The beta distribution: A statistical model for world cloud cover

NASA Technical Reports Server (NTRS)

Falls, L. W.

1973-01-01

Much work has been performed in developing empirical global cloud cover models. This investigation was made to determine an underlying theoretical statistical distribution to represent worldwide cloud cover. The beta distribution with probability density function is given to represent the variability of this random variable. It is shown that the beta distribution possesses the versatile statistical characteristics necessary to assume the wide variety of shapes exhibited by cloud cover. A total of 160 representative empirical cloud cover distributions were investigated and the conclusion was reached that this study provides sufficient statical evidence to accept the beta probability distribution as the underlying model for world cloud cover.

Comparison of culture, single and multiplex real-time PCR for detection of Sabin poliovirus shedding in recently vaccinated Indian children.

PubMed

Giri, Sidhartha; Rajan, Anand K; Kumar, Nirmal; Dhanapal, Pavithra; Venkatesan, Jayalakshmi; Iturriza-Gomara, Miren; Taniuchi, Mami; John, Jacob; Abraham, Asha Mary; Kang, Gagandeep

2017-08-01

Although, culture is considered the gold standard for poliovirus detection from stool samples, real-time PCR has emerged as a faster and more sensitive alternative. Detection of poliovirus from the stool of recently vaccinated children by culture, single and multiplex real-time PCR was compared. Of the 80 samples tested, 55 (68.75%) were positive by culture compared to 61 (76.25%) and 60 (75%) samples by the single and one step multiplex real-time PCR assays respectively. Real-time PCR (singleplex and multiplex) is more sensitive than culture for poliovirus detection in stool, although the difference was not statistically significant. © 2017 Wiley Periodicals, Inc.

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

NASA Technical Reports Server (NTRS)

Platnick, Steven E.

2011-01-01

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2006-01-01

A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

NASA Technical Reports Server (NTRS)

Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.

1992-01-01

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

Evaluation of wind field statistics near and inside clouds using a coherent Doppler lidar

NASA Astrophysics Data System (ADS)

Lottman, Brian Todd

1998-09-01

This work proposes advanced techniques for measuring the spatial wind field statistics near and inside clouds using a vertically pointing solid state coherent Doppler lidar on a fixed ground based platform. The coherent Doppler lidar is an ideal instrument for high spatial and temporal resolution velocity estimates. The basic parameters of lidar are discussed, including a complete statistical description of the Doppler lidar signal. This description is extended to cases with simple functional forms for aerosol backscatter and velocity. An estimate for the mean velocity over a sensing volume is produced by estimating the mean spectra. There are many traditional spectral estimators, which are useful for conditions with slowly varying velocity and backscatter. A new class of estimators (novel) is introduced that produces reliable velocity estimates for conditions with large variations in aerosol backscatter and velocity with range, such as cloud conditions. Performance of traditional and novel estimators is computed for a variety of deterministic atmospheric conditions using computer simulated data. Wind field statistics are produced for actual data for a cloud deck, and for multi- layer clouds. Unique results include detection of possible spectral signatures for rain, estimates for the structure function inside a cloud deck, reliable velocity estimation techniques near and inside thin clouds, and estimates for simple wind field statistics between cloud layers.

Global statistics of liquid water content and effective number density of water clouds over ocean derived from combined CALIPSO and MODIS measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.

2007-03-01

This study presents an empirical relation that links layer integrated depolarization ratios, the extinction coefficients, and effective radii of water clouds, based on Monte Carlo simulations of CALIPSO lidar observations. Combined with cloud effective radius retrieved from MODIS, cloud liquid water content and effective number density of water clouds are estimated from CALIPSO lidar depolarization measurements in this study. Global statistics of the cloud liquid water content and effective number density are presented.

Integrated spatial multiplexing of heralded single-photon sources

PubMed Central

Collins, M.J.; Xiong, C.; Rey, I.H.; Vo, T.D.; He, J.; Shahnia, S.; Reardon, C.; Krauss, T.F.; Steel, M.J.; Clark, A.S.; Eggleton, B.J.

2013-01-01

The non-deterministic nature of photon sources is a key limitation for single-photon quantum processors. Spatial multiplexing overcomes this by enhancing the heralded single-photon yield without enhancing the output noise. Here the intrinsic statistical limit of an individual source is surpassed by spatially multiplexing two monolithic silicon-based correlated photon pair sources in the telecommunications band, demonstrating a 62.4% increase in the heralded single-photon output without an increase in unwanted multipair generation. We further demonstrate the scalability of this scheme by multiplexing photons generated in two waveguides pumped via an integrated coupler with a 63.1% increase in the heralded photon rate. This demonstration paves the way for a scalable architecture for multiplexing many photon sources in a compact integrated platform and achieving efficient two-photon interference, required at the core of optical quantum computing and quantum communication protocols. PMID:24107840

Multiplexed single-molecule force spectroscopy using a centrifuge.

PubMed

Yang, Darren; Ward, Andrew; Halvorsen, Ken; Wong, Wesley P

2016-03-17

We present a miniature centrifuge force microscope (CFM) that repurposes a benchtop centrifuge for high-throughput single-molecule experiments with high-resolution particle tracking, a large force range, temperature control and simple push-button operation. Incorporating DNA nanoswitches to enable repeated interrogation by force of single molecular pairs, we demonstrate increased throughput, reliability and the ability to characterize population heterogeneity. We perform spatiotemporally multiplexed experiments to collect 1,863 bond rupture statistics from 538 traceable molecular pairs in a single experiment, and show that 2 populations of DNA zippers can be distinguished using per-molecule statistics to reduce noise.

Multiplexed single-molecule force spectroscopy using a centrifuge

PubMed Central

Yang, Darren; Ward, Andrew; Halvorsen, Ken; Wong, Wesley P.

2016-01-01

We present a miniature centrifuge force microscope (CFM) that repurposes a benchtop centrifuge for high-throughput single-molecule experiments with high-resolution particle tracking, a large force range, temperature control and simple push-button operation. Incorporating DNA nanoswitches to enable repeated interrogation by force of single molecular pairs, we demonstrate increased throughput, reliability and the ability to characterize population heterogeneity. We perform spatiotemporally multiplexed experiments to collect 1,863 bond rupture statistics from 538 traceable molecular pairs in a single experiment, and show that 2 populations of DNA zippers can be distinguished using per-molecule statistics to reduce noise. PMID:26984516

Cloud Size Distributions from Multi-sensor Observations of Shallow Cumulus Clouds

NASA Astrophysics Data System (ADS)

Kleiss, J.; Riley, E.; Kassianov, E.; Long, C. N.; Riihimaki, L.; Berg, L. K.

2017-12-01

Combined radar-lidar observations have been used for almost two decades to document temporal changes of shallow cumulus clouds at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Facility's Southern Great Plains (SGP) site in Oklahoma, USA. Since the ARM zenith-pointed radars and lidars have a narrow field-of-view (FOV), the documented cloud statistics, such as distributions of cloud chord length (or horizontal length scale), represent only a slice along the wind direction of a region surrounding the SGP site, and thus may not be representative for this region. To investigate this impact, we compare cloud statistics obtained from wide-FOV sky images collected by ground-based observations at the SGP site to those from the narrow FOV active sensors. The main wide-FOV cloud statistics considered are cloud area distributions of shallow cumulus clouds, which are frequently required to evaluate model performance, such as routine large eddy simulation (LES) currently being conducted by the ARM LASSO (LES ARM Symbiotic Simulation and Observation) project. We obtain complementary macrophysical properties of shallow cumulus clouds, such as cloud chord length, base height and thickness, from the combined radar-lidar observations. To better understand the broader observational context where these narrow FOV cloud statistics occur, we compare them to collocated and coincident cloud area distributions from wide-FOV sky images and high-resolution satellite images. We discuss the comparison results and illustrate the possibility to generate a long-term climatology of cloud size distributions from multi-sensor observations at the SGP site.

Applications of the DOE/NASA wind turbine engineering information system

NASA Technical Reports Server (NTRS)

Neustadter, H. E.; Spera, D. A.

1981-01-01

A statistical analysis of data obtained from the Technology and Engineering Information Systems was made. The systems analyzed consist of the following elements: (1) sensors which measure critical parameters (e.g., wind speed and direction, output power, blade loads and component vibrations); (2) remote multiplexing units (RMUs) on each wind turbine which frequency-modulate, multiplex and transmit sensor outputs; (3) on-site instrumentation to record, process and display the sensor output; and (4) statistical analysis of data. Two examples of the capabilities of these systems are presented. The first illustrates the standardized format for application of statistical analysis to each directly measured parameter. The second shows the use of a model to estimate the variability of the rotor thrust loading, which is a derived parameter.

Cloud encounter statistics in the 28.5-43.5 KFT altitude region from four years of GASP observations

NASA Technical Reports Server (NTRS)

Jasperson, W. H.; Nastrom, G. D.; Davis, R. E.; Holdeman, J. D.

1983-01-01

The results of an analysis of cloud encounter measurements taken at aircraft flight altitudes as part of the Global Atmospheric Sampling Program are summarized. The results can be used in estimating the probability of cloud encounter and in assessing the economic feasibility of laminar flow control aircraft along particular routes. The data presented clearly show the tropical circulation and its seasonal migration; characteristics of the mid-latitude regime, such as the large-scale traveling cyclones in the winter and increased convective activity in the summer, can be isolated in the data. The cloud encounter statistics are shown to be consistent with the mid-latitude cyclone model. A model for TIC (time-in-clouds), a cloud encounter statistic, is presented for several common airline routes.

The three-dimensional structure of cumulus clouds over the ocean. 1: Structural analysis

NASA Technical Reports Server (NTRS)

Kuo, Kwo-Sen; Welch, Ronald M.; Weger, Ronald C.; Engelstad, Mark A.; Sengupta, S. K.

1993-01-01

Thermal channel (channel 6, 10.4-12.5 micrometers) images of five Landsat thematic mapper cumulus scenes over the ocean are examined. These images are thresholded using the standard International Satellite Cloud Climatology Project (ISCCP) thermal threshold algorithm. The individual clouds in the cloud fields are segmented to obtain their structural statistics which include size distribution, orientation angle, horizontal aspect ratio, and perimeter-to-area (PtA) relationship. The cloud size distributions exhibit a double power law with the smaller clouds having a smaller absolute exponent. The cloud orientation angles, horizontal aspect ratios, and PtA exponents are found in good agreement with earlier studies. A technique also is developed to recognize individual cells within a cloud so that statistics of cloud cellular structure can be obtained. Cell structural statistics are computed for each cloud. Unicellular clouds are generally smaller (less than or equal to 1 km) and have smaller PtA exponents, while multicellular clouds are larger (greater than or equal to 1 km) and have larger PtA exponents. Cell structural statistics are similar to those of the smaller clouds. When each cell is approximated as a quadric surface using a linear least squares fit, most cells have the shape of a hyperboloid of one sheet, but about 15% of the cells are best modeled by a hyperboloid of two sheets. Less than 1% of the clouds are ellipsoidal. The number of cells in a cloud increases slightly faster than linearly with increasing cloud size. The mean nearest neighbor distance between cells in a cloud, however, appears to increase linearly with increasing cloud size and to reach a maximum when the cloud effective diameter is about 10 km; then it decreases with increasing cloud size. Sensitivity studies of threshold and lapse rate show that neither has a significant impact upon the results. A goodness-of-fit ratio is used to provide a quantitative measure of the individual cloud results. Significantly improved results are obtained after applying a smoothing operator, suggesting the eliminating subresolution scale variations with higher spatial resolution may yield even better shape analyses.

Electric Field Magnitude and Radar Reflectivity as a Function of Distance from Cloud Edge

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Merceret, Francis J.

2004-01-01

The results of analyses of data collected during a field investigation of thunderstorm anvil and debris clouds are reported. Statistics of the magnitude of the electric field are determined as a function of distance from cloud edge. Statistics of radar reflectivity near cloud edge are also determined. Both analyses use in-situ airborne field mill and cloud physics data coupled with ground-based radar measurements obtained in east-central Florida during the summer convective season. Electric fields outside of anvil and debris clouds averaged less than 3 kV/m. The average radar reflectivity at the cloud edge ranged between 0 and 5 dBZ.

Evaluation and Applications of Cloud Climatologies from CALIOP

NASA Technical Reports Server (NTRS)

Winker, David; Getzewitch, Brian; Vaughan, Mark

2008-01-01

Clouds have a major impact on the Earth radiation budget and differences in the representation of clouds in global climate models are responsible for much of the spread in predicted climate sensitivity. Existing cloud climatologies, against which these models can be tested, have many limitations. The CALIOP lidar, carried on the CALIPSO satellite, has now acquired over two years of nearly continuous cloud and aerosol observations. This dataset provides an improved basis for the characterization of 3-D global cloudiness. Global average cloud cover measured by CALIOP is about 75%, significantly higher than for existing cloud climatologies due to the sensitivity of CALIOP to optically thin cloud. Day/night biases in cloud detection appear to be small. This presentation will discuss detection sensitivity and other issues associated with producing a cloud climatology, characteristics of cloud cover statistics derived from CALIOP data, and applications of those statistics.

Fuzzy-logic based strategy for validation of multiplex methods: example with qualitative GMO assays.

PubMed

Bellocchi, Gianni; Bertholet, Vincent; Hamels, Sandrine; Moens, W; Remacle, José; Van den Eede, Guy

2010-02-01

This paper illustrates the advantages that a fuzzy-based aggregation method could bring into the validation of a multiplex method for GMO detection (DualChip GMO kit, Eppendorf). Guidelines for validation of chemical, bio-chemical, pharmaceutical and genetic methods have been developed and ad hoc validation statistics are available and routinely used, for in-house and inter-laboratory testing, and decision-making. Fuzzy logic allows summarising the information obtained by independent validation statistics into one synthetic indicator of overall method performance. The microarray technology, introduced for simultaneous identification of multiple GMOs, poses specific validation issues (patterns of performance for a variety of GMOs at different concentrations). A fuzzy-based indicator for overall evaluation is illustrated in this paper, and applied to validation data for different genetically modified elements. Remarks were drawn on the analytical results. The fuzzy-logic based rules were shown to be applicable to improve interpretation of results and facilitate overall evaluation of the multiplex method.

An Attached Payload Operations Center (APOC) at the Goddard Space Flight Center (GSFC), volume 2

NASA Technical Reports Server (NTRS)

1983-01-01

An overview of the APOC is given. For Spacelab payloads channel 2 and 3 data are input via a Statistical Multiplexer (SM) to the various SIPS functions. These include recording of the data on High Density Recorders (HDR), DQM and demultiplexing of the composite data stream by the High Rate Demultiplexer (HRDM). This system performs the inverse functions of the onboard Spacelab High Rate Multiplexer (HRM) enabling access to the data streams as multiplexed onboard the Spacelab. The contents and characteristics of channels one, two and three data as downlinked by the Tracking and Data Relay Satellite System (TDRSS) ku-band are given.

Multiplexing of ChIP-Seq Samples in an Optimized Experimental Condition Has Minimal Impact on Peak Detection.

PubMed

Kacmarczyk, Thadeous J; Bourque, Caitlin; Zhang, Xihui; Jiang, Yanwen; Houvras, Yariv; Alonso, Alicia; Betel, Doron

2015-01-01

Multiplexing samples in sequencing experiments is a common approach to maximize information yield while minimizing cost. In most cases the number of samples that are multiplexed is determined by financial consideration or experimental convenience, with limited understanding on the effects on the experimental results. Here we set to examine the impact of multiplexing ChIP-seq experiments on the ability to identify a specific epigenetic modification. We performed peak detection analyses to determine the effects of multiplexing. These include false discovery rates, size, position and statistical significance of peak detection, and changes in gene annotation. We found that, for histone marker H3K4me3, one can multiplex up to 8 samples (7 IP + 1 input) at ~21 million single-end reads each and still detect over 90% of all peaks found when using a full lane for sample (~181 million reads). Furthermore, there are no variations introduced by indexing or lane batch effects and importantly there is no significant reduction in the number of genes with neighboring H3K4me3 peaks. We conclude that, for a well characterized antibody and, therefore, model IP condition, multiplexing 8 samples per lane is sufficient to capture most of the biological signal.

