepte, Qing Z.; Palikonda, Rabindra; Ayers, Jeffrey K.; Spangenberg, Doulas A.

2012-01-01

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

Using Radar, Lidar, and Radiometer measurements to Classify Cloud Type and Study Middle-Level Cloud Properties

Energy Technology Data Exchange (ETDEWEB)

Wang, Zhien

2010-06-29

The project is mainly focused on the characterization of cloud macrophysical and microphysical properties, especially for mixed-phased clouds and middle level ice clouds by combining radar, lidar, and radiometer measurements available from the ACRF sites. First, an advanced mixed-phase cloud retrieval algorithm will be developed to cover all mixed-phase clouds observed at the ACRF NSA site. The algorithm will be applied to the ACRF NSA observations to generate a long-term arctic mixed-phase cloud product for model validations and arctic mixed-phase cloud processes studies. To improve the representation of arctic mixed-phase clouds in GCMs, an advanced understanding of mixed-phase cloud processes is needed. By combining retrieved mixed-phase cloud microphysical properties with in situ data and large-scale meteorological data, the project aim to better understand the generations of ice crystals in supercooled water clouds, the maintenance mechanisms of the arctic mixed-phase clouds, and their connections with large-scale dynamics. The project will try to develop a new retrieval algorithm to study more complex mixed-phase clouds observed at the ACRF SGP site. Compared with optically thin ice clouds, optically thick middle level ice clouds are less studied because of limited available tools. The project will develop a new two wavelength radar technique for optically thick ice cloud study at SGP site by combining the MMCR with the W-band radar measurements. With this new algorithm, the SGP site will have a better capability to study all ice clouds. Another area of the proposal is to generate long-term cloud type classification product for the multiple ACRF sites. The cloud type classification product will not only facilitates the generation of the integrated cloud product by applying different retrieval algorithms to different types of clouds operationally, but will also support other research to better understand cloud properties and to validate model simulations. The

A 50-m forest cover map in Southeast Asia from ALOS/PALSAR and its application on forest fragmentation assessment.

Directory of Open Access Journals (Sweden)

Jinwei Dong

Full Text Available Southeast Asia experienced higher rates of deforestation than other continents in the 1990s and still was a hotspot of forest change in the 2000s. Biodiversity conservation planning and accurate estimation of forest carbon fluxes and pools need more accurate information about forest area, spatial distribution and fragmentation. However, the recent forest maps of Southeast Asia were generated from optical images at spatial resolutions of several hundreds of meters, and they do not capture well the exceptionally complex and dynamic environments in Southeast Asia. The forest area estimates from those maps vary substantially, ranging from 1.73×10(6 km(2 (GlobCover to 2.69×10(6 km(2 (MCD12Q1 in 2009; and their uncertainty is constrained by frequent cloud cover and coarse spatial resolution. Recently, cloud-free imagery from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR onboard the Advanced Land Observing Satellite (ALOS became available. We used the PALSAR 50-m orthorectified mosaic imagery in 2009 to generate a forest cover map of Southeast Asia at 50-m spatial resolution. The validation, using ground-reference data collected from the Geo-Referenced Field Photo Library and high-resolution images in Google Earth, showed that our forest map has a reasonably high accuracy (producer's accuracy 86% and user's accuracy 93%. The PALSAR-based forest area estimates in 2009 are significantly correlated with those from GlobCover and MCD12Q1 at national and subnational scales but differ in some regions at the pixel scale due to different spatial resolutions, forest definitions, and algorithms. The resultant 50-m forest map was used to quantify forest fragmentation and it revealed substantial details of forest fragmentation. This new 50-m map of tropical forests could serve as a baseline map for forest resource inventory, deforestation monitoring, reducing emissions from deforestation and forest degradation (REDD+ implementation, and

Making the most of the cloud how to choose and implement the best services for your library

CERN Document Server

Hastings, Robin

2014-01-01

Cloud computing can be confusing - the number and types of services that are available through "the cloud" are growing by the day. Making the Most of the Cloud: How to Choose and Implement the Best Services for Your Library takes you through some of the more popular cloud services in libraries and breaks down what you need to know to pick the best one for your library. Some of the cloud services covered are: -Email -Integrated Library Systems (ILS) -Backups -Project Management -Graphics Software -and much more...With chapters covering cloud topics from the definition of a "cloud" to security in the cloud, this book will be beneficial for any library which is thinking of moving their services outside their organization.

Marine Cloud Brightening

Energy Technology Data Exchange (ETDEWEB)

Latham, John; Bower, Keith; Choularton, Tom; Coe, H.; Connolly, P.; Cooper, Gary; Craft, Tim; Foster, Jack; Gadian, Alan; Galbraith, Lee; Iacovides, Hector; Johnston, David; Launder, Brian; Leslie, Brian; Meyer, John; Neukermans, Armand; Ormond, Bob; Parkes, Ben; Rasch, Philip J.; Rush, John; Salter, Stephen; Stevenson, Tom; Wang, Hailong; Wang, Qin; Wood, Robert

2012-09-07

The idea behind the marine cloud-brightening (MCB) geoengineering technique is that seeding marine stratocumulus clouds with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the cloud droplet number concentration, and thereby the cloud albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could - subject to satisfactory resolution of technical and scientific problems identified herein - have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involves (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in cloud brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seedparticle salt-mass, air-mass characteristics, updraught speed and other parameters on cloud-albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, cloud albedo might be enhanced by seeding marine stratocumulus clouds on a spatial scale of around 100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action.

Marine cloud brightening.

Science.gov (United States)

Latham, John; Bower, Keith; Choularton, Tom; Coe, Hugh; Connolly, Paul; Cooper, Gary; Craft, Tim; Foster, Jack; Gadian, Alan; Galbraith, Lee; Iacovides, Hector; Johnston, David; Launder, Brian; Leslie, Brian; Meyer, John; Neukermans, Armand; Ormond, Bob; Parkes, Ben; Rasch, Phillip; Rush, John; Salter, Stephen; Stevenson, Tom; Wang, Hailong; Wang, Qin; Wood, Rob

2012-09-13

The idea behind the marine cloud-brightening (MCB) geoengineering technique is that seeding marine stratocumulus clouds with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the cloud droplet number concentration, and thereby the cloud albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could-subject to satisfactory resolution of technical and scientific problems identified herein-have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involves (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in cloud brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seed-particle salt-mass, air-mass characteristics, updraught speed and other parameters on cloud-albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, cloud albedo might be enhanced by seeding marine stratocumulus clouds on a spatial scale of around 100×100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action.

Three-dimensional cloud characterization from paired whole-sky imaging cameras

International Nuclear Information System (INIS)

Allmen, M.; Kegelmeyer, W.P. Jr.

1994-01-01

Three-dimensional (3-D) cloud characterization permits the derivation of important cloud geometry properties such as fractional cloudiness, mean cloud and clear length, aspect ratio, and the morphology of cloud cover. These properties are needed as input to the hierarchical diagnosis (HD) and instantaneous radiative transfer (IRF) models, to validate sub-models for cloud occurrence and formation, and to Central Site radiative flux calculations. A full 3-D characterization will eventually require the integration of disparate Cloud and Radiation Testbed (CART) data sources: whole-sky imagers (WSIs), radar, satellites, ceilometers, volume-imaging lidar, and other sensors. In this paper, we demonstrate how an initial 3-D cloud property, cloud base height, can be determined from fusing paired times series of images from two whole-sky imagers

Cloud computing and ROI a new framework for it strategy

CERN Document Server

Mohapatra, Sanjay

2014-01-01

This book develops an IT strategy for cloud computing that helps businesses evaluate their readiness for cloud services and calculate the ROI. The framework provided helps reduce risks involved in transitioning from traditional "on site" IT strategy to virtual "cloud computing." Since the advent of cloud computing, many organizations have made substantial gains implementing this innovation. Cloud computing allows companies to focus more on their core competencies, as IT enablement is taken care of through cloud services. Cloud Computing and ROI includes case studies covering retail, automobile and food processing industries. Each of these case studies have successfully implemented the cloud computing framework and their strategies are explained. As cloud computing may not be ideal for all businesses, criteria?are also offered to help determine if this strategy should be adopt.

Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions: SCM SIMULATIONS OF CLOUD TRANSITIONS

Energy Technology Data Exchange (ETDEWEB)

Neggers, R. A. J. [Institute for Geophysics and Meteorology, Department of Geosciences, University of Cologne, Cologne Germany; Royal Netherlands Meteorological Institute, De Bilt The Netherlands; Ackerman, A. S. [NASA Goddard Institute for Space Studies, New York NY USA; Angevine, W. M. [CIRES, University of Colorado, Boulder CO USA; NOAA Earth System Research Laboratory, Boulder CO USA; Bazile, E. [Météo France/CNRM, Toulouse France; Beau, I. [Météo France/ENM, Toulouse France; Blossey, P. N. [Department of Atmospheric Sciences, University of Washington, Seattle WA USA; Boutle, I. A. [Met Office, Exeter UK; de Bruijn, C. [Royal Netherlands Meteorological Institute, De Bilt The Netherlands; Cheng, A. [NOAA Center for Weather and Climate Prediction, Environmental Modeling Center, College Park MD USA; van der Dussen, J. [Department of Geoscience and Remote Sensing, Delft University of Technology, Delft The Netherlands; Fletcher, J. [Department of Atmospheric Sciences, University of Washington, Seattle WA USA; University of Leeds, Leeds UK; Dal Gesso, S. [Institute for Geophysics and Meteorology, Department of Geosciences, University of Cologne, Cologne Germany; Royal Netherlands Meteorological Institute, De Bilt The Netherlands; Jam, A. [Météo-France/CNRM & CNRS/IPSL/LMD, Toulouse France; Kawai, H. [Meteorological Research Institute, Climate Research Department, Japan Meteorological Agency, Tsukuba Japan; Cheedela, S. K. [Department of Atmosphere in the Earth System, Max-Planck Institut für Meteorologie, Hamburg Germany; Larson, V. E. [Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee WI USA; Lefebvre, M. -P. [Météo-France/CNRM & CNRS/IPSL/LMD, Toulouse France; Lock, A. P. [Met Office, Exeter UK; Meyer, N. R. [Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee WI USA; de Roode, S. R. [Department of Geoscience and Remote Sensing, Delft University of Technology, Delft The Netherlands; de Rooy, W. [Royal Netherlands Meteorological Institute, De Bilt The Netherlands; Sandu, I. [Section of Physical Aspects, European Centre for Medium-Range Weather Forecasts, Reading UK; Xiao, H. [University of California at Los Angeles, Los Angeles CA USA; Pacific Northwest National Laboratory, Richland WA USA; Xu, K. -M. [NASA Langley Research Centre, Hampton VI USA

2017-10-01

Results are presented of the GASS/EUCLIPSE single-column model inter-comparison study on the subtropical marine low-level cloud transition. A central goal is to establish the performance of state-of-the-art boundary-layer schemes for weather and climate mod- els for this cloud regime, using large-eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North-Eastern Pa- cific, while one reflects conditions in the North-Eastern Atlantic. A set of variables is considered that reflects key aspects of the transition process, making use of simple met- rics to establish the model performance. Using this method some longstanding problems in low level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure and the associated impact on radia- tive transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median ex- hibits the well-known “too few too bright” problem. The boundary layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular the verti- cal structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid pa- rameterization.

IRAS associations with dark clouds of opacity class 6

International Nuclear Information System (INIS)

Parker, N.D.

1988-01-01

Accurate positions of the opacity class 6 clouds from the Lynds Catalog of Dark Nebulae have been measured on blue and red prints from the Polomar Observatory Sky Survey (POSS) plates. These revised positions and the dimensions of ellipses fitted to the clouds are listed. The IRAS point source catalog has been searched for sources lying within the boundaries of the 147 clouds in the sample. The distribution and properties of these IRAS sources are discussed briefly. (author)

Direct Evidence of Reduction of Cloud Water after Spreading Diatomite Particles in Stratus Clouds in Beijing, China

Directory of Open Access Journals (Sweden)

Qiang Zhang

2010-01-01

Full Text Available Artificial weather modification experiments have been intensively practiced in many years over China, and some progresses have been made, including more methodologies and advanced instruments. However, a challenge question still remains for providing convincing scientific evidence during these practices and experiments. This is a very difficult scientific issue, which is related to complicated cloud physical science, such as to accurately predict the large natural variability of cloud formation and precipitation. In this study, we report a clear evidence that the cloud water is reduced after spreading diatomite particles in stratus clouds during a field experiment in Beijing, China. The analysis shows that the diatomite particles (15–20 μm in radius are large and have strong hygroscopic property (absorbing cloud water. As a result, during the experiment, spreading large diatomite particles lead to downward motion (producing more stable atmospheric condition and reduction of cloud water. It is noted that due to lacks of instruments, this designed experiment only can provide a qualitative result (such as photo evidence, and no quantitative result can be drawn from this experiment.

A combined spectral and object-based approach to transparent cloud removal in an operational setting for Landsat ETM+

Science.gov (United States)

Watmough, Gary R.; Atkinson, Peter M.; Hutton, Craig W.

2011-04-01

The automated cloud cover assessment (ACCA) algorithm has provided automated estimates of cloud cover for the Landsat ETM+ mission since 2001. However, due to the lack of a band around 1.375 μm, cloud edges and transparent clouds such as cirrus cannot be detected. Use of Landsat ETM+ imagery for terrestrial land analysis is further hampered by the relatively long revisit period due to a nadir only viewing sensor. In this study, the ACCA threshold parameters were altered to minimise omission errors in the cloud masks. Object-based analysis was used to reduce the commission errors from the extended cloud filters. The method resulted in the removal of optically thin cirrus cloud and cloud edges which are often missed by other methods in sub-tropical areas. Although not fully automated, the principles of the method developed here provide an opportunity for using otherwise sub-optimal or completely unusable Landsat ETM+ imagery for operational applications. Where specific images are required for particular research goals the method can be used to remove cloud and transparent cloud helping to reduce bias in subsequent land cover classifications.

The variation of cloud amount and light rainy days under heavy pollution over South China during 1960-2009.

Science.gov (United States)

Fu, Chuanbo; Dan, Li

2018-01-01

The ground observation data was used to analyze the variation of cloud amount and light precipitation over South China during 1960-2009. The total cloud cover (TCC) decreases in this period, whereas the low cloud cover (LCC) shows the obvious opposite change with increasing trends. LCP defined as low cloud cover/total cloud cover has increased, and small rainy days (pollution in the form of anthropogenic aerosols. The horizontal visibility and sunshine duration are used to depict the anthropogenic aerosol loading. When horizontal visibility declines to 20 km or sunshine duration decreases to 5 h per day, LCC increases 52% or more and LCP increases significantly. The correlation coefficients between LCC and horizontal visibility or sunshine duration are - 0.533 and - 0.927, and the values between LCP and horizontal visibility or sunshine duration are - 0.849 and - 0.641, which pass 0.001 significance level. The results indicated that aerosols likely impacted the long-term trend of cloud amount and light precipitation over South China.

Cloud screening Coastal Zone Color Scanner images using channel 5

Science.gov (United States)

Eckstein, B. A.; Simpson, J. J.

1991-01-01

Clouds are removed from Coastal Zone Color Scanner (CZCS) data using channel 5. Instrumentation problems require pre-processing of channel 5 before an intelligent cloud-screening algorithm can be used. For example, at intervals of about 16 lines, the sensor records anomalously low radiances. Moreover, the calibration equation yields negative radiances when the sensor records zero counts, and pixels corrupted by electronic overshoot must also be excluded. The remaining pixels may then be used in conjunction with the procedure of Simpson and Humphrey to determine the CZCS cloud mask. These results plus in situ observations of phytoplankton pigment concentration show that pre-processing and proper cloud-screening of CZCS data are necessary for accurate satellite-derived pigment concentrations. This is especially true in the coastal margins, where pigment content is high and image distortion associated with electronic overshoot is also present. The pre-processing algorithm is critical to obtaining accurate global estimates of pigment from spacecraft data.

Retrieval of Cloud Properties for Partially Cloud-Filled Pixels During CRYSTAL-FACE

Science.gov (United States)

Nguyen, L.; Minnis, P.; Smith, W. L.; Khaiyer, M. M.; Heck, P. W.; Sun-Mack, S.; Uttal, T.; Comstock, J.

2003-12-01

Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each

Point Cloud Management Through the Realization of the Intelligent Cloud Viewer Software

Science.gov (United States)

Costantino, D.; Angelini, M. G.; Settembrini, F.

2017-05-01

The paper presents a software dedicated to the elaboration of point clouds, called Intelligent Cloud Viewer (ICV), made in-house by AESEI software (Spin-Off of Politecnico di Bari), allowing to view point cloud of several tens of millions of points, also on of "no" very high performance systems. The elaborations are carried out on the whole point cloud and managed by means of the display only part of it in order to speed up rendering. It is designed for 64-bit Windows and is fully written in C ++ and integrates different specialized modules for computer graphics (Open Inventor by SGI, Silicon Graphics Inc), maths (BLAS, EIGEN), computational geometry (CGAL, Computational Geometry Algorithms Library), registration and advanced algorithms for point clouds (PCL, Point Cloud Library), advanced data structures (BOOST, Basic Object Oriented Supporting Tools), etc. ICV incorporates a number of features such as, for example, cropping, transformation and georeferencing, matching, registration, decimation, sections, distances calculation between clouds, etc. It has been tested on photographic and TLS (Terrestrial Laser Scanner) data, obtaining satisfactory results. The potentialities of the software have been tested by carrying out the photogrammetric survey of the Castel del Monte which was already available in previous laser scanner survey made from the ground by the same authors. For the aerophotogrammetric survey has been adopted a flight height of approximately 1000ft AGL (Above Ground Level) and, overall, have been acquired over 800 photos in just over 15 minutes, with a covering not less than 80%, the planned speed of about 90 knots.

POINT CLOUD MANAGEMENT THROUGH THE REALIZATION OF THE INTELLIGENT CLOUD VIEWER SOFTWARE

Directory of Open Access Journals (Sweden)

D. Costantino

2017-05-01

Full Text Available The paper presents a software dedicated to the elaboration of point clouds, called Intelligent Cloud Viewer (ICV, made in-house by AESEI software (Spin-Off of Politecnico di Bari, allowing to view point cloud of several tens of millions of points, also on of “no” very high performance systems. The elaborations are carried out on the whole point cloud and managed by means of the display only part of it in order to speed up rendering. It is designed for 64-bit Windows and is fully written in C ++ and integrates different specialized modules for computer graphics (Open Inventor by SGI, Silicon Graphics Inc, maths (BLAS, EIGEN, computational geometry (CGAL, Computational Geometry Algorithms Library, registration and advanced algorithms for point clouds (PCL, Point Cloud Library, advanced data structures (BOOST, Basic Object Oriented Supporting Tools, etc. ICV incorporates a number of features such as, for example, cropping, transformation and georeferencing, matching, registration, decimation, sections, distances calculation between clouds, etc. It has been tested on photographic and TLS (Terrestrial Laser Scanner data, obtaining satisfactory results. The potentialities of the software have been tested by carrying out the photogrammetric survey of the Castel del Monte which was already available in previous laser scanner survey made from the ground by the same authors. For the aerophotogrammetric survey has been adopted a flight height of approximately 1000ft AGL (Above Ground Level and, overall, have been acquired over 800 photos in just over 15 minutes, with a covering not less than 80%, the planned speed of about 90 knots.

Airborne hyperspectral observations of surface and cloud directional reflectivity using a commercial digital camera

Directory of Open Access Journals (Sweden)

A. Ehrlich

2012-04-01

Full Text Available Spectral radiance measurements by a digital single-lens reflex camera were used to derive the directional reflectivity of clouds and different surfaces in the Arctic. The camera has been calibrated radiometrically and spectrally to provide accurate radiance measurements with high angular resolution. A comparison with spectral radiance measurements with the Spectral Modular Airborne Radiation measurement sysTem (SMART-Albedometer showed an agreement within the uncertainties of both instruments (6% for both. The directional reflectivity in terms of the hemispherical directional reflectance factor (HDRF was obtained for sea ice, ice-free ocean and clouds. The sea ice, with an albedo of ρ = 0.96 (at 530 nm wavelength, showed an almost isotropic HDRF, while sun glint was observed for the ocean HDRF (ρ = 0.12. For the cloud observations with ρ = 0.62, the cloudbow – a backscatter feature typically for scattering by liquid water droplets – was covered by the camera. For measurements above heterogeneous stratocumulus clouds, the required number of images to obtain a mean HDRF that clearly exhibits the cloudbow has been estimated at about 50 images (10 min flight time. A representation of the HDRF as a function of the scattering angle only reduces the image number to about 10 (2 min flight time.

The measured cloud and ocean HDRF have been compared to radiative transfer simulations. The ocean HDRF simulated with the observed surface wind speed of 9 m s⁻¹ agreed best with the measurements. For the cloud HDRF, the best agreement was obtained by a broad and weak cloudbow simulated with a cloud droplet effective radius of R_eff = 4 μm. This value agrees with the particle sizes derived from in situ measurements and retrieved from the spectral radiance of the SMART-Albedometer.

Comparison of Cloud Detection Using the CERES-MODIS Ed4 and LaRC AVHRR Cloud Masks and CALIPSO Vertical Feature Mask

Science.gov (United States)

Trepte, Q. Z.; Minnis, P.; Palikonda, R.; Bedka, K. M.; Sun-Mack, S.

2011-12-01

Accurate detection of cloud amount and distribution using satellite observations is crucial in determining cloud radiative forcing and earth energy budget. The CERES-MODIS (CM) Edition 4 cloud mask is a global cloud detection algorithm for application to Terra and Aqua MODIS data with the aid of other ancillary data sets. It is used operationally for the NASA's Cloud and Earth's Radiant Energy System (CERES) project. The LaRC AVHRR cloud mask, which uses only five spectral channels, is based on a subset of the CM cloud mask which employs twelve MODIS channels. The LaRC mask is applied to AVHRR data for the NOAA Climate Data Record Program. Comparisons among the CM Ed4, and LaRC AVHRR cloud masks and the CALIPSO Vertical Feature Mask (VFM) constitute a powerful means for validating and improving cloud detection globally. They also help us understand the strengths and limitations of the various cloud retrievals which use either active and passive satellite sensors. In this paper, individual comparisons will be presented for different types of clouds over various surfaces, including daytime and nighttime, and polar and non-polar regions. Additionally, the statistics of the global, regional, and zonal cloud occurrence and amount from the CERES Ed4, AVHRR cloud masks and CALIPSO VFM will be discussed.

Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

Science.gov (United States)

Teixeira, J.; Cardoso, S.; Bonazzola, M.; Cole, J.; DeGenio, A.; DeMott, C.; Franklin, C.; Hannay, C.; Jakob, C.; Jiao, Y.;

Mesoscale to Synoptic Scale Cloud Variability

Science.gov (United States)

Rossow, William B.

1998-01-01

The atmospheric circulation and its interaction with the oceanic circulation involve non-linear and non-local exchanges of energy and water over a very large range of space and time scales. These exchanges are revealed, in part, by the related variations of clouds, which occur on a similar range of scales as the atmospheric motions that produce them. Collection of comprehensive measurements of the properties of the atmosphere, clouds and surface allows for diagnosis of some of these exchanges. The use of a multi-satellite-network approach by the International Satellite Cloud Climatology Project (ISCCP) comes closest to providing complete coverage of the relevant range space and time scales over which the clouds, atmosphere and ocean vary. A nearly 15-yr dataset is now available that covers the range from 3 hr and 30 km to decade and planetary. This paper considers three topics: (1) cloud variations at the smallest scales and how they may influence radiation-cloud interactions, and (2) cloud variations at "moderate" scales and how they may cause natural climate variability, and (3) cloud variations at the largest scales and how they affect the climate. The emphasis in this discussion is on the more mature subject of cloud-radiation interactions. There is now a need to begin similar detailed diagnostic studies of water exchange processes.