Multiplexing of ChIP-Seq Samples in an Optimized Experimental Condition Has Minimal Impact on Peak Detection

PubMed Central

Kacmarczyk, Thadeous J.; Bourque, Caitlin; Zhang, Xihui; Jiang, Yanwen; Houvras, Yariv; Alonso, Alicia; Betel, Doron

2015-01-01

Multiplexing samples in sequencing experiments is a common approach to maximize information yield while minimizing cost. In most cases the number of samples that are multiplexed is determined by financial consideration or experimental convenience, with limited understanding on the effects on the experimental results. Here we set to examine the impact of multiplexing ChIP-seq experiments on the ability to identify a specific epigenetic modification. We performed peak detection analyses to determine the effects of multiplexing. These include false discovery rates, size, position and statistical significance of peak detection, and changes in gene annotation. We found that, for histone marker H3K4me3, one can multiplex up to 8 samples (7 IP + 1 input) at ~21 million single-end reads each and still detect over 90% of all peaks found when using a full lane for sample (~181 million reads). Furthermore, there are no variations introduced by indexing or lane batch effects and importantly there is no significant reduction in the number of genes with neighboring H3K4me3 peaks. We conclude that, for a well characterized antibody and, therefore, model IP condition, multiplexing 8 samples per lane is sufficient to capture most of the biological signal. PMID:26066343

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Statistical Analyses of Satellite Cloud Object Data from CERES. Part II; Tropical Convective Cloud Objects During 1998 El Nino and Validation of the Fixed Anvil Temperature Hypothesis

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man; Wong, Takmeng; Wielicki, Bruce a.; Parker, Lindsay; Lin, Bing; Eitzen, Zachary A.; Branson, Mark

2006-01-01

Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January-August 1998 are examined using the Tropical Rainfall Measuring Mission/ Clouds and the Earth s Radiant Energy System single scanner footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud-object size, sea surface temperature (SST), and satellite precessing cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the Earth composed of satellite footprints within a single dominant cloud-system type. It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100 - 150 km (small), 150 - 300 km (medium), and > 300 km (large), respectively, except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed towards high SSTs, high cloud tops, low cloud-top temperature, large ice water path, high cloud optical depth, low outgoing longwave (LW) radiation, and high albedo than the smaller-size category. As SST varied from one satellite precessing cycle to another, the changes in macrophysical properties of cloud objects over the entire tropical Pacific were small for the large-size category of cloud objects, relative to those of the small- and medium-size categories. This result suggests that the fixed anvil temperature hypothesis of Hartmann and Larson may be valid for the large-size category. Combining with the result that a higher percentage of the large-size category of cloud objects occurs during higher SST subperiods, this implies that macrophysical properties of cloud objects would be less sensitive to further warming of the climate. On the other hand, when cloud objects are classified according to SSTs where large-scale dynamics plays important roles, statistical characteristics of cloud microphysical properties, optical depth and albedo are not sensitive to the SST, but those of cloud macrophysical properties are strongly dependent upon the SST. Frequency distributions of vertical velocity from the European Center for Medium-range Weather Forecasts model that is matched to each cloud object are used to interpret some of the findings in this study.

Application of microarray analysis on computer cluster and cloud platforms.

PubMed

Bernau, C; Boulesteix, A-L; Knaus, J

2013-01-01

Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

Protein Multiplexed Immunoassay Analysis with R.

PubMed

Breen, Edmond J

2017-01-01

Plasma samples from 177 control and type 2 diabetes patients collected at three Australian hospitals are screened for 14 analytes using six custom-made multiplex kits across 60 96-well plates. In total 354 samples were collected from the patients, representing one baseline and one end point sample from each patient. R methods and source code for analyzing the analyte fluorescence response obtained from these samples by Luminex Bio-Plex ® xMap multiplexed immunoassay technology are disclosed. Techniques and R procedures for reading Bio-Plex ® result files for statistical analysis and data visualization are also presented. The need for technical replicates and the number of technical replicates are addressed as well as plate layout design strategies. Multinomial regression is used to determine plate to sample covariate balance. Methods for matching clinical covariate information to Bio-Plex ® results and vice versa are given. As well as methods for measuring and inspecting the quality of the fluorescence responses are presented. Both fixed and mixed-effect approaches for immunoassay statistical differential analysis are presented and discussed. A random effect approach to outlier analysis and detection is also shown. The bioinformatics R methodology present here provides a foundation for rigorous and reproducible analysis of the fluorescence response obtained from multiplexed immunoassays.

Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields

NASA Astrophysics Data System (ADS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-07-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

NASA Technical Reports Server (NTRS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-01-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Test scheduling optimization for 3D network-on-chip based on cloud evolutionary algorithm of Pareto multi-objective

NASA Astrophysics Data System (ADS)

Xu, Chuanpei; Niu, Junhao; Ling, Jing; Wang, Suyan

2018-03-01

In this paper, we present a parallel test strategy for bandwidth division multiplexing under the test access mechanism bandwidth constraint. The Pareto solution set is combined with a cloud evolutionary algorithm to optimize the test time and power consumption of a three-dimensional network-on-chip (3D NoC). In the proposed method, all individuals in the population are sorted in non-dominated order and allocated to the corresponding level. Individuals with extreme and similar characteristics are then removed. To increase the diversity of the population and prevent the algorithm from becoming stuck around local optima, a competition strategy is designed for the individuals. Finally, we adopt an elite reservation strategy and update the individuals according to the cloud model. Experimental results show that the proposed algorithm converges to the optimal Pareto solution set rapidly and accurately. This not only obtains the shortest test time, but also optimizes the power consumption of the 3D NoC.

Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report

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

Kollias, Pavlos

This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation ratemore » retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.« less

Shallow cloud statistics over Tropical Western Pacific: CAM5 versus ARM Comparison

NASA Astrophysics Data System (ADS)

Chandra, A.; Zhang, C.; Klein, S. A.; Ma, H. Y.; Kollias, P.; Xie, S.

2014-12-01

The role of shallow convection in the tropical convective cloud life cycle has received increasing interest because of its sensitivity to simulate large-scale tropical disturbances such as MJO. Though previous studies have proposed several hypotheses to explain the role of shallow clouds in the convective life cycle, our understanding on the role of shallow clouds is still premature. There are more questions needs to be addressed related to the role of different cloud population, conditions favorable for shallow to deep convection transitions, and their characteristics at different stages of the convective cloud life. The present study aims to improve the understanding of the shallow clouds by documenting the role of different shallow cloud population for the Year of Tropical Convection period using Atmospheric Radiation Measurement observations at the Tropical Western Pacific Manus site. The performance of the CAM5 model to simulate shallow clouds are tested using observed cloud statistics.

A cloud and radiation model-based algorithm for rainfall retrieval from SSM/I multispectral microwave measurements

NASA Technical Reports Server (NTRS)

Xiang, Xuwu; Smith, Eric A.; Tripoli, Gregory J.

1992-01-01

A hybrid statistical-physical retrieval scheme is explored which combines a statistical approach with an approach based on the development of cloud-radiation models designed to simulate precipitating atmospheres. The algorithm employs the detailed microphysical information from a cloud model as input to a radiative transfer model which generates a cloud-radiation model database. Statistical procedures are then invoked to objectively generate an initial guess composite profile data set from the database. The retrieval algorithm has been tested for a tropical typhoon case using Special Sensor Microwave/Imager (SSM/I) data and has shown satisfactory results.

Some Technical Aspects of a CALIOP and MODIS Data Analysis that Examines Near-Cloud Aerosol Properties as a Function of Cloud Fraction

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Yang, Weidong; Marshak, Alexander

2016-01-01

CALIOP shows stronger near-cloud changes in aerosol properties at higher cloud fractions. Cloud fraction variations explain a third of near-cloud changes in overall aerosol statistics. Cloud fraction and aerosol particle size distribution have a complex relationship.

Probability density cloud as a geometrical tool to describe statistics of scattered light.

PubMed

Yaitskova, Natalia

2017-04-01

First-order statistics of scattered light is described using the representation of the probability density cloud, which visualizes a two-dimensional distribution for complex amplitude. The geometric parameters of the cloud are studied in detail and are connected to the statistical properties of phase. The moment-generating function for intensity is obtained in a closed form through these parameters. An example of exponentially modified normal distribution is provided to illustrate the functioning of this geometrical approach.

Simultaneous multiplexed materials characterization using a high-precision hard X-ray micro-slit array.

PubMed

Zhang, Fan; Allen, Andrew J; Levine, Lyle E; Mancini, Derrick C; Ilavsky, Jan

2015-05-01

The needs both for increased experimental throughput and for in operando characterization of functional materials under increasingly realistic experimental conditions have emerged as major challenges across the whole of crystallography. A novel measurement scheme that allows multiplexed simultaneous measurements from multiple nearby sample volumes is presented. This new approach enables better measurement statistics or direct probing of heterogeneous structure, dynamics or elemental composition. To illustrate, the submicrometer precision that optical lithography provides has been exploited to create a multiplexed form of ultra-small-angle scattering based X-ray photon correlation spectroscopy (USAXS-XPCS) using micro-slit arrays fabricated by photolithography. Multiplexed USAXS-XPCS is applied to follow the equilibrium dynamics of a simple colloidal suspension. While the dependence of the relaxation time on momentum transfer, and its relationship with the diffusion constant and the static structure factor, follow previous findings, this measurements-in-parallel approach reduces the statistical uncertainties of this photon-starved technique to below those associated with the instrument resolution. More importantly, we note the potential of the multiplexed scheme to elucidate the response of different components of a heterogeneous sample under identical experimental conditions in simultaneous measurements. In the context of the X-ray synchrotron community, this scheme is, in principle, applicable to all in-line synchrotron techniques. Indeed, it has the potential to open a new paradigm for in operando characterization of heterogeneous functional materials, a situation that will be even further enhanced by the ongoing development of multi-bend achromat storage ring designs as the next evolution of large-scale X-ray synchrotron facilities around the world.

Simultaneous multiplexed materials characterization using a high-precision hard X-ray micro-slit array

DOE PAGES

Zhang, Fan; Allen, Andrew J.; Levine, Lyle E.; ...

2015-01-01

Here, the needs both for increased experimental throughput and forin operandocharacterization of functional materials under increasingly realistic experimental conditions have emerged as major challenges across the whole of crystallography. A novel measurement scheme that allows multiplexed simultaneous measurements from multiple nearby sample volumes is presented. This new approach enables better measurement statistics or direct probing of heterogeneous structure, dynamics or elemental composition. To illustrate, the submicrometer precision that optical lithography provides has been exploited to create a multiplexed form of ultra-small-angle scattering based X-ray photon correlation spectroscopy (USAXS-XPCS) using micro-slit arrays fabricated by photolithography. Multiplexed USAXS-XPCS is applied to followmore » the equilibrium dynamics of a simple colloidal suspension. While the dependence of the relaxation time on momentum transfer, and its relationship with the diffusion constant and the static structure factor, follow previous findings, this measurements-in-parallel approach reduces the statistical uncertainties of this photon-starved technique to below those associated with the instrument resolution. More importantly, we note the potential of the multiplexed scheme to elucidate the response of different components of a heterogeneous sample underidenticalexperimental conditions in simultaneous measurements. Lastly, in the context of the X-ray synchrotron community, this scheme is, in principle, applicable to all in-line synchrotron techniques. Indeed, it has the potential to open a new paradigm for in operando characterization of heterogeneous functional materials, a situation that will be even further enhanced by the ongoing development of multi-bend achromat storage ring designs as the next evolution of large-scale X-ray synchrotron facilities around the world.« less

The role of ensemble-based statistics in variational assimilation of cloud-affected observations from infrared imagers

NASA Astrophysics Data System (ADS)

Hacker, Joshua; Vandenberghe, Francois; Jung, Byoung-Jo; Snyder, Chris

2017-04-01

Effective assimilation of cloud-affected radiance observations from space-borne imagers, with the aim of improving cloud analysis and forecasting, has proven to be difficult. Large observation biases, nonlinear observation operators, and non-Gaussian innovation statistics present many challenges. Ensemble-variational data assimilation (EnVar) systems offer the benefits of flow-dependent background error statistics from an ensemble, and the ability of variational minimization to handle nonlinearity. The specific benefits of ensemble statistics, relative to static background errors more commonly used in variational systems, have not been quantified for the problem of assimilating cloudy radiances. A simple experiment framework is constructed with a regional NWP model and operational variational data assimilation system, to provide the basis understanding the importance of ensemble statistics in cloudy radiance assimilation. Restricting the observations to those corresponding to clouds in the background forecast leads to innovations that are more Gaussian. The number of large innovations is reduced compared to the more general case of all observations, but not eliminated. The Huber norm is investigated to handle the fat tails of the distributions, and allow more observations to be assimilated without the need for strict background checks that eliminate them. Comparing assimilation using only ensemble background error statistics with assimilation using only static background error statistics elucidates the importance of the ensemble statistics. Although the cost functions in both experiments converge to similar values after sufficient outer-loop iterations, the resulting cloud water, ice, and snow content are greater in the ensemble-based analysis. The subsequent forecasts from the ensemble-based analysis also retain more condensed water species, indicating that the local environment is more supportive of clouds. In this presentation we provide details that explain the apparent benefit from using ensembles for cloudy radiance assimilation in an EnVar context.

Statistics of optical and geometrical properties of cirrus cloud over tibetan plateau measured by lidar and radiosonde

NASA Astrophysics Data System (ADS)

Dai, Guangyao; Wu, Songhua; Song, Xiaoquan; Zhai, Xiaochun

2018-04-01

Cirrus clouds affect the energy budget and hydrological cycle of the earth's atmosphere. The Tibetan Plateau (TP) plays a significant role in the global and regional climate. Optical and geometrical properties of cirrus clouds in the TP were measured in July-August 2014 by lidar and radiosonde. The statistics and temperature dependences of the corresponding properties are analyzed. The cirrus cloud formations are discussed with respect to temperature deviation and dynamic processes.

Southeast Atlantic Cloud Properties in a Multivariate Statistical Model - How Relevant is Air Mass History for Local Cloud Properties?

NASA Astrophysics Data System (ADS)

Fuchs, Julia; Cermak, Jan; Andersen, Hendrik

2017-04-01

This study aims at untangling the impacts of external dynamics and local conditions on cloud properties in the Southeast Atlantic (SEA) by combining satellite and reanalysis data using multivariate statistics. 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, SEA stratocumulus cloud properties are observed not only as the result of local environmental conditions but also as affected by external dynamics and spatial origins of air masses entering the study area. In order to assess to what extent cloud properties are impacted by aerosol concentration, air mass history, and meteorology, a multivariate approach is conducted using satellite observations of aerosol and cloud properties (MODIS, SEVIRI), information on aerosol species composition (MACC) and meteorological context (ERA-Interim reanalysis). To account for the often-neglected but important role of air mass origin, information on air mass history based on HYSPLIT modeling is included in the statistical model. This multivariate approach is intended to lead to a better understanding of the physical processes behind observed stratocumulus cloud properties in the SEA.

Sensitivity of single column model simulations of Arctic springtime clouds to different cloud cover and mixed phase cloud parameterizations

NASA Astrophysics Data System (ADS)

Zhang, Junhua; Lohmann, Ulrike

2003-08-01

The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.

Statistical Evaluation of CRM-Simulated Cloud and Precipitation Structures Using Multi- sensor TRMM Measurements and Retrievals

NASA Astrophysics Data System (ADS)

Posselt, D.; L'Ecuyer, T.; Matsui, T.

2009-05-01

Cloud resolving models are typically used to examine the characteristics of clouds and precipitation and their relationship to radiation and the large-scale circulation. As such, they are not required to reproduce the exact location of each observed convective system, much less each individual cloud. Some of the most relevant information about clouds and precipitation is provided by instruments located on polar-orbiting satellite platforms, but these observations are intermittent "snapshots" in time, making assessment of model performance challenging. In contrast to direct comparison, model results can be evaluated statistically. This avoids the requirement for the model to reproduce the observed systems, while returning valuable information on the performance of the model in a climate-relevant sense. The focus of this talk is a model evaluation study, in which updates to the microphysics scheme used in a three-dimensional version of the Goddard Cumulus Ensemble (GCE) model are evaluated using statistics of observed clouds, precipitation, and radiation. We present the results of multiday (non-equilibrium) simulations of organized deep convection using single- and double-moment versions of a the model's cloud microphysical scheme. Statistics of TRMM multi-sensor derived clouds, precipitation, and radiative fluxes are used to evaluate the GCE results, as are simulated TRMM measurements obtained using a sophisticated instrument simulator suite. We present advantages and disadvantages of performing model comparisons in retrieval and measurement space and conclude by motivating the use of data assimilation techniques for analyzing and improving model parameterizations.