The use of marine cloud water samples as a diagnostic tool for aqueous chemistry, cloud microphysical processes and dynamics

Science.gov (United States)

Crosbie, E.; Ziemba, L. D.; Moore, R.; Shook, M.; Jordan, C.; Thornhill, K. L., II; Winstead, E.; Shingler, T.; Brown, M.; MacDonald, A. B.; Dadashazar, H.; Sorooshian, A.; Weiss-Penzias, P. S.; Anderson, B.

2017-12-01

Clouds play several roles in the Earth's climate system. In addition to their clear significance to the hydrological cycle, they strongly modulate the shortwave and longwave radiative balance of the atmosphere, with subsequent feedback on the atmospheric circulation. Furthermore, clouds act as a conduit for the fate and emergence of important trace chemical species and are the predominant removal mechanism for atmospheric aerosols. Marine boundary layer clouds cover large swaths of the global oceans. Because of their global significance, they have attracted significant attention into understanding how changes in aerosols are translated into changes in cloud macro- and microphysical properties. The circular nature of the influence of clouds-on-aerosols and aerosols-on-clouds has been used to explain the chaotic patterns often seen in marine clouds, however, this feedback also presents a substantial hurdle in resolving the uncertain role of anthropogenic aerosols on climate. Here we discuss ways in which the chemical constituents found in cloud water can offer insight into the physical and chemical processes inherent in marine clouds, through the use of aircraft measurements. We focus on observational data from cloud water samples collected during flights conducted over the remote North Atlantic and along coastal California across multiple campaigns. We explore topics related to aqueous processing, wet scavenging and source apportionment.

DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Science.gov (United States)

Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.

2017-12-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remotesensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud/shadow mask from geostationary satellite data iscritical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds, which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoder-decoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multi-spectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

CLOUD COMPUTING BASED INFORMATION SYSTEMS -PRESENT AND FUTURE

Directory of Open Access Journals (Sweden)

Maximilian ROBU

2012-12-01

Full Text Available The current economic crisis and the global recession have affected the IT market as well. A solution camefrom the Cloud Computing area by optimizing IT budgets and eliminating different types of expenses (servers, licenses,and so on. Cloud Computing is an exciting and interesting phenomenon, because of its relative novelty and explodinggrowth. Because of its raise in popularity and usage Cloud Computing has established its role as a research topic.However the tendency is to focus on the technical aspects of Cloud Computing, thus leaving the potential that thistechnology offers unexplored. With the help of this technology new market player arise and they manage to break thetraditional value chain of service provision. The main focus of this paper is the business aspects of Cloud. In particularwe will talk about the economic aspects that cover using Cloud Computing (when, why and how to use, and theimpacts on the infrastructure, the legalistic issues that come from using Cloud Computing; the scalability and partiallyunclear legislation.

Cloud Computing for Geosciences--GeoCloud for standardized geospatial service platforms (Invited)

Science.gov (United States)

Nebert, D. D.; Huang, Q.; Yang, C.

2013-12-01

paper presents the background, architectural design, and activities of GeoCloud in support of the Geospatial Platform Initiative. System security strategies and approval processes for migrating federal geospatial data, information, and applications into cloud, and cost estimation for cloud operations are covered. Finally, some lessons learned from the GeoCloud project are discussed as reference for geoscientists to consider in the adoption of cloud computing.

Marine cloud brightening

Science.gov (United States)

Latham, John; Bower, Keith; Choularton, Tom; Coe, Hugh; Connolly, Paul; Cooper, Gary; Craft, Tim; Foster, Jack; Gadian, Alan; Galbraith, Lee; Iacovides, Hector; Johnston, David; Launder, Brian; Leslie, Brian; Meyer, John; Neukermans, Armand; Ormond, Bob; Parkes, Ben; Rasch, Phillip; Rush, John; Salter, Stephen; Stevenson, Tom; Wang, Hailong; Wang, Qin; Wood, Rob

2012-01-01

The idea behind the marine cloud-brightening (MCB) geoengineering technique is that seeding marine stratocumulus clouds with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the cloud droplet number concentration, and thereby the cloud albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could—subject to satisfactory resolution of technical and scientific problems identified herein—have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involves (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in cloud brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seed-particle salt-mass, air-mass characteristics, updraught speed and other parameters on cloud–albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, cloud albedo might be enhanced by seeding marine stratocumulus clouds on a spatial scale of around 100×100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

Science.gov (United States)

Belle, Jessica H.; Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

Directory of Open Access Journals (Sweden)

Jessica H. Belle

2017-10-01

Full Text Available Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5 concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

Is ozone model bias driven by errors in cloud predictions? A quantitative assessment using satellite cloud retrievals in WRF-Chem

Science.gov (United States)

Ryu, Y. H.; Hodzic, A.; Barré, J.; Descombes, G.; Minnis, P.

2017-12-01

Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much of the bias in O3 predictions is caused by inaccurate cloud predictions. This study quantifies the errors in surface O3 predictions associated with clouds in summertime over CONUS using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Cloud fields used for photochemistry are corrected based on satellite cloud retrievals in sensitivity simulations. It is found that the WRF-Chem model is able to detect about 60% of clouds in the right locations and generally underpredicts cloud optical depths. The errors in hourly O3 due to the errors in cloud predictions can be up to 60 ppb. On average in summertime over CONUS, the errors in 8-h average O3 of 1-6 ppb are found to be attributable to those in cloud predictions under cloudy sky conditions. The contribution of changes in photolysis rates due to clouds is found to be larger ( 80 % on average) than that of light-dependent BVOC emissions. The effects of cloud corrections on O­3 are about 2 times larger in VOC-limited than NOx-limited regimes, suggesting that the benefits of accurate cloud predictions would be greater in VOC-limited than NOx-limited regimes.

A Climatology of Midlatitude Continental Clouds from the ARM SGP Site. Part II; Cloud Fraction and Surface Radiative Forcing

Science.gov (United States)

Xi, B.; Minnis, P.

2006-01-01

Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of cloud fraction and radiative forcing between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layered low (0-3 km), middle (3-6 km), and high clouds (more than 6 km) using ARM SCG ground-based paired lidar-radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties of approximately 10 Wm(exp -2). The annual averages of total, and single-layered low, middle and high cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total and low cloud amounts peak during January and February and reach a minimum during July and August, high clouds occur more frequently than other types of clouds with a peak in summer. The average annual downwelling surface SW fluxes for total and low clouds (151 and 138 Wm(exp-2), respectively) are less than those under middle and high clouds (188 and 201 Wm(exp -2), respectively), but the downwelling LW fluxes (349 and 356 Wm(exp -2)) underneath total and low clouds are greater than those from middle and high clouds (337 and 333 Wm(exp -2)). Low clouds produce the largest LW warming (55 Wm(exp -2) and SW cooling (-91 Wm(exp -2)) effects with maximum and minimum absolute values in spring and summer, respectively. High clouds have the smallest LW warming (17 Wm(exp -2)) and SW cooling (-37 Wm(exp -2)) effects at the surface. All-sky SW CRF decreases and LW CRF increases with increasing cloud fraction with mean slopes of -0.984 and 0.616 Wm(exp -2)%(exp -1), respectively. Over the entire diurnal cycle, clouds deplete the amount of surface insolation more than they add to the downwelling LW flux. The calculated CRFs do not appear to be significantly

Installing and Scaling out Ubuntu Enterprise Cloud in Virtual Environment

DEFF Research Database (Denmark)

Pantić, Zoran; Ali Babar, Muhammad

This document contains the supplemental material to the book “Guidelines for Building a Private Cloud Infrastructure”. This document provides guidance on how to install Ubuntu Enterprise Cloud in virtual environment, and afterwards how to scale out when needed. The purpose of this supplemental book...... is to provide a practical, step-by-step, detailed guide on how to dimension and install the machines and network. Some initial steps of configuring the cloud are also covered. The installation is performed in a virtual environment based on Windows 7 and VMware Workstation 7. The cloud installation is performed...... cloud, both using the command line tools, and GUI based tool HybridFox....

A Study of the Link between Cosmic Rays and Clouds with a Cloud Chamber at the CERN PS

CERN Multimedia

Laakso, L K; Lehtipalo, K; Miettinen, P K; Duarte branco da silva santos, F; Stojkov, Y; Jud, W; Wurm, F; Pinterich, T; Dommen, J; Curtius, J; Kreissl, F C; Minginette, P; Azeredo lima, J M; Kulmala, M T; Petaja, T T; Volkamer, R M; Schafer, M; Rodrigues tome, A; Viisanen, Y A; Onnela, A T O; Kristic, R; Ehrhart, S K; Amorim, A J; Maksumov, O; Kupc, A; Sitals, R P; Dunne, E M; Riipinen, I A; Downard, A J; Virtanen, A; Tsagkogeorgas, G; Schuchmann, S; Kvashnin, A; Hansel, A; Gonzalez carracedo, L R; Vrtala, A; Schallhart, S; Yan, C; Stratmann, F; Pinto mogo, S I; Makhmutov, V; Riccobono, F; Weingartner, E P; Kurten, C A; Rondo, L; Ruuskanen, T M; Finkenzeller, H F; Laaksonen, A J; De menezes, L; Hauser, D; Kajos, M K; Schmitt, T M; Mathot, S; Wasem, A; Guida, R; Metzger, A E; Baltensperger, U; Kirkby, J; Duplissy, J; Franchin, A; Rorup, B; Flagan, R C; Wex, H D

2002-01-01

Three recent independent observations suggest that galactic cosmic rays may exert a significant influence on the climate. Firstly, satellite data suggest a positive correlation between variations of cosmic ray intensity and the fraction of Earth covered by low clouds. Secondly, palaeoclimatic data provide extensive evidence for an association between cosmic ray intensity and climate over the last 10 kyr and at earlier times. Finally, the presence of ion-induced nucleation of new aerosol in the atmosphere is supported by recent observations. If cosmic rays do indeed enhance aerosol production and low cloud formation, this could exert a strong cooling influence on the radiative energy balance of Earth. Physical mechanisms by which cosmic rays may affect aerosol and clouds have been proposed and modelled, but definitive experiments are lacking. The aim of CLOUD is to investigate the nature and significance of cosmic ray-aerosol-cloud mechanisms under controlled laboratory conditions using the T11 beam at the CER...

THE GALFA-H I COMPACT CLOUD CATALOG

Energy Technology Data Exchange (ETDEWEB)

Saul, Destry R.; Peek, J. E. G.; Grcevich, J.; Putman, M. E.; Brown, A. R. H.; Hamden, E. T. [Department of Astronomy, Columbia University, New York, NY 10027 (United States); Douglas, K. A. [Physics and Astronomy, University of Calgary/Dominion Radio Astrophysical Observatory, P.O. Box 248, Penticton, BC V2A 6J9 (Canada); Korpela, E. J. [Space Sciences Laboratory, University of California, Berkeley, CA 94720 (United States); Stanimirovic, S.; Lee, M.; Burkhart, B.; Pingel, N. M. [Department of Astronomy, University of Wisconsin, Madison, 475 N Charter St, Madison, WI 53703 (United States); Heiles, C. [Radio Astronomy Lab, UC Berkeley, 601 Campbell Hall, Berkeley, CA 94720 (United States); Gibson, S. J. [Department of Physics and Astronomy, Western Kentucky University, Bowling Green, KY 42101 (United States); Begum, A. [Indian Institute of Science Education and Research, ITI Campus (Gas Rahat) Building, Govindpura, Bhopal-23 (India); Tonnesen, S. [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

2012-10-10

We present a catalog of 1964 isolated, compact neutral hydrogen clouds from the Galactic Arecibo L-Band Feed Array Survey Data Release One. The clouds were identified by a custom machine-vision algorithm utilizing the difference of Gaussian kernels to search for clouds smaller than 20'. The clouds have velocities typically between |V{sub LSR}| =20 and 400 km s{sup -1}, line widths of 2.5-35 km s{sup -1}, and column densities ranging from 1 to 35 Multiplication-Sign 10{sup 18} cm{sup -2}. The distances to the clouds in this catalog may cover several orders of magnitude, so the masses may range from less than a solar mass for clouds within the Galactic disk, to greater than 10{sup 4} M{sub Sun} for high-velocity clouds (HVCs) at the tip of the Magellanic Stream. To search for trends, we separate the catalog into five populations based on position, velocity, and line width: HVCs; galaxy candidates; cold low-velocity clouds (LVCs); warm, low positive-velocity clouds in the third Galactic quadrant; and the remaining warm LVCs. The observed HVCs are found to be associated with previously identified HVC complexes. We do not observe a large population of isolated clouds at high velocities as some models predict. We see evidence for distinct histories at low velocities in detecting populations of clouds corotating with the Galactic disk and a set of clouds that is not corotating.

Self-Similar Spin Images for Point Cloud Matching

Science.gov (United States)

Pulido, Daniel

The rapid growth of Light Detection And Ranging (Lidar) technologies that collect, process, and disseminate 3D point clouds have allowed for increasingly accurate spatial modeling and analysis of the real world. Lidar sensors can generate massive 3D point clouds of a collection area that provide highly detailed spatial and radiometric information. However, a Lidar collection can be expensive and time consuming. Simultaneously, the growth of crowdsourced Web 2.0 data (e.g., Flickr, OpenStreetMap) have provided researchers with a wealth of freely available data sources that cover a variety of geographic areas. Crowdsourced data can be of varying quality and density. In addition, since it is typically not collected as part of a dedicated experiment but rather volunteered, when and where the data is collected is arbitrary. The integration of these two sources of geoinformation can provide researchers the ability to generate products and derive intelligence that mitigate their respective disadvantages and combine their advantages. Therefore, this research will address the problem of fusing two point clouds from potentially different sources. Specifically, we will consider two problems: scale matching and feature matching. Scale matching consists of computing feature metrics of each point cloud and analyzing their distributions to determine scale differences. Feature matching consists of defining local descriptors that are invariant to common dataset distortions (e.g., rotation and translation). Additionally, after matching the point clouds they can be registered and processed further (e.g., change detection). The objective of this research is to develop novel methods to fuse and enhance two point clouds from potentially disparate sources (e.g., Lidar and crowdsourced Web 2.0 datasets). The scope of this research is to investigate both scale and feature matching between two point clouds. The specific focus of this research will be in developing a novel local descriptor

Improving Climate Projections by Understanding How Cloud Phase affects Radiation

Science.gov (United States)

Cesana, Gregory; Storelvmo, Trude

2017-01-01

Whether a cloud is predominantly water or ice strongly influences interactions between clouds and radiation coming down from the Sun or up from the Earth. Being able to simulate cloud phase transitions accurately in climate models based on observational data sets is critical in order to improve confidence in climate projections, because this uncertainty contributes greatly to the overall uncertainty associated with cloud-climate feedbacks. Ultimately, it translates into uncertainties in Earth's sensitivity to higher CO2 levels. While a lot of effort has recently been made toward constraining cloud phase in climate models, more remains to be done to document the radiative properties of clouds according to their phase. Here we discuss the added value of a new satellite data set that advances the field by providing estimates of the cloud radiative effect as a function of cloud phase and the implications for climate projections.

Fast Cloud Adjustment to Increasing CO2 in a Superparameterized Climate Model

Directory of Open Access Journals (Sweden)

Marat Khairoutdinov

2012-05-01

Full Text Available Two-year simulation experiments with a superparameterized climate model, SP-CAM, are performed to understand the fast tropical (30S-30N cloud response to an instantaneous quadrupling of CO2 concentration with SST held fixed at present-day values.The greenhouse effect of the CO2 perturbation quickly warms the tropical land surfaces by an average of 0.5 K. This shifts rising motion, surface precipitation, and cloud cover at all levels from the ocean to the land, with only small net tropical-mean cloud changes. There is a widespread average reduction of about 80 m in the depth of the trade inversion capping the marine boundary layer (MBL over the cooler subtropical oceans.One apparent contributing factor is CO2-enhanced downwelling longwave radiation, which reduces boundary-layer radiative cooling, a primary driver of turbulent entrainment through the trade inversion. A second contributor is a slight CO2-induced heating of the free troposphere above the MBL, which strengthens the trade inversion and also inhibits entrainment. There is a corresponding downward displacement of MBL clouds with a very slight decrease in mean cloud cover and albedo.Two-dimensional cloud-resolving model (CRM simulations of this MBL response are run to steady state using composite SP-CAM simulated thermodynamic and wind profiles from a representative cool subtropical ocean regime, for the control and 4xCO2 cases. Simulations with a CRM grid resolution equal to that of SP-CAM are compared with much finer resolution simulations. The coarse-resolution simulations maintain a cloud fraction and albedo comparable to SP-CAM, but the fine-resolution simulations have a much smaller cloud fraction. Nevertheless, both CRM configurations simulate a reduction in inversion height comparable to SP-CAM. The changes in low cloud cover and albedo in the CRM simulations are small, but both simulations predict a slight reduction in low cloud albedo as in SP-CAM.

Laboratory study of orographic cloud-like flow

Science.gov (United States)

Singh, Kanwar Nain; Sreenivas, K. R.

2013-11-01

Clouds are one of the major sources of uncertainty in climate prediction, listed in ``the most urgent scientific problems requiring attention'' IPCC. Also, convective clouds are of utmost importance to study the dynamics of tropical meteorology and therefore, play a key role in understanding monsoons. The present work is to study the dynamics of orographic clouds. Parameterization of these clouds will help in forecasting the precipitation accurately. Also, one could validate laboratory results from our study by actually measuring cloud development along a sloping terrain. In this context a planar buoyant turbulent wall jet is considered as an appropriate low order fluid-dynamical model for studying the turbulence and entrainment in orographic-clouds. Flow is volumetrically heated to mimic the latent heat release due to condensation in an actual cloud. This is the first step in studying the entrainment dynamics of the evolving orographic cloud. We are going to present some results on the cloud development using techniques that allows us to construct a 3-dimensional flow field at each instance and its development over the time. By combining velocity field from PIV and flow volume from PLIF at successive instances, we estimate the entrainment coefficient. Since the life-cycle of a cloud is determined by the entrainment of ambient air, these results could be extremely helpful in understanding the dynamics of the clouds. Detailed results will be presented at the conference.

Cloud-based Architecture Capabilities Summary Report

Energy Technology Data Exchange (ETDEWEB)

Vang, Leng [Idaho National Lab. (INL), Idaho Falls, ID (United States); Prescott, Steven R [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2014-09-01

In collaborating scientific research arena it is important to have an environment where analysts have access to a shared of information documents, software tools and be able to accurately maintain and track historical changes in models. A new cloud-based environment would be accessible remotely from anywhere regardless of computing platforms given that the platform has available of Internet access and proper browser capabilities. Information stored at this environment would be restricted based on user assigned credentials. This report reviews development of a Cloud-based Architecture Capabilities (CAC) as a web portal for PRA tools.

An interfacial mechanism for cloud droplet formation on organic aerosols.

Science.gov (United States)

Ruehl, Christopher R; Davies, James F; Wilson, Kevin R

2016-03-25

Accurate predictions of aerosol/cloud interactions require simple, physically accurate parameterizations of the cloud condensation nuclei (CCN) activity of aerosols. Current models assume that organic aerosol species contribute to CCN activity by lowering water activity. We measured droplet diameters at the point of CCN activation for particles composed of dicarboxylic acids or secondary organic aerosol and ammonium sulfate. Droplet activation diameters were 40 to 60% larger than predicted if the organic was assumed to be dissolved within the bulk droplet, suggesting that a new mechanism is needed to explain cloud droplet formation. A compressed film model explains how surface tension depression by interfacial organic molecules can alter the relationship between water vapor supersaturation and droplet size (i.e., the Köhler curve), leading to the larger diameters observed at activation. Copyright © 2016, American Association for the Advancement of Science.

On the spread of changes in marine low cloud cover in climate model simulations of the 21st century

Science.gov (United States)

Qu, Xin; Hall, Alex; Klein, Stephen A.; Caldwell, Peter M.

2014-05-01

In 36 climate change simulations associated with phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5), changes in marine low cloud cover (LCC) exhibit a large spread, and may be either positive or negative. Here we develop a heuristic model to understand the source of the spread. The model's premise is that simulated LCC changes can be interpreted as a linear combination of contributions from factors shaping the clouds' large-scale environment. We focus primarily on two factors—the strength of the inversion capping the atmospheric boundary layer (measured by the estimated inversion strength, EIS) and sea surface temperature (SST). For a given global model, the respective contributions of EIS and SST are computed. This is done by multiplying (1) the current-climate's sensitivity of LCC to EIS or SST variations, by (2) the climate-change signal in EIS or SST. The remaining LCC changes are then attributed to changes in greenhouse gas and aerosol concentrations, and other environmental factors. The heuristic model is remarkably skillful. Its SST term dominates, accounting for nearly two-thirds of the intermodel variance of LCC changes in CMIP3 models, and about half in CMIP5 models. Of the two factors governing the SST term (the SST increase and the sensitivity of LCC to SST perturbations), the SST sensitivity drives the spread in the SST term and hence the spread in the overall LCC changes. This sensitivity varies a great deal from model to model and is strongly linked to the types of cloud and boundary layer parameterizations used in the models. EIS and SST sensitivities are also estimated using observational cloud and meteorological data. The observed sensitivities are generally consistent with the majority of models as well as expectations from prior research. Based on the observed sensitivities and the relative magnitudes of simulated EIS and SST changes (which we argue are also physically reasonable), the heuristic model predicts LCC

One of the Approaches to Creation of Hybrid Cloud Secure Environment

Directory of Open Access Journals (Sweden)

Andrey Konstantinovich Kachko

2014-02-01

Full Text Available In response to the ever growing needs in the storage and processing of data the main position are occupied by informational-telecommunication systems, operating on the basis of cloud computing. In this case, the key point in the use of cloud computing is the problem of information security. This article is primarily intended to cover the main information safety issues that occur in cloud environments and ways of their solutions in the construction of an integrated information security management system on the cloud architecture.

Cloud Response to Arctic Sea Ice Loss and Implications for Feedbacks in the CESM1 Climate Model

Science.gov (United States)

Morrison, A.; Kay, J. E.; Chepfer, H.; Guzman, R.; Bonazzola, M.

2017-12-01

Clouds have the potential to accelerate or slow the rate of Arctic sea ice loss through their radiative influence on the surface. Cloud feedbacks can therefore play into Arctic warming as clouds respond to changes in sea ice cover. As the Arctic moves toward an ice-free state, understanding how cloud - sea ice relationships change in response to sea ice loss is critical for predicting the future climate trajectory. From satellite observations we know the effect of present-day sea ice cover on clouds, but how will clouds respond to sea ice loss as the Arctic transitions to a seasonally open water state? In this study we use a lidar simulator to first evaluate cloud - sea ice relationships in the Community Earth System Model (CESM1) against present-day observations (2006-2015). In the current climate, the cloud response to sea ice is well-represented in CESM1: we see no summer cloud response to changes in sea ice cover, but more fall clouds over open water than over sea ice. Since CESM1 is credible for the current Arctic climate, we next assess if our process-based understanding of Arctic cloud feedbacks related to sea ice loss is relevant for understanding future Arctic clouds. In the future Arctic, summer cloud structure continues to be insensitive to surface conditions. As the Arctic warms in the fall, however, the boundary layer deepens and cloud fraction increases over open ocean during each consecutive decade from 2020 - 2100. This study will also explore seasonal changes in cloud properties such as opacity and liquid water path. Results thus far suggest that a positive fall cloud - sea ice feedback exists in the present-day and future Arctic climate.

The effect of cloud screening on MAX-DOAS aerosol retrievals.

Science.gov (United States)

Gielen, Clio; Van Roozendael, Michel; Hendrik, Francois; Fayt, Caroline; Hermans, Christian; Pinardi, Gaia; De Backer, Hugo; De Bock, Veerle; Laffineur, Quentin; Vlemmix, Tim

2014-05-01

In recent years, ground-based multi-axis differential absorption spectroscopy (MAX-DOAS) has shown to be ideally suited for the retrieval of tropospheric trace gases and deriving information on the aerosol properties. These measurements are invaluable to our understanding of the physics and chemistry of the atmospheric system, and the impact on the Earth's climate. Unfortunately, MAX-DOAS measurements are often performed under strong non-clear-sky conditions, causing strong data quality degradation and uncertainties on the retrievals. Here we present the result of our cloud-screening method, using the colour index (CI), on aerosol retrievals from MAX-DOAS measurements (AOD and vertical profiles). We focus on two large data sets, from the Brussels and Beijing area. Using the CI we define 3 different sky conditions: bad (=full thick cloud cover/extreme aerosols), mediocre (=thin clouds/aerosols) and good (=clear sky). We also flag the presence of broken/scattered clouds. We further compare our cloud-screening method with results from cloud-cover fractions derived from thermic infrared measurements. In general, our method shows good results to qualify the sky and cloud conditions of MAX-DOAS measurements, without the need for other external cloud-detection systems. Removing data under bad-sky and broken-cloud conditions results in a strongly improved agreement, in both correlation and slope, between the MAX-DOAS aerosol retrievals and data from other instruments (e.g. AERONET, Brewer). With the improved AOD retrievals, the seasonal and diurnal variations of the aerosol content and vertical distribution at both sites can be investigated in further detail. By combining with additional information derived by other instruments (Brewer, lidar, ...) operated at the stations, we will further study the observed aerosol characteristics, and their influence on and by meteorological conditions such as clouds and/or the boundary layer height.

Cosmic rays, clouds, and climate

DEFF Research Database (Denmark)

Marsh, N.; Svensmark, Henrik

2000-01-01

cloud radiative properties. Thus, a moderate influence on atmospheric aerosol distributions from cosmic ray ionisation would have a strong influence on the Earth's radiation budget. Historical evidence over the past 1000 years indicates that changes in climate have occurred in accord with variability......A correlation between a global average of low cloud cover and the flux of cosmic rays incident in the atmosphere has been observed during the last solar cycle. The ionising potential of Earth bound cosmic rays are modulated by the state of the heliosphere, while clouds play an important role...... in the Earth's radiation budget through trapping outgoing radiation and reflecting incoming radiation. If a physical link between these two features can be established, it would provide a mechanism linking solar activity and Earth's climate. Recent satellite observations have further revealed a correlation...

Experimental evaluation of ALS point cloud ground extraction over different land cover in the Malopolska Province

Science.gov (United States)

Korzeniowska, Karolina; Mandlburger, Gottfried; Klimczyk, Agata

2013-04-01

The paper presents an evaluation of different terrain point extraction algorithms for Airborne Laser Scanning (ALS) point clouds. The research area covers eight test sites in the Małopolska Province (Poland) with varying point density between 3-15points/m² and surface as well as land cover characteristics. In this paper the existing implementations of algorithms were considered. Approaches based on mathematical morphology, progressive densification, robust surface interpolation and segmentation were compared. From the group of morphological filters, the Progressive Morphological Filter (PMF) proposed by Zhang K. et al. (2003) in LIS software was evaluated. From the progressive densification filter methods developed by Axelsson P. (2000) the Martin Isenburg's implementation in LAStools software (LAStools, 2012) was chosen. The third group of methods are surface-based filters. In this study, we used the hierarchic robust interpolation approach by Kraus K., Pfeifer N. (1998) as implemented in SCOP++ (Trimble, 2012). The fourth group of methods works on segmentation. From this filtering concept the segmentation algorithm available in LIS was tested (Wichmann V., 2012). The main aim in executing the automatic classification for ground extraction was operating in default mode or with default parameters which were selected by the developers of the algorithms. It was assumed that the default settings were equivalent to the parameters on which the best results can be achieved. In case it was not possible to apply an algorithm in default mode, a combination of the available and most crucial parameters for ground extraction were selected. As a result of these analyses, several output LAS files with different ground classification were achieved. The results were described on the basis of qualitative and quantitative analyses, both being in a formal description. The classification differences were verified on point cloud data. Qualitative verification of ground extraction was

Global distributions of cloud properties for CERES

Science.gov (United States)

Sun-Mack, S.; Minnis, P.; Heck, P.; Young, D.

2003-04-01

The microphysical and macrophysical properties of clouds play a crucial role in the earth's radiation budget. Simultaneous measurement of the radiation and cloud fields on a global basis has long been recognized as a key component in understanding and modeling the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. With the implementation of the NASA Clouds and Earth's Radiant Energy System (CERES) in 1998, this need is being met. Broadband shortwave and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth from the TRMM Visible Infrared Scanner and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. The combined cloud-radiation product has already been used for developing new, highly accurate anisotropic directional models for converting broadband radiances to flux. They also provide a consistent measure of cloud properties at different times of day over the globe since January 1998. These data will be valuable for determining the indirect effects of aerosols and for linking cloud water to cloud radiation. This paper provides an overview of the CERES cloud products from the three satellites including the retrieval methodology, validation, and global distributions. Availability and access to the datasets will also be discussed.

Comparison of Cloud and Aerosol Detection between CERES Edition 3 Cloud Mask and CALIPSO Version 2 Data Products

Science.gov (United States)

Trepte, Qing; Minnis, Patrick; Sun-Mack, Sunny; Trepte, Charles

Clouds and aerosol play important roles in the global climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a crucial first step in determining their influence on surface and top-of-atmosphere radiative fluxes. This paper presents a comparison analysis of a new version of the Clouds and Earth's Radiant Energy System (CERES) Edition 3 cloud detection algorithms using Aqua MODIS data with the recently released Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Version 2 Vertical Feature Mask (VFM). Improvements in CERES Edition 3 cloud mask include dust detection, thin cirrus tests, enhanced low cloud detection at night, and a smoother transition from mid-latitude to polar regions. For the CALIPSO Version 2 data set, changes to the lidar calibration can result in significant improvements to its identification of optically thick aerosol layers. The Aqua and CALIPSO satellites, part of the A-train satellite constellation, provide a unique opportunity for validating passive sensor cloud and aerosol detection using an active sensor. In this paper, individual comparison cases will be discussed for different types of clouds and aerosols over various surfaces, for daytime and nighttime conditions, and for regions ranging from the tropics to the poles. Examples will include an assessment of the CERES detection algorithm for optically thin cirrus, marine stratus, and polar night clouds as well as its ability to characterize Saharan dust plumes off the African coast. With the CALIPSO lidar's unique ability to probe the vertical structure of clouds and aerosol layers, it provides an excellent validation data set for cloud detection algorithms, especially for polar nighttime clouds.

Low cloud properties influenced by cosmic rays

DEFF Research Database (Denmark)

Marsh, Nigel; Svensmark, Henrik

2000-01-01

The influence of solar variability on climate is currently uncertain. Recent observations have indicated a possible mechanism via the influence of solar modulated cosmic rays on global cloud cover. Surprisingly the influence of solar variability is strongest in low clouds (less than or equal to3 km......), which points to a microphysical mechanism involving aerosol formation that is enhanced by ionization due to cosmic rays. If confirmed it suggests that the average state of the heliosphere is important for climate on Earth....

Accomplish the Application Area in Cloud Computing

OpenAIRE

Bansal, Nidhi; Awasthi, Amit

2012-01-01

In the cloud computing application area of accomplish, we find the fact that cloud computing covers a lot of areas are its main asset. At a top level, it is an approach to IT where many users, some even from different companies get access to shared IT resources such as servers, routers and various file extensions, instead of each having their own dedicated servers. This offers many advantages like lower costs and higher efficiency. Unfortunately there have been some high profile incidents whe...

A multi-temporal analysis approach for land cover mapping in support of nuclear incident response

Science.gov (United States)

Sah, Shagan; van Aardt, Jan A. N.; McKeown, Donald M.; Messinger, David W.

2012-06-01

Remote sensing can be used to rapidly generate land use maps for assisting emergency response personnel with resource deployment decisions and impact assessments. In this study we focus on constructing accurate land cover maps to map the impacted area in the case of a nuclear material release. The proposed methodology involves integration of results from two different approaches to increase classification accuracy. The data used included RapidEye scenes over Nine Mile Point Nuclear Power Station (Oswego, NY). The first step was building a coarse-scale land cover map from freely available, high temporal resolution, MODIS data using a time-series approach. In the case of a nuclear accident, high spatial resolution commercial satellites such as RapidEye or IKONOS can acquire images of the affected area. Land use maps from the two image sources were integrated using a probability-based approach. Classification results were obtained for four land classes - forest, urban, water and vegetation - using Euclidean and Mahalanobis distances as metrics. Despite the coarse resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. The classifications were augmented using this fused approach, with few supplementary advantages such as correction for cloud cover and independence from time of year. We concluded that this method would generate highly accurate land maps, using coarse spatial resolution time series satellite imagery and a single date, high spatial resolution, multi-spectral image.

Cloud classification in a mediterranean location using radiation data and sky images

International Nuclear Information System (INIS)

Martinez-Chico, M.; Batlles, F.J.; Bosch, J.L.

2011-01-01

Knowledge regarding the solar radiation reaching the earth's surface and its geographical distribution is very important for the use of solar energy as a resource to produce electricity. Therefore, a proper assessment of available solar resource is particularly important to determine the placement and operation of solar thermal power plants. To perform this analysis correctly, it is necessary to determine the main factors influencing the radiation reaching the earth's surface, such as the earth's geometry, terrain, and atmospheric attenuation by gases, particles and clouds. Among these factors, it is important to emphasise the role of clouds as the main attenuating factor of radiation. Information about the amount and type of clouds present in the sky is therefore necessary to analyse both their attenuation levels and the prevalence of different sky conditions. Cloud cover is characterised according to attenuation levels, using the beam transmittance (k b , ratio of direct radiation incident on the surface to the extraterrestrial solar radiation) and hemispherical sky images. An analysis of the frequency and duration of each type of cloud cover blocking the sun's disk is also performed. Results show prevailing sky situations that make the studied area very suitable for the use of solar energy systems. -- Highlights: → Beam transmittance index k b have been used successfully to classify the cloud cover. → The proposed classification has been used to study a Mediterranean location in south-eastern Spain. → Percentage of cloudless/cloudy situations showed a good potential for solar energy applications in the studied area.

Machine learning based cloud mask algorithm driven by radiative transfer modeling

Science.gov (United States)

Chen, N.; Li, W.; Tanikawa, T.; Hori, M.; Shimada, R.; Stamnes, K. H.

2017-12-01

Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.

Lidar Cloud Detection with Fully Convolutional Networks

Science.gov (United States)

Cromwell, E.; Flynn, D.

2017-12-01

The vertical distribution of clouds from active remote sensing instrumentation is a widely used data product from global atmospheric measuring sites. The presence of clouds can be expressed as a binary cloud mask and is a primary input for climate modeling efforts and cloud formation studies. Current cloud detection algorithms producing these masks do not accurately identify the cloud boundaries and tend to oversample or over-represent the cloud. This translates as uncertainty for assessing the radiative impact of clouds and tracking changes in cloud climatologies. The Atmospheric Radiation Measurement (ARM) program has over 20 years of micro-pulse lidar (MPL) and High Spectral Resolution Lidar (HSRL) instrument data and companion automated cloud mask product at the mid-latitude Southern Great Plains (SGP) and the polar North Slope of Alaska (NSA) atmospheric observatory. Using this data, we train a fully convolutional network (FCN) with semi-supervised learning to segment lidar imagery into geometric time-height cloud locations for the SGP site and MPL instrument. We then use transfer learning to train a FCN for (1) the MPL instrument at the NSA site and (2) for the HSRL. In our semi-supervised approach, we pre-train the classification layers of the FCN with weakly labeled lidar data. Then, we facilitate end-to-end unsupervised pre-training and transition to fully supervised learning with ground truth labeled data. Our goal is to improve the cloud mask accuracy and precision for the MPL instrument to 95% and 80%, respectively, compared to the current cloud mask algorithms of 89% and 50%. For the transfer learning based FCN for the HSRL instrument, our goal is to achieve a cloud mask accuracy of 90% and a precision of 80%.

APPLICABILITY ANALYSIS OF CLOTH SIMULATION FILTERING ALGORITHM FOR MOBILE LIDAR POINT CLOUD

Directory of Open Access Journals (Sweden)

S. Cai

2018-04-01

Full Text Available Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging data post-processing. Cloth simulation filtering (CSF algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM, 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44 %, 0.77 % and1.20 %. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

Influence of 3D effects on 1D aerosol retrievals in synthetic, partially clouded scenes

International Nuclear Information System (INIS)

Stap, F.A.; Hasekamp, O.P.; Emde, C.; Röckmann, T.

2016-01-01

An important challenge in aerosol remote sensing is to retrieve aerosol properties in the vicinity of clouds and in cloud contaminated scenes. Satellite based multi-wavelength, multi-angular, photo-polarimetric instruments are particularly suited for this task as they have the ability to separate scattering by aerosol and cloud particles. Simultaneous aerosol/cloud retrievals using 1D radiative transfer codes cannot account for 3D effects such as shadows, cloud induced enhancements and darkening of cloud edges. In this study we investigate what errors are introduced on the retrieved optical and micro-physical aerosol properties, when these 3D effects are neglected in retrievals where the partial cloud cover is modeled using the Independent Pixel Approximation. To this end a generic, synthetic data set of PARASOL like observations for 3D scenes with partial, liquid water cloud cover is created. It is found that in scenes with random cloud distributions (i.e. broken cloud fields) and either low cloud optical thickness or low cloud fraction, the inversion algorithm can fit the observations and retrieve optical and micro-physical aerosol properties with sufficient accuracy. In scenes with non-random cloud distributions (e.g. at the edge of a cloud field) the inversion algorithm can fit the observations, however, here the retrieved real part of the refractive indices of both modes is biased. - Highlights: • An algorithm for retrieval of both aerosol and cloud properties is presented. • Radiative transfer models of 3D, partially clouded scenes are simulated. • Errors introduced in the retrieved aerosol properties are discussed.

Baryon magnetic moments in the quark model and pion cloud contributions

International Nuclear Information System (INIS)

Sato, Toshiro; Sawada, Shoji

1981-01-01

Baryon magnetic moment is studied paying attention to the effects of pion cloud which is surrounding the 'bare' baryon whose magnetic moment is given by the quark model with broken SU(6) symmetry. The precisely measured nucleon magnetic moments are reproduced by the pion cloud contributions from the distance larger than 1.4 fm. The effects of pion cloud on the hyperon magnetic moments are also discussed. It is shown that the pion cloud contributions largely reduce the discrepancies between the quark model predictions and the recent accurate experimental data on the hyperon magnetic moments. (author)

On Elasticity Measurement in Cloud Computing

Directory of Open Access Journals (Sweden)

Wei Ai

2016-01-01

Full Text Available Elasticity is the foundation of cloud performance and can be considered as a great advantage and a key benefit of cloud computing. However, there is no clear, concise, and formal definition of elasticity measurement, and thus no effective approach to elasticity quantification has been developed so far. Existing work on elasticity lack of solid and technical way of defining elasticity measurement and definitions of elasticity metrics have not been accurate enough to capture the essence of elasticity measurement. In this paper, we present a new definition of elasticity measurement and propose a quantifying and measuring method using a continuous-time Markov chain (CTMC model, which is easy to use for precise calculation of elasticity value of a cloud computing platform. Our numerical results demonstrate the basic parameters affecting elasticity as measured by the proposed measurement approach. Furthermore, our simulation and experimental results validate that the proposed measurement approach is not only correct but also robust and is effective in computing and comparing the elasticity of cloud platforms. Our research in this paper makes significant contribution to quantitative measurement of elasticity in cloud computing.

Clouds blown by the solar wind

International Nuclear Information System (INIS)

Voiculescu, M; Condurache-Bota, S; Usoskin, I

2013-01-01

In this letter we investigate possible relationships between the cloud cover (CC) and the interplanetary electric field (IEF), which is modulated by the solar wind speed and the interplanetary magnetic field. We show that CC at mid–high latitudes systematically correlates with positive IEF, which has a clear energetic input into the atmosphere, but not with negative IEF, in general agreement with predictions of the global electric circuit (GEC)-related mechanism. Thus, our results suggest that mid–high latitude clouds might be affected by the solar wind via the GEC. Since IEF responds differently to solar activity than, for instance, cosmic ray flux or solar irradiance, we also show that such a study allows distinguishing one solar-driven mechanism of cloud evolution, via the GEC, from others. (letter)

Upper tropospheric cloud systems determined from IR Sounders and their influence on the atmosphere

Science.gov (United States)

Stubenrauch, Claudia; Protopapadaki, Sofia; Feofilov, Artem; Velasco, Carola Barrientos

2017-02-01

Covering about 30% of the Earth, upper tropospheric clouds play a key role in the climate system by modulating the Earth's energy budget and heat transport. Infrared Sounders reliably identify cirrus down to an IR optical depth of 0.1. Recently LMD has built global cloud climate data records from AIRS and IASI observations, covering the periods from 2003-2015 and 2008-2015, respectively. Upper tropospheric clouds often form mesoscale systems. Their organization and properties are being studied by (1) distinguishing cloud regimes within 2° × 2° regions and (2) applying a spatial composite technique on adjacent cloud pressures, which estimates the horizontal extent of the mesoscale cloud systems. Convective core, cirrus anvil and thin cirrus of these systems are then distinguished by their emissivity. Compared to other studies of tropical mesoscale convective systems our data include also the thinner anvil parts, which make out about 30% of the area of tropical mesoscale convective systems. Once the horizontal and vertical structure of these upper tropospheric cloud systems is known, we can estimate their radiative effects in terms of top of atmosphere and surface radiative fluxes and by computing their heating rates.

Quantifying Uncertainty in Satellite-Retrieved Land Surface Temperature from Cloud Detection Errors

Directory of Open Access Journals (Sweden)

Claire E. Bulgin

2018-04-01

Full Text Available Clouds remain one of the largest sources of uncertainty in remote sensing of surface temperature in the infrared, but this uncertainty has not generally been quantified. We present a new approach to do so, applied here to the Advanced Along-Track Scanning Radiometer (AATSR. We use an ensemble of cloud masks based on independent methodologies to investigate the magnitude of cloud detection uncertainties in area-average Land Surface Temperature (LST retrieval. We find that at a grid resolution of 625 km 2 (commensurate with a 0.25 ∘ grid size at the tropics, cloud detection uncertainties are positively correlated with cloud-cover fraction in the cell and are larger during the day than at night. Daytime cloud detection uncertainties range between 2.5 K for clear-sky fractions of 10–20% and 1.03 K for clear-sky fractions of 90–100%. Corresponding night-time uncertainties are 1.6 K and 0.38 K, respectively. Cloud detection uncertainty shows a weaker positive correlation with the number of biomes present within a grid cell, used as a measure of heterogeneity in the background against which the cloud detection must operate (e.g., surface temperature, emissivity and reflectance. Uncertainty due to cloud detection errors is strongly dependent on the dominant land cover classification. We find cloud detection uncertainties of a magnitude of 1.95 K over permanent snow and ice, 1.2 K over open forest, 0.9–1 K over bare soils and 0.09 K over mosaic cropland, for a standardised clear-sky fraction of 74.2%. As the uncertainties arising from cloud detection errors are of a significant magnitude for many surface types and spatially heterogeneous where land classification varies rapidly, LST data producers are encouraged to quantify cloud-related uncertainties in gridded products.

ATLAS Tier-2 monitoring system for the German cloud

Energy Technology Data Exchange (ETDEWEB)

Meyer, Joerg; Quadt, Arnulf; Weber, Pavel [II. Physikalisches Institut, Georg-August-Universitaet, Goettingen (Germany)

2011-07-01

The ATLAS tier centers in Germany provide their computing resources for the ATLAS experiment. The stable and sustainable operation of this so-called DE-cloud heavily relies on effective monitoring of the Tier-1 center GridKa and its associated Tier-2 centers. Central and local grid information services constantly collect and publish the status information from many computing resources and sites. The cloud monitoring system discussed in this presentation evaluates the information related to different cloud resources and provides a coherent and comprehensive view of the cloud. The main monitoring areas covered by the tool are data transfers, cloud software installation, site batch systems, Service Availability Monitoring (SAM). The cloud monitoring system consists of an Apache-based Python application, which retrieves the information and publishes it on the generated HTML web page. This results in an easy-to-use web interface for the limited number of sites in the cloud with fast and efficient access to the required information starting from a high level summary for the whole cloud to detailed diagnostics for the single site services. This approach provides the efficient identification of correlated site problems and simplifies the administration on both cloud and site level.

Combining MOD10A1 and MYD10A1 Images For Snow Cover Area Monitoring

Science.gov (United States)

Tekeli, A. E.

2008-12-01

MOD10A1 and MYD10A1 daily snow cover maps at 500 m resolution are available from MODIS sensors on Terra and Aqua satellites. Aqua obtains the image of same region approximately three hours after Terra over Turkey region. MODIS is an optic sensor and cloud cover degrades the usability of derived snow cover maps. Moreover, spectral similarity between clouds and snow complicates their separability in visible imagery. Fortunately, dynamic behavior of clouds enables their discrimination from snow stationary on the surface. Combined use of MOD10A1 and MYD10A1 images mostly reduces the cloud cover present in one image alone and provides better representation of surface snow cover. Comparison of merged images with in situ data indicated higher hit ratios. The individual comparison of MOD10A1 and MYD10A1 images with ground data each yielded 31% hit ratio whereas, the merged images provided 38%. One-day shifts in comparisons increased hit ratios to 52 % and 46% whereas and two-day shifts gave 77 % and 79 % for MOD10A1 and MYD10A1 respectively. Merged maps yielded 54% and 83% for one and two day shifts. The improvement provided by the merging technique is found to be 7% for the present day, 7 % for one- day and 5% for two-day shifts for the whole season. Monthly decomposition resulted 25% improvement as the maximum. The snow cover product obtained by merging Terra and Aqua satellites provided higher hit ratios, as expected.

New Stereo Vision Digital Camera System for Simultaneous Measurement of Cloud Base Height and Atmospheric Visibility

Science.gov (United States)

Janeiro, F. M.; Carretas, F.; Palma, N.; Ramos, P. M.; Wagner, F.