AN EXPLORATION OF THE STATISTICAL SIGNATURES OF STELLAR FEEDBACK

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

Boyden, Ryan D.; Offner, Stella S. R.; Koch, Eric W.

2016-12-20

All molecular clouds are observed to be turbulent, but the origin, means of sustenance, and evolution of the turbulence remain debated. One possibility is that stellar feedback injects enough energy into the cloud to drive observed motions on parsec scales. Recent numerical studies of molecular clouds have found that feedback from stars, such as protostellar outflows and winds, injects energy and impacts turbulence. We expand upon these studies by analyzing magnetohydrodynamic simulations of molecular clouds, including stellar winds, with a range of stellar mass-loss rates and magnetic field strengths. We generate synthetic {sup 12}CO(1–0) maps assuming that the simulations aremore » at the distance of the nearby Perseus molecular cloud. By comparing the outputs from different initial conditions and evolutionary times, we identify differences in the synthetic observations and characterize these using common astrostatistics. We quantify the different statistical responses using a variety of metrics proposed in the literature. We find that multiple astrostatistics, including the principal component analysis, the spectral correlation function, and the velocity coordinate spectrum (VCS), are sensitive to changes in stellar mass-loss rates and/or time evolution. A few statistics, including the Cramer statistic and VCS, are sensitive to the magnetic field strength. These findings demonstrate that stellar feedback influences molecular cloud turbulence and can be identified and quantified observationally using such statistics.« less

Concept of Fractal Dimension use of Multifractal Cloud Liquid Models Based on Real Data as Input to Monte Carlo Radiation Models

NASA Technical Reports Server (NTRS)

Wiscombe, W.

1999-01-01

The purpose of this paper is discuss the concept of fractal dimension; multifractal statistics as an extension of this; the use of simple multifractal statistics (power spectrum, structure function) to characterize cloud liquid water data; and to understand the use of multifractal cloud liquid water models based on real data as input to Monte Carlo radiation models of shortwave radiation transfer in 3D clouds, and the consequences of this in two areas: the design of aircraft field programs to measure cloud absorptance; and the explanation of the famous "Landsat scale break" in measured radiance.

Comparison of Histograms for Use in Cloud Observation and Modeling

NASA Technical Reports Server (NTRS)

Green, Lisa; Xu, Kuan-Man

2005-01-01

Cloud observation and cloud modeling data can be presented in histograms for each characteristic to be measured. Combining information from single-cloud histograms yields a summary histogram. Summary histograms can be compared to each other to reach conclusions about the behavior of an ensemble of clouds in different places at different times or about the accuracy of a particular cloud model. As in any scientific comparison, it is necessary to decide whether any apparent differences are statistically significant. The usual methods of deciding statistical significance when comparing histograms do not apply in this case because they assume independent data. Thus, a new method is necessary. The proposed method uses the Euclidean distance metric and bootstrapping to calculate the significance level.

Global statistics of liquid water content and effective number concentration of water clouds over ocean derived from combined CALIPSO and MODIS measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.

2007-06-01

This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liquid water content and the effective number concentration of water clouds. The method is applied to collocated CALIPSO and MODIS measurements obtained during July and October of 2006, and January 2007. Global statistics of the cloud liquid water content and effective number concentration are presented.

Development of a Multiplexed Bead-Based Suspension Array for the Detection and Discrimination of Pospiviroid Plant Pathogens

PubMed Central

van Brunschot, Sharon L.; Bergervoet, Jan H. W.; Pagendam, Daniel E.; de Weerdt, Marjanne; Geering, Andrew D. W.; Drenth, André; van der Vlugt, René A. A.

2014-01-01

Efficient and reliable diagnostic tools for the routine indexing and certification of clean propagating material are essential for the management of pospiviroid diseases in horticultural crops. This study describes the development of a true multiplexed diagnostic method for the detection and identification of all nine currently recognized pospiviroid species in one assay using Luminex bead-based suspension array technology. In addition, a new data-driven, statistical method is presented for establishing thresholds for positivity for individual assays within multiplexed arrays. When applied to the multiplexed array data generated in this study, the new method was shown to have better control of false positives and false negative results than two other commonly used approaches for setting thresholds. The 11-plex Luminex MagPlex-TAG pospiviroid array described here has a unique hierarchical assay design, incorporating a near-universal assay in addition to nine species-specific assays, and a co-amplified plant internal control assay for quality assurance purposes. All assays of the multiplexed array were shown to be 100% specific, sensitive and reproducible. The multiplexed array described herein is robust, easy to use, displays unambiguous results and has strong potential for use in routine pospiviroid indexing to improve disease management strategies. PMID:24404188

Statistical Analyses of Satellite Cloud Object Data From CERES. Part 4; Boundary-layer Cloud Objects During 1998 El Nino

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man; Wong, Takmeng; Wielicki, Bruce A.; Parker, Lindsay

2006-01-01

Three boundary-layer cloud object types, stratus, stratocumulus and cumulus, that occurred over the Pacific Ocean during January-August 1998, are identified from the CERES (Clouds and the Earth s Radiant Energy System) single scanner footprint (SSF) data from the TRMM (Tropical Rainfall Measuring Mission) satellite. This study emphasizes the differences and similarities in the characteristics of each cloud-object type between the tropical and subtropical regions and among different size categories and among small geographic areas. Both the frequencies of occurrence and statistical distributions of cloud physical properties are analyzed. In terms of frequencies of occurrence, stratocumulus clouds dominate the entire boundary layer cloud population in all regions and among all size categories. Stratus clouds are more prevalent in the subtropics and near the coastal regions, while cumulus clouds are relatively prevalent over open ocean and the equatorial regions, particularly, within the small size categories. The largest size category of stratus cloud objects occurs more frequently in the subtropics than in the tropics and has much larger average size than its cumulus and stratocumulus counterparts. Each of the three cloud object types exhibits small differences in statistical distributions of cloud optical depth, liquid water path, TOA albedo and perhaps cloud-top height, but large differences in those of cloud-top temperature and OLR between the tropics and subtropics. Differences in the sea surface temperature (SST) distributions between the tropics and subtropics influence some of the cloud macrophysical properties, but cloud microphysical properties and albedo for each cloud object type are likely determined by (local) boundary-layer dynamics and structures. Systematic variations of cloud optical depth, TOA albedo, cloud-top height, OLR and SST with cloud object sizes are pronounced for the stratocumulus and stratus types, which are related to systematic variations of the strength of inversion with cloud object sizes, produced by large-scale subsidence. The differences in cloud macrophysical properties over small regions are significantly larger than those of cloud microphysical properties and TOA albedo, suggesting a greater control of (local) large-scale dynamics and other factors on cloud object properties. When the three cloud object types are combined, the relative population among the three types is the most important factor for determining the cloud object properties in a Pacific transect where the transition of boundary-layer cloud types takes place.

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Galina; Zhang, Zhibo; Ackerman, Steven A.; Maddux, Brent

2012-01-01

The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

NASA Astrophysics Data System (ADS)

Protat, A.; Delanoë, J.; May, P. T.; Haynes, J.; Jakob, C.; O'Connor, E.; Pope, M.; Wheeler, M. C.

2011-08-01

The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.

Statistics of link blockage due to cloud cover for free-space optical communications using NCDC surface weather observation data

NASA Technical Reports Server (NTRS)

Slobin, S. D.; Piazzolla, S.

2002-01-01

Cloud opacity is one of the main atmospheric physical phenomena that can jeopardize the successful completion of an optical link between a spacecraft and a ground station. Hence, the site location chosen for a telescope used for optical communications must rely on knowledge of weather and cloud cover statistics for the geographical area where the telescope itself is located.

Airborne polarimetric Doppler weather radar: trade-offs between various engineering specifications

NASA Astrophysics Data System (ADS)

Vivekanandan, Jothiram; Loew, Eric

2018-01-01

NCAR EOL is investigating potential configurations for the next-generation airborne phased array radar (APAR) that is capable of retrieving dynamic and microphysical characteristics of clouds and precipitation. The APAR will operate at C band. The APAR will use the electronic scanning (e-scan) feature to acquire the optimal number of independent samples for recording research-quality measurements. Since the airborne radar has only a limited time for collecting measurements over a specified region (moving aircraft platform ˜ 100 m s-1), beam multiplexing will significantly enhance its ability to collect high-resolution, research-quality measurements. Beam multiplexing reduces errors in radar measurements while providing rapid updates of scan volumes. Beamwidth depends on the size of the antenna aperture. Beamwidth and directivity of elliptical, circular, and rectangular antenna apertures are compared and radar sensitivity is evaluated for various polarimetric configurations and transmit-receive (T/R) elements. In the case of polarimetric measurements, alternate transmit with alternate receive (single-channel receiver) and simultaneous reception (dual-channel receiver) is compared. From an overall architecture perspective, element-level digitization of T/R module versus digital sub-array is considered with regard to flexibility in adaptive beamforming, polarimetric performance, calibration, and data quality. Methodologies for calibration of the radar and removing bias in polarimetric measurements are outlined. The above-mentioned engineering options are evaluated for realizing an optimal APAR system suitable for measuring the high temporal and spatial resolutions of Doppler and polarimetric measurements of precipitation and clouds.

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

Newsom, R. K.; Sivaraman, C.; Shippert, T. R.

Accurate height-resolved measurements of higher-order statistical moments of vertical velocity fluctuations are crucial for improved understanding of turbulent mixing and diffusion, convective initiation, and cloud life cycles. The Atmospheric Radiation Measurement (ARM) Climate Research Facility operates coherent Doppler lidar systems at several sites around the globe. These instruments provide measurements of clear-air vertical velocity profiles in the lower troposphere with a nominal temporal resolution of 1 sec and height resolution of 30 m. The purpose of the Doppler lidar vertical velocity statistics (DLWSTATS) value-added product (VAP) is to produce height- and time-resolved estimates of vertical velocity variance, skewness, and kurtosismore » from these raw measurements. The VAP also produces estimates of cloud properties, including cloud-base height (CBH), cloud frequency, cloud-base vertical velocity, and cloud-base updraft fraction.« less

A statistical approach to the life cycle analysis of cumulus clouds selected in a virtual reality environment

NASA Astrophysics Data System (ADS)

Heus, Thijs; Jonker, Harm J. J.; van den Akker, Harry E. A.; Griffith, Eric J.; Koutek, Michal; Post, Frits H.

2009-03-01

In this study, a new method is developed to investigate the entire life cycle of shallow cumuli in large eddy simulations. Although trained observers have no problem in distinguishing the different life stages of a cloud, this process proves difficult to automate, because cloud-splitting and cloud-merging events complicate the distinction between a single system divided in several cloudy parts and two independent systems that collided. Because the human perception is well equipped to capture and to make sense of these time-dependent three-dimensional features, a combination of automated constraints and human inspection in a three-dimensional virtual reality environment is used to select clouds that are exemplary in their behavior throughout their entire life span. Three specific cases (ARM, BOMEX, and BOMEX without large-scale forcings) are analyzed in this way, and the considerable number of selected clouds warrants reliable statistics of cloud properties conditioned on the phase in their life cycle. The most dominant feature in this statistical life cycle analysis is the pulsating growth that is present throughout the entire lifetime of the cloud, independent of the case and of the large-scale forcings. The pulses are a self-sustained phenomenon, driven by a balance between buoyancy and horizontal convergence of dry air. The convective inhibition just above the cloud base plays a crucial role as a barrier for the cloud to overcome in its infancy stage, and as a buffer region later on, ensuring a steady supply of buoyancy into the cloud.

Global Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Riedi, Jerome C.; Baum, Bryan A.

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.

Statistical analysis of lightning electric field measured under Malaysian condition

NASA Astrophysics Data System (ADS)

Salimi, Behnam; Mehranzamir, Kamyar; Abdul-Malek, Zulkurnain

2014-02-01

Lightning is an electrical discharge during thunderstorms that can be either within clouds (Inter-Cloud), or between clouds and ground (Cloud-Ground). The Lightning characteristics and their statistical information are the foundation for the design of lightning protection system as well as for the calculation of lightning radiated fields. Nowadays, there are various techniques to detect lightning signals and to determine various parameters produced by a lightning flash. Each technique provides its own claimed performances. In this paper, the characteristics of captured broadband electric fields generated by cloud-to-ground lightning discharges in South of Malaysia are analyzed. A total of 130 cloud-to-ground lightning flashes from 3 separate thunderstorm events (each event lasts for about 4-5 hours) were examined. Statistical analyses of the following signal parameters were presented: preliminary breakdown pulse train time duration, time interval between preliminary breakdowns and return stroke, multiplicity of stroke, and percentages of single stroke only. The BIL model is also introduced to characterize the lightning signature patterns. Observations on the statistical analyses show that about 79% of lightning signals fit well with the BIL model. The maximum and minimum of preliminary breakdown time duration of the observed lightning signals are 84 ms and 560 us, respectively. The findings of the statistical results show that 7.6% of the flashes were single stroke flashes, and the maximum number of strokes recorded was 14 multiple strokes per flash. A preliminary breakdown signature in more than 95% of the flashes can be identified.

Validation of AIRS/AMSU Cloud Retrievals Using MODIS Cloud Analyses

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel

2005-01-01

The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.

MiniX-STR multiplex system population study in Japan and application to degraded DNA analysis.

PubMed

Asamura, H; Sakai, H; Kobayashi, K; Ota, M; Fukushima, H

2006-05-01

We sought to evaluate a more effective system for analyzing X-chromosomal short tandem repeats (X-STRs) in highly degraded DNA. To generate smaller amplicon lengths, we designed new polymerase chain reaction (PCR) primers for DXS7423, DXS6789, DXS101, GATA31E08, DXS8378, DXS7133, DXS7424, and GATA165B12 at X-linked short tandem repeat (STR) loci, devising two miniX-multiplex PCR systems. Among 333 Japanese individuals, these X-linked loci were detected in amplification products ranging in length from 76 to 169 bp, and statistical analyses of the eight loci indicated a high usefulness for the Japanese forensic practice. Results of tests on highly degraded DNA indicated the miniX-STR multiplex strategies to be an effective system for analyzing degraded DNA. We conclude that analysis by the current miniX-STR multiplex systems offers high effectiveness for personal identification from degraded DNA samples.

Fronthaul evolution: From CPRI to Ethernet

NASA Astrophysics Data System (ADS)

Gomes, Nathan J.; Chanclou, Philippe; Turnbull, Peter; Magee, Anthony; Jungnickel, Volker

2015-12-01

It is proposed that using Ethernet in the fronthaul, between base station baseband unit (BBU) pools and remote radio heads (RRHs), can bring a number of advantages, from use of lower-cost equipment, shared use of infrastructure with fixed access networks, to obtaining statistical multiplexing and optimised performance through probe-based monitoring and software-defined networking. However, a number of challenges exist: ultra-high-bit-rate requirements from the transport of increased bandwidth radio streams for multiple antennas in future mobile networks, and low latency and jitter to meet delay requirements and the demands of joint processing. A new fronthaul functional division is proposed which can alleviate the most demanding bit-rate requirements by transport of baseband signals instead of sampled radio waveforms, and enable statistical multiplexing gains. Delay and synchronisation issues remain to be solved.

Characterization of Cloud Water-Content Distribution

NASA Technical Reports Server (NTRS)

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.

Satellite-based Assessment of Global Warm Cloud Properties Associated with Aerosols, Atmospheric Stability, and Diurnal Cycle

NASA Technical Reports Server (NTRS)

Matsui, Toshihisa; Masunaga, Hirohiko; Kreidenweis, Sonia M.; Pielke, Roger A., Sr.; Tao, Wei-Kuo; Chin, Mian; Kaufman, Yoram J.

2006-01-01

This study examines variability in marine low cloud properties derived from semi-global observations by the Tropical Rainfall Measuring Mission (TRMM) satellite, as linked to the aerosol index (AI) and lower-tropospheric stability (LTS). AI is derived from the Moderate Resolution Imaging Spectroradiometer (Terra MODIS) sensor and the Goddard Chemistry Aerosol Radiation and Transportation (GOCART) model, and is used to represent column-integrated aerosol concentrations. LTS is derived from the NCEP/NCAR reanalysis, and represents the background thermodynamic environment in which the clouds form. Global statistics reveal that cloud droplet size tends to be smallest in polluted (high-AI) and strong inversion (high-LTS) environments. Statistical quantification shows that cloud droplet size is better correlated with AI than it is with LTS. Simultaneously, the cloud liquid water path (CLWP) tends to decrease as AI increases. This correlation does not support the hypothesis or assumption that constant or increased CLWP is associated with high aerosol concentrations. Global variability in corrected cloud albedo (CCA), the product of cloud optical depth and cloud fraction, is very well explained by LTS, while both AI and LTS are needed to explain local variability in CCA. Most of the local correlations between AI and cloud properties are similar to the results from the global statistics, while weak anomalous aerosol-cloud correlations appear locally in the regions where simultaneous high (low) AI and low (high) LTS compensate each other. Daytime diurnal cycles explain additional variability in cloud properties. CCA has the largest diurnal cycle in high-LTS regions. Cloud droplet size and CLWP have weak diurnal cycles that differ between clean and polluted environments. The combined results suggest that investigations of marine low cloud radiative forcing and its relationship to hypothesized aerosol indirect effects must consider the combined effects of aerosols, thermodynamics, and the diurnal cycle.

DETERMINATION OF CLOUD PARAMETERS FOR NEROS II FROM DIGITAL SATELLITE DATA

EPA Science Inventory

As part of the input for their regional-scale photochemical oxidant model of air pollution, known as the Regional Oxidant Model, requires statistical descriptions of total cloud amount, cumulus cloud amount, and cumulus cloud top height for certain regions and dates. These statis...

An application of statistical mechanics for representing equilibrium perimeter distributions of tropical convective clouds

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Alva, S.; Glenn, I. B.; Krueger, S. K.

2015-12-01

There are two possible approaches for parameterizing sub-grid cloud dynamics in a coarser grid model. The most common is to use a fine scale model to explicitly resolve the mechanistic details of clouds to the best extent possible, and then to parameterize these behaviors cloud state for the coarser grid. A second is to invoke physical intuition and some very general theoretical principles from equilibrium statistical mechanics. This approach avoids any requirement to resolve time-dependent processes in order to arrive at a suitable solution. The second approach is widely used elsewhere in the atmospheric sciences: for example the Planck function for blackbody radiation is derived this way, where no mention is made of the complexities of modeling a large ensemble of time-dependent radiation-dipole interactions in order to obtain the "grid-scale" spectrum of thermal emission by the blackbody as a whole. We find that this statistical approach may be equally suitable for modeling convective clouds. Specifically, we make the physical argument that the dissipation of buoyant energy in convective clouds is done through mixing across a cloud perimeter. From thermodynamic reasoning, one might then anticipate that vertically stacked isentropic surfaces are characterized by a power law dlnN/dlnP = -1, where N(P) is the number clouds of perimeter P. In a Giga-LES simulation of convective clouds within a 100 km square domain we find that such a power law does appear to characterize simulated cloud perimeters along isentropes, provided a sufficient cloudy sample. The suggestion is that it may be possible to parameterize certain important aspects of cloud state without appealing to computationally expensive dynamic simulations.

Millstone: software for multiplex microbial genome analysis and engineering

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

Goodman, Daniel B.; Kuznetsov, Gleb; Lajoie, Marc J.

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. Here, we describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

Millstone: software for multiplex microbial genome analysis and engineering.

PubMed

Goodman, Daniel B; Kuznetsov, Gleb; Lajoie, Marc J; Ahern, Brian W; Napolitano, Michael G; Chen, Kevin Y; Chen, Changping; Church, George M

2017-05-25

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. We describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

Millstone: software for multiplex microbial genome analysis and engineering

DOE PAGES

Goodman, Daniel B.; Kuznetsov, Gleb; Lajoie, Marc J.; ...

2017-05-25

Inexpensive DNA sequencing and advances in genome editing have made computational analysis a major rate-limiting step in adaptive laboratory evolution and microbial genome engineering. Here, we describe Millstone, a web-based platform that automates genotype comparison and visualization for projects with up to hundreds of genomic samples. To enable iterative genome engineering, Millstone allows users to design oligonucleotide libraries and create successive versions of reference genomes. Millstone is open source and easily deployable to a cloud platform, local cluster, or desktop, making it a scalable solution for any lab.

Active sensor synergy for arctic cloud microphysics

NASA Astrophysics Data System (ADS)

Sato, Kaori; Okamoto, Hajime; Katagiri, Shuichiro; Shiobara, Masataka; Yabuki, Masanori; Takano, Toshiaki

2018-04-01

In this study, we focus on the retrieval of liquid and ice-phase cloud microphysics from spaceborne and ground-based lidar-cloud radar synergy. As an application of the cloud retrieval algorithm developed for the EarthCARE satellite mission (JAXA-ESA) [1], the derived statistics of cloud microphysical properties in high latitudes and their relation to the Arctic climate are investigated.

A statistical retrieval of cloud parameters for the millimeter wave Ice Cloud Imager on board MetOp-SG

NASA Astrophysics Data System (ADS)

Prigent, Catherine; Wang, Die; Aires, Filipe; Jimenez, Carlos

2017-04-01

The meteorological observations from satellites in the microwave domain are currently limited to below 190 GHz. However, the next generation of European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation-EPS-SG will carry an instrument, the Ice Cloud Imager (ICI), with frequencies up to 664 GHz, to improve the characterization of the cloud frozen phase. In this paper, a statistical retrieval of cloud parameters for ICI is developed, trained on a synthetic database derived from the coupling of a mesoscale cloud model and radiative transfer calculations. The hydrometeor profiles simulated with the Weather Research and Forecasting model (WRF) for twelve diverse European mid-latitude situations are used to simulate the brightness temperatures with the Atmospheric Radiative Transfer Simulator (ARTS) to prepare the retrieval database. The WRF+ARTS simulations have been compared to the Special Sensor Microwave Imager/Sounder (SSMIS) observations up to 190 GHz: this successful evaluation gives us confidence in the simulations at the ICI channels from 183 to 664 GHz. Statistical analyses have been performed on this simulated retrieval database, showing that it is not only physically realistic but also statistically satisfactory for retrieval purposes. A first Neural Network (NN) classifier is used to detect the cloud presence. A second NN is developed to retrieve the liquid and ice integrated cloud quantities over sea and land separately. The detection and retrieval of the hydrometeor quantities (i.e., ice, snow, graupel, rain, and liquid cloud) are performed with ICI-only, and with ICI combined with observations from the MicroWave Imager (MWI, with frequencies from 19 to 190 GHz, also on board MetOp-SG). The ICI channels have been optimized for the detection and quantification of the cloud frozen phases: adding the MWI channels improves the performance of the vertically integrated hydrometeor contents, especially for the cloud liquid phases. The relative error for the retrieved integrated frozen water content (FWP, i.e., ice+snow+graupel) is below 40% for 0.1kg/m2 < FWP < 0.5kg/m2 and below 20% for FWP > 0.5 kg/m2.

A simple biota removal algorithm for 35 GHz cloud radar measurements

NASA Astrophysics Data System (ADS)

Kalapureddy, Madhu Chandra R.; Sukanya, Patra; Das, Subrata K.; Deshpande, Sachin M.; Pandithurai, Govindan; Pazamany, Andrew L.; Ambuj K., Jha; Chakravarty, Kaustav; Kalekar, Prasad; Krishna Devisetty, Hari; Annam, Sreenivas

2018-03-01

Cloud radar reflectivity profiles can be an important measurement for the investigation of cloud vertical structure (CVS). However, extracting intended meteorological cloud content from the measurement often demands an effective technique or algorithm that can reduce error and observational uncertainties in the recorded data. In this work, a technique is proposed to identify and separate cloud and non-hydrometeor echoes using the radar Doppler spectral moments profile measurements. The point and volume target-based theoretical radar sensitivity curves are used for removing the receiver noise floor and identified radar echoes are scrutinized according to the signal decorrelation period. Here, it is hypothesized that cloud echoes are observed to be temporally more coherent and homogenous and have a longer correlation period than biota. That can be checked statistically using ˜ 4 s sliding mean and standard deviation value of reflectivity profiles. The above step helps in screen out clouds critically by filtering out the biota. The final important step strives for the retrieval of cloud height. The proposed algorithm potentially identifies cloud height solely through the systematic characterization of Z variability using the local atmospheric vertical structure knowledge besides to the theoretical, statistical and echo tracing tools. Thus, characterization of high-resolution cloud radar reflectivity profile measurements has been done with the theoretical echo sensitivity curves and observed echo statistics for the true cloud height tracking (TEST). TEST showed superior performance in screening out clouds and filtering out isolated insects. TEST constrained with polarimetric measurements was found to be more promising under high-density biota whereas TEST combined with linear depolarization ratio and spectral width perform potentially to filter out biota within the highly turbulent shallow cumulus clouds in the convective boundary layer (CBL). This TEST technique is promisingly simple in realization but powerful in performance due to the flexibility in constraining, identifying and filtering out the biota and screening out the true cloud content, especially the CBL clouds. Therefore, the TEST algorithm is superior for screening out the low-level clouds that are strongly linked to the rainmaking mechanism associated with the Indian Summer Monsoon region's CVS.

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

NASA Astrophysics Data System (ADS)

Platnick, S.; Wind, G.; Zhang, Z.; Ackerman, S. A.; Maddux, B. C.

2012-12-01

The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the 1.6, 2.1, and 3.7 μm spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "not-clear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud edges (defined by immediate adjacency to "clear" MOD/MYD35 pixels) as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the 1D cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

COLLABORATIVE RESEARCH:USING ARM OBSERVATIONS & ADVANCED STATISTICAL TECHNIQUES TO EVALUATE CAM3 CLOUDS FOR DEVELOPMENT OF STOCHASTIC CLOUD-RADIATION

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

Somerville, Richard

2013-08-22

The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key stepmore » in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been a collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen).« less

Climatology analysis of cirrus cloud in ARM site: South Great Plain

NASA Astrophysics Data System (ADS)

Olayinka, K.

2017-12-01

Cirrus cloud play an important role in the atmospheric energy balance and hence in the earth's climate system. The properties of optically thin clouds can be determined from measurements of transmission of the direct solar beam. The accuracy of cloud optical properties determined in this way is compromised by contamination of the direct transmission by light that is scattered into the sensors field of view. With the forward scattering correction method developed by Min et al., (2004), the accuracy of thin cloud retrievals from MFRSR has been improved. Our result shows over 30% of cirrus cloud present in the atmosphere are within optical depth between (1-2). In this study, we do statistics studies on cirrus clouds properties based on multi-years cirrus cloud measurements from MFRSR at ARM site from the South Great Plain (SGP) site due to its relatively easy accessibility, wide variability of climate cloud types and surface flux properties, large seasonal variation in temperature and specific humidity. Through the statistic studies, temporal and spatial variations of cirrus clouds are investigated. Since the presence of cirrus cloud increases the effect of greenhouse gases, we will retrieve the aerosol optical depth in all the cirrus cloud regions using a radiative transfer model for atmospheric correction. Calculate thin clouds optical depth (COD), and aerosol optical depth (AOD) using a radiative transfer model algorithm, e.g.: MODTRAN (MODerate resolution atmospheric TRANsmission)

Physical View of Cloud Seeding

ERIC Educational Resources Information Center

Tribus, Myron

1970-01-01

Reviews experimental data on various aspects of climate control. Includes a discussion of (1) the physics of cloud seeding, (2) the applications of cloud seeding, and (3) the role of statistics in the field of weather modification. Bibliography. (LC)

Modeling and parameterization of horizontally inhomogeneous cloud radiative properties

NASA Technical Reports Server (NTRS)

Welch, R. M.

1995-01-01

One of the fundamental difficulties in modeling cloud fields is the large variability of cloud optical properties (liquid water content, reflectance, emissivity). The stratocumulus and cirrus clouds, under special consideration for FIRE, exhibit spatial variability on scales of 1 km or less. While it is impractical to model individual cloud elements, the research direction is to model a statistical ensembles of cloud elements with mean-cloud properties specified. The major areas of this investigation are: (1) analysis of cloud field properties; (2) intercomparison of cloud radiative model results with satellite observations; (3) radiative parameterization of cloud fields; and (4) development of improved cloud classification algorithms.

Shallow cumuli ensemble statistics for development of a stochastic parameterization

NASA Astrophysics Data System (ADS)

Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

2014-05-01

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

Macrophysical and optical properties of midlatitude high-altitude clouds from 4 ground-based lidars and collocated CALIOP observations

NASA Astrophysics Data System (ADS)

Dupont, J. C.; Haeffelin, M.; Morille, Y.; Noel, V.; Keckhut, P.; Comstock, J.; Winker, D.; Chervet, P.; Roblin, A.

2009-04-01

Cirrus clouds not only play a major role in the energy budget of the Earth-Atmosphere system, but are also important in the hydrological cycle [Stephens et al., 1990; Webster, 1994]. According to satellite passive remote sensing, high-altitude clouds cover as much as 40% of the earth's surface on average (Liou 1986; Stubenrauch et al., 2006) and can reach 70% of cloud cover over the Tropics (Wang et al., 1996; Nazaryan et al., 2008). Hence, given their very large cloud cover, they have a major role in the climate system (Lynch et al. 2001). Cirrus clouds can be classified into three distinct families according to their optical thickness, namely subvisible clouds (OD<0.03), semi-transparent clouds (0.03

Statistical thermodynamics and the size distributions of tropical convective clouds.

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Glenn, I. B.; Krueger, S. K.; Ferlay, N.

2017-12-01

Parameterizations for sub-grid cloud dynamics are commonly developed by using fine scale modeling or measurements to explicitly resolve the mechanistic details of clouds to the best extent possible, and then to formulating these behaviors cloud state for use within a coarser grid. A second is to invoke physical intuition and some very general theoretical principles from equilibrium statistical thermodynamics. This second approach is quite widely used elsewhere in the atmospheric sciences: for example to explain the heat capacity of air, blackbody radiation, or even the density profile or air in the atmosphere. Here we describe how entrainment and detrainment across cloud perimeters is limited by the amount of available air and the range of moist static energy in the atmosphere, and that constrains cloud perimeter distributions to a power law with a -1 exponent along isentropes and to a Boltzmann distribution across isentropes. Further, the total cloud perimeter density in a cloud field is directly tied to the buoyancy frequency of the column. These simple results are shown to be reproduced within a complex dynamic simulation of a tropical convective cloud field and in passive satellite observations of cloud 3D structures. The implication is that equilibrium tropical cloud structures can be inferred from the bulk thermodynamic structure of the atmosphere without having to analyze computationally expensive dynamic simulations.

Evolution of Precipitation Particle Size Distributions within MC3E Systems and its Impact on Aerosol-Cloud-Precipitation Interactions: Final Report

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

Kollias, Pavlos

2017-08-08

This is a multi-institutional, collaborative project using observations and modeling to study the evolution (e.g. formation and growth) of hydrometeors in continental convective clouds. Our contribution was in data analysis for the generation of high-value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: i) the development of novel, state-of-the-art dual-wavelength radar algorithms for the retrieval of cloud microphysical properties and ii) the evaluation of large domain, high-resolution models using comprehensive multi-sensor observations. Our research group developed statistical summaries from numerous sensors and developed retrievals of vertical airmore » motion in deep convection.« less

Rise in the frequency of cloud cover in LANDSAT data for the period 1973 to 1981. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Mendonca, F. J.; Neto, G. C.

1983-01-01

Percentages of cloud cover in LANDSAT imagery were used to calculate the cloud cover monthly average statistic for each LANDSAT scene in Brazil, during the period of 1973 to 1981. The average monthly cloud cover and the monthly minimum cloud cover were also calculated for the regions of north, northeast, central west, southeast and south, separately.

OTD Observations of Continental US Ground and Cloud Flashes

NASA Technical Reports Server (NTRS)

Koshak, William

2007-01-01

Lightning optical flash parameters (e.g., radiance, area, duration, number of optical groups, and number of optical events) derived from almost five years of Optical Transient Detector (OTD) data are analyzed. Hundreds of thousands of OTD flashes occurring over the continental US are categorized according to flash type (ground or cloud flash) using US National Lightning Detection Network TM (NLDN) data. The statistics of the optical characteristics of the ground and cloud flashes are inter-compared on an overall basis, and as a function of ground flash polarity. A standard two-distribution hypothesis test is used to inter-compare the population means of a given lightning parameter for the two flash types. Given the differences in the statistics of the optical characteristics, it is suggested that statistical analyses (e.g., Bayesian Inference) of the space-based optical measurements might make it possible to successfully discriminate ground and cloud flashes a reasonable percentage of the time.