2013-12-01

Clouds play an important role in many aspects of everyday life. They affect both the local weather as well as the global climate and are an important parameter on climate change studies. Cloud parameters are also important for weather prediction models which make use of actual measurements. It is thus important to have low-cost instrumentation that can be deployed in the field to measure those parameters. This kind of instruments should also be automated and robust since they may be deployed in remote places and be subject to adverse weather conditions. Although clouds are very important in environmental systems, they are also an essential component of airplane safety when visual flight rules (VFR) are enforced, such as in most small aerodromes where it is not economically viable to install instruments for assisted flying. Under VFR there are strict limits on the height of the cloud base, cloud cover and atmospheric visibility that ensure the safety of the pilots and planes. Although there are instruments, available in the market, to measure those parameters, their relatively high cost makes them unavailable in many local aerodromes. In this work we present a new prototype which has been recently developed and deployed in a local aerodrome as proof of concept. It is composed by two digital cameras that capture photographs of the sky and allow the measurement of the cloud height from the parallax effect. The new developments consist on having a new geometry which allows the simultaneous measurement of cloud base height, wind speed at cloud base height and atmospheric visibility, which was not previously possible with only two cameras. The new orientation of the cameras comes at the cost of a more complex geometry to measure the cloud base height. The atmospheric visibility is calculated from the Lambert-Beer law after the measurement of the contrast between a set of dark objects and the background sky. The prototype includes the latest hardware developments that

Tracking the debris cloud from a Chinese nuclear test

International Nuclear Information System (INIS)

Peterson, K.R.

1977-01-01

As the radioactive debris cloud from a Chinese nuclear test on September 26, 1976 began drifting eastward, the Laboratory's computational facilities were pressed into service to predict the possible environmental effects. ERDA asked us to calculate cloud trajectories and to estimate the fallout dose. The FAA asked us to provide dose estimates both for commercial aircraft flights within the U.S. and for transatlantic flights of the Concorde SST. Our dose estimates, calculated with 2BPUFF, a large-cloud diffusion code, proved to be accurate predictions, correlating well with later observations. At FAA and ERDA request, we also worked with EG and G to measure cabin dose rates in some transatlantic SST and subsonic flights while the debris cloud moved out over the Atlantic Ocean

Improving Forecast Skill by Assimilation of AIRS Cloud Cleared Radiances RiCC

Science.gov (United States)

Susskind, Joel; Rosenberg, Robert I.; Iredell, Lena

2015-01-01

ECMWF, NCEP, and GMAO routinely assimilate radiosonde and other in-situ observations along with satellite IR and MW Sounder radiance observations. NCEP and GMAO use the NCEP GSI Data Assimilation System (DAS).GSI DAS assimilates AIRS, CrIS, IASI channel radiances Ri on a channel-by-channel, case-by-case basis, only for those channels i thought to be unaffected by cloud cover. This test excludes Ri for most tropospheric sounding channels under partial cloud cover conditions. AIRS Version-6 RiCC is a derived quantity representative of what AIRS channel i would have seen if the AIRS FOR were cloud free. All values of RiCC have case-by-case error estimates RiCC associated with them. Our experiments present to the GSI QCd values of AIRS RiCC in place of AIRS Ri observations. GSI DAS assimilates only those values of RiCC it thinks are cloud free. This potentially allows for better coverage of assimilated QCd values of RiCC as compared to Ri.

Top-down and Bottom-up aerosol-cloud-closure: towards understanding sources of unvertainty in deriving cloud radiative flux

Science.gov (United States)

Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.

2017-12-01

accounting for cloud-top entrainment. This work demonstrates the need to take in-situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux.

High-mass star formation possibly triggered by cloud-cloud collision in the H II region RCW 34

Science.gov (United States)

Hayashi, Katsuhiro; Sano, Hidetoshi; Enokiya, Rei; Torii, Kazufumi; Hattori, Yusuke; Kohno, Mikito; Fujita, Shinji; Nishimura, Atsushi; Ohama, Akio; Yamamoto, Hiroaki; Tachihara, Kengo; Hasegawa, Yutaka; Kimura, Kimihiro; Ogawa, Hideo; Fukui, Yasuo

2018-05-01

We report on the possibility that the high-mass star located in the H II region RCW 34 was formed by a triggering induced by a collision of molecular clouds. Molecular gas distributions of the 12CO and 13CO J = 2-1 and 12CO J = 3-2 lines in the direction of RCW 34 were measured using the NANTEN2 and ASTE telescopes. We found two clouds with velocity ranges of 0-10 km s-1 and 10-14 km s-1. Whereas the former cloud is as massive as ˜1.4 × 104 M⊙ and has a morphology similar to the ring-like structure observed in the infrared wavelengths, the latter cloud, with a mass of ˜600 M⊙, which has not been recognized by previous observations, is distributed to just cover the bubble enclosed by the other cloud. The high-mass star with a spectral type of O8.5V is located near the boundary of the two clouds. The line intensity ratio of 12CO J = 3-2/J = 2-1 yields high values (≳1.0), suggesting that these clouds are associated with the massive star. We also confirm that the obtained position-velocity diagram shows a similar distribution to that derived by a numerical simulation of the supersonic collision of two clouds. Using the relative velocity between the two clouds (˜5 km s-1), the collisional time scale is estimated to be ˜0.2 Myr with the assumption of a distance of 2.5 kpc. These results suggest that the high-mass star in RCW 34 was formed rapidly within a time scale of ˜0.2 Myr via a triggering of a cloud-cloud collision.

Analysis of Co-Located MODIS and CALIPSO Observations Near Clouds

Science.gov (United States)

Varnai, Tamas; Marshak, Alexander

2011-01-01

The purpose of this paper is to help researchers combine data from different satellites and thus gain new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects, For this, the paper explores whether cloud information from the Aqua satellite's MODIS instrument can help characterize systematic aerosol changes near clouds by refining earlier perceptions of these changes that were based on the CALIPSO satellite's CALIOP instrument. Similar to a radar but using visible and ncar-infrared light, CALIOP sends out laser pulses and provides aerosol and cloud information along a single line that tracks the satellite orbit by measuring the reflection of its pulses. In contrast, MODIS takes images of reflected sunlight and emitted infrared radiation at several wavelengths, and covers wide areas around the satellite track. This paper analyzes a year-long global dataset covering all ice-free oceans, and finds that MODIS can greatly help the interpretation of CALIOP observations, especially by detecting clouds that lie outside the line observed by CALlPSO. The paper also finds that complications such as differences in view direction or clouds drifting in the 72 seconds that elapse between MODIS and CALIOP observations have only a minor impact. The study also finds that MODIS data helps refine but does not qualitatively alter perceptions of the systematic aerosol changes that were detected in earlier studies using only CALIOP data. It then proposes a statistical approach to account for clouds lying outside the CALIOP track even when MODIS cannot as reliably detect low clouds, for example at night or over ice. Finally, the paper finds that, because of variations in cloud amount and type, the typical distance to clouds in maritime clear areas varies with season and location. The overall median distance to clouds in maritime clear areas around 4-5 km. The fact that half of all clear areas is

Forest Cover Mapping in Iskandar Malaysia Using Satellite Data

Science.gov (United States)

Kanniah, K. D.; Mohd Najib, N. E.; Vu, T. T.

2016-09-01

Malaysia is the third largest country in the world that had lost forest cover. Therefore, timely information on forest cover is required to help the government to ensure that the remaining forest resources are managed in a sustainable manner. This study aims to map and detect changes of forest cover (deforestation and disturbance) in Iskandar Malaysia region in the south of Peninsular Malaysia between years 1990 and 2010 using Landsat satellite images. The Carnegie Landsat Analysis System-Lite (CLASlite) programme was used to classify forest cover using Landsat images. This software is able to mask out clouds, cloud shadows, terrain shadows, and water bodies and atmospherically correct the images using 6S radiative transfer model. An Automated Monte Carlo Unmixing technique embedded in CLASlite was used to unmix each Landsat pixel into fractions of photosynthetic vegetation (PV), non photosynthetic vegetation (NPV) and soil surface (S). Forest and non-forest areas were produced from the fractional cover images using appropriate threshold values of PV, NPV and S. CLASlite software was found to be able to classify forest cover in Iskandar Malaysia with only a difference between 14% (1990) and 5% (2010) compared to the forest land use map produced by the Department of Agriculture, Malaysia. Nevertheless, the CLASlite automated software used in this study was found not to exclude other vegetation types especially rubber and oil palm that has similar reflectance to forest. Currently rubber and oil palm were discriminated from forest manually using land use maps. Therefore, CLASlite algorithm needs further adjustment to exclude these vegetation and classify only forest cover.

Analyzing cloud base at local and regional scales to understand tropical montane cloud forest vulnerability to climate change

Science.gov (United States)

Van Beusekom, Ashley E.; González, Grizelle; Scholl, Martha A.

2017-01-01

The degree to which cloud immersion provides water in addition to rainfall, suppresses transpiration, and sustains tropical montane cloud forests (TMCFs) during rainless periods is not well understood. Climate and land use changes represent a threat to these forests if cloud base altitude rises as a result of regional warming or deforestation. To establish a baseline for quantifying future changes in cloud base, we installed a ceilometer at 100 m altitude in the forest upwind of the TMCF that occupies an altitude range from ∼ 600 m to the peaks at 1100 m in the Luquillo Mountains of eastern Puerto Rico. Airport Automated Surface Observing System (ASOS) ceilometer data, radiosonde data, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite data were obtained to investigate seasonal cloud base dynamics, altitude of the trade-wind inversion (TWI), and typical cloud thickness for the surrounding Caribbean region. Cloud base is rarely quantified near mountains, so these results represent a first look at seasonal and diurnal cloud base dynamics for the TMCF. From May 2013 to August 2016, cloud base was lowest during the midsummer dry season, and cloud bases were lower than the mountaintops as often in the winter dry season as in the wet seasons. The lowest cloud bases most frequently occurred at higher elevation than 600 m, from 740 to 964 m. The Luquillo forest low cloud base altitudes were higher than six other sites in the Caribbean by ∼ 200–600 m, highlighting the importance of site selection to measure topographic influence on cloud height. Proximity to the oceanic cloud system where shallow cumulus clouds are seasonally invariant in altitude and cover, along with local trade-wind orographic lifting and cloud formation, may explain the dry season low clouds. The results indicate that climate change threats to low-elevation TMCFs are not limited to the dry season; changes in synoptic-scale weather patterns

A study of the link between cosmic rays and clouds with a cloud chamber at the CERN PS

CERN Document Server

Fastrup, B; Lillestøl, Egil; Thorn, E; Bosteels, Michel; Gonidec, A; Harigel, G G; Kirkby, Jasper; Mele, S; Minginette, P; Nicquevert, Bertrand; Schinzel, D; Seidl, W; Grundsøe, P; Marsh, N D; Polny, J; Svensmark, H; Viisanen, Y; Kurvinen, K L; Orava, Risto; Hämeri, K; Kulmala, M; Laakso, I; Mäkelä, J M; O'Dowd, C D; Afrosimov, V; Basalaev, A; Panov, M; Laaksonen, B D; Joutsensaari, J; Ermakov, V; Makhmutov, V S; Maksumov, O; Pokrevsky, P; Stozhkov, Yu I; Svirzhevsky, N S; Carslaw, K; Yin, Y; Trautmann, T; Arnold, F; Wohlfrom, K H; Hagen, D; Schmitt, J; Whitefield, P; Aplin, K; Harrison, R G; Bingham, R; Close, Francis Edwin; Gibbins, C; Irving, A; Kellett, B; Lockwood, M; Petersen, D; Szymanski, W W; Wagner, P E; Vrtala, A; CERN. Geneva. SPS-PS Experiments Committee

2000-01-01

Recent satellite data have revealed a surprising correlation between galactic cosmic ray (GCR) intensity and the fraction of the Earth covered by clouds. If this correlation were to be established by a causal mechanism, it could provide a crucial step in understanding the long-sought mechanism connecting solar and climate variability. The Earth's climate seems to be remarkably sensitive to solar activity, but variations of the Sun's electromagnetic radiation appear to be too small to account for the observed climate variability. However, since the GCR intensity is strongly modulated by the solar wind, a GCR-cloud link may provide a sufficient amplifying mechanism. Moreover if this connection were to be confirmed, it could have profound consequences for our understanding of the solar contributions to the current global warming. The CLOUD (Cosmics Leaving OUtdoor Droplets) project proposes to test experimentally the existence a link between cosmic rays and cloud formation, and to understand the microphysical me...

Fuzzy AutoEncode Based Cloud Detection for Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

Zhenfeng Shao

2017-03-01

Full Text Available Cloud detection of remote sensing imagery is quite challenging due to the influence of complicated underlying surfaces and the variety of cloud types. Currently, most of the methods mainly rely on prior knowledge to extract features artificially for cloud detection. However, these features may not be able to accurately represent the cloud characteristics under complex environment. In this paper, we adopt an innovative model named Fuzzy Autoencode Model (FAEM to integrate the feature learning ability of stacked autoencode networks and the detection ability of fuzzy function for highly accurate cloud detection on remote sensing imagery. Our proposed method begins by selecting and fusing spectral, texture, and structure information. Thereafter, the proposed technique established a FAEM to learn the deep discriminative features from a great deal of selected information. Finally, the learned features are mapped to the corresponding cloud density map with a fuzzy function. To demonstrate the effectiveness of the proposed method, 172 Landsat ETM+ images and 25 GF-1 images with different spatial resolutions are used in this paper. For the convenience of accuracy assessment, ground truth data are manually outlined. Results show that the average RER (ratio of right rate and error rate on Landsat images is greater than 29, while the average RER of Support Vector Machine (SVM is 21.8 and Random Forest (RF is 23. The results on GF-1 images exhibit similar performance as Landsat images with the average RER of 25.9, which is much higher than the results of SVM and RF. Compared to traditional methods, our technique has attained higher average cloud detection accuracy for either different spatial resolutions or various land surfaces.

Land cover mapping of North and Central America—Global Land Cover 2000

Science.gov (United States)

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

SAR processing in the cloud for oil detection in the Arctic

Science.gov (United States)

Garron, J.; Stoner, C.; Meyer, F. J.

2016-12-01

A new world of opportunity is being thawed from the ice of the Arctic, driven by decreased persistent Arctic sea-ice cover, increases in shipping, tourism, natural resource development. Tools that can automatically monitor key sea ice characteristics and potential oil spills are essential for safe passage in these changing waters. Synthetic aperture radar (SAR) data can be used to discriminate sea ice types and oil on the ocean surface and also for feature tracking. Additionally, SAR can image the earth through the night and most weather conditions. SAR data is volumetrically large and requires significant computing power to manipulate. Algorithms designed to identify key environmental features, like oil spills, in SAR imagery require secondary processing, and are computationally intensive, which can functionally limit their application in a real-time setting. Cloud processing is designed to manage big data and big data processing jobs by means of small cycles of off-site computations, eliminating up-front hardware costs. Pairing SAR data with cloud processing has allowed us to create and solidify a processing pipeline for SAR data products in the cloud to compare operational algorithms efficiency and effectiveness when run using an Alaska Satellite Facility (ASF) defined Amazon Machine Image (AMI). The products created from this secondary processing, were compared to determine which algorithm was most accurate in Arctic feature identification, and what operational conditions were required to produce the results on the ASF defined AMI. Results will be used to inform a series of recommendations to oil-spill response data managers and SAR users interested in expanding their analytical computing power.

Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

Science.gov (United States)

Comiso, Joey C.

1995-01-01

Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have

SnowCloud - a Framework to Predict Streamflow in Snowmelt-dominated Watersheds Using Cloud-based Computing

Science.gov (United States)

Sproles, E. A.; Crumley, R. L.; Nolin, A. W.; Mar, E.; Lopez-Moreno, J. J.

2017-12-01

Streamflow in snowy mountain regions is extraordinarily challenging to forecast, and prediction efforts are hampered by the lack of timely snow data—particularly in data sparse regions. SnowCloud is a prototype web-based framework that integrates remote sensing, cloud computing, interactive mapping tools, and a hydrologic model to offer a new paradigm for delivering key data to water resource managers. We tested the skill of SnowCloud to forecast monthly streamflow with one month lead time in three snow-dominated headwaters. These watersheds represent a range of precipitation/runoff schemes: the Río Elqui in northern Chile (200 mm/yr, entirely snowmelt); the John Day River, Oregon, USA (635 mm/yr, primarily snowmelt); and the Río Aragon in the northern Spain (850 mm/yr, snowmelt dominated). Model skill corresponded to snowpack contribution with Nash-Sutcliffe Efficiencies of 0.86, 0.52, and 0.21 respectively. SnowCloud does not require the user to possess advanced programming skills or proprietary software. We access NASA's MOD10A1 snow cover product to calculate the snow metrics globally using Google Earth Engine's geospatial analysis and cloud computing service. The analytics and forecast tools are provided through a web-based portal that requires only internet access and minimal training. To test the efficacy of SnowCloud we provided the tools and a series of tutorials in English and Spanish to water resource managers in Chile, Spain, and the United States. Participants assessed their user experience and provided feedback, and the results of our multi-cultural assessment are also presented. While our results focus on SnowCloud, they outline methods to develop cloud-based tools that function effectively across cultures and languages. Our approach also addresses the primary challenges of science-based computing; human resource limitations, infrastructure costs, and expensive proprietary software. These challenges are particularly problematic in developing

On the relationship between low cloud variability and lower tropospheric stability in the Southeast Pacific

Directory of Open Access Journals (Sweden)

F. Sun

2011-09-01

Full Text Available In this study, we examine marine low cloud cover variability in the Southeast Pacific and its association with lower-tropospheric stability (LTS across a spectrum of timescales. On both daily and interannual timescales, LTS and low cloud amount are very well correlated in austral summer (DJF. Meanwhile in winter (JJA, when ambient LTS increases, the LTS–low cloud relationship substantially weakens. The DJF LTS–low cloud relationship also weakens in years with unusually large ambient LTS values. These are generally strong El Niño years, in which DJF LTS values are comparable to those typically found in JJA. Thus the LTS–low cloud relationship is strongly modulated by the seasonal cycle and the ENSO phenomenon. We also investigate the origin of LTS anomalies closely associated with low cloud variability during austral summer. We find that the ocean and atmosphere are independently involved in generating anomalies in LTS and hence variability in the Southeast Pacific low cloud deck. This highlights the importance of the physical (as opposed to chemical component of the climate system in generating internal variability in low cloud cover. It also illustrates the coupled nature of the climate system in this region, and raises the possibility of cloud feedbacks related to LTS. We conclude by addressing the implications of the LTS–low cloud relationship in the Southeast Pacific for low cloud feedbacks in anthropogenic climate change.

H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Science.gov (United States)

Kalia, Subodh; Ganguly, Sangram; Li, Shuang; Nemani, Ramakrishna R.

2017-01-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

SUNYA Regional Climate Model Simulations of East Asia Summer Monsoon: Effects of Cloud Vertical Structure on the Surface Energy Balance

Directory of Open Access Journals (Sweden)

Wei Gong and Wei-Chyung Wang

2007-01-01

Full Text Available We used the State University of New York at Albany (SUNYA regional climate model to study the effect of cloud vertical distribution in affecting the surface energy balance of the East Asia summer monsoon (EASM. Simulations were conducted for the summers of 1988 and 1989, during which large contrast in the intra-seasonal cloud radiative forcing (CRF was observed at the top of the atmosphere. The model results indicate that both the high and low clouds are persistent throughout the summer months in both years. Because of large cloud water, low clouds significantly reduce the solar radiation flux reaching the surface, which nevertheless still dominate the surface energy balance, accounting for more than 50% of the surface heating. The low clouds also contribute significantly the downward longwave radiation to the surface with values strongly dependent on the cloud base temperature. The presence of low clouds effectively decreases the temperature and moisture gradients near surface, resulting in a substantial decrease in the sensible and latent heat fluxes from surface, which partially compensate the decrease of the net radiative cooling of the surface. For example, in the two days, May 8 and July 11 of 1988, the total cloud cover of 80% is simulated, but the respective low cloud cover (water was 63% (114 gm-2 and 22% (21 gm-2. As a result, the downward solar radiation is smaller by 161 Wm-2 in May 8. On the other hand, the cloud temperature was _ lower, yielding 56 Wm-2 smaller downward longwave radiation. The near surface temperature and gradient is more than _ smaller (and moisture gradient, leading to 21 and 81 Wm-2 smaller sensible heat and latent heat fluxes. It is also demonstrated that the model is capable to reproduce the intraseasonal variation of shortwave CRF, and catches the relationship between total cloud cover and SW CRF. The model results show the dominance of high cloud on the regional mean longwave CRF and low cloud on the intra

Cloud Infrastructure & Applications - CloudIA

Science.gov (United States)

Sulistio, Anthony; Reich, Christoph; Doelitzscher, Frank

The idea behind Cloud Computing is to deliver Infrastructure-as-a-Services and Software-as-a-Service over the Internet on an easy pay-per-use business model. To harness the potentials of Cloud Computing for e-Learning and research purposes, and to small- and medium-sized enterprises, the Hochschule Furtwangen University establishes a new project, called Cloud Infrastructure & Applications (CloudIA). The CloudIA project is a market-oriented cloud infrastructure that leverages different virtualization technologies, by supporting Service-Level Agreements for various service offerings. This paper describes the CloudIA project in details and mentions our early experiences in building a private cloud using an existing infrastructure.

Marine low cloud sensitivity to an idealized climate change : The CGILS LES intercomparison

NARCIS (Netherlands)

Blossey, P.N.; Bretherton, C.S.; Zhang, M.; Cheng, A.; Endo, S.; Heus, T.; Liu, Y.; Lock, A.P.; De Roode, S.R.; Xu, K.M.

2013-01-01

Subtropical marine low cloud sensitivity to an idealized climate change is compared in six large-eddy simulation (LES) models as part of CGILS. July cloud cover is simulated at three locations over the subtropical northeast Pacific Ocean, which are typified by cold sea surface temperatures (SSTs)

Land cover change mapping using MODIS time series to improve emissions inventories

Science.gov (United States)

López-Saldaña, Gerardo; Quaife, Tristan; Clifford, Debbie

2016-04-01

MELODIES is an FP7 funded project to develop innovative and sustainable services, based upon Open Data, for users in research, government, industry and the general public in a broad range of societal and environmental benefit areas. Understanding and quantifying land surface changes is necessary for estimating greenhouse gas and ammonia emissions, and for meeting air quality limits and targets. More sophisticated inventories methodologies for at least key emission source are needed due to policy-driven air quality directives. Quantifying land cover changes on an annual basis requires greater spatial and temporal disaggregation of input data. The main aim of this study is to develop a methodology for using Earth Observations (EO) to identify annual land surface changes that will improve emissions inventories from agriculture and land use/land use change and forestry (LULUCF) in the UK. First goal is to find the best sets of input features that describe accurately the surface dynamics. In order to identify annual and inter-annual land surface changes, a times series of surface reflectance was used to capture seasonal variability. Daily surface reflectance images from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500m resolution were used to invert a Bidirectional Reflectance Distribution Function (BRDF) model to create the seamless time series. Given the limited number of cloud-free observations, a BRDF climatology was used to constrain the model inversion and where no high-scientific quality observations were available at all, as a gap filler. The Land Cover Map 2007 (LC2007) produced by the Centre for Ecology & Hydrology (CEH) was used for training and testing purposes. A land cover product was created for 2003 to 2015 and a bayesian approach was created to identified land cover changes. We will present the results of the time series development and the first exercises when creating the land cover and land cover changes products.

Identifying clouds over the Pierre Auger Observatory using infrared satellite data

Energy Technology Data Exchange (ETDEWEB)

Abreu, Pedro; et al.,

2013-12-01

We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

Feasibility and demonstration of a cloud-based RIID analysis system

Science.gov (United States)

Wright, Michael C.; Hertz, Kristin L.; Johnson, William C.; Sword, Eric D.; Younkin, James R.; Sadler, Lorraine E.