The UAE Rainfall Enhancement Assessment Program: Implications of Thermodynamic Profiles on the Development of Precipitation in Convective Clouds over the Oman Mountains

NASA Astrophysics Data System (ADS)

Breed, D.; Bruintjes, R.; Jensen, T.; Salazar, V.; Fowler, T.

2005-12-01

During the winter and summer seasons of 2001 and 2002, data were collected to assess the efficacy of cloud seeding to enhance precipitation in the United Arab Emirates (UAE). The results of the feasibility study concluded: 1) that winter clouds in the UAE rarely produced conditions amenable to hygroscopic cloud seeding; 2) that summer convective clouds developed often enough, particularly over the Oman Mountains (e.g., the Hajar Mountains along the eastern UAE border and into Oman) to justify a randomized seeding experiment; 3) that collecting quantitative radar observations continues to be a complex but essential part of evaluating a cloud seeding experiment; 4) that successful flight operations would require solving several logistical issues; and 5) that several scientific questions would need to be studied in order to fully evaluate the efficacy and feasibility of hygroscopic cloud seeding, including cloud physical responses, radar-derived rainfall estimates as related to rainfall at the ground, and hydrological impacts. Based on these results, the UAE program proceeded through the design and implemention of a randomized hygroscopic cloud seeding experiment during the summer seasons to statistically quantify the potential for cloud seeding to enhance rainfall, specifically over the UAE and Oman Mountains, while collecting concurrent and separate physical measurements to support the statistical results and provide substantiation for the physical hypothesis. The randomized seeding experiment was carried out over the summers of 2003 and 2004, and a total of 134 cases were treated over the two summer seasons, of which 96 met the analysis criteria established in the experimental design of the program. The statistical evaluation of these cases yielded largely inconclusive results. Evidence will show that the thermodynamic profile had a large influence on storm characteristics and on precipitation development. This in turn provided a confounding factor in the conduct of the seeding experiment, particularly in the lateness of treatment in the storm cycle. The prevalence of capping inversions and the sensitivity of clouds to the level of the inversions as well as to wind shear will be shown using several data sets (soundings, aircraft, radar, numerical models). Concurrent physical measurements with the randomized experiment provided new insights into the physical processes of precipitation that developed in summertime convective clouds over the UAE that in turn helped in the interpretation of the statistical results.

Evaluating statistical cloud schemes: What can we gain from ground-based remote sensing?

NASA Astrophysics Data System (ADS)

Grützun, V.; Quaas, J.; Morcrette, C. J.; Ament, F.

2013-09-01

Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based remote sensing such as lidar, microwave, and radar to evaluate prognostic distribution moments using the "perfect model approach." This means that we employ a high-resolution weather model as virtual reality and retrieve full three-dimensional atmospheric quantities and virtual ground-based observations. We then use statistics from the virtual observation to validate the modeled 3-D statistics. Since the data are entirely consistent, any discrepancy occurring is due to the method. Focusing on total water mixing ratio, we find that the mean ratio can be evaluated decently but that it strongly depends on the meteorological conditions as to whether the variance and skewness are reliable. Using some simple schematic description of different synoptic conditions, we show how statistics obtained from point or line measurements can be poor at representing the full three-dimensional distribution of water in the atmosphere. We argue that a careful analysis of measurement data and detailed knowledge of the meteorological situation is necessary to judge whether we can use the data for an evaluation of higher moments of the humidity distribution used by a statistical cloud scheme.

Determinants of public cooperation in multiplex networks

NASA Astrophysics Data System (ADS)

Battiston, Federico; Perc, Matjaž; Latora, Vito

2017-07-01

Synergies between evolutionary game theory and statistical physics have significantly improved our understanding of public cooperation in structured populations. Multiplex networks, in particular, provide the theoretical framework within network science that allows us to mathematically describe the rich structure of interactions characterizing human societies. While research has shown that multiplex networks may enhance the resilience of cooperation, the interplay between the overlap in the structure of the layers and the control parameters of the corresponding games has not yet been investigated. With this aim, we consider here the public goods game on a multiplex network, and we unveil the role of the number of layers and the overlap of links, as well as the impact of different synergy factors in different layers, on the onset of cooperation. We show that enhanced public cooperation emerges only when a significant edge overlap is combined with at least one layer being able to sustain some cooperation by means of a sufficiently high synergy factor. In the absence of either of these conditions, the evolution of cooperation in multiplex networks is determined by the bounds of traditional network reciprocity with no enhanced resilience. These results caution against overly optimistic predictions that the presence of multiple social domains may in itself promote cooperation, and they help us better understand the complexity behind prosocial behavior in layered social systems.

The new challenges of multiplex networks: Measures and models

NASA Astrophysics Data System (ADS)

Battiston, Federico; Nicosia, Vincenzo; Latora, Vito

2017-02-01

What do societies, the Internet, and the human brain have in common? They are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents, namely individuals, computers, or neurons, rather than only by the properties of the units themselves. In the last two decades, network scientists have proposed models of increasing complexity to better understand real-world systems. Only recently we have realised that multiplexity, i.e. the coexistence of several types of interactions among the constituents of a complex system, is responsible for substantial qualitative and quantitative differences in the type and variety of behaviours that a complex system can exhibit. As a consequence, multilayer and multiplex networks have become a hot topic in complexity science. Here we provide an overview of some of the measures proposed so far to characterise the structure of multiplex networks, and a selection of models aiming at reproducing those structural properties and quantifying their statistical significance. Focusing on a subset of relevant topics, this brief review is a quite comprehensive introduction to the most basic tools for the analysis of multiplex networks observed in the real-world. The wide applicability of multiplex networks as a framework to model complex systems in different fields, from biology to social sciences, and the colloquial tone of the paper will make it an interesting read for researchers working on both theoretical and experimental analysis of networked systems.

Automatic cloud coverage assessment of Formosat-2 image

NASA Astrophysics Data System (ADS)

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.

Use of FEC coding to improve statistical multiplexing performance for video transport over ATM networks

NASA Astrophysics Data System (ADS)

Kurceren, Ragip; Modestino, James W.

1998-12-01

The use of forward error-control (FEC) coding, possibly in conjunction with ARQ techniques, has emerged as a promising approach for video transport over ATM networks for cell-loss recovery and/or bit error correction, such as might be required for wireless links. Although FEC provides cell-loss recovery capabilities it also introduces transmission overhead which can possibly cause additional cell losses. A methodology is described to maximize the number of video sources multiplexed at a given quality of service (QoS), measured in terms of decoded cell loss probability, using interlaced FEC codes. The transport channel is modelled as a block interference channel (BIC) and the multiplexer as single server, deterministic service, finite buffer supporting N users. Based upon an information-theoretic characterization of the BIC and large deviation bounds on the buffer overflow probability, the described methodology provides theoretically achievable upper limits on the number of sources multiplexed. Performance of specific coding techniques using interlaced nonbinary Reed-Solomon (RS) codes and binary rate-compatible punctured convolutional (RCPC) codes is illustrated.

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

P-Mart was designed specifically to allow cancer researchers to perform robust statistical processing of publicly available cancer proteomic datasets. To date an online statistical processing suite for proteomics does not exist. The P-Mart software is designed to allow statistical programmers to utilize these algorithms through packages in the R programming language as well as offering a web-based interface using the Azure cloud technology. The Azure cloud technology also allows the release of the software via Docker containers.

Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

NASA Technical Reports Server (NTRS)

Platnick, Steven

2004-01-01

MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

Multiplexity and multireciprocity in directed multiplexes.

PubMed

Gemmetto, Valerio; Squartini, Tiziano; Picciolo, Francesco; Ruzzenenti, Franco; Garlaschelli, Diego

2016-10-01

Real-world multilayer networks feature nontrivial dependencies among links of different layers. Here we argue that if links are directed, then dependencies are twofold. Besides the ordinary tendency of links of different layers to align as the result of "multiplexity," there is also a tendency to antialign as a result of what we call "multireciprocity," i.e., the fact that links in one layer can be reciprocated by opposite links in a different layer. Multireciprocity generalizes the scalar definition of single-layer reciprocity to that of a square matrix involving all pairs of layers. We introduce multiplexity and multireciprocity matrices for both binary and weighted multiplexes and validate their statistical significance against maximum-entropy null models that filter out the effects of node heterogeneity. We then perform a detailed empirical analysis of the world trade multiplex (WTM), representing the import-export relationships between world countries in different commodities. We show that the WTM exhibits strong multiplexity and multireciprocity, an effect which is, however, largely encoded into the degree or strength sequences of individual layers. The residual effects are still significant and allow us to classify pairs of commodities according to their tendency to be traded together in the same direction and/or in opposite ones. We also find that the multireciprocity of the WTM is significantly lower than the usual reciprocity measured on the aggregate network. Moreover, layers with low (high) internal reciprocity are embedded within sets of layers with comparably low (high) mutual multireciprocity. This suggests that, in the WTM, reciprocity is inherent to groups of related commodities rather than to individual commodities. We discuss the implications for international trade research focusing on product taxonomies, the product space, and fitness and complexity metrics.

Estimates of the aerosol indirect effect over the Baltic Sea region derived from 12 years of MODIS observations

NASA Astrophysics Data System (ADS)

Saponaro, Giulia; Kolmonen, Pekka; Sogacheva, Larisa; Rodriguez, Edith; Virtanen, Timo; de Leeuw, Gerrit

2017-02-01

Retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the Aqua satellite, 12 years (2003-2014) of aerosol and cloud properties were used to statistically quantify aerosol-cloud interaction (ACI) over the Baltic Sea region, including the relatively clean Fennoscandia and the more polluted central-eastern Europe. These areas allowed us to study the effects of different aerosol types and concentrations on macro- and microphysical properties of clouds: cloud effective radius (CER), cloud fraction (CF), cloud optical thickness (COT), cloud liquid water path (LWP) and cloud-top height (CTH). Aerosol properties used are aerosol optical depth (AOD), Ångström exponent (AE) and aerosol index (AI). The study was limited to low-level water clouds in the summer. The vertical distributions of the relationships between cloud properties and aerosols show an effect of aerosols on low-level water clouds. CF, COT, LWP and CTH tend to increase with aerosol loading, indicating changes in the cloud structure, while the effective radius of cloud droplets decreases. The ACI is larger at relatively low cloud-top levels, between 900 and 700 hPa. Most of the studied cloud variables were unaffected by the lower-tropospheric stability (LTS), except for the cloud fraction. The spatial distribution of aerosol and cloud parameters and ACI, here defined as the change in CER as a function of aerosol concentration for a fixed LWP, shows positive and statistically significant ACI over the Baltic Sea and Fennoscandia, with the former having the largest values. Small negative ACI values are observed in central-eastern Europe, suggesting that large aerosol concentrations saturate the ACI.

Collaborative Research: Using ARM Observations to Evaluate GCM Cloud Statistics for Development of Stochastic Cloud-Radiation Parameterizations

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

Shen, Samuel S. P.

2013-09-01

The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key stepmore » in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been an interdisciplinary collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen). The motivation and long-term goal underlying this work is the utilization of stochastic radiative transfer theory (Lane-Veron and Somerville, 2004; Lane et al., 2002) to develop a new class of parametric representations of cloud-radiation interactions and closely related processes for atmospheric models. The theoretical advantage of the stochastic approach is that it can accurately calculate the radiative heating rates through a broken cloud layer without requiring an exact description of the cloud geometry.« less

Confronting Models with Data: The GEWEX Cloud Systems Study

NASA Technical Reports Server (NTRS)

Randall, David; Curry, Judith; Duynkerke, Peter; Krueger, Steven; Moncrieff, Mitchell; Ryan, Brian; Starr, David OC.; Miller, Martin; Rossow, William; Tselioudis, George

2002-01-01

The GEWEX Cloud System Study (GCSS; GEWEX is the Global Energy and Water Cycle Experiment) was organized to promote development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. The strategy of GCSS is to use two distinct kinds of models to analyze and understand observations of the behavior of several different types of clouds systems. Cloud-system-resolving models (CSRMs) have high enough spatial and temporal resolutions to represent individual cloud elements, but cover a wide enough range of space and time scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the surgically extracted column physics of atmospheric general circulation models. SCMs are used to test cloud parameterizations in an un-coupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data is collected in various field programs and provided to the CSRM Community, which uses the data to "certify" the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM Community. We report here the results of a re-thinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, and an explicit recognition of the importance of data integration.

Making Spatial Statistics Service Accessible On Cloud Platform

NASA Astrophysics Data System (ADS)

Mu, X.; Wu, J.; Li, T.; Zhong, Y.; Gao, X.

2014-04-01

Web service can bring together applications running on diverse platforms, users can access and share various data, information and models more effectively and conveniently from certain web service platform. Cloud computing emerges as a paradigm of Internet computing in which dynamical, scalable and often virtualized resources are provided as services. With the rampant growth of massive data and restriction of net, traditional web services platforms have some prominent problems existing in development such as calculation efficiency, maintenance cost and data security. In this paper, we offer a spatial statistics service based on Microsoft cloud. An experiment was carried out to evaluate the availability and efficiency of this service. The results show that this spatial statistics service is accessible for the public conveniently with high processing efficiency.

Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global Cloud-Permiting Models

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

Zhang, Chidong

Motivated by the success of the AMIE/DYNAMO field campaign, which collected unprecedented observations of cloud and precipitation from the tropical Indian Ocean in Octber 2011 – March 2012, this project explored how such observations can be applied to assist the development of global cloud-permitting models through evaluating and correcting model biases in cloud statistics. The main accomplishment of this project were made in four categories: generating observational products for model evaluation, using AMIE/DYNAMO observations to validate global model simulations, using AMIE/DYNAMO observations in numerical studies of cloud-permitting models, and providing leadership in the field. Results from this project provide valuablemore » information for building a seamless bridge between DOE ASR program’s component on process level understanding of cloud processes in the tropics and RGCM focus on global variability and regional extremes. In particular, experience gained from this project would be directly applicable to evaluation and improvements of ACME, especially as it transitions to a non-hydrostatic variable resolution model.« less

Microwave noise temperature and attenuation of clouds - Statistics of these effects at various sites in the United States, Alaska, and Hawaii

NASA Technical Reports Server (NTRS)

Slobin, S. D.

1982-01-01

The microwave attenuation and noise temperature effects of clouds can result in serious degradation of telecommunications link performance, especially for low-noise systems presently used in deep-space communications. Although cloud effects are generally less than rain effects, the frequent presence of clouds will cause some amount of link degradation a large portion of the time. This paper presents a general review of cloud types and their water particle densities, attenuation and noise temperature calculations, and basic link signal-to-noise ratio calculations. Tabular results of calculations for 12 different cloud models are presented for frequencies in the range 10-50 GHz. Curves of average-year attenuation and noise temperature statistics at frequencies ranging from 10 to 90 GHz, calculated from actual surface and radiosonde observations, are given for 15 climatologically distinct regions in the contiguous United States, Alaska, and Hawaii. Nonuniform sky cover is considered in these calculations.

Cloud Statistics and Discrimination in the Polar Regions

NASA Astrophysics Data System (ADS)

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-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.

Comparison of Cirrus Cloud Models: A Project of the GEWEX Cloud System Study (GCSS) Working Group on Cirrus Cloud Systems

NASA Technical Reports Server (NTRS)

Starr, David O'C.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus M.; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric

2000-01-01

The GEWEX Cloud System Study (GCSS, GEWEX is the Global Energy and Water Cycle Experiment) is a community activity aiming to promote development of improved cloud parameterizations for application in the large-scale general circulation models (GCMs) used for climate research and for numerical weather prediction. The GCSS strategy is founded upon the use of cloud-system models (CSMs). These are "process" models with sufficient spatial and temporal resolution to represent individual cloud elements, but spanning a wide range of space and time scales to enable statistical analysis of simulated cloud systems. GCSS also employs single-column versions of the parametric cloud models (SCMs) used in GCMs. GCSS has working groups on boundary-layer clouds, cirrus clouds, extratropical layer cloud systems, precipitating deep convective cloud systems, and polar clouds.

Study on Diagnosing Three Dimensional Cloud Region

NASA Astrophysics Data System (ADS)

Cai, M., Jr.; Zhou, Y., Sr.