2015-06-01

A significant limitation in the operational utility of handheld and backpack radioisotope identifiers (RIIDs) is the inability of their onboard algorithms to accurately and reliably identify the isotopic sources of the measured gamma-ray energy spectrum. A possible solution is to move the spectral analysis computations to an external device, the cloud, where significantly greater capabilities are available. The implementation and demonstration of a prototype cloud-based RIID analysis system have shown this type of system to be feasible with currently available communication and computational technology. A system study has shown that the potential user community could derive significant benefits from an appropriately implemented cloud-based analysis system and has identified the design and operational characteristics required by the users and stakeholders for such a system. A general description of the hardware and software necessary to implement reliable cloud-based analysis, the value of the cloud expressed by the user community, and the aspects of the cloud implemented in the demonstrations are discussed.

Reshaping Smart Businesses with Cloud Database Solutions

Directory of Open Access Journals (Sweden)

Bogdan NEDELCU

2015-03-01

Full Text Available The aim of this article is to show the importance of Big Data and its growing influence on companies. We can also see how much are the companies willing to invest in big data and how much are they currently gaining from their big data. In this big data era, there is a fiercely competition between the companies and the technologies they use when building their strategies. There are almost no boundaries when it comes to the possibilities and facilities some databases can offer. However, the most challenging part lays in the development of efficient solutions - where and when to take the right decision, which cloud service is the most accurate being given a certain scenario, what database is suitable for the business taking in consideration the data types. These are just a few aspects which will be dealt with in the following chapters as well as exemplifications of the most accurate cloud services (e.g. NoSQL databases used by business leaders nowadays.

The impact of cloud inhomogeneities on the Earth radiation budget: the 14 October 1989 I.C.E. convective cloud case study

Directory of Open Access Journals (Sweden)

F. Parol

1994-01-01

Full Text Available Through their multiple interactions with radiation, clouds have an important impact on the climate. Nonetheless, the simulation of clouds in climate models is still coarse. The present evolution of modeling tends to a more realistic representation of the liquid water content; thus the problem of its subgrid scale distribution is crucial. For a convective cloud field observed during ICE 89, Landsat TM data (resolution: 30m have been analyzed in order to quantify the respective influences of both the horizontal distribution of liquid water content and cloud shape on the Earth radiation budget. The cloud field was found to be rather well-represented by a stochastic distribution of hemi-ellipsoidal clouds whose horizontal aspect ratio is close to 2 and whose vertical aspect ratio decreases as the cloud cell area increases. For that particular cloud field, neglecting the influence of the cloud shape leads to an over-estimate of the outgoing longwave flux; in the shortwave, it leads to an over-estimate of the reflected flux for high solar elevations but strongly depends on cloud cell orientations for low elevations. On the other hand, neglecting the influence of cloud size distribution leads to systematic over-estimate of their impact on the shortwave radiation whereas the effect is close to zero in the thermal range. The overall effect of the heterogeneities is estimated to be of the order of 10 W m-2 for the conditions of that Landsat picture (solar zenith angle 65°, cloud cover 70%; it might reach 40 W m-2 for an overhead sun and overcast cloud conditions.

The impact of cloud inhomogeneities on the Earth radiation budget: the 14 October 1989 I.C.E. convective cloud case study

Directory of Open Access Journals (Sweden)

F. Parol

Full Text Available Through their multiple interactions with radiation, clouds have an important impact on the climate. Nonetheless, the simulation of clouds in climate models is still coarse. The present evolution of modeling tends to a more realistic representation of the liquid water content; thus the problem of its subgrid scale distribution is crucial. For a convective cloud field observed during ICE 89, Landsat TM data (resolution: 30m have been analyzed in order to quantify the respective influences of both the horizontal distribution of liquid water content and cloud shape on the Earth radiation budget. The cloud field was found to be rather well-represented by a stochastic distribution of hemi-ellipsoidal clouds whose horizontal aspect ratio is close to 2 and whose vertical aspect ratio decreases as the cloud cell area increases. For that particular cloud field, neglecting the influence of the cloud shape leads to an over-estimate of the outgoing longwave flux; in the shortwave, it leads to an over-estimate of the reflected flux for high solar elevations but strongly depends on cloud cell orientations for low elevations. On the other hand, neglecting the influence of cloud size distribution leads to systematic over-estimate of their impact on the shortwave radiation whereas the effect is close to zero in the thermal range. The overall effect of the heterogeneities is estimated to be of the order of 10 W m^-2 for the conditions of that Landsat picture (solar zenith angle 65°, cloud cover 70%; it might reach 40 W m^-2 for an overhead sun and overcast cloud conditions.

A New Method of Cloud Detection Based on Cascaded AdaBoost

International Nuclear Information System (INIS)

Ma, C; Chen, F; Liu, J; Duan, J

2014-01-01

Cloud detection of remote sensing image is a critical step in the processing of the remote sensing images. How to quickly, accurately and effectively detect cloud on remote sensing images, is still a challenging issue in this area. In order to avoid disadvantages of the current algorithms, the cascaded AdaBoost classifier algorithm is successfully applied to the cloud detection. A new algorithm combined cascaded AdaBoost classifier and multi-features, is proposed in this paper. First, multi-features based on the color, texture and spectral features are extracted from the remote sensing image. Second, the automatic cloud detection model is obtained based on the cascaded AdaBoost algorithm. In this paper, the results show that the new algorithm can determine cloud detection model and threshold values adaptively for different resolution remote sensing training data. The accuracy of cloud detection is improved. So it is a new effective algorithm for the cloud detection of remote sensing images

Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM

Directory of Open Access Journals (Sweden)

U. Lohmann

2007-07-01

Full Text Available The double-moment cloud microphysics scheme from ECHAM4 that predicts both the mass mixing ratios and number concentrations of cloud droplets and ice crystals has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass, number concentrations and mixing state. The simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and −35° C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient.

The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to −1.9 W m⁻² in ECHAM5, when a relative humidity dependent cloud cover scheme and aerosol emissions representative for the years 1750 and 2000 from the AeroCom emission inventory are used. The contribution of the cloud albedo effect amounts to −0.7 W m⁻². The total anthropogenic aerosol effect is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed because the cloud lifetime effect increases.

VMware vCloud Director essentials

CERN Document Server

Pal, Lipika

2014-01-01

If you are a technical professional with system administration knowledge, then this book is for you. The book also covers areas of importance if you are a virtualization engineer, consultant, architect, senior system engineer, or senior system analyst. You should possess core vSphere platform knowledge necessary to serve as a base to learn vCloud Director and its associated components.

MODIS Snow Cover Recovery Using Variational Interpolation

Science.gov (United States)

Tran, H.; Nguyen, P.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Cloud obscuration is one of the major problems that limit the usages of satellite images in general and in NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) global Snow-Covered Area (SCA) products in particular. Among the approaches to resolve the problem, the Variational Interpolation (VI) algorithm method, proposed by Xia et al., 2012, obtains cloud-free dynamic SCA images from MODIS. This method is automatic and robust. However, computational deficiency is a main drawback that degrades applying the method for larger scales (i.e., spatial and temporal scales). To overcome this difficulty, this study introduces an improved version of the original VI. The modified VI algorithm integrates the MINimum RESidual (MINRES) iteration (Paige and Saunders., 1975) to prevent the system from breaking up when applied to much broader scales. An experiment was done to demonstrate the crash-proof ability of the new algorithm in comparison with the original VI method, an ability that is obtained when maintaining the distribution of the weights set after solving the linear system. After that, the new VI algorithm was applied to the whole Contiguous United States (CONUS) over four winter months of 2016 and 2017, and validated using the snow station network (SNOTEL). The resulting cloud free images have high accuracy in capturing the dynamical changes of snow in contrast with the MODIS snow cover maps. Lastly, the algorithm was applied to create a Cloud free images dataset from March 10, 2000 to February 28, 2017, which is able to provide an overview of snow trends over CONUS for nearly two decades. ACKNOWLEDGMENTSWe would like to acknowledge NASA, NOAA Office of Hydrologic Development (OHD) National Weather Service (NWS), Cooperative Institute for Climate and Satellites (CICS), Army Research Office (ARO), ICIWaRM, and UNESCO for supporting this research.

Spectral Longwave Cloud Radiative Forcing as Observed by AIRS

Science.gov (United States)

Blaisdell, John M.; Susskind, Joel; Lee, Jae N.; Iredell, Lena

2016-01-01

AIRS V6 products contain the spectral contributions to Outgoing Longwave Radiation (OLR), clear-sky OLR (OLR(sub CLR)), and Longwave Cloud Radiative Forcing (LWCRF) in 16 bands from 100 cm(exp -1) to 3260 cm(exp -1). We show climatologies of selected spectrally resolved AIRS V6 products over the period of September 2002 through August 2016. Spectrally resolved LWCRF can better describe the response of the Earth system to cloud and cloud feedback processes. The spectral LWCRF enables us to estimate the fraction of each contributing factor to cloud forcing, i.e.: surface temperature, mid to upper tropospheric water vapor, and tropospheric temperature. This presentation also compares the spatial characteristics of LWCRF from AIRS, CERES_EBAF Edition-2.8, and MERRA-2. AIRS and CERES LWCRF products show good agreement. The OLR bias between AIRS and CERES is very close to that of OLR(sub CLR). This implies that both AIRS and CERES OLR products accurately account for the effect of clouds on OLR.

The accuracy of remotely-sensed IWC: An assessment from MLS, TRMM and CloudSat statistics

Science.gov (United States)

Wu, D. L.; Heymsfield, A. J.

2006-12-01

Understanding climate change requires accurate global cloud ice water content (IWC) measurements. Satellite remote sensing has been the major tool to provide such global observations, but the accuracy of deduced IWC depends on knowledge of cloud microphysics learned from in-situ samples. Because only limited number and type of ice clouds have been measured by in-situ sensors, the knowledge about cloud microphysics is incomplete, and the IWC accuracy from remote sensing can vary from 30% to 200% from case to case. Recent observations from MLS, TRMM and CloudSat allow us to evaluate consistency and accuracy of IWCs deduced from passive and active satellite techniques. In this study we conduct statistical analyses on the tropical and subtropical IWCs observed by MLS, TRMM and CloudSat. The probability density functions (PDFs) of IWC are found to depend on the volume size of averaging, and therefore data need to be averaged into the same volume in order for fair comparisons. Showing measurement noise, bias and sensitivity, the PDF is a better characterization than an average for evaluating IWC accuracy because an averaged IWC depends on cloud-detection threshold that can vary from sensor to sensor. Different thresholds will not only change the average value but also change cloud fraction and occurrence frequency. Our study shows that MLS and TRMM IWCs, despite large differences in sensitivity with little overlap, can still be compared under PDF. The two statistics are generally consistent within 50% at ~13 km, obeying an approximate lognormal distribution as suggested by some ground-based radar observations. MLS has sensitivity to IWC of 1-100 mg/m3 whereas TRMM can improve its sensitivity to IWC as low as 70 mg/m3 if the radar data are averaged properly for the equivalent volume of MLS samples. The proper statistical averaging requires full characteristics of IWC noise, which are not available for products normally derived from radar reflectivity, and therefore we

Jupiter's Multi-level Clouds

Science.gov (United States)

1997-01-01

Clouds and hazes at various altitudes within the dynamic Jovian atmosphere are revealed by multi-color imaging taken by the Near-Infrared Mapping Spectrometer (NIMS) onboard the Galileo spacecraft. These images were taken during the second orbit (G2) on September 5, 1996 from an early-morning vantage point 2.1 million kilometers (1.3 million miles) above Jupiter. They show the planet's appearance as viewed at various near-infrared wavelengths, with distinct differences due primarily to variations in the altitudes and opacities of the cloud systems. The top left and right images, taken at 1.61 microns and 2.73 microns respectively, show relatively clear views of the deep atmosphere, with clouds down to a level about three times the atmospheric pressure at the Earth's surface.By contrast, the middle image in top row, taken at 2.17 microns, shows only the highest altitude clouds and hazes. This wavelength is severely affected by the absorption of light by hydrogen gas, the main constituent of Jupiter's atmosphere. Therefore, only the Great Red Spot, the highest equatorial clouds, a small feature at mid-northern latitudes, and thin, high photochemical polar hazes can be seen. In the lower left image, at 3.01 microns, deeper clouds can be seen dimly against gaseous ammonia and methane absorption. In the lower middle image, at 4.99 microns, the light observed is the planet's own indigenous heat from the deep, warm atmosphere.The false color image (lower right) succinctly shows various cloud and haze levels seen in the Jovian atmosphere. This image indicates the temperature and altitude at which the light being observed is produced. Thermally-rich red areas denote high temperatures from photons in the deep atmosphere leaking through minimal cloud cover; green denotes cool temperatures of the tropospheric clouds; blue denotes cold of the upper troposphere and lower stratosphere. The polar regions appear purplish, because small-particle hazes allow leakage and reflectivity

The impact of atmospheric stability and wind shear on vertical cloud overlap over the Tibetan Plateau

Directory of Open Access Journals (Sweden)

J. Li

2018-05-01

Full Text Available Studies have shown that changes in cloud cover are responsible for the rapid climate warming over the Tibetan Plateau (TP in the past 3 decades. To simulate the total cloud cover, atmospheric models have to reasonably represent the characteristics of vertical overlap between cloud layers. Until now, however, this subject has received little attention due to the limited availability of observations, especially over the TP. Based on the above information, the main aim of this study is to examine the properties of cloud overlaps over the TP region and to build an empirical relationship between cloud overlap properties and large-scale atmospheric dynamics using 4 years (2007–2010 of data from the CloudSat cloud product and collocated ERA-Interim reanalysis data. To do this, the cloud overlap parameter α, which is an inverse exponential function of the cloud layer separation D and decorrelation length scale L, is calculated using CloudSat and is discussed. The parameters α and L are both widely used to characterize the transition from the maximum to random overlap assumption with increasing layer separations. For those non-adjacent layers without clear sky between them (that is, contiguous cloud layers, it is found that the overlap parameter α is sensitive to the unique thermodynamic and dynamic environment over the TP, i.e., the unstable atmospheric stratification and corresponding weak wind shear, which leads to maximum overlap (that is, greater α values. This finding agrees well with the previous studies. Finally, we parameterize the decorrelation length scale L as a function of the wind shear and atmospheric stability based on a multiple linear regression. Compared with previous parameterizations, this new scheme can improve the simulation of total cloud cover over the TP when the separations between cloud layers are greater than 1 km. This study thus suggests that the effects of both wind shear and atmospheric stability on cloud overlap

The impact of atmospheric stability and wind shear on vertical cloud overlap over the Tibetan Plateau

Science.gov (United States)

Li, Jiming; Lv, Qiaoyi; Jian, Bida; Zhang, Min; Zhao, Chuanfeng; Fu, Qiang; Kawamoto, Kazuaki; Zhang, Hua

2018-05-01

Studies have shown that changes in cloud cover are responsible for the rapid climate warming over the Tibetan Plateau (TP) in the past 3 decades. To simulate the total cloud cover, atmospheric models have to reasonably represent the characteristics of vertical overlap between cloud layers. Until now, however, this subject has received little attention due to the limited availability of observations, especially over the TP. Based on the above information, the main aim of this study is to examine the properties of cloud overlaps over the TP region and to build an empirical relationship between cloud overlap properties and large-scale atmospheric dynamics using 4 years (2007-2010) of data from the CloudSat cloud product and collocated ERA-Interim reanalysis data. To do this, the cloud overlap parameter α, which is an inverse exponential function of the cloud layer separation D and decorrelation length scale L, is calculated using CloudSat and is discussed. The parameters α and L are both widely used to characterize the transition from the maximum to random overlap assumption with increasing layer separations. For those non-adjacent layers without clear sky between them (that is, contiguous cloud layers), it is found that the overlap parameter α is sensitive to the unique thermodynamic and dynamic environment over the TP, i.e., the unstable atmospheric stratification and corresponding weak wind shear, which leads to maximum overlap (that is, greater α values). This finding agrees well with the previous studies. Finally, we parameterize the decorrelation length scale L as a function of the wind shear and atmospheric stability based on a multiple linear regression. Compared with previous parameterizations, this new scheme can improve the simulation of total cloud cover over the TP when the separations between cloud layers are greater than 1 km. This study thus suggests that the effects of both wind shear and atmospheric stability on cloud overlap should be taken into

Statistical Monitoring of Changes to Land Cover

KAUST Repository

Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying

2018-01-01

Accurate detection of changes in land cover leads to better understanding of the dynamics of landscapes. This letter reports the development of a reliable approach to detecting changes in land cover based on remote sensing and radiometric data

Formation of Massive Molecular Cloud Cores by Cloud-cloud Collision

OpenAIRE

Inoue, Tsuyoshi; Fukui, Yasuo

2013-01-01

Recent observations of molecular clouds around rich massive star clusters including NGC3603, Westerlund 2, and M20 revealed that the formation of massive stars could be triggered by a cloud-cloud collision. By using three-dimensional, isothermal, magnetohydrodynamics simulations with the effect of self-gravity, we demonstrate that massive, gravitationally unstable, molecular cloud cores are formed behind the strong shock waves induced by the cloud-cloud collision. We find that the massive mol...

A cosmic ray-climate link and cloud observations

Directory of Open Access Journals (Sweden)

Dunne Eimear M.

2012-11-01

Full Text Available Despite over 35 years of constant satellite-based measurements of cloud, reliable evidence of a long-hypothesized link between changes in solar activity and Earth’s cloud cover remains elusive. This work examines evidence of a cosmic ray cloud link from a range of sources, including satellite-based cloud measurements and long-term ground-based climatological measurements. The satellite-based studies can be divided into two categories: (1 monthly to decadal timescale analysis and (2 daily timescale epoch-superpositional (composite analysis. The latter analyses frequently focus on sudden high-magnitude reductions in the cosmic ray flux known as Forbush decrease events. At present, two long-term independent global satellite cloud datasets are available (ISCCP and MODIS. Although the differences between them are considerable, neither shows evidence of a solar-cloud link at either long or short timescales. Furthermore, reports of observed correlations between solar activity and cloud over the 1983–1995 period are attributed to the chance agreement between solar changes and artificially induced cloud trends. It is possible that the satellite cloud datasets and analysis methods may simply be too insensitive to detect a small solar signal. Evidence from ground-based studies suggests that some weak but statistically significant cosmic ray-cloud relationships may exist at regional scales, involving mechanisms related to the global electric circuit. However, a poor understanding of these mechanisms and their effects on cloud makes the net impacts of such links uncertain. Regardless of this, it is clear that there is no robust evidence of a widespread link between the cosmic ray flux and clouds.

Numerical simulations of altocumulus with a cloud resolving model

Energy Technology Data Exchange (ETDEWEB)

Liu, S.; Krueger, S.K. [Univ. of Utah, Salt Lake City, UT (United States)

1996-04-01

Altocumulus and altostratus clouds together cover approximately 22% of the earth`s surface. They play an important role in the earth`s energy budget through their effect on solar and infrared radiation. However, there has been little altocumulus cloud investigation by either modelers or observational programs. Starr and Cox (SC) (1985a,b) simulated an altostratus case as part of the same study in which they modeled a thin layer of cirrus. Although this calculation was originally described as representing altostratus, it probably better represents altocumulus stratiformis. In this paper, we simulate altocumulus cloud with a cloud resolving model (CRM). We simply describe the CRM first. We calculate the same middle-level cloud case as SC to compare our results with theirs. We will look at the role of cloud-scale processes in response to large-scale forcing. We will also discuss radiative effects by simulating diurnal and nocturnal cases. Finally, we discuss the utility of a 1D model by comparing 1D simulations and 2D simulations.

Use of the computer program in a cloud computing

Directory of Open Access Journals (Sweden)

Radovanović Sanja

2013-01-01

Full Text Available Cloud computing represents a specific networking, in which a computer program simulates the operation of one or more server computers. In terms of copyright, all technological processes that take place within the cloud computing are covered by the notion of copying computer programs, and exclusive right of reproduction. However, this right suffers some limitations in order to allow normal use of computer program by users. Based on the fact that the cloud computing is virtualized network, the issue of normal use of the computer program requires to put all aspects of the permitted copying into the context of a specific computing environment and specific processes within the cloud. In this sense, the paper pointed out that the user of a computer program in cloud computing, needs to obtain the consent of the right holder for any act which he undertakes using the program. In other words, the copyright in the cloud computing is a full scale, and thus the freedom of contract (in the case of this particular restriction as well.

Sky cover from MFRSR observations

Directory of Open Access Journals (Sweden)

E. Kassianov

2011-07-01

Full Text Available The diffuse all-sky surface irradiances measured at two nearby wavelengths in the visible spectral range and their modeled clear-sky counterparts are the main components of a new method for estimating the fractional sky cover of different cloud types, including cumuli. The performance of this method is illustrated using 1-min resolution data from a ground-based Multi-Filter Rotating Shadowband Radiometer (MFRSR. The MFRSR data are collected at the US Department of Energy Atmospheric Radiation Measurement (ARM Climate Research Facility (ACRF Southern Great Plains (SGP site during the summer of 2007 and represent 13 days with cumuli. Good agreement is obtained between estimated values of the fractional sky cover and those provided by a well-established independent method based on broadband observations.

Cloud field classification based on textural features

Science.gov (United States)

Sengupta, Sailes Kumar

1989-01-01

An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes

Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

Science.gov (United States)

Ehrlich, André; Bierwirth, Eike; Istomina, Larysa; Wendisch, Manfred

2017-09-01

The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff

Modelling micro- and macrophysical contributors to the dissipation of an Arctic mixed-phase cloud during the Arctic Summer Cloud Ocean Study (ASCOS

Directory of Open Access Journals (Sweden)

K. Loewe

2017-06-01

Full Text Available The Arctic climate is changing; temperature changes in the Arctic are greater than at midlatitudes, and changing atmospheric conditions influence Arctic mixed-phase clouds, which are important for the Arctic surface energy budget. These low-level clouds are frequently observed across the Arctic. They impact the turbulent and radiative heating of the open water, snow, and sea-ice-covered surfaces and influence the boundary layer structure. Therefore the processes that affect mixed-phase cloud life cycles are extremely important, yet relatively poorly understood. In this study, we present sensitivity studies using semi-idealized large eddy simulations (LESs to identify processes contributing to the dissipation of Arctic mixed-phase clouds. We found that one potential main contributor to the dissipation of an observed Arctic mixed-phase cloud, during the Arctic Summer Cloud Ocean Study (ASCOS field campaign, was a low cloud droplet number concentration (CDNC of about 2 cm−3. Introducing a high ice crystal concentration of 10 L−1 also resulted in cloud dissipation, but such high ice crystal concentrations were deemed unlikely for the present case. Sensitivity studies simulating the advection of dry air above the boundary layer inversion, as well as a modest increase in ice crystal concentration of 1 L−1, did not lead to cloud dissipation. As a requirement for small droplet numbers, pristine aerosol conditions in the Arctic environment are therefore considered an important factor determining the lifetime of Arctic mixed-phase clouds.

Soft X-ray variability and the covering fraction of active galactic nuclei

International Nuclear Information System (INIS)

Wachter, K.W.; Strauss, M.A.; Filippenko, A.V.

1988-01-01

A model to explain the observed soft X-ray variability to some low-luminosity Seyfert 1 galaxies is developed. The variability is due to changes in the covering fraction of the central source as broad-line clouds move across our line of sight. A formalism is developed which is used to demonstrate how analysis of a soft X-ray light curve can provide three important quantities: the radius of the X-ray emitting region, the radius of a typical broad-line cloud, and the electron density in the cloud. It is shown that the results are rather insensitive to the assumed radial dependence of the surface brightness of the source, but are quite sensitive to a large dispersion in cloud sizes. 55 references

Relationship between cloud radiative forcing, cloud fraction and cloud albedo, and new surface-based approach for determining cloud albedo

OpenAIRE

Y. Liu; W. Wu; M. P. Jensen; T. Toto

2011-01-01

This paper focuses on three interconnected topics: (1) quantitative relationship between surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo; (2) surfaced-based approach for measuring cloud albedo; (3) multiscale (diurnal, annual and inter-annual) variations and covariations of surface shortwave cloud radiative forcing, cloud fraction, and cloud albedo. An analytical expression is first derived to quantify the relationship between cloud radiative forcing, cloud fractio...

A CERES-like Cloud Property Climatology Using AVHRR Data

Science.gov (United States)

Minnis, P.; Bedka, K. M.; Yost, C. R.; Trepte, Q.; Bedka, S. T.; Sun-Mack, S.; Doelling, D.

2015-12-01

Clouds affect the climate system by modulating the radiation budget and distributing precipitation. Variations in cloud patterns and properties are expected to accompany changes in climate. The NASA Clouds and the Earth's Radiant Energy System (CERES) Project developed an end-to-end analysis system to measure broadband radiances from a radiometer and retrieve cloud properties from collocated high-resolution MODerate-resolution Imaging Spectroradiometer (MODIS) data to generate a long-term climate data record of clouds and clear-sky properties and top-of-atmosphere radiation budget. The first MODIS was not launched until 2000, so the current CERES record is only 15 years long at this point. The core of the algorithms used to retrieve the cloud properties from MODIS is based on the spectral complement of the Advanced Very High Resolution Radiometer (AVHRR), which has been aboard a string of satellites since 1978. The CERES cloud algorithms were adapted for application to AVHRR data and have been used to produce an ongoing CERES-like cloud property and surface temperature product that includes an initial narrowband-based radiation budget. This presentation will summarize this new product, which covers nearly 37 years, and its comparability with cloud parameters from CERES, CALIPSO, and other satellites. Examples of some applications of this dataset are given and the potential for generating a long-term radiation budget CDR is also discussed.

1 Integrating land cover and terrain characteristics to explain plague ...

African Journals Online (AJOL)

influence of land cover and terrain factors on the abundance and spatial distribution ... factors operating at diverse scales, including climate (Debien et al., 2009; Ben Ari .... A cloud free three-band SPOT 5 image captured on 27 February 2007, ...

IMAGE CAPTURE WITH SYNCHRONIZED MULTIPLE-CAMERAS FOR EXTRACTION OF ACCURATE GEOMETRIES

Directory of Open Access Journals (Sweden)

M. Koehl

2016-06-01

Full Text Available This paper presents a project of recording and modelling tunnels, traffic circles and roads from multiple sensors. The aim is the representation and the accurate 3D modelling of a selection of road infrastructures as dense point clouds in order to extract profiles and metrics from it. Indeed, these models will be used for the sizing of infrastructures in order to simulate exceptional convoy truck routes. The objective is to extract directly from the point clouds the heights, widths and lengths of bridges and tunnels, the diameter of gyrating and to highlight potential obstacles for a convoy. Light, mobile and fast acquisition approaches based on images and videos from a set of synchronized sensors have been tested in order to obtain useable point clouds. The presented solution is based on a combination of multiple low-cost cameras designed on an on-boarded device allowing dynamic captures. The experimental device containing GoPro Hero4 cameras has been set up and used for tests in static or mobile acquisitions. That way, various configurations have been tested by using multiple synchronized cameras. These configurations are discussed in order to highlight the best operational configuration according to the shape of the acquired objects. As the precise calibration of each sensor and its optics are major factors in the process of creation of accurate dense point clouds, and in order to reach the best quality available from such cameras, the estimation of the internal parameters of fisheye lenses of the cameras has been processed. Reference measures were also realized by using a 3D TLS (Faro Focus 3D to allow the accuracy assessment.

Image Capture with Synchronized Multiple-Cameras for Extraction of Accurate Geometries

Science.gov (United States)

Koehl, M.; Delacourt, T.; Boutry, C.

2016-06-01

This paper presents a project of recording and modelling tunnels, traffic circles and roads from multiple sensors. The aim is the representation and the accurate 3D modelling of a selection of road infrastructures as dense point clouds in order to extract profiles and metrics from it. Indeed, these models will be used for the sizing of infrastructures in order to simulate exceptional convoy truck routes. The objective is to extract directly from the point clouds the heights, widths and lengths of bridges and tunnels, the diameter of gyrating and to highlight potential obstacles for a convoy. Light, mobile and fast acquisition approaches based on images and videos from a set of synchronized sensors have been tested in order to obtain useable point clouds. The presented solution is based on a combination of multiple low-cost cameras designed on an on-boarded device allowing dynamic captures. The experimental device containing GoPro Hero4 cameras has been set up and used for tests in static or mobile acquisitions. That way, various configurations have been tested by using multiple synchronized cameras. These configurations are discussed in order to highlight the best operational configuration according to the shape of the acquired objects. As the precise calibration of each sensor and its optics are major factors in the process of creation of accurate dense point clouds, and in order to reach the best quality available from such cameras, the estimation of the internal parameters of fisheye lenses of the cameras has been processed. Reference measures were also realized by using a 3D TLS (Faro Focus 3D) to allow the accuracy assessment.

Top-down and bottom-up aerosol-cloud closure: towards understanding sources of uncertainty in deriving cloud shortwave radiative flux

Science.gov (United States)

Sanchez, Kevin J.; Roberts, Gregory C.; Calmer, Radiance; Nicoll, Keri; Hashimshoni, Eyal; Rosenfeld, Daniel; Ovadnevaite, Jurgita; Preissler, Jana; Ceburnis, Darius; O'Dowd, Colin; Russell, Lynn M.

2017-08-01

, satellite-derived cloud droplet number concentrations (CDNCs) were within 30 % of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after accounting for cloud-top entrainment. This work demonstrates the need to take in situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux. 1The regulatory term for UAV is remotely piloted aircraft (RPA).

Arsia Mons Spiral Cloud

Science.gov (United States)

2002-01-01

One of the benefits of the Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) Extended Mission is the opportunity to observe how the planet's weather changes during a second full martian year. This picture of Arsia Mons was taken June 19, 2001; southern spring equinox occurred the same day. Arsia Mons is a volcano nearly large enough to cover the state of New Mexico. On this particular day (the first day of Spring), the MOC wide angle cameras documented an unusual spiral-shaped cloud within the 110 km (68 mi) diameter caldera--the summit crater--of the giant volcano. Because the cloud is bright both in the red and blue images acquired by the wide angle cameras, it probably consisted mostly of fine dust grains. The cloud's spin may have been induced by winds off the inner slopes of the volcano's caldera walls resulting from the temperature differences between the walls and the caldera floor, or by a vortex as winds blew up and over the caldera. Similar spiral clouds were seen inside the caldera for several days; we don't know if this was a single cloud that persisted throughout that time or one that regenerated each afternoon. Sunlight illuminates this scene from the left/upper left.Malin Space Science Systems and the California Institute of Technology built the MOC using spare hardware from the Mars Observer mission. MSSS operates the camera from its facilities in San Diego, CA. The Jet Propulsion Laboratory's Mars Surveyor Operations Project operates the Mars Global Surveyor spacecraft with its industrial partner, Lockheed Martin Astronautics, from facilities in Pasadena, CA and Denver, CO.

Variability and trend of diurnal temperature range in China and their relationship to total cloud cover and sunshine duration

Energy Technology Data Exchange (ETDEWEB)

Xia, X. [Chinese Academy of Sciences, Beijing (China). LAGEO

2013-07-01

This study aims to investigate the effect of total cloud cover (TCC) and sunshine duration (SSD) in the variation of diurnal temperature range (DTR) in China during 1954-2009. As expected, the inter-annual variation of DTR was mainly determined by TCC. Analysis of trends of 30- year moving windows of DTR and TCC time series showed that TCC changes could account for that of DTR in some cases. However, TCC decreased during 1954-2009, which did not support DTR reduction across China. DTRs under sky conditions such as clear, cloudy and overcast showed nearly the same decreasing rate that completely accounted for the overall DTR reduction. Nevertheless, correlation between SSD and DTR was weak and not significant under clear sky conditions in which aerosol direct radiative effect should be dominant. Furthermore, 30-60% of DTR reduction was associated with DTR decrease under overcast conditions in south China. This implies that aerosol direct radiative effect appears not to be one of the main factors determining long-term changes in DTR in China. (orig.)

ON THE STAR FORMATION RATES IN MOLECULAR CLOUDS

International Nuclear Information System (INIS)

Lada, Charles J.; Lombardi, Marco; Alves, Joao F.

2010-01-01

In this paper, we investigate the level of star formation activity within nearby molecular clouds. We employ a uniform set of infrared extinction maps to provide accurate assessments of cloud mass and structure and compare these with inventories of young stellar objects within the clouds. We present evidence indicating that both the yield and rate of star formation can vary considerably in local clouds, independent of their mass and size. We find that the surface density structure of such clouds appears to be important in controlling both these factors. In particular, we find that the star formation rate (SFR) in molecular clouds is linearly proportional to the cloud mass (M 0.8 ) above an extinction threshold of A K ∼ 0.8 mag, corresponding to a gas surface density threshold of Σ gas ∼ 116 M sun pc 2 . We argue that this surface density threshold corresponds to a gas volume density threshold which we estimate to be n(H 2 ) ∼ 10 4 cm -3 . Specifically, we find SFR (M sun yr -1 ) = 4.6 ± 2.6 x 10 -8 M 0.8 (M sun ) for the clouds in our sample. This relation between the rate of star formation and the amount of dense gas in molecular clouds appears to be in excellent agreement with previous observations of both galactic and extragalactic star-forming activity. It is likely the underlying physical relationship or empirical law that most directly connects star formation activity with interstellar gas over many spatial scales within and between individual galaxies. These results suggest that the key to obtaining a predictive understanding of the SFRs in molecular clouds and galaxies is to understand those physical factors which give rise to the dense components of these clouds.

Temporal co-registration for TROPOMI cloud clearing

Directory of Open Access Journals (Sweden)

I. Genkova

2012-03-01

Full Text Available The TROPOspheric Monitoring Instrument (TROPOMI is anticipated to provide high-quality and timely global atmospheric composition information through observations of atmospheric constituents such as ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, methane, formaldehyde and aerosol properties. The methane and the aerosol retrievals require very precise cloud clearing, which is difficult to achieve at the TROPOMI spatial resolution (7 by 7 km and without thermal IR measurements. The TROPOMI carrier – the Sentinel 5 Precursor (S5P, does not include a cloud imager, thus it is planned to fly the S5P mission in a constellation with an instrument yielding an accurate cloud mask. The cloud imagery data will be provided by the US NPOESS Preparatory Project (NPP mission, which will have the Visible Infrared Imager Radiometer Suite (VIIRS on board (Scalione, 2004. This paper investigates the temporal co-registration requirements for suitable time differences between the VIIRS measurements of clouds and the TROPOMI methane and aerosol measurements, so that the former could be used for cloud clearing. The temporal co-registration is studied using Meteosat Second Generation (MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI data with 15 min temporal resolution (Veefkind, 2008b, and with data from the Geostationary Operational Environmental Satellite – 10 (GOES-10 having 1 min temporal resolution. The aim is to understand and assess the relation between the amount of allowed cloud contamination and the required time difference between the two satellites' overflights. Quantitative analysis shows that a time difference of approximately 5 min is sufficient (in most conditions to use the cloud information from the first instrument for cloud clearing in the retrievals using data from the second instrument. In recent years the A-train constellation demonstrated the benefit of flying satellites in formation. Therefore this study's findings will be

New Approach for Snow Cover Detection through Spectral Pattern Recognition with MODIS Data

Directory of Open Access Journals (Sweden)

Kyeong-Sang Lee

2017-01-01

Full Text Available Snow cover plays an important role in climate and hydrology, at both global and regional scales. Most previous studies have used static threshold techniques to detect snow cover, which can lead to errors such as misclassification of snow and clouds, because the reflectance of snow cover exhibits variability and is affected by several factors. Therefore, we present a simple new algorithm for mapping snow cover from Moderate Resolution Imaging Spectroradiometer (MODIS data using dynamic wavelength warping (DWW, which is based on dynamic time warping (DTW. DTW is a pattern recognition technique that is widely used in various fields such as human action recognition, anomaly detection, and clustering. Before performing DWW, we constructed 49 snow reflectance spectral libraries as reference data for various solar zenith angle and digital elevation model conditions using approximately 1.6 million sampled data. To verify the algorithm, we compared our results with the MODIS swath snow cover product (MOD10_L2. Producer’s accuracy, user’s accuracy, and overall accuracy values were 92.92%, 78.41%, and 92.24%, respectively, indicating good overall classification accuracy. The proposed algorithm is more useful for discriminating between snow cover and clouds than threshold techniques in some areas, such as those with a high viewing zenith angle.

Dynamics of Cavitation Clouds within a High-Intensity Focused Ultrasonic Beam

Science.gov (United States)

2012-03-01

the cloud size. I. INTRODUCTION High-intensity focused ultrasound (HIFU), along with the associated cavitation , is used in a variety of fields. The...Article 3. DATES COVERED (From - To) March 2012- May 2012 4. TITLE AND SUBTITLE Dynamics of Cavitation Clouds within a High-Intensity Focused...in initially quiescent water. The resulting pressure field and behavior of the cavitation bubbles are measured using high-speed digital in-line

Final Report for 'Modeling Electron Cloud Diagnostics for High-Intensity Proton Accelerators'

International Nuclear Information System (INIS)

Veitzer, Seth A.

2009-01-01

Electron clouds in accelerators such as the ILC degrade beam quality and limit operating efficiency. The need to mitigate electron clouds has a direct impact on the design and operation of these accelerators, translating into increased cost and reduced performance. Diagnostic techniques for measuring electron clouds in accelerating cavities are needed to provide an assessment of electron cloud evolution and mitigation. Accurate numerical modeling of these diagnostics is needed to validate the experimental techniques. In this Phase I, we developed detailed numerical models of microwave propagation through electron clouds in accelerating cavities with geometries relevant to existing and future high-intensity proton accelerators such as Project X and the ILC. Our numerical techniques and simulation results from the Phase I showed that there was a high probability of success in measuring both the evolution of electron clouds and the effects of non-uniform electron density distributions in Phase II.

A Security Monitoring Method Based on Autonomic Computing for the Cloud Platform

Directory of Open Access Journals (Sweden)

Jingjie Zhang

2018-01-01

Full Text Available With the continuous development of cloud computing, cloud security has become one of the most important issues in cloud computing. For example, data stored in the cloud platform may be attacked, and its security is difficult to be guaranteed. Therefore, we must attach weight to the issue of how to protect the data stored in the cloud. To protect data, data monitoring is a necessary process. Based on autonomic computing, we develop a cloud data monitoring system on the cloud platform, monitoring whether the data is abnormal in the cycle and analyzing the security of the data according to the monitored results. In this paper, the feasibility of the scheme can be verified through simulation. The results show that the proposed method can adapt to the dynamic change of cloud platform load, and it can also accurately evaluate the degree of abnormal data. Meanwhile, by adjusting monitoring frequency automatically, it improves the accuracy and timeliness of monitoring. Furthermore, it can reduce the monitoring cost of the system in normal operation process.

Aerosol-cloud interactions in Arctic mixed-phase stratocumulus

Science.gov (United States)

Solomon, A.

2017-12-01

Reliable climate projections require realistic simulations of Arctic cloud feedbacks. Of particular importance is accurately simulating Arctic mixed-phase stratocumuli (AMPS), which are ubiquitous and play an important role in regional climate due to their impact on the surface energy budget and atmospheric boundary layer structure through cloud-driven turbulence, radiative forcing, and precipitation. AMPS are challenging to model due to uncertainties in ice microphysical processes that determine phase partitioning between ice and radiatively important cloud liquid water. Since temperatures in AMPS are too warm for homogenous ice nucleation, ice must form through heterogeneous nucleation. In this presentation we discuss a relatively unexplored source of ice production-recycling of ice nuclei in regions of ice subsaturation. AMPS frequently have ice-subsaturated air near the cloud-driven mixed-layer base where falling ice crystals can sublimate, leaving behind IN. This study provides an idealized framework to understand feedbacks between dynamics and microphysics that maintain phase-partitioning in AMPS. In addition, the results of this study provide insight into the mechanisms and feedbacks that may maintain cloud ice in AMPS even when entrainment of IN at the mixed-layer boundaries is weak.

A 10-Year Climatology of Cloud Cover and Vertical Distribution Derived from Both Surface and GOES Observations Over the DOE ARM SGP Site

Science.gov (United States)

Xi, Baike; Dong, Xiquan; Minnis, P.; Khaiyer, M.

2010-01-01

Analysis of a decade of ARM radar-lidar and GOES observations at the SGP site reveal that 0.5 and 4-hr averages of the surface cloud fraction correspond closely to 0.5deg and 2.5deg averages of GOES cloudiness, respectively. The long-term averaged surface and GOES cloud fractions agree to within 0.5%. Cloud frequency increases and cloud amount decreases as the temporal and spatial averaging scales increase. Clouds occurred most often during winter and spring. Single-layered clouds account for 61.5% of the total cloud frequency. There are distinct bimodal vertical distributions of clouds with a lower peak around 1 km and an upper one that varies from 7.5 to 10.8 km between winter and summer, respectively. The frequency of occurrence for nighttime GOES high-cloud tops agree well with the surface observations, but are underestimated during the day.

BUSINESS MODELLING AND DATABASE DESIGN IN CLOUD COMPUTING

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Mihai-Constantin AVORNICULUI

2015-04-01

Full Text Available Electronic commerce is growing constantly from one year to another in the last decade, few are the areas that also register such a growth. It covers the exchanges of computerized data, but also electronic messaging, linear data banks and electronic transfer payment. Cloud computing, a relatively new concept and term, is a model of access services via the internet to distributed systems of configurable calculus resources at request which can be made available quickly with minimum management effort and intervention from the client and the provider. Behind an electronic commerce system in cloud there is a data base which contains the necessary information for the transactions in the system. Using business modelling, we get many benefits, which makes the design of the database used by electronic commerce systems in cloud considerably easier.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

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Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Cardiovascular imaging environment: will the future be cloud-based?

Science.gov (United States)

Kawel-Boehm, Nadine; Bluemke, David A

2017-07-01

In cardiovascular CT and MR imaging large datasets have to be stored, post-processed, analyzed and distributed. Beside basic assessment of volume and function in cardiac magnetic resonance imaging e.g., more sophisticated quantitative analysis is requested requiring specific software. Several institutions cannot afford various types of software and provide expertise to perform sophisticated analysis. Areas covered: Various cloud services exist related to data storage and analysis specifically for cardiovascular CT and MR imaging. Instead of on-site data storage, cloud providers offer flexible storage services on a pay-per-use basis. To avoid purchase and maintenance of specialized software for cardiovascular image analysis, e.g. to assess myocardial iron overload, MR 4D flow and fractional flow reserve, evaluation can be performed with cloud based software by the consumer or complete analysis is performed by the cloud provider. However, challenges to widespread implementation of cloud services include regulatory issues regarding patient privacy and data security. Expert commentary: If patient privacy and data security is guaranteed cloud imaging is a valuable option to cope with storage of large image datasets and offer sophisticated cardiovascular image analysis for institutions of all sizes.

Statistical Monitoring of Changes to Land Cover

KAUST Repository

Zerrouki, Nabil

2018-04-06

Accurate detection of changes in land cover leads to better understanding of the dynamics of landscapes. This letter reports the development of a reliable approach to detecting changes in land cover based on remote sensing and radiometric data. This approach integrates the multivariate exponentially weighted moving average (MEWMA) chart with support vector machines (SVMs) for accurate and reliable detection of changes to land cover. Here, we utilize the MEWMA scheme to identify features corresponding to changed regions. Unfortunately, MEWMA schemes cannot discriminate between real changes and false changes. If a change is detected by the MEWMA algorithm, then we execute the SVM algorithm that is based on features corresponding to detected pixels to identify the type of change. We assess the effectiveness of this approach by using the remote-sensing change detection database and the SZTAKI AirChange benchmark data set. Our results show the capacity of our approach to detect changes to land cover.

Toward the Characterization of Mixed-Phase Clouds Using Remote Sensing

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Andronache, C.

2015-12-01

Mixed-phase clouds consist of a mixture of ice particles and liquid droplets at temperatures below 0 deg C. They are present in all seasons in many regions of the world, account for about 30% of the global cloud coverage, and are linked to cloud electrification and aircraft icing. The mix of ice particles, liquid droplets, and water vapor is unstable, and such clouds are thought to have a short lifetime. A characteristic parameter is the phase composition of mixed-phase clouds. It affects the cloud life cycle and the rate of precipitation. This parameter is important for cloud parameters retrievals by radar, lidar, and satellite and is relevant for climate modeling. The phase transformation includes the remarkable Wegener-Bergeron-Findeisen (WBF) process. The direction and the rate of the phase transformations depend on the local thermodynamic and microphysical properties. Cloud condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and the dynamic response of clouds to aerosols. The complexity of dynamics and microphysics involved in mixed-phase clouds requires a set of observational and modeling tools that continue to be refined. Among these techniques, the remote sensing methods provide an increasing number of parameters, covering large regions of the world. Thus, a series of studies were dedicated to stratiform mixed-phase clouds revealing longer lifetime than previously thought. Satellite data and aircraft in situ measurements in deep convective clouds suggest that highly supercooled water often occurs in vigorous continental convective storms. In this study, we use cases of convective clouds to discuss the feasibility of mixed-phase clouds characterization and potential advantages of remote sensing.

Synergetic cloud fraction determination for SCIAMACHY using MERIS

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C. Schlundt

2011-02-01

Full Text Available Since clouds play an essential role in the Earth's climate system, it is important to understand the cloud characteristics as well as their distribution on a global scale using satellite observations. The main scientific objective of SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY onboard the ENVISAT satellite is the retrieval of vertical columns of trace gases.

On the one hand, SCIAMACHY has to be sensitive to low variations in trace gas concentrations which means the ground pixel size has to be large enough. On the other hand, such a large pixel size leads to the problem that SCIAMACHY spectra are often contaminated by clouds. SCIAMACHY spectral measurements are not well suitable to derive a reliable sub-pixel cloud fraction that can be used as input parameter for subsequent retrievals of cloud properties or vertical trace gas columns. Therefore, we use MERIS/ENVISAT spectral measurements with its high spatial resolution as sub-pixel information for the determination of MerIs Cloud fRation fOr Sciamachy (MICROS. Since MERIS covers an even broader swath width than SCIAMACHY, no problems in spatial and temporal collocation of measurements occur. This enables the derivation of a SCIAMACHY cloud fraction with an accuracy much higher as compared with other current cloud fractions that are based on SCIAMACHY's PMD (Polarization Measurement Device data.

We present our new developed MICROS algorithm, based on the threshold approach, as well as a qualitative validation of our results with MERIS satellite images for different locations, especially with respect to bright surfaces such as snow/ice and sands. In addition, the SCIAMACHY cloud fractions derived from MICROS are intercompared with other current SCIAMACHY cloud fractions based on different approaches demonstrating a considerable improvement regarding geometric cloud fraction determination using the MICROS algorithm.

Synergistic multi-sensor and multi-frequency retrieval of cloud ice water path constrained by CloudSat collocations

International Nuclear Information System (INIS)

Islam, Tanvir; Srivastava, Prashant K.