2017-12-01

Cloud mask and relative humidity (RH) provided by Cloudsat products from 2007 to 2008 are statistical analyzed to get RH Threshold between cloud and clear sky and its variation with height. A diagnosis method is proposed based on reanalysis data and applied to three-dimensional cloud field diagnosis of a real case. Diagnostic cloud field was compared to satellite, radar and other cloud precipitation observation. Main results are as follows. 1.Cloud region where cloud mask is bigger than 20 has a good space and time corresponding to the high value relative humidity region, which is provide by ECWMF AUX product. Statistical analysis of the RH frequency distribution within and outside cloud indicated that, distribution of RH in cloud at different height range shows single peak type, and the peak is near a RH value of 100%. Local atmospheric environment affects the RH distribution outside cloud, which leads to TH distribution vary in different region or different height. 2. RH threshold and its vertical distribution used for cloud diagnostic was analyzed from Threat Score method. The method is applied to a three dimension cloud diagnosis case study based on NCEP reanalysis data and th diagnostic cloud field is compared to satellite, radar and cloud precipitation observation on ground. It is found that, RH gradient is very big around cloud region and diagnosed cloud area by RH threshold method is relatively stable. Diagnostic cloud area has a good corresponding to updraft region. The cloud and clear sky distribution corresponds to satellite the TBB observations overall. Diagnostic cloud depth, or sum cloud layers distribution consists with optical thickness and precipitation on ground better. The cloud vertical profile reveals the relation between cloud vertical structure and weather system clearly. Diagnostic cloud distribution correspond to cloud observations on ground very well. 3. The method is improved by changing the vertical interval from altitude to temperature. The result shows that, the five factors , including TS score for clear sky, empty forecast, missed forecast, and especially TS score for cloud region and the accurate rate increased obviously. So, the RH threshold and its vertical distribution with temperature is better than with altitude. More tests and comparision should be done to assess the diagnosis method.

Use of High-Resolution Satellite Observations to Evaluate Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations

NASA Astrophysics Data System (ADS)

Zhou, Y.; Tao, W.; Hou, A. Y.; Zeng, X.; Shie, C.

2007-12-01

The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model for different environmental conditions, i.e., the South China Sea Monsoon Experiment (SCSMEX), CRYSTAL-FACE, and KAWJEX are compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and as well as cloud observations from the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. The model presents large discrepancies in rain spectrum and vertical hydrometer profiles. The discrepancy in the precipitation field is also consistent with the cloud and radiation observations. The study will focus on the effects of large scale forcing and microphysics to the simulated model- observation discrepancies.

Methods of editing cloud and atmospheric layer affected pixels from satellite data

NASA Technical Reports Server (NTRS)

Nixon, P. R. (Principal Investigator); Wiegand, C. L.; Richardson, A. J.; Johnson, M. P.

1982-01-01

Practical methods of computer screening cloud-contaminated pixels from data of various satellite systems are proposed. Examples are given of the location of clouds and representative landscape features in HCMM spectral space of reflectance (VIS) vs emission (IR). Methods of screening out cloud affected HCMM are discussed. The character of subvisible absorbing-emitting atmospheric layers (subvisible cirrus or SCi) in HCMM data is considered and radiosonde soundings are examined in relation to the presence of SCi. The statistical characteristics of multispectral meteorological satellite data in clear and SCi affected areas are discussed. Examples in TIROS-N and NOAA-7 data from several states and Mexico are presented. The VIS-IR cluster screening method for removing clouds is applied to a 262, 144 pixel HCMM scene from south Texas and northeast Mexico. The SCi that remain after cluster screening are sited out by applying a statistically determined IR limit.

Multiplex Microsphere Immunoassays for the Detection of IgM and IgG to Arboviral Diseases

PubMed Central

Basile, Alison J.; Horiuchi, Kalanthe; Panella, Amanda J.; Laven, Janeen; Kosoy, Olga; Lanciotti, Robert S.; Venkateswaran, Neeraja; Biggerstaff, Brad J.

2013-01-01

Serodiagnosis of arthropod-borne viruses (arboviruses) at the Division of Vector-Borne Diseases, CDC, employs a combination of individual enzyme-linked immunosorbent assays and microsphere immunoassays (MIAs) to test for IgM and IgG, followed by confirmatory plaque-reduction neutralization tests. Based upon the geographic origin of a sample, it may be tested concurrently for multiple arboviruses, which can be a cumbersome task. The advent of multiplexing represents an opportunity to streamline these types of assays; however, because serologic cross-reactivity of the arboviral antigens often confounds results, it is of interest to employ data analysis methods that address this issue. Here, we constructed 13-virus multiplexed IgM and IgG MIAs that included internal and external controls, based upon the Luminex platform. Results from samples tested using these methods were analyzed using 8 different statistical schemes to identify the best way to classify the data. Geographic batteries were also devised to serve as a more practical diagnostic format, and further samples were tested using the abbreviated multiplexes. Comparative error rates for the classification schemes identified a specific boosting method based on logistic regression “Logitboost” as the classification method of choice. When the data from all samples tested were combined into one set, error rates from the multiplex IgM and IgG MIAs were <5% for all geographic batteries. This work represents both the most comprehensive, validated multiplexing method for arboviruses to date, and also the most systematic attempt to determine the most useful classification method for use with these types of serologic tests. PMID:24086608

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

Hagos, Samson M.; Feng, Zhe; Burleyson, Casey D.

Regional cloud permitting model simulations of cloud populations observed during the 2011 ARM Madden Julian Oscillation Investigation Experiment/ Dynamics of Madden-Julian Experiment (AMIE/DYNAMO) field campaign are evaluated against radar and ship-based measurements. Sensitivity of model simulated surface rain rate statistics to parameters and parameterization of hydrometeor sizes in five commonly used WRF microphysics schemes are examined. It is shown that at 2 km grid spacing, the model generally overestimates rain rate from large and deep convective cores. Sensitivity runs involving variation of parameters that affect rain drop or ice particle size distribution (more aggressive break-up process etc) generally reduce themore » bias in rain-rate and boundary layer temperature statistics as the smaller particles become more vulnerable to evaporation. Furthermore significant improvement in the convective rain-rate statistics is observed when the horizontal grid-spacing is reduced to 1 km and 0.5 km, while it is worsened when run at 4 km grid spacing as increased turbulence enhances evaporation. The results suggest modulation of evaporation processes, through parameterization of turbulent mixing and break-up of hydrometeors may provide a potential avenue for correcting cloud statistics and associated boundary layer temperature biases in regional and global cloud permitting model simulations.« less

Subject-enabled analytics model on measurement statistics in health risk expert system for public health informatics.

PubMed

Chung, Chi-Jung; Kuo, Yu-Chen; Hsieh, Yun-Yu; Li, Tsai-Chung; Lin, Cheng-Chieh; Liang, Wen-Miin; Liao, Li-Na; Li, Chia-Ing; Lin, Hsueh-Chun

2017-11-01

This study applied open source technology to establish a subject-enabled analytics model that can enhance measurement statistics of case studies with the public health data in cloud computing. The infrastructure of the proposed model comprises three domains: 1) the health measurement data warehouse (HMDW) for the case study repository, 2) the self-developed modules of online health risk information statistics (HRIStat) for cloud computing, and 3) the prototype of a Web-based process automation system in statistics (PASIS) for the health risk assessment of case studies with subject-enabled evaluation. The system design employed freeware including Java applications, MySQL, and R packages to drive a health risk expert system (HRES). In the design, the HRIStat modules enforce the typical analytics methods for biomedical statistics, and the PASIS interfaces enable process automation of the HRES for cloud computing. The Web-based model supports both modes, step-by-step analysis and auto-computing process, respectively for preliminary evaluation and real time computation. The proposed model was evaluated by computing prior researches in relation to the epidemiological measurement of diseases that were caused by either heavy metal exposures in the environment or clinical complications in hospital. The simulation validity was approved by the commercial statistics software. The model was installed in a stand-alone computer and in a cloud-server workstation to verify computing performance for a data amount of more than 230K sets. Both setups reached efficiency of about 10 5 sets per second. The Web-based PASIS interface can be used for cloud computing, and the HRIStat module can be flexibly expanded with advanced subjects for measurement statistics. The analytics procedure of the HRES prototype is capable of providing assessment criteria prior to estimating the potential risk to public health. Copyright © 2017 Elsevier B.V. All rights reserved.

Cloud and circulation feedbacks in a near-global aquaplanet cloud-resolving model

DOE PAGES

Narenpitak, Pornampai; Bretherton, Christopher S.; Khairoutdinov, Marat F.

2017-05-08

A near-global aquaplanet cloud-resolving model (NGAqua) with fixed meridionally varying sea-surface temperature (SST) is used to investigate cloud feedbacks due to three climate perturbations: a uniform 4 K SST increase, a quadrupled-CO2 concentration, and both combined. NGAqua has a horizontal resolution of 4 km with no cumulus parameterization. Its domain is a zonally periodic 20,480 km-long tropical channel, spanning 46°S–N. It produces plausible mean distributions of clouds, rainfall, and winds. After spin-up, 80 days are analyzed for the control and increased-SST simulations, and 40 days for those with quadrupled CO 2. The Intertropical Convergence Zone width and tropical cloud covermore » are not strongly affected by SST warming or CO 2 increase, except for the expected upward shift in high clouds with warming, but both perturbations weaken the Hadley circulation. Increased SST induces a statistically significant increase in subtropical low cloud fraction and in-cloud liquid water content but decreases midlatitude cloud, yielding slightly positive domain-mean shortwave cloud feedbacks. CO 2 quadrupling causes a slight shallowing and a statistically insignificant reduction of subtropical low cloud fraction. Warming-induced low cloud changes are strongly correlated with changes in estimated inversion strength, which increases modestly in the subtropics but decreases in the midlatitudes. Enhanced clear-sky boundary layer radiative cooling in the warmer climate accompanies the robust subtropical low cloud increase. The probability distribution of column relative humidity across the tropics and subtropics is compared between the control and increased-SST simulations. It shows no evidence of bimodality or increased convective aggregation in a warmer climate.« less

Cloud and circulation feedbacks in a near-global aquaplanet cloud-resolving model

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

Narenpitak, Pornampai; Bretherton, Christopher S.; Khairoutdinov, Marat F.

A near-global aquaplanet cloud-resolving model (NGAqua) with fixed meridionally varying sea-surface temperature (SST) is used to investigate cloud feedbacks due to three climate perturbations: a uniform 4 K SST increase, a quadrupled-CO2 concentration, and both combined. NGAqua has a horizontal resolution of 4 km with no cumulus parameterization. Its domain is a zonally periodic 20,480 km-long tropical channel, spanning 46°S–N. It produces plausible mean distributions of clouds, rainfall, and winds. After spin-up, 80 days are analyzed for the control and increased-SST simulations, and 40 days for those with quadrupled CO 2. The Intertropical Convergence Zone width and tropical cloud covermore » are not strongly affected by SST warming or CO 2 increase, except for the expected upward shift in high clouds with warming, but both perturbations weaken the Hadley circulation. Increased SST induces a statistically significant increase in subtropical low cloud fraction and in-cloud liquid water content but decreases midlatitude cloud, yielding slightly positive domain-mean shortwave cloud feedbacks. CO 2 quadrupling causes a slight shallowing and a statistically insignificant reduction of subtropical low cloud fraction. Warming-induced low cloud changes are strongly correlated with changes in estimated inversion strength, which increases modestly in the subtropics but decreases in the midlatitudes. Enhanced clear-sky boundary layer radiative cooling in the warmer climate accompanies the robust subtropical low cloud increase. The probability distribution of column relative humidity across the tropics and subtropics is compared between the control and increased-SST simulations. It shows no evidence of bimodality or increased convective aggregation in a warmer climate.« less

Marine Stratocumulus Cloud Fields off the Coast of Southern California Observed Using LANDSAT Imagery. Part II: Textural Analysis.

NASA Astrophysics Data System (ADS)

Welch, R. M.; Sengupta, S. K.; Kuo, K. S.

1988-04-01

Statistical measures of the spatial distributions of gray levels (cloud reflectivities) are determined for LANDSAT Multispectral Scanner digital data. Textural properties for twelve stratocumulus cloud fields, seven cumulus fields, and two cirrus fields are examined using the Spatial Gray Level Co-Occurrence Matrix method. The co-occurrence statistics are computed for pixel separations ranging from 57 m to 29 km and at angles of 0°, 45°, 90° and 135°. Nine different textual measures are used to define the cloud field spatial relationships. However, the measures of contrast and correlation appear to be most useful in distinguishing cloud structure.Cloud field macrotexture describes general cloud field characteristics at distances greater than the size of typical cloud elements. It is determined from the spatial asymptotic values of the texture measures. The slope of the texture curves at small distances provides a measure of the microtexture of individual cloud cells. Cloud fields composed primarily of small cells have very steep slopes and reach their asymptotic values at short distances from the origin. As the cells composing the cloud field grow larger, the slope becomes more gradual and the asymptotic distance increases accordingly. Low asymptotic values of correlation show that stratocumulus cloud fields have no large scale organized structure.Besides the ability to distinguish cloud field structure, texture appears to be a potentially valuable tool in cloud classification. Stratocumulus clouds are characterized by low values of angular second moment and large values of entropy. Cirrus clouds appear to have extremely low values of contrast, low values of entropy, and very large values of correlation.Finally, we propose that sampled high spatial resolution satellite data be used in conjunction with coarser resolution operational satellite data to detect and identify cloud field structure and directionality and to locate regions of subresolution scale cloud contamination.

Statistical characteristics of cloud variability. Part 1: Retrieved cloud liquid water path at three ARM sites: Observed cloud variability at ARM sites

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

Huang, Dong; Campos, Edwin; Liu, Yangang

2014-09-17

Statistical characteristics of cloud variability are examined for their dependence on averaging scales and best representation of probability density function with the decade-long retrieval products of cloud liquid water path (LWP) from the tropical western Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy’s Atmospheric Radiation Measurement Program. The statistical moments of LWP show some seasonal variation at the SGP and NSA sites but not much at the TWP site. It is found that the standard deviation, relative dispersion (the ratio of the standard deviation to the mean), and skewness allmore » quickly increase with the averaging window size when the window size is small and become more or less flat when the window size exceeds 12 h. On average, the cloud LWP at the TWP site has the largest values of standard deviation, relative dispersion, and skewness, whereas the NSA site exhibits the least. Correlation analysis shows that there is a positive correlation between the mean LWP and the standard deviation. The skewness is found to be closely related to the relative dispersion with a correlation coefficient of 0.6. The comparison further shows that the log normal, Weibull, and gamma distributions reasonably explain the observed relationship between skewness and relative dispersion over a wide range of scales.« less

Comparison of Cirrus Cloud Models: A Project of the GEWEX Cloud System Study (GCSS) Working Group on Cirrus Cloud Systems

NASA Technical Reports Server (NTRS)

Starr, David OC.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus M.; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric; Khvorostyanov, Vitaly;

Statistical Analysis of the Polarimetric Cloud Analysis and Seeding Test (POLCAST) Field Projects

NASA Astrophysics Data System (ADS)

Ekness, Jamie Lynn

The North Dakota farming industry brings in more than $4.1 billion annually in cash receipts. Unfortunately, agriculture sales vary significantly from year to year, which is due in large part to weather events such as hail storms and droughts. One method to mitigate drought is to use hygroscopic seeding to increase the precipitation efficiency of clouds. The North Dakota Atmospheric Research Board (NDARB) sponsored the Polarimetric Cloud Analysis and Seeding Test (POLCAST) research project to determine the effectiveness of hygroscopic seeding in North Dakota. The POLCAST field projects obtained airborne and radar observations, while conducting randomized cloud seeding. The Thunderstorm Identification Tracking and Nowcasting (TITAN) program is used to analyze radar data (33 usable cases) in determining differences in the duration of the storm, rain rate and total rain amount between seeded and non-seeded clouds. The single ratio of seeded to non-seeded cases is 1.56 (0.28 mm/0.18 mm) or 56% increase for the average hourly rainfall during the first 60 minutes after target selection. A seeding effect is indicated with the lifetime of the storms increasing by 41 % between seeded and non-seeded clouds for the first 60 minutes past seeding decision. A double ratio statistic, a comparison of radar derived rain amount of the last 40 minutes of a case (seed/non-seed), compared to the first 20 minutes (seed/non-seed), is used to account for the natural variability of the cloud system and gives a double ratio of 1.85. The Mann-Whitney test on the double ratio of seeded to non-seeded cases (33 cases) gives a significance (p-value) of 0.063. Bootstrapping analysis of the POLCAST set indicates that 50 cases would provide statistically significant results based on the Mann-Whitney test of the double ratio. All the statistical analysis conducted on the POLCAST data set show that hygroscopic seeding in North Dakota does increase precipitation. While an additional POLCAST field project would be necessary to obtain standardly accepted statistically significant results (p < 0.5) for the double ratio of precipitation amount, the obtained p-value of 0.063 is close and considering the positive result from other hygroscopic seeding experiments, the North Dakota Cloud Modification Project should consider implementation of hygroscopic seeding.