2015-01-01

The cloud ice water path (IWP) is one of the major parameters that have a strong influence on earth's radiation budget. Onboard satellite sensors are recognized as valuable tools to measure the IWP in a global scale. Albeit, active sensors such as the Cloud Profiling Radar (CPR) onboard the CloudSat satellite has better capability to measure the ice water content profile, thus, its vertical integral, IWP, than any passive microwave (MW) or infrared (IR) sensors. In this study, we investigate the retrieval of IWP from MW and IR sensors, including AMSU-A, MHS, and HIRS instruments on-board the N19 satellite, such that the retrieval is consistent with the CloudSat IWP estimates. This is achieved through the collocations between the passive satellite measurements and CloudSat scenes. Potential benefit of synergistic multi-sensor multi-frequency retrieval is investigated. Two modeling approaches are explored for the IWP retrieval – generalized linear model (GLM) and neural network (NN). The investigation has been carried out over both ocean and land surface types. The MW/IR synergy is found to be retrieved more accurate IWP than the individual AMSU-A, MHS, or HIRS measurements. Both GLM and NN approaches have been able to exploit the synergistic retrievals. - Highlights: • MW/IR synergy is investigated for IWP retrieval. • The IWP retrieval is modeled using CloudSat collocations. • Two modeling approaches are explored – GLM and ANN. • MW/IR synergy performs better than the MW or IR only retrieval

Impact of MIE-Resonances on the Atmospheric Absorption of Water Clouds

Science.gov (United States)

Wiscombe, W.; Kinne, S.; Nussenzveig, H.; Lau, William K. M. (Technical Monitor)

2002-01-01

Clouds strongly modulate radiative transfer processes in the Earth's atmosphere. Studies, which simulate bulk properties of clouds, such as absorption, require methods that accurately account for multiple scattering among individual cloud particles. Multiple scattering processes are well described by MIE-theory, if interacting particles have a spherical shape. This is a good assumption for water droplets. Thus, simulations for water clouds (especially for interactions with solar radiation) usually apply readily available MIE-codes. The presence of different drop-sizes, however, necessitates repetitive calculations for many sizes. The usual representation by a few sizes is likely to miss contributions from densely distributed, sharp resonances. Despite their usually narrow width, integrated over the entire size-spectrum of a cloud droplet distribution, the impact of missed resonances could add up. The consideration of these resonances tends to increase cloud extinction and cloud absorption. This mechanism for a larger (than by MIE-methods predicted) solar absorption has the potential to explain observational evidence of larger than predicted cloud absorption at solar wavelengths. The presentation will address the absorption impact of added resonances for typical properties of water clouds (e.g. drop size distributions, drop concentrations and cloud geometry). Special attention will be given to scenarios with observational evidence of law than simulated solar absorption; particularly if simultaneous measurements of cloud micro- and macrophysical properties are available.

Retrieval of subvisual cirrus cloud optical thickness from limb-scatter measurements

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J. T. Wiensz

2013-01-01

Full Text Available We present a technique for estimating the optical thickness of subvisual cirrus clouds detected by OSIRIS (Optical Spectrograph and Infrared Imaging System, a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Cross-sections and phase functions from an in situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is shown that the retrieved extinction profile, for an assumed effective cloud particle size, models well the measured in-cloud radiances from OSIRIS. The greatest sensitivity of the retrieved optical thickness is to the effective cloud particle size. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

Science.gov (United States)

Barta, András; Horváth, Gábor; Horváth, Ákos; Egri, Ádám; Blahó, Miklós; Barta, Pál; Bumke, Karl; Macke, Andreas

2015-02-10

Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

HNSciCloud - Overview and technical Challenges

Science.gov (United States)

Gasthuber, Martin; Meinhard, Helge; Jones, Robert

2017-10-01

HEP is only one of many sciences with sharply increasing compute requirements that cannot be met by profiting from Moore’s law alone. Commercial clouds potentially allow for realising larger economies of scale. While some small-scale experience requiring dedicated effort has been collected, public cloud resources have not been integrated yet with the standard workflows of science organisations in their private data centres; in addition, European science has not ramped up to significant scale yet. The HELIX NEBULA Science Cloud project - HNSciCloud, partly funded by the European Commission, addresses these points. Ten organisations under CERN’s leadership, covering particle physics, bioinformatics, photon science and other sciences, have joined to procure public cloud resources as well as dedicated development efforts towards this integration. The HNSciCloud project faces the challenge to accelerate developments performed by the selected commercial providers. In order to guarantee cost efficient usage of IaaS resources across a wide range of scientific communities, the technical requirements had to be carefully constructed. With respect to current IaaS offerings, dataintensive science is the biggest challenge; other points that need to be addressed concern identity federations, network connectivity and how to match business practices of large IaaS providers with those of public research organisations. In the first section, this paper will give an overview of the project and explain the findings so far. The last section will explain the key points of the technical requirements and present first results of the experience of the procurers with the services in comparison to their’on-premise’ infrastructure.

Aerosol-Cloud Interactions During Puijo Cloud Experiments - The effects of weather and local sources

Science.gov (United States)

Komppula, Mika; Portin, Harri; Leskinen, Ari; Romakkaniemi, Sami; Brus, David; Neitola, Kimmo; Hyvärinen, Antti-Pekka; Kortelainen, Aki; Hao, Liqing; Miettinen, Pasi; Jaatinen, Antti; Ahmad, Irshad; Lihavainen, Heikki; Laaksonen, Ari; Lehtinen, Kari E. J.

2013-04-01

The Puijo measurement station has provided continuous data on aerosol-cloud interactions since 2006. The station is located on top of the Puijo observation tower (306 m a.s.l, 224 m above the surrounding lake level) in Kuopio, Finland. The top of the tower is covered by cloud about 15 % of the time, offering perfect conditions for studying aerosol-cloud interactions. With a twin-inlet setup (total and interstitial inlets) we are able to separate the activated particles from the interstitial (non-activated) particles. The continuous twin-inlet measurements include aerosol size distribution, scattering and absorption. In addition cloud droplet number and size distribution are measured continuously with weather parameters. During the campaigns the twin-inlet system was additionally equipped with aerosol mass spectrometer (AMS) and Single Particle Soot Photometer (SP-2). This way we were able to define the differences in chemical composition of the activated and non-activated particles. Potential cloud condensation nuclei (CCN) in different supersaturations were measured with two CCN counters (CCNC). The other CCNC was operated with a Differential Mobility Analyzer (DMA) to obtain size selected CCN spectra. Other additional measurements included Hygroscopic Tandem Differential Mobility Analyzer (HTDMA) for particle hygroscopicity. Additionally the valuable vertical wind profiles (updraft velocities) are available from Halo Doppler lidar during the 2011 campaign. Cloud properties (droplet number and effective radius) from MODIS instrument onboard Terra and Aqua satellites were retrieved and compared with the measured values. This work summarizes the two latest intensive campaigns, Puijo Cloud Experiments (PuCE) 2010 & 2011. We study especially the effect of the local sources on the cloud activation behaviour of the aerosol particles. The main local sources include a paper mill, a heating plant, traffic and residential areas. The sources can be categorized and identified

UAV-BASED PHOTOGRAMMETRIC POINT CLOUDS – TREE STEM MAPPING IN OPEN STANDS IN COMPARISON TO TERRESTRIAL LASER SCANNER POINT CLOUDS

Directory of Open Access Journals (Sweden)

A. Fritz

2013-08-01

Full Text Available In both ecology and forestry, there is a high demand for structural information of forest stands. Forest structures, due to their heterogeneity and density, are often difficult to assess. Hence, a variety of technologies are being applied to account for this "difficult to come by" information. Common techniques are aerial images or ground- and airborne-Lidar. In the present study we evaluate the potential use of unmanned aerial vehicles (UAVs as a platform for tree stem detection in open stands. A flight campaign over a test site near Freiburg, Germany covering a target area of 120 × 75 [m2] was conducted. The dominant tree species of the site is oak (quercus robur with almost no understory growth. Over 1000 images with a tilt angle of 45° were shot. The flight pattern applied consisted of two antipodal staggered flight routes at a height of 55 [m] above the ground. We used a Panasonic G3 consumer camera equipped with a 14–42 [mm] standard lens and a 16.6 megapixel sensor. The data collection took place in leaf-off state in April 2013. The area was prepared with artificial ground control points for transformation of the structure-from-motion (SFM point cloud into real world coordinates. After processing, the results were compared with a terrestrial laser scanner (TLS point cloud of the same area. In the 0.9 [ha] test area, 102 individual trees above 7 [cm] diameter at breast height were located on in the TLS-cloud. We chose the software CMVS/PMVS-2 since its algorithms are developed with focus on dense reconstruction. The processing chain for the UAV-acquired images consists of six steps: a. cleaning the data: removing of blurry, under- or over exposed and off-site images; b. applying the SIFT operator [Lowe, 2004]; c. image matching; d. bundle adjustment; e. clustering; and f. dense reconstruction. In total, 73 stems were considered as reconstructed and located within one meter of the reference trees. In general stems were far less accurate

Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

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A. Ehrlich

2017-09-01

Full Text Available The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow. Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C.In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S, λ2 = 1650 nm (sensitive to τ, and λ3 = 2100 nm (sensitive to reff, C are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012 were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice

Land cover change of watersheds in Southern Guam from 1973 to 2001.

Science.gov (United States)

Wen, Yuming; Khosrowpanah, Shahram; Heitz, Leroy

2011-08-01

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.

Cloud type comparisons of AIRS, CloudSat, and CALIPSO cloud height and amount

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B. H. Kahn

2008-03-01

Full Text Available The precision of the two-layer cloud height fields derived from the Atmospheric Infrared Sounder (AIRS is explored and quantified for a five-day set of observations. Coincident profiles of vertical cloud structure by CloudSat, a 94 GHz profiling radar, and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO, are compared to AIRS for a wide range of cloud types. Bias and variability in cloud height differences are shown to have dependence on cloud type, height, and amount, as well as whether CloudSat or CALIPSO is used as the comparison standard. The CloudSat-AIRS biases and variability range from −4.3 to 0.5±1.2–3.6 km for all cloud types. Likewise, the CALIPSO-AIRS biases range from 0.6–3.0±1.2–3.6 km (−5.8 to −0.2±0.5–2.7 km for clouds ≥7 km (<7 km. The upper layer of AIRS has the greatest sensitivity to Altocumulus, Altostratus, Cirrus, Cumulonimbus, and Nimbostratus, whereas the lower layer has the greatest sensitivity to Cumulus and Stratocumulus. Although the bias and variability generally decrease with increasing cloud amount, the ability of AIRS to constrain cloud occurrence, height, and amount is demonstrated across all cloud types for many geophysical conditions. In particular, skill is demonstrated for thin Cirrus, as well as some Cumulus and Stratocumulus, cloud types infrared sounders typically struggle to quantify. Furthermore, some improvements in the AIRS Version 5 operational retrieval algorithm are demonstrated. However, limitations in AIRS cloud retrievals are also revealed, including the existence of spurious Cirrus near the tropopause and low cloud layers within Cumulonimbus and Nimbostratus clouds. Likely causes of spurious clouds are identified and the potential for further improvement is discussed.

Cloud attenuation studies of the six major climatic zones of Africa for Ka and V satellite system design

Directory of Open Access Journals (Sweden)

Temidayo Victor Omotosho

2014-01-01

Full Text Available Normal 0 false false false EN-GB X-NONE X-NONE Cloud cover statistics, cloud base and top height, cloud temperature, frequency of precipitation, freezing height, total cloud liquid water content (TCLWC and cloud attenuation data have been obtained for the six major climatic zones of Africa. The present results reveal a strong positive correlation between the monthly distribution of low cloud cover, cloud top height, cloud temperature, and frequency of precipitation in the six zones. The cumulative distribution of the TCLWC derived from radiosonde measurement in each climatic zone shows a departure from the TCLWC recommended by the ITU Study Group 3 data, with an exceedance percentage difference of 32% to 90% occurring 0.01% to 10% of the time. The underestimation of the TCLWC is greatest in the tropical rain forest. A comparison of the cloud attenuation cumulative distribution in the Ka and V bands reveals that the International Telecommunication Union – Region (ITU-R is an intergovernmental organization that develops rain model based on collected data around the world. This model underestimates the cloud attenuation in all of the six climatic zones by 2.0 dB and 4.7 dB for the arid Sahara desert, 1.3 dB and 3.0 dB in semi-arid North Africa, 1.3 dB and 1.5 dB in savannah North Africa, 2.0 dB and 3.6 dB in the tropical rain forest, 1.3 dB and 2.9 dB in savannah South Africa and 0.9 dB and 2.6 dB in semi-arid South Africa, respectively, at 30 and 50 GHz. Overall, the cloud attenuation in the tropical rain-forest zone is very high because of the high annual total cloud cover (98%, high annual frequency of precipitation (4.5, low annual clear sky amount (8%, high cloud depth (10,937 m, high 0°C isotherm height (4.7 km, high TCLWC (4.0 kg/m2 at 0.01% and low seasonal cloud base height (356 m.

Manifestation of Aerosol Indirect Effects in Arctic Clouds

Science.gov (United States)

Lubin, D.; Vogelmann, A. M.

2009-12-01

The first aerosol indirect effect has traditionally been conceived as an enhancement of shortwave cloud reflectance in response to decreased effective droplet size at fixed liquid water path, as cloud nucleating aerosol becomes entrained in the cloud. The high Arctic, with its pervasive low-level stratiform cloud cover and frequent episodes of anthropogenic aerosol (Artic "haze"), has in recent years served as a natural laboratory for research on actual manifestations of aerosol indirect effects. This paper will review the surprising set of developments: (1) the detection of the indirect effect as a source of surface warming, rather than cooling, throughout early spring, (2) a transition to a cooling effect in late spring, corresponding to the beginning of the sea ice melt season, and (3) detection of an indirect effect during summer, outside of the "Arctic haze" season. This paper will also discuss measurements of spectral shortwave irradiance (350-2200 nm) made at Barrow, Alaska, during the U.S. Department of Energy's Indirect and Semi-Direct Aerosol Campaign (ISDAC), which reveal complications in our conception of the indirect effect related to the ice phase in Arctic stratiform clouds.

A comparison of shock-cloud and wind-cloud interactions: effect of increased cloud density contrast on cloud evolution

Science.gov (United States)

Goldsmith, K. J. A.; Pittard, J. M.

2018-05-01

The similarities, or otherwise, of a shock or wind interacting with a cloud of density contrast χ = 10 were explored in a previous paper. Here, we investigate such interactions with clouds of higher density contrast. We compare the adiabatic hydrodynamic interaction of a Mach 10 shock with a spherical cloud of χ = 103 with that of a cloud embedded in a wind with identical parameters to the post-shock flow. We find that initially there are only minor morphological differences between the shock-cloud and wind-cloud interactions, compared to when χ = 10. However, once the transmitted shock exits the cloud, the development of a turbulent wake and fragmentation of the cloud differs between the two simulations. On increasing the wind Mach number, we note the development of a thin, smooth tail of cloud material, which is then disrupted by the fragmentation of the cloud core and subsequent `mass-loading' of the flow. We find that the normalized cloud mixing time (tmix) is shorter at higher χ. However, a strong Mach number dependence on tmix and the normalized cloud drag time, t_{drag}^' }, is not observed. Mach-number-dependent values of tmix and t_{drag}^' } from comparable shock-cloud interactions converge towards the Mach-number-independent time-scales of the wind-cloud simulations. We find that high χ clouds can be accelerated up to 80-90 per cent of the wind velocity and travel large distances before being significantly mixed. However, complete mixing is not achieved in our simulations and at late times the flow remains perturbed.

Cloud Computing, Tieto Cloud Server Model

OpenAIRE

Suikkanen, Saara

2013-01-01

The purpose of this study is to find out what is cloud computing. To be able to make wise decisions when moving to cloud or considering it, companies need to understand what cloud is consists of. Which model suits best to they company, what should be taken into account before moving to cloud, what is the cloud broker role and also SWOT analysis of cloud? To be able to answer customer requirements and business demands, IT companies should develop and produce new service models. IT house T...

Top-down and bottom-up aerosol–cloud closure: towards understanding sources of uncertainty in deriving cloud shortwave radiative flux

Directory of Open Access Journals (Sweden)

K. J. Sanchez

2017-08-01

accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNCs were within 30 % of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m−2 after accounting for cloud-top entrainment and up to 50 W m−2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m−2, even high (> 30 W m−2 after accounting for cloud-top entrainment. This work demonstrates the need to take in situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux. 1The regulatory term for UAV is remotely piloted aircraft (RPA.

Structure, shape, and evolution of radiatively accelerated QSO emission-line clouds

International Nuclear Information System (INIS)

Blumenthal, G.R.; Mathews, W.G.

1979-01-01

The possibility that the broad emission-line regions of QSOs and active galactic nuclei are formed by a multitude of small clouds which are radiatively accelerated is discussed. Although this model is by no means certain at present, it has four virtues: (1) Observed emission-line widths can be produced with observationally allowed electron densities, UV luminosities, and ionization levels. (2) The acceleration force is coherent in each cloud are found. (3) Reasonable line profiles can result for all emission lines. (4) Photoionization of hydrogen accounts for both heating and acceleration of the emission-line gas. A self-consistent model is developed for the structure, shape, and evolution of radiatively accelerated clouds. The shape varies with cloud mass, and two distinct types of clouds. Fully ionized clouds of very low mass approach a nearly spherical shape. However, all clouds having masses greater than some critical mass adopt a ''pancake'' shape. The condition for constant cloud mass in the cloud frame is shown to be equivalent to the equation of motion of a cloud in the rest frame of the QSO. The emission-line profiles can be sensitive to radial variations in the properties of the intercloud medium, and those properties that correspond to observed profiles are discussed. Finally, the covering factor of a system of pancake clouds is estimated along with the total number of clouds required--approximately 10 14 clouds in each QSO

A Climatology of Surface Cloud Radiative Effects at the ARM Tropical Western Pacific Sites

Energy Technology Data Exchange (ETDEWEB)

McFarlane, Sally A.; Long, Charles N.; Flaherty, Julia E.

2013-04-01

Cloud radiative effects on surface downwelling fluxes are investigated using long-term datasets from the three Atmospheric Radiation Measurement (ARM) sites in the Tropical Western Pacific (TWP) region. The Nauru and Darwin sites show significant variability in sky cover, downwelling radiative fluxes, and surface cloud radiative effect (CRE) due to El Niño and the Australian monsoon, respectively, while the Manus site shows little intra-seasonal or interannual variability. Cloud radar measurement of cloud base and top heights are used to define cloud types so that the effect of cloud type on the surface CRE can be examined. Clouds with low bases contribute 71-75% of the surface shortwave (SW) CRE and 66-74% of the surface longwave (LW) CRE at the three TWP sites, while clouds with mid-level bases contribute 8-9% of the SW CRE and 12-14% of the LW CRE, and clouds with high bases contribute 16-19% of the SW CRE and 15-21% of the LW CRE.

Secure Dynamic access control scheme of PHR in cloud computing.

Science.gov (United States)

Chen, Tzer-Shyong; Liu, Chia-Hui; Chen, Tzer-Long; Chen, Chin-Sheng; Bau, Jian-Guo; Lin, Tzu-Ching

2012-12-01

With the development of information technology and medical technology, medical information has been developed from traditional paper records into electronic medical records, which have now been widely applied. The new-style medical information exchange system "personal health records (PHR)" is gradually developed. PHR is a kind of health records maintained and recorded by individuals. An ideal personal health record could integrate personal medical information from different sources and provide complete and correct personal health and medical summary through the Internet or portable media under the requirements of security and privacy. A lot of personal health records are being utilized. The patient-centered PHR information exchange system allows the public autonomously maintain and manage personal health records. Such management is convenient for storing, accessing, and sharing personal medical records. With the emergence of Cloud computing, PHR service has been transferred to storing data into Cloud servers that the resources could be flexibly utilized and the operation cost can be reduced. Nevertheless, patients would face privacy problem when storing PHR data into Cloud. Besides, it requires a secure protection scheme to encrypt the medical records of each patient for storing PHR into Cloud server. In the encryption process, it would be a challenge to achieve accurately accessing to medical records and corresponding to flexibility and efficiency. A new PHR access control scheme under Cloud computing environments is proposed in this study. With Lagrange interpolation polynomial to establish a secure and effective PHR information access scheme, it allows to accurately access to PHR with security and is suitable for enormous multi-users. Moreover, this scheme also dynamically supports multi-users in Cloud computing environments with personal privacy and offers legal authorities to access to PHR. From security and effectiveness analyses, the proposed PHR access

Accurate cloud-based smart IMT measurement, its validation and stroke risk stratification in carotid ultrasound: A web-based point-of-care tool for multicenter clinical trial.

Science.gov (United States)

Saba, Luca; Banchhor, Sumit K; Suri, Harman S; Londhe, Narendra D; Araki, Tadashi; Ikeda, Nobutaka; Viskovic, Klaudija; Shafique, Shoaib; Laird, John R; Gupta, Ajay; Nicolaides, Andrew; Suri, Jasjit S

2016-08-01

This study presents AtheroCloud™ - a novel cloud-based smart carotid intima-media thickness (cIMT) measurement tool using B-mode ultrasound for stroke/cardiovascular risk assessment and its stratification. This is an anytime-anywhere clinical tool for routine screening and multi-center clinical trials. In this pilot study, the physician can upload ultrasound scans in one of the following formats (DICOM, JPEG, BMP, PNG, GIF or TIFF) directly into the proprietary cloud of AtheroPoint from the local server of the physician's office. They can then run the intelligent and automated AtheroCloud™ cIMT measurements in point-of-care settings in less than five seconds per image, while saving the vascular reports in the cloud. We statistically benchmark AtheroCloud™ cIMT readings against sonographer (a registered vascular technologist) readings and manual measurements derived from the tracings of the radiologist. One hundred patients (75 M/25 F, mean age: 68±11 years), IRB approved, Toho University, Japan, consisted of Left/Right common carotid artery (CCA) artery (200 ultrasound scans), (Toshiba, Tokyo, Japan) were collected using a 7.5MHz transducer. The measured cIMTs for L/R carotid were as follows (in mm): (i) AtheroCloud™ (0.87±0.20, 0.77±0.20); (ii) sonographer (0.97±0.26, 0.89±0.29) and (iii) manual (0.90±0.20, 0.79±0.20), respectively. The coefficient of correlation (CC) between sonographer and manual for L/R cIMT was 0.74 (Preliability and accuracy of the results. The proposed AtheroCloud™ system is completely reliable, automated, fast (3-5 seconds depending upon the image size having an internet speed of 180Mbps), accurate, and an intelligent, web-based clinical tool for multi-center clinical trials and routine telemedicine clinical care. Copyright © 2016 Elsevier Ltd. All rights reserved.