Lagrangian Particle Tracking Simulation for Warm-Rain Processes in Quasi-One-Dimensional Domain

NASA Astrophysics Data System (ADS)

Kunishima, Y.; Onishi, R.

2017-12-01

Conventional cloud simulations are based on the Euler method and compute each microphysics process in a stochastic way assuming infinite numbers of particles within each numerical grid. They therefore cannot provide the Lagrangian statistics of individual particles in cloud microphysics (i.e., aerosol particles, cloud particles, and rain drops) nor discuss the statistical fluctuations due to finite number of particles. We here simulate the entire precipitation process of warm-rain, with tracking individual particles. We use the Lagrangian Cloud Simulator (LCS), which is based on the Euler-Lagrangian framework. In that framework, flow motion and scalar transportation are computed with the Euler method, and particle motion with the Lagrangian one. The LCS tracks particle motions and collision events individually with considering the hydrodynamic interaction between approaching particles with a superposition method, that is, it can directly represent the collisional growth of cloud particles. It is essential for trustworthy collision detection to take account of the hydrodynamic interaction. In this study, we newly developed a stochastic model based on the Twomey cloud condensation nuclei (CCN) activation for the Lagrangian tracking simulation and integrated it into the LCS. Coupling with the Euler computation for water vapour and temperature fields, the initiation and condensational growth of water droplets were computed in the Lagrangian way. We applied the integrated LCS for a kinematic simulation of warm-rain processes in a vertically-elongated domain of, at largest, 0.03×0.03×3000 (m3) with horizontal periodicity. Aerosol particles with a realistic number density, 5×107 (m3), were evenly distributed over the domain at the initial state. Prescribed updraft at the early stage initiated development of a precipitating cloud. We have confirmed that the obtained bulk statistics fairly agree with those from a conventional spectral-bin scheme for a vertical column domain. The centre of the discussion will be the Lagrangian statistics which is collected from the individual behaviour of the tracked particles.

Cloud statistics over the Indonesian Maritime Continent during the first and second CPEA campaigns

NASA Astrophysics Data System (ADS)

Marzuki; Vonnisa, Mutya; Rahayu, Aulya; Hashiguchi, Hiroyuki

2017-06-01

Improvement of precipitation prediction requires an understanding of the organization mechanism, such as the initiation and evolution of organized convective systems. This paper is a follow-up of a previous study on cloud propagation over the Indonesian Maritime Continent (IMC). Here, the infrared blackbody brightness temperature data is analyzed. A comprehensive cloud statistics model, including span, speed, duration, all possible directions, and size was estimated by applying the modified tracking reflectivity echoes by correlation (TREC) method to time-latitude-longitude space. Comparisons were made to cloud statistics during the first and second campaigns of Coupling Processes in the Equatorial Atmosphere, hereinafter called CPEA-I and CPEA-II. Although the two campaigns were conducted in different monsoon seasons, the cloud propagation directions during each campaign were similar. The cloud systems moved in most directions, except north and east, and preferred southwestward, westward and northwestward movements. Thus, westward-moving clouds were more dominant than eastward-moving clouds, in agreement with previous studies. This feature is consistent with the prevailing easterly wind in the middle and upper troposphere despite the difference in low-level wind during each campaign. The two campaign periods were different due to the phase of the Madden-Julian Oscillation (MJO). CPEA-I took place over the active MJO phase, with larger-sized clouds than CPEA-II. Thus, the MJO had an enormous impact on cloud size, but such an impact was not significantly observed in the speed, lifetime, span and direction of propagation. In the two campaigns, clouds moved with a speed of 3-30 m s-1 and in duration from a few hours to longer than one day. Clouds with long spans and high speeds were generally observed during the strong vertical shear of horizontal winds. In contrast, clouds with short spans and low speeds were found in the more varied environment of the IMC, but were dominant over land, which may have been associated with the diurnal heating cycle. Finally, the present results showed more complex behavior than a previous study in the Bay of Bengal, indicating precipitation mechanisms over the IMC including interactions between large-scale atmospheric phenomena (e.g., monsoon and MJO) with the diurnal precipitation cycles.

Structure and covariance of cloud and rain water in marine stratocumulus

NASA Astrophysics Data System (ADS)

Witte, Mikael; Morrison, Hugh; Gettelman, Andrew

2017-04-01

Many state of the art cloud microphysics parameterizations in large-scale models use assumed probability density functions (pdfs) to represent subgrid scale variability of relevant resolved scale variables such as vertical velocity and cloud liquid water content (LWC). Integration over the assumed pdfs of small scale variability results in physically consistent prediction of nonlinear microphysical process rates and obviates the need to apply arbitrary tuning parameters to the calculated rates. In such parameterizations, the covariance of cloud and rain LWC is an important quantity for parameterizing the accretion process by which rain drops grow via collection of cloud droplets. This covariance has been diagnosed by other workers from a variety of observational and model datasets (Boutle et al., 2013; Larson and Griffin, 2013; Lebsock et al., 2013), but there is poor agreement in findings across the studies. Two key assumptions that may explain some of the discrepancies among past studies are 1) LWC (both cloud and rain) distributions are statistically stationary and 2) spatial structure may be neglected. Given the highly intermittent nature of precipitation and the fact that cloud LWC has been found to be poorly represented by stationary pdfs (e.g. Marshak et al., 1997), neither of the aforementioned assumptions are valid. Therefore covariance must be evaluated as a function of spatial scale without the assumption of stationary statistics (i.e. variability cannot be expressed as a fractional standard deviation, which necessitates well-defined first and second moments of the LWC distribution). The present study presents multifractal analyses of both rain and cloud LWC using aircraft data from the VOCALS-REx field campaign to illustrate the importance of spatial structure in microphysical parameterizations and extends the results of Boutle et al. (2013) to provide a parameterization of rain-cloud water covariance as a function of spatial scale without the assumption of statistical stationarity.

Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing

NASA Astrophysics Data System (ADS)

Srivastava, Somesh; Rao, A. Ravishankar; Sheinin, Vadim

2011-03-01

Statistical image reconstruction algorithms potentially offer many advantages to x-ray computed tomography (CT), e.g. lower radiation dose. But, their adoption in practical CT scanners requires extra computation power, which is traditionally provided by incorporating additional computing hardware (e.g. CPU-clusters, GPUs, FPGAs etc.) into a scanner. An alternative solution is to access the required computation power over the internet from a cloud computing service, which is orders-of-magnitude more cost-effective. This is because users only pay a small pay-as-you-go fee for the computation resources used (i.e. CPU time, storage etc.), and completely avoid purchase, maintenance and upgrade costs. In this paper, we investigate the benefits and shortcomings of using cloud computing for statistical image reconstruction. We parallelized the most time-consuming parts of our application, the forward and back projectors, using MapReduce, the standard parallelization library on clouds. From preliminary investigations, we found that a large speedup is possible at a very low cost. But, communication overheads inside MapReduce can limit the maximum speedup, and a better MapReduce implementation might become necessary in the future. All the experiments for this paper, including development and testing, were completed on the Amazon Elastic Compute Cloud (EC2) for less than $20.

Rapid and Accurate Diagnosis of Acute Pyogenic Meningitis Due to Streptococcus Pneumoniae, Haemophilus influenzae Type b and Neisseria meningitidis Using A Multiplex PCR Assay.

PubMed

Seth, Rajeev; Murthy, Peela Sree Ramchandra; Sistla, Sujatha; Subramanian, Mahadevan; Tamilarasu, Kadhiravan

2017-09-01

Acute bacterial meningitis is one of the major causes of morbidity and mortality in children and geriatric population, especially in developing countries. Methods of identification are standard culture and other phenotypic tests in many resource poor settings. To use molecular methods for the improvement of aetiological diagnosis of acute pyogenic meningitis in patients. CSF samples of 125 patients were included for the study. Gram staining and culture were performed according to standard procedures. Antigen was detected using commercial latex agglutination test kit. Multiplex PCR was performed using previously published primers and protocols. Fischer's exact test was used for finding association between presence of the disease and clinical/biochemical parameters, considering two tailed p<0.05 as statistically significant. Sensitivity, specificity, positive and negative predictive values were calculated using Graphpad QuicCalc software. A total of 39 cases (31.2%) were confirmed to be of acute pyogenic meningitis based on biochemical methods. Only 10/39 was positive for the three organisms tested. Multiplex PCR was able to detect one additional isolate each of Streptococcus pneumoniae and Haemophilus influenzae type b. When compared with multiplex PCR as the gold standard, culture and latex agglutination tests had same sensitivity (80%), specificity (100%), PPV (100%) and NPV (97.8%), whereas Gram stain had poor sensitivity (40%) and good specificity (95.6%). Detection rates were higher in multiplex PCR for the two organisms Streptococcus pneumoniae and Haemophilus influenzae type b. Multiplex PCR was more sensitive than culture or antigen detection, and employing this assay can significantly increase the speed and accuracy of identification of the pathogen.

Vertical Cloud Climatology During TC4 Derived from High-Altitude Aircraft Merged Lidar and Radar Profiles

NASA Technical Reports Server (NTRS)

Hlavka, Dennis; Tian, Lin; Hart, William; Li, Lihua; McGill, Matthew; Heymsfield, Gerald

2009-01-01

Aircraft lidar works by shooting laser pulses toward the earth and recording the return time and intensity of any of the light returning to the aircraft after scattering off atmospheric particles and/or the Earth s surface. The scattered light signatures can be analyzed to tell the exact location of cloud and aerosol layers and, with the aid of a few optical assumptions, can be analyzed to retrieve estimates of optical properties such as atmospheric transparency. Radar works in a similar fashion except it sends pulses toward earth at a much larger wavelength than lidar. Radar records the return time and intensity of cloud or rain reflection returning to the aircraft. Lidar can measure scatter from optically thin cirrus and aerosol layers whose particles are too small for the radar to detect. Radar can provide reflection profiles through thick cloud layers of larger particles that lidar cannot penetrate. Only after merging the two instrument products can accurate measurements of the locations of all layers in the full atmospheric column be achieved. Accurate knowledge of the vertical distribution of clouds is important information for understanding the Earth/atmosphere radiative balance and for improving weather/climate forecast models. This paper describes one such merged data set developed from the Tropical Composition, Cloud and Climate Coupling (TC4) experiment based in Costa Rica in July-August 2007 using the nadir viewing Cloud Physics Lidar (CPL) and the Cloud Radar System (CRS) on board the NASA ER-2 aircraft. Statistics were developed concerning cloud probability through the atmospheric column and frequency of the number of cloud layers. These statistics were calculated for the full study area, four sub-regions, and over land compared to over ocean across all available flights. The results are valid for the TC4 experiment only, as preferred cloud patterns took priority during mission planning. The TC4 Study Area was a very cloudy region, with cloudy profiles occurring 94 percent of the time during the ER-2 flights. One to three cloud layers were common, with the average calculated at 2.03 layers per profile. The upper troposphere had a cloud frequency generally over 30%, reaching 42 percent near 13 km during the study. There were regional differences. The Caribbean was much clearer than the Pacific regions. Land had a much higher frequency of high clouds than ocean areas. One region just south and west of Panama had a high probability of clouds below 15 km altitude with the frequency never dropping below 25% and reaching a maximum of 60% at 11-13 km altitude. These cloud statistics will help characterize the cloud volume for TC4 scientists as they try to understand the complexities of the tropical atmosphere.

Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations . Part II; Sensitivity Tests and Results

NASA Technical Reports Server (NTRS)

da Silva, Arlindo M.; Norris, Peter M.

2013-01-01

Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

Experience of the JPL Exploratory Data Analysis Team at validating HIRS2/MSU cloud parameters

NASA Technical Reports Server (NTRS)

Kahn, Ralph; Haskins, Robert D.; Granger-Gallegos, Stephanie; Pursch, Andrew; Delgenio, Anthony

1992-01-01

Validation of the HIRS2/MSU cloud parameters began with the cloud/climate feedback problem. The derived effective cloud amount is less sensitive to surface temperature for higher clouds. This occurs because as the cloud elevation increases, the difference between surface temperature and cloud temperature increases, so only a small change in cloud amount is needed to effect a large change in radiance at the detector. By validating the cloud parameters it is meant 'developing a quantitative sense for the physical meaning of the measured parameters', by: (1) identifying the assumptions involved in deriving parameters from the measured radiances, (2) testing the input data and derived parameters for statistical error, sensitivity, and internal consistency, and (3) comparing with similar parameters obtained from other sources using other techniques.

The 15 273 Å diffuse interstellar band in the dark cloud Barnard 68

NASA Astrophysics Data System (ADS)

Elyajouri, Meriem; Cox, Nick L. J.; Lallement, Rosine

2017-09-01

High obscuration of background stars behind dark clouds precludes the detection of optical diffuse interstellar bands (DIBs) and hence our knowledge of DIB carriers in these environments. Taking advantage of the reduced obscuration of starlight in the near-infrared (NIR) we used one of the strongest NIR DIBs at 15 273 Å to probe the presence and properties of its carrier throughout the nearby interstellar dark cloud Barnard 68. We measured equivalent widths (EW) for different ranges of visual extinction AV, using VLT/KMOS H-band (1.46-1.85 μm) moderate-resolution (R 4000) spectra of 43 stars situated behind the cloud. To do so, we fitted the data with synthetic stellar spectra from the APOGEE project and TAPAS synthetic telluric transmissions appropriate for the observing site and time period. The results show an increase of DIB EW with increasing AV. However, the rate of increase is much flatter than expected from the EW-AV quasi-proportionality established for this DIB in the Galactic diffuse interstellar medium. Based on a simplified inversion assuming sphericity, it is found that the volume density of the DIB carrier is 2.7 and 7.9 times lower than this expected average value in the external and central regions of the cloud, which have nH≃ 0.4 and 3.5 × 105 cm-3, respectively. Further measurements with multiplex NIR spectrographs should allow detailed modeling of such an edge effect of this DIB and other bands and help clarify its actual origin. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere under ESO programme 096.C-0931(A).

Quantifying and Modelling the Effect of Cloud Shadows on the Surface Irradiance at Tropical and Midlatitude Forests

NASA Astrophysics Data System (ADS)

Kivalov, Sergey N.; Fitzjarrald, David R.

2018-02-01

Cloud shadows lead to alternating light and dark periods at the surface, with the most abrupt changes occurring in the presence of low-level forced cumulus clouds. We examine multiyear irradiance time series observed at a research tower in a midlatitude mixed deciduous forest (Harvard Forest, Massachusetts, USA: 42.53{°}N, 72.17{°}W) and one made at a similar tower in a tropical rain forest (Tapajós National Forest, Pará, Brazil: 2.86{°}S, 54.96{°}W). We link the durations of these periods statistically to conventional meteorological reports of sky type and cloud height at the two forests and present a method to synthesize the surface irradiance time series from sky-type information. Four classes of events describing distinct sequential irradiance changes at the transition from cloud shadow and direct sunlight are identified: sharp-to-sharp, slow-to-slow, sharp-to-slow, and slow-to-sharp. Lognormal and the Weibull statistical distributions distinguish among cloudy-sky types. Observers' qualitative reports of `scattered' and `broken' clouds are quantitatively distinguished by a threshold value of the ratio of mean clear to cloudy period durations. Generated synthetic time series based on these statistics adequately simulate the temporal "radiative forcing" linked to sky type. Our results offer a quantitative way to connect the conventional meteorological sky type to the time series of irradiance experienced at the surface.

Long-term trend analysis and climatology of tropical cirrus clouds using 16 years of lidar data set over Southern India

NASA Astrophysics Data System (ADS)

Pandit, A. K.; Gadhavi, H. S.; Venkat Ratnam, M.; Raghunath, K.; Rao, S. V. B.; Jayaraman, A.

2015-12-01

Sixteen-year (1998-2013) climatology of cirrus clouds and their macrophysical (base height, top height and geometrical thickness) and optical properties (cloud optical thickness) observed using a ground-based lidar over Gadanki (13.5° N, 79.2° E), India, is presented. The climatology obtained from the ground-based lidar is compared with the climatology obtained from 7 and a half years (June 2006-December 2013) of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. A very good agreement is found between the two climatologies in spite of their opposite viewing geometries and the differences in sampling frequencies. Nearly 50-55 % of cirrus clouds were found to possess geometrical thickness less than 2 km. Ground-based lidar is found to detect a higher number of sub-visible clouds than CALIOP which has implications for global warming studies as sub-visible cirrus clouds have significant positive radiative forcing. Cirrus clouds with mid-cloud temperatures between -50 to -70 °C have a mean geometrical thickness greater than 2 km in contrast to the earlier reported value of 1.7 km. Trend analyses reveal a statistically significant increase in the altitude of sub-visible cirrus clouds which is consistent with the recent climate model simulations. The mid-cloud altitude of sub-visible cirrus clouds is found to be increasing at the rate of 41 ± 21 m year-1. Statistically significant decrease in optical thickness of sub-visible and thick cirrus clouds is observed. Also, the fraction of sub-visible cirrus cloud is found to have increased by 9 % in the last 16 years (1998 to 2013). This increase is mainly compensated by a 7 % decrease in thin cirrus cloud fraction. This has implications for the temperature and water vapour budget in the tropical tropopause layer.

Piglet colibacillosis diagnosis based on multiplex polymerase chain reaction and immunohistochemistry of paraffin-embedded tissues

PubMed Central

de Andrade, Caroline P.; Machado, Verônica S. L.; Bianchi, Matheus V.; Rolim, Veronica M.; Cruz, Raquel A. S.; Driemeier, David

2018-01-01

Enterotoxigenic Escherichia coli (ETEC) causes diarrhea in pigs, referred to as colibacillosis. The aim of this study was to optimize multiplex polymerase chain reaction (PCR) and immunohistochemistry (IHC) analyses of paraffin-embedded material to detect pathogenic E. coli strains causing colibacillosis in pigs. Multiplex PCR was optimized for fimbriae (F18, F4, F6, F5, and F41) and toxins (types A and B heat-stable toxins [STaP and STb], heat-labile toxin [LT], and type 2 Shiga toxin [STx2e]), and IHC was optimized for an anti-E. coli polyclonal antibody. Samples (132) from pigs received between 2006 and 2014 with clinical and histopathological diagnoses of colibacillosis were analyzed. E. coli was detected by IHC in 78.7%, and at least one virulence factor gene was detected in 71.2%. Pathogenic strains of ETEC with at least one fimbria and one toxin were detected in 40% of the samples in multiplex PCR. The most frequent virulence types were F18-STaP (7.5%), F18-STaP-STb (5.7%), and F4-STaP (3.8%). A statistically significant association was noted between virulence factors F4, F18, STaP, and STb and positive immunostaining results. Colibacillosis diagnosis through multiplex PCR and IHC of paraffin-embedded tissues is a practical approach, as samples can be fixed and stored for long periods before analysis. PMID:28693311

Time-cumulated visible and infrared histograms used as descriptor of cloud cover

NASA Technical Reports Server (NTRS)

Seze, G.; Rossow, W.

1987-01-01

To study the statistical behavior of clouds for different climate regimes, the spatial and temporal stability of VIS-IR bidimensional histograms is tested. Also, the effect of data sampling and averaging on the histogram shapes is considered; in particular the sampling strategy used by the International Satellite Cloud Climatology Project is tested.

Cloud Impacts on Pavement Temperature in Energy Balance Models

NASA Astrophysics Data System (ADS)

Walker, C. L.

2013-12-01

Forecast systems provide decision support for end-users ranging from the solar energy industry to municipalities concerned with road safety. Pavement temperature is an important variable when considering vehicle response to various weather conditions. A complex, yet direct relationship exists between tire and pavement temperatures. Literature has shown that as tire temperature increases, friction decreases which affects vehicle performance. Many forecast systems suffer from inaccurate radiation forecasts resulting in part from the inability to model different types of clouds and their influence on radiation. This research focused on forecast improvement by determining how cloud type impacts the amount of shortwave radiation reaching the surface and subsequent pavement temperatures. The study region was the Great Plains where surface solar radiation data were obtained from the High Plains Regional Climate Center's Automated Weather Data Network stations. Road pavement temperature data were obtained from the Meteorological Assimilation Data Ingest System. Cloud properties and radiative transfer quantities were obtained from the Clouds and Earth's Radiant Energy System mission via Aqua and Terra Moderate Resolution Imaging Spectroradiometer satellite products. An additional cloud data set was incorporated from the Naval Research Laboratory Cloud Classification algorithm. Statistical analyses using a modified nearest neighbor approach were first performed relating shortwave radiation variability with road pavement temperature fluctuations. Then statistical associations were determined between the shortwave radiation and cloud property data sets. Preliminary results suggest that substantial pavement forecasting improvement is possible with the inclusion of cloud-specific information. Future model sensitivity testing seeks to quantify the magnitude of forecast improvement.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 1: Method.

PubMed

Norris, Peter M; da Silva, Arlindo M

2016-07-01

A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC.

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 1: Method

NASA Technical Reports Server (NTRS)

Norris, Peter M.; Da Silva, Arlindo M.

2016-01-01

A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 1: Method

PubMed Central

Norris, Peter M.; da Silva, Arlindo M.

2018-01-01

A method is presented to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation. The gridcolumn model includes assumed probability density function (PDF) intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used in the current study are Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. The current study uses a skewed-triangle distribution for layer moisture. The article also includes a discussion of the Metropolis and multiple-try Metropolis versions of MCMC. PMID:29618847

Statistical retrieval of thin liquid cloud microphysical properties using ground-based infrared and microwave observations

NASA Astrophysics Data System (ADS)

Marke, Tobias; Ebell, Kerstin; Löhnert, Ulrich; Turner, David D.

2016-12-01

In this article, liquid water cloud microphysical properties are retrieved by a combination of microwave and infrared ground-based observations. Clouds containing liquid water are frequently occurring in most climate regimes and play a significant role in terms of interaction with radiation. Small perturbations in the amount of liquid water contained in the cloud can cause large variations in the radiative fluxes. This effect is enhanced for thin clouds (liquid water path, LWP <100 g/m2), which makes accurate retrieval information of the cloud properties crucial. Due to large relative errors in retrieving low LWP values from observations in the microwave domain and a high sensitivity for infrared methods when the LWP is low, a synergistic retrieval based on a neural network approach is built to estimate both LWP and cloud effective radius (reff). These statistical retrievals can be applied without high computational demand but imply constraints like prior information on cloud phase and cloud layering. The neural network retrievals are able to retrieve LWP and reff for thin clouds with a mean relative error of 9% and 17%, respectively. This is demonstrated using synthetic observations of a microwave radiometer (MWR) and a spectrally highly resolved infrared interferometer. The accuracy and robustness of the synergistic retrievals is confirmed by a low bias in a radiative closure study for the downwelling shortwave flux, even for marginally invalid scenes. Also, broadband infrared radiance observations, in combination with the MWR, have the potential to retrieve LWP with a higher accuracy than a MWR-only retrieval.

Application of advanced data assimilation techniques to the study of cloud and precipitation feedbacks in the tropical climate system

NASA Astrophysics Data System (ADS)

Posselt, Derek J.

The research documented in this study centers around two topics: evaluation of the response of precipitating cloud systems to changes in the tropical climate system, and assimilation of cloud and precipitation information from remote-sensing platforms. The motivation for this work proceeds from the following outstanding problems: (1) Use of models to study the response of clouds to perturbations in the climate system is hampered by uncertainties in cloud microphysical parameterizations. (2) Though there is an ever-growing set of available observations, cloud and precipitation assimilation remains a difficult problem, particularly in the tropics. (3) Though it is widely acknowledged that cloud and precipitation processes play a key role in regulating the Earth's response to surface warming, the response of the tropical hydrologic cycle to climate perturbations remains largely unknown. The above issues are addressed in the following manner. First, Markov chain Monte Carlo (MCMC) methods are used to quantify the sensitivity of the NASA Goddard Cumulus Ensemble (GCE) cloud resolving model (CRM) to changes in its cloud odcrnpbymiC8l parameters. TRMM retrievals of precipitation rate, cloud properties, and radiative fluxes and heating rates over the South China Sea are then assimilated into the GCE model to constrain cloud microphysical parameters to values characteristic of convection in the tropics, and the resulting observation-constrained model is used to assess the response of the tropical hydrologic cycle to surface warming. The major findings of this study are the following: (1) MCMC provides an effective tool with which to evaluate both model parameterizations and the assumption of Gaussian statistics used in optimal estimation procedures. (2) Statistics of the tropical radiation budget and hydrologic cycle can be used to effectively constrain CRM cloud microphysical parameters. (3) For 2D CRM simulations run with and without shear, the precipitation efficiency of cloud systems increases with increasing sea surface temperature, while the high cloud fraction and outgoing shortwave radiation decrease.

Global statistics of microphysical properties of cloud-top ice crystals

NASA Astrophysics Data System (ADS)

van Diedenhoven, B.; Fridlind, A. M.; Cairns, B.; Ackerman, A. S.; Riedi, J.

2017-12-01

Ice crystals in clouds are highly complex. Their sizes, macroscale shape (i.e., habit), mesoscale shape (i.e., aspect ratio of components) and microscale shape (i.e., surface roughness) determine optical properties and affect physical properties such as fall speeds, growth rates and aggregation efficiency. Our current understanding on the formation and evolution of ice crystals under various conditions can be considered poor. Commonly, ice crystal size and shape are related to ambient temperature and humidity, but global observational statistics on the variation of ice crystal size and particularly shape have not been available. Here we show results of a project aiming to infer ice crystal size, shape and scattering properties from a combination of MODIS measurements and POLDER-PARASOL multi-angle polarimetry. The shape retrieval procedure infers the mean aspect ratios of components of ice crystals and the mean microscale surface roughness levels, which are quantifiable parameters that mostly affect the scattering properties, in contrast to "habit". We present global statistics on the variation of ice effective radius, component aspect ratio, microscale surface roughness and scattering asymmetry parameter as a function of cloud top temperature, latitude, location, cloud type, season, etc. Generally, with increasing height, sizes decrease, roughness increases, asymmetry parameters decrease and aspect ratios increase towards unity. Some systematic differences are observed for clouds warmer and colder than the homogeneous freezing level. Uncertainties in the retrievals will be discussed. These statistics can be used as observational targets for modeling efforts and to better constrain other satellite remote sensing applications and their uncertainties.

Global Statistics of Microphysical Properties of Cloud-Top Ice Crystals

NASA Technical Reports Server (NTRS)

Van Diedenhoven, Bastiaan; Fridlind, Ann; Cairns, Brian; Ackerman, Andrew; Riedl, Jerome

2017-01-01

Ice crystals in clouds are highly complex. Their sizes, macroscale shape (i.e., habit), mesoscale shape (i.e., aspect ratio of components) and microscale shape (i.e., surface roughness) determine optical properties and affect physical properties such as fall speeds, growth rates and aggregation efficiency. Our current understanding on the formation and evolution of ice crystals under various conditions can be considered poor. Commonly, ice crystal size and shape are related to ambient temperature and humidity, but global observational statistics on the variation of ice crystal size and particularly shape have not been available. Here we show results of a project aiming to infer ice crystal size, shape and scattering properties from a combination of MODIS measurements and POLDER-PARASOL multi-angle polarimetry. The shape retrieval procedure infers the mean aspect ratios of components of ice crystals and the mean microscale surface roughness levels, which are quantifiable parameters that mostly affect the scattering properties, in contrast to a habit. We present global statistics on the variation of ice effective radius, component aspect ratio, microscale surface roughness and scattering asymmetry parameter as a function of cloud top temperature, latitude, location, cloud type, season, etc. Generally, with increasing height, sizes decrease, roughness increases, asymmetry parameters decrease and aspect ratios increase towards unity. Some systematic differences are observed for clouds warmer and colder than the homogeneous freezing level. Uncertainties in the retrievals will be discussed. These statistics can be used as observational targets for modeling efforts and to better constrain other satellite remote sensing applications and their uncertainties.

Cloud microphysical background for the Israel-4 cloud seeding experiment

NASA Astrophysics Data System (ADS)

Freud, Eyal; Koussevitzky, Hagai; Goren, Tom; Rosenfeld, Daniel

2015-05-01

The modest amount of rainfall in Israel occurs in winter storms that bring convective clouds from the Mediterranean Sea when the cold post frontal air interacts with its relatively warm surface. These clouds were seeded in the Israel-1 and Israel-2 cloud glaciogenic seeding experiments, which have shown statistically significant positive effect of added rainfall of at least 13% in northern Israel, whereas the Israel-3 experiment showed no added rainfall in the south. This was followed by operational seeding in the north since 1975. The lack of physical evidence for the causes of the positive effects in the north caused a lack of confidence in the statistical results and led to the Israel-4 randomized seeding experiment in northern Israel. This experiment started in the winter of 2013/14. The main difference from the previous experiments is the focus on the orographic clouds in the catchment of the Sea of Galilee. The decision to commence the experiment was partially based on evidence supporting the existence of seeding potential, which is reported here. Aircraft and satellite microphysical and dynamic measurements of the clouds document the critical roles of aerosols, especially sea spray, on cloud microstructure and precipitation forming processes. It was found that the convective clouds over sea and coastal areas are naturally seeded hygroscopically by sea spray and develop precipitation efficiently. The diminution of the large sea spray aerosols farther inland along with the increase in aerosol concentrations causes the clouds to develop precipitation more slowly. The short time available for the precipitation forming processes in super-cooled orographic clouds over the Golan Heights farthest inland represents the best glaciogenic seeding potential.

Role of Gravity Waves in Determining Cirrus Cloud Properties

NASA Technical Reports Server (NTRS)

OCStarr, David; Singleton, Tamara; Lin, Ruei-Fong

2008-01-01

Cirrus clouds are important in the Earth's radiation budget. They typically exhibit variable physical properties within a given cloud system and from system to system. Ambient vertical motion is a key factor in determining the cloud properties in most cases. The obvious exception is convectively generated cirrus (anvils), but even in this case, the subsequent cloud evolution is strongly influenced by the ambient vertical motion field. It is well know that gravity waves are ubiquitous in the atmosphere and occur over a wide range of scales and amplitudes. Moreover, researchers have found that inclusion of statistical account of gravity wave effects can markedly improve the realism of simulations of persisting large-scale cirrus cloud features. Here, we use a 1 -dimensional (z) cirrus cloud model, to systematically examine the effects of gravity waves on cirrus cloud properties. The model includes a detailed representation of cloud microphysical processes (bin microphysics and aerosols) and is run at relatively fine vertical resolution so as to adequately resolve nucleation events, and over an extended time span so as to incorporate the passage of multiple gravity waves. The prescribed gravity waves "propagate" at 15 m s (sup -1), with wavelengths from 5 to 100 km, amplitudes range up to 1 m s (sup -1)'. Despite the fact that the net gravity wave vertical motion forcing is zero, it will be shown that the bulk cloud properties, e.g., vertically-integrated ice water path, can differ quite significantly from simulations without gravity waves and that the effects do depend on the wave characteristics. We conclude that account of gravity wave effects is important if large-scale models are to generate realistic cirrus cloud property climatology (statistics).

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability using High-Resolution Cloud Observations

NASA Astrophysics Data System (ADS)

Norris, P. M.; da Silva, A. M., Jr.

2016-12-01

Norris and da Silva recently published a method to constrain a statistical model of sub-gridcolumn moisture variability using high-resolution satellite cloud data. The method can be used for large-scale model parameter estimation or cloud data assimilation (CDA). The gridcolumn model includes assumed-PDF intra-layer horizontal variability and a copula-based inter-layer correlation model. The observables used are MODIS cloud-top pressure, brightness temperature and cloud optical thickness, but the method should be extensible to direct cloudy radiance assimilation for a small number of channels. The algorithm is a form of Bayesian inference with a Markov chain Monte Carlo (MCMC) approach to characterizing the posterior distribution. This approach is especially useful in cases where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach is not gradient-based and allows jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. The new approach not only significantly reduces mean and standard deviation biases with respect to the assimilated observables, but also improves the simulated rotational-Ramman scattering cloud optical centroid pressure against independent (non-assimilated) retrievals from the OMI instrument. One obvious difficulty for the method, and other CDA methods, is