On the Influence of Air Mass Origin on Low-Cloud Properties in the Southeast Atlantic

Science.gov (United States)

Fuchs, Julia; Cermak, Jan; Andersen, Hendrik; Hollmann, Rainer; Schwarz, Katharina

2017-10-01

This study investigates the impact of air mass origin and dynamics on cloud property changes in the Southeast Atlantic (SEA) during the biomass burning season. The understanding of clouds and their determinants at different scales is important for constraining the Earth's radiative budget and thus prominent in climate system research. In this study, the thermodynamically stable SEA stratocumulus cover is observed not only as the result of local environmental conditions but also as connected to large-scale meteorology by the often neglected but important role of spatial origins of air masses entering this region. In order to assess to what extent cloud properties are impacted by aerosol concentration, air mass history, and meteorology, a Hybrid Single-Particle Lagrangian Integrated Trajectory cluster analysis is conducted linking satellite observations of cloud properties (Spinning-Enhanced Visible and Infrared Imager), information on aerosol species (Monitoring Atmospheric Composition and Climate), and meteorological context (ERA-Interim reanalysis) to air mass clusters. It is found that a characteristic pattern of air mass origins connected to distinct synoptical conditions leads to marked cloud property changes in the southern part of the study area. Long-distance air masses are related to midlatitude weather disturbances that affect the cloud microphysics, especially in the southwestern subdomain of the study area. Changes in cloud effective radius are consistent with a boundary layer deepening and changes in lower tropospheric stability (LTS). In the southeastern subdomain cloud cover is controlled by a generally higher LTS, while air mass origin plays a minor role. This study leads to a better understanding of the dynamical drivers behind observed stratocumulus cloud properties in the SEA and frames potentially interesting conditions for aerosol-cloud interactions.

A scalable and multi-purpose point cloud server (PCS) for easier and faster point cloud data management and processing

Science.gov (United States)

Cura, Rémi; Perret, Julien; Paparoditis, Nicolas

2017-05-01

In addition to more traditional geographical data such as images (rasters) and vectors, point cloud data are becoming increasingly available. Such data are appreciated for their precision and true three-Dimensional (3D) nature. However, managing point clouds can be difficult due to scaling problems and specificities of this data type. Several methods exist but are usually fairly specialised and solve only one aspect of the management problem. In this work, we propose a comprehensive and efficient point cloud management system based on a database server that works on groups of points (patches) rather than individual points. This system is specifically designed to cover the basic needs of point cloud users: fast loading, compressed storage, powerful patch and point filtering, easy data access and exporting, and integrated processing. Moreover, the proposed system fully integrates metadata (like sensor position) and can conjointly use point clouds with other geospatial data, such as images, vectors, topology and other point clouds. Point cloud (parallel) processing can be done in-base with fast prototyping capabilities. Lastly, the system is built on open source technologies; therefore it can be easily extended and customised. We test the proposed system with several billion points obtained from Lidar (aerial and terrestrial) and stereo-vision. We demonstrate loading speeds in the ˜50 million pts/h per process range, transparent-for-user and greater than 2 to 4:1 compression ratio, patch filtering in the 0.1 to 1 s range, and output in the 0.1 million pts/s per process range, along with classical processing methods, such as object detection.

Multiview point clouds denoising based on interference elimination

Science.gov (United States)

Hu, Yang; Wu, Qian; Wang, Le; Jiang, Huanyu

2018-03-01

Newly emerging low-cost depth sensors offer huge potentials for three-dimensional (3-D) modeling, but existing high noise restricts these sensors from obtaining accurate results. Thus, we proposed a method for denoising registered multiview point clouds with high noise to solve that problem. The proposed method is aimed at fully using redundant information to eliminate the interferences among point clouds of different views based on an iterative procedure. In each iteration, noisy points are either deleted or moved to their weighted average targets in accordance with two cases. Simulated data and practical data captured by a Kinect v2 sensor were tested in experiments qualitatively and quantitatively. Results showed that the proposed method can effectively reduce noise and recover local features from highly noisy multiview point clouds with good robustness, compared to truncated signed distance function and moving least squares (MLS). Moreover, the resulting low-noise point clouds can be further smoothed by the MLS to achieve improved results. This study provides the feasibility of obtaining fine 3-D models with high-noise devices, especially for depth sensors, such as Kinect.

Automatic cloud coverage assessment of Formosat-2 image

Science.gov (United States)

Hsu, Kuo-Hsien

2011-11-01

Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.

Long Read Alignment with Parallel MapReduce Cloud Platform

Directory of Open Access Journals (Sweden)

Ahmed Abdulhakim Al-Absi

2015-01-01

Full Text Available Genomic sequence alignment is an important technique to decode genome sequences in bioinformatics. Next-Generation Sequencing technologies produce genomic data of longer reads. Cloud platforms are adopted to address the problems arising from storage and analysis of large genomic data. Existing genes sequencing tools for cloud platforms predominantly consider short read gene sequences and adopt the Hadoop MapReduce framework for computation. However, serial execution of map and reduce phases is a problem in such systems. Therefore, in this paper, we introduce Burrows-Wheeler Aligner’s Smith-Waterman Alignment on Parallel MapReduce (BWASW-PMR cloud platform for long sequence alignment. The proposed cloud platform adopts a widely accepted and accurate BWA-SW algorithm for long sequence alignment. A custom MapReduce platform is developed to overcome the drawbacks of the Hadoop framework. A parallel execution strategy of the MapReduce phases and optimization of Smith-Waterman algorithm are considered. Performance evaluation results exhibit an average speed-up of 6.7 considering BWASW-PMR compared with the state-of-the-art Bwasw-Cloud. An average reduction of 30% in the map phase makespan is reported across all experiments comparing BWASW-PMR with Bwasw-Cloud. Optimization of Smith-Waterman results in reducing the execution time by 91.8%. The experimental study proves the efficiency of BWASW-PMR for aligning long genomic sequences on cloud platforms.

Long Read Alignment with Parallel MapReduce Cloud Platform

Science.gov (United States)

Al-Absi, Ahmed Abdulhakim; Kang, Dae-Ki

2015-01-01

Genomic sequence alignment is an important technique to decode genome sequences in bioinformatics. Next-Generation Sequencing technologies produce genomic data of longer reads. Cloud platforms are adopted to address the problems arising from storage and analysis of large genomic data. Existing genes sequencing tools for cloud platforms predominantly consider short read gene sequences and adopt the Hadoop MapReduce framework for computation. However, serial execution of map and reduce phases is a problem in such systems. Therefore, in this paper, we introduce Burrows-Wheeler Aligner's Smith-Waterman Alignment on Parallel MapReduce (BWASW-PMR) cloud platform for long sequence alignment. The proposed cloud platform adopts a widely accepted and accurate BWA-SW algorithm for long sequence alignment. A custom MapReduce platform is developed to overcome the drawbacks of the Hadoop framework. A parallel execution strategy of the MapReduce phases and optimization of Smith-Waterman algorithm are considered. Performance evaluation results exhibit an average speed-up of 6.7 considering BWASW-PMR compared with the state-of-the-art Bwasw-Cloud. An average reduction of 30% in the map phase makespan is reported across all experiments comparing BWASW-PMR with Bwasw-Cloud. Optimization of Smith-Waterman results in reducing the execution time by 91.8%. The experimental study proves the efficiency of BWASW-PMR for aligning long genomic sequences on cloud platforms. PMID:26839887

+Cloud: An Agent-Based Cloud Computing Platform

OpenAIRE

González, Roberto; Hernández de la Iglesia, Daniel; de la Prieta Pintado, Fernando; Gil González, Ana Belén

2017-01-01

Cloud computing is revolutionizing the services provided through the Internet, and is continually adapting itself in order to maintain the quality of its services. This study presents the platform +Cloud, which proposes a cloud environment for storing information and files by following the cloud paradigm. This study also presents Warehouse 3.0, a cloud-based application that has been developed to validate the services provided by +Cloud.

The effect of clouds on the earth's solar and infrared radiation budgets

Science.gov (United States)

Herman, G. F.; Wu, M.-L. C.; Johnson, W. T.

1980-01-01

The effect of global cloudiness on the solar and infrared components of the earth's radiation balance is studied in general circulation model experiments. A wintertime simulation is conducted in which the cloud radiative transfer calculations use realistic cloud optical properties and are fully interactive with model-generated cloudiness. This simulation is compared to others in which the clouds are alternatively non-interactive with respect to the solar or thermal radiation calculations. Other cloud processes (formation, latent heat release, precipitation, vertical mixing) were accurately simulated in these experiments. It is concluded that on a global basis clouds increase the global radiation balance by 40 W/sq m by absorbing longwave radiation, but decrease it by 56 W/sq m by reflecting solar radiation to space. The net cloud effect is therefore a reduction of the radiation balance by 16 W/sq m, and is dominated by the cloud albedo effect. Changes in cloud frequency and distribution and in atmospheric and land temperatures are also reported for the control and for the non-interactive simulations. In general, removal of the clouds' infrared absorption cools the atmosphere and causes additional cloudiness to occur, while removal of the clouds' solar radiative properties warms the atmosphere and causes fewer clouds to form. It is suggested that layered clouds and convective clouds over water enter the climate system as positive feedback components, while convective clouds over land enter as negative components.

Characterisation of the artificial neural network CiPS for cirrus cloud remote sensing with MSG/SEVIRI

Directory of Open Access Journals (Sweden)

J. Strandgren

2017-11-01

Full Text Available Cirrus clouds remain one of the key uncertainties in atmospheric research. To better understand the properties and physical processes of cirrus clouds, accurate large-scale observations from satellites are required. Artificial neural networks (ANNs have proved to be a useful tool for cirrus cloud remote sensing. Since physics is not modelled explicitly in ANNs, a thorough characterisation of the networks is necessary. In this paper the CiPS (Cirrus Properties from SEVIRI algorithm is characterised using the space-borne lidar CALIOP. CiPS is composed of a set of ANNs for the cirrus cloud detection, opacity identification and the corresponding cloud top height, ice optical thickness and ice water path retrieval from the imager SEVIRI aboard the geostationary Meteosat Second Generation satellites. First, the retrieval accuracy is characterised with respect to different land surface types. The retrieval works best over water and vegetated surfaces, whereas a surface covered by permanent snow and ice or barren reduces the cirrus detection ability and increases the retrieval errors for the ice optical thickness and ice water path if the cirrus cloud is thin (optical thickness less than approx. 0.3. Second, the retrieval accuracy is characterised with respect to the vertical arrangement of liquid, ice clouds and aerosol layers as derived from CALIOP lidar data. The CiPS retrievals show little interference from liquid water clouds and aerosol layers below an observed cirrus cloud. A liquid water cloud vertically close or adjacent to the cirrus clearly increases the average retrieval errors for the optical thickness and ice water path, respectively, only for thin cirrus clouds with an optical thickness below 0.3 or ice water path below 5.0 g m−2. For the cloud top height retrieval, only aerosol layers affect the retrieval error, with an increased positive bias when the cirrus is at low altitudes. Third, the CiPS retrieval error is

Il laser scanning e CloudCUBE per le grotte di Naica

Directory of Open Access Journals (Sweden)

Erminio Paolo Canevese

2008-03-01

Full Text Available Laser scanning and CloudCube for Naica caves On May 2007, Virtualgeo, a geomatic software development and communication company, took part in the first official expedition to Mexico. The Project, coined "Naica", involves researchers from ten universities, four companies and several laboratories. Virtualgeo carried out the survey by applying laser scanning technology to hypogeal caves covered with selenite crystals. The data was processed using CloudCUBE, a proprietary software designed to manage and model 3D point clouds. The first results of the laser scanning survey of a spectacular “forest of crystals” are presented here.

Il laser scanning e CloudCUBE per le grotte di Naica

Directory of Open Access Journals (Sweden)

Erminio Paolo Canevese

2008-03-01

Full Text Available Laser scanning and CloudCube for Naica cavesOn May 2007, Virtualgeo, a geomatic software development and communication company, took part in the first official expedition to Mexico. The Project, coined "Naica", involves researchers from ten universities, four companies and several laboratories. Virtualgeo carried out the survey by applying laser scanning technology to hypogeal caves covered with selenite crystals. The data was processed using CloudCUBE, a proprietary software designed to manage and model 3D point clouds. The first results of the laser scanning survey of a spectacular “forest of crystals” are presented here.

GATE Monte Carlo simulation of dose distribution using MapReduce in a cloud computing environment.

Science.gov (United States)

Liu, Yangchuan; Tang, Yuguo; Gao, Xin

2017-12-01

The GATE Monte Carlo simulation platform has good application prospects of treatment planning and quality assurance. However, accurate dose calculation using GATE is time consuming. The purpose of this study is to implement a novel cloud computing method for accurate GATE Monte Carlo simulation of dose distribution using MapReduce. An Amazon Machine Image installed with Hadoop and GATE is created to set up Hadoop clusters on Amazon Elastic Compute Cloud (EC2). Macros, the input files for GATE, are split into a number of self-contained sub-macros. Through Hadoop Streaming, the sub-macros are executed by GATE in Map tasks and the sub-results are aggregated into final outputs in Reduce tasks. As an evaluation, GATE simulations were performed in a cubical water phantom for X-ray photons of 6 and 18 MeV. The parallel simulation on the cloud computing platform is as accurate as the single-threaded simulation on a local server and the simulation correctness is not affected by the failure of some worker nodes. The cloud-based simulation time is approximately inversely proportional to the number of worker nodes. For the simulation of 10 million photons on a cluster with 64 worker nodes, time decreases of 41× and 32× were achieved compared to the single worker node case and the single-threaded case, respectively. The test of Hadoop's fault tolerance showed that the simulation correctness was not affected by the failure of some worker nodes. The results verify that the proposed method provides a feasible cloud computing solution for GATE.

Influence of the Arctic Oscillation on the vertical distribution of clouds as observed by the A-Train constellation of satellites

Directory of Open Access Journals (Sweden)

A. Devasthale

2012-11-01

Full Text Available The main purpose of this study is to investigate the influence of the Arctic Oscillation (AO, the dominant mode of natural variability over the northerly high latitudes, on the spatial (horizontal and vertical distribution of clouds in the Arctic. To that end, we use a suite of sensors onboard NASA's A-Train satellites that provide accurate observations of the distribution of clouds along with information on atmospheric thermodynamics. Data from three independent sensors are used (AQUA-AIRS, CALIOP-CALIPSO and CPR-CloudSat covering two time periods (winter half years, November through March, of 2002–2011 and 2006–2011, respectively along with data from the ERA-Interim reanalysis.

We show that the zonal vertical distribution of cloud fraction anomalies averaged over 67–82° N to a first approximation follows a dipole structure (referred to as "Greenland cloud dipole anomaly", GCDA, such that during the positive phase of the AO, positive and negative cloud anomalies are observed eastwards and westward of Greenland respectively, while the opposite is true for the negative phase of AO. By investigating the concurrent meteorological conditions (temperature, humidity and winds, we show that differences in the meridional energy and moisture transport during the positive and negative phases of the AO and the associated thermodynamics are responsible for the conditions that are conducive for the formation of this dipole structure. All three satellite sensors broadly observe this large-scale GCDA despite differences in their sensitivities, spatio-temporal and vertical resolutions, and the available lengths of data records, indicating the robustness of the results. The present study also provides a compelling case to carry out process-based evaluation of global and regional climate models.

Evaluation of blast wave damage from very large unconfined vapour cloud explosions

International Nuclear Information System (INIS)

Munday, G.

1975-01-01

A mathematical model is described for estimating the damage potential from unconfined vapour cloud explosions. An attempt has been made to cover the salient details of the explosive phenomenon including finite flame accelerations and finite vapour cloud sizes. The model has been evaluated against two industrial incidents and the results extrapolated to large-volume vapour clouds. The authors conclude, on the evidence of this model, that great care must be taken in the evaluation of the explosion hazard from the probable occurrence of very large unconfined explosions even at distances in excess of 1 km from the centre of initiation. (author)

A comparison of food crispness based on the cloud model.

Science.gov (United States)

Wang, Minghui; Sun, Yonghai; Hou, Jumin; Wang, Xia; Bai, Xue; Wu, Chunhui; Yu, Libo; Yang, Jie

2018-02-01

The cloud model is a typical model which transforms the qualitative concept into the quantitative description. The cloud model has been used less extensively in texture studies before. The purpose of this study was to apply the cloud model in food crispness comparison. The acoustic signals of carrots, white radishes, potatoes, Fuji apples, and crystal pears were recorded during compression. And three time-domain signal characteristics were extracted, including sound intensity, maximum short-time frame energy, and waveform index. The three signal characteristics and the cloud model were used to compare the crispness of the samples mentioned above. The crispness based on the Ex value of the cloud model, in a descending order, was carrot > potato > white radish > Fuji apple > crystal pear. To verify the results of the acoustic signals, mechanical measurement and sensory evaluation were conducted. The results of the two verification experiments confirmed the feasibility of the cloud model. The microstructures of the five samples were also analyzed. The microstructure parameters were negatively related with crispness (p cloud model method can be used for crispness comparison of different kinds of foods. The method is more accurate than the traditional methods such as mechanical measurement and sensory evaluation. The cloud model method can also be applied to other texture studies extensively. © 2017 Wiley Periodicals, Inc.

Feasibility and demonstration of a cloud-based RIID analysis system

Energy Technology Data Exchange (ETDEWEB)

Wright, Michael C., E-mail: wrightmc@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Hertz, Kristin L.; Johnson, William C. [Sandia National Laboratories, Livermore, CA 94551 (United States); Sword, Eric D.; Younkin, James R. [Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Sadler, Lorraine E. [Sandia National Laboratories, Livermore, CA 94551 (United States)

2015-06-01

A significant limitation in the operational utility of handheld and backpack radioisotope identifiers (RIIDs) is the inability of their onboard algorithms to accurately and reliably identify the isotopic sources of the measured gamma-ray energy spectrum. A possible solution is to move the spectral analysis computations to an external device, the cloud, where significantly greater capabilities are available. The implementation and demonstration of a prototype cloud-based RIID analysis system have shown this type of system to be feasible with currently available communication and computational technology. A system study has shown that the potential user community could derive significant benefits from an appropriately implemented cloud-based analysis system and has identified the design and operational characteristics required by the users and stakeholders for such a system. A general description of the hardware and software necessary to implement reliable cloud-based analysis, the value of the cloud expressed by the user community, and the aspects of the cloud implemented in the demonstrations are discussed. - Highlights: • A prototype cloud-based RIID analysis system was implemented and demonstrated. • A cloud-based system was shown to be feasible with currently available technology. • A system study identified the operational characteristics required by the users. • The system study showed that the user community could derive significant benefit. • An architecture was defined for field testing by users in relevant environments.

Feasibility and demonstration of a cloud-based RIID analysis system

International Nuclear Information System (INIS)

Wright, Michael C.; Hertz, Kristin L.; Johnson, William C.; Sword, Eric D.; Younkin, James R.; Sadler, Lorraine E.

2015-01-01

A significant limitation in the operational utility of handheld and backpack radioisotope identifiers (RIIDs) is the inability of their onboard algorithms to accurately and reliably identify the isotopic sources of the measured gamma-ray energy spectrum. A possible solution is to move the spectral analysis computations to an external device, the cloud, where significantly greater capabilities are available. The implementation and demonstration of a prototype cloud-based RIID analysis system have shown this type of system to be feasible with currently available communication and computational technology. A system study has shown that the potential user community could derive significant benefits from an appropriately implemented cloud-based analysis system and has identified the design and operational characteristics required by the users and stakeholders for such a system. A general description of the hardware and software necessary to implement reliable cloud-based analysis, the value of the cloud expressed by the user community, and the aspects of the cloud implemented in the demonstrations are discussed. - Highlights: • A prototype cloud-based RIID analysis system was implemented and demonstrated. • A cloud-based system was shown to be feasible with currently available technology. • A system study identified the operational characteristics required by the users. • The system study showed that the user community could derive significant benefit. • An architecture was defined for field testing by users in relevant environments

Hydrologic scales, cloud variability, remote sensing, and models: Implications for forecasting snowmelt and streamflow

Science.gov (United States)

Simpson, James J.; Dettinger, M.D.; Gehrke, F.; McIntire, T.J.; Hufford, Gary L.

2004-01-01

Accurate prediction of available water supply from snowmelt is needed if the myriad of human, environmental, agricultural, and industrial demands for water are to be satisfied, especially given legislatively imposed conditions on its allocation. Robust retrievals of hydrologic basin model variables (e.g., insolation or areal extent of snow cover) provide several advantages over the current operational use of either point measurements or parameterizations to help to meet this requirement. Insolation can be provided at hourly time scales (or better if needed during rapid melt events associated with flooding) and at 1-km spatial resolution. These satellite-based retrievals incorporate the effects of highly variable (both in space and time) and unpredictable cloud cover on estimates of insolation. The insolation estimates are further adjusted for the effects of basin topography using a high-resolution digital elevation model prior to model input. Simulations of two Sierra Nevada rivers in the snowmelt seasons of 1998 and 1999 indicate that even the simplest improvements in modeled insolation can improve snowmelt simulations, with 10%-20% reductions in root-mean-square errors. Direct retrieval of the areal extent of snow cover may mitigate the need to rely entirely on internal calculations of this variable, a reliance that can yield large errors that are difficult to correct until long after the season is complete and that often leads to persistent underestimates or overestimates of the volumes of the water to operational reservoirs. Agencies responsible for accurately predicting available water resources from the melt of snowpack [e.g., both federal (the National Weather Service River Forecast Centers) and state (the California Department of Water Resources)] can benefit by incorporating concepts developed herein into their operational forecasting procedures. ?? 2004 American Meteorological Society.

Comparison of monthly nighttime cloud fraction products from MODIS and AIRS and ground-based camera over Manila Observatory (14.64N, 121.07E)

Science.gov (United States)

Gacal, G. F. B.; Lagrosas, N.

2017-12-01

Cloud detection nowadays is primarily achieved by the utilization of various sensors aboard satellites. These include MODIS Aqua, MODIS Terra, and AIRS with products that include nighttime cloud fraction. Ground-based instruments are, however, only secondary to these satellites when it comes to cloud detection. Nonetheless, these ground-based instruments (e.g., LIDARs, ceilometers, and sky-cameras) offer significant datasets about a particular region's cloud cover values. For nighttime operations of cloud detection instruments, satellite-based instruments are more reliably and prominently used than ground-based ones. Therefore if a ground-based instrument for nighttime operations is operated, it ought to produce reliable scientific datasets. The objective of this study is to do a comparison between the results of a nighttime ground-based instrument (sky-camera) and that of MODIS Aqua and MODIS Terra. A Canon Powershot A2300 is placed ontop of Manila Observatory (14.64N, 121.07E) and is configured to take images of the night sky at 5min intervals. To detect pixels with clouds, the pictures are converted to grayscale format. Thresholding technique is used to screen pixels with cloud and pixels without clouds. If the pixel value is greater than 17, it is considered as a cloud; otherwise, a noncloud (Gacal et al., 2016). This algorithm is applied to the data gathered from Oct 2015 to Oct 2016. A scatter plot between satellite cloud fraction in the area covering the area 14.2877N, 120.9869E, 14.7711N and 121.4539E and ground cloud cover is graphed to find the monthly correlation. During wet season (June - November), the satellite nighttime cloud fraction vs ground measured cloud cover produce an acceptable R2 (Aqua= 0.74, Terra= 0.71, AIRS= 0.76). However, during dry season, poor R2 values are obtained (AIRS= 0.39, Aqua & Terra = 0.01). The high correlation during wet season can be attributed to a high probability that the camera and satellite see the same clouds

Silicon Photonics Cloud (SiCloud)

DEFF Research Database (Denmark)

DeVore, P. T. S.; Jiang, Y.; Lynch, M.

2015-01-01

Silicon Photonics Cloud (SiCloud.org) is the first silicon photonics interactive web tool. Here we report new features of this tool including mode propagation parameters and mode distribution galleries for user specified waveguide dimensions and wavelengths.......Silicon Photonics Cloud (SiCloud.org) is the first silicon photonics interactive web tool. Here we report new features of this tool including mode propagation parameters and mode distribution galleries for user specified waveguide dimensions and wavelengths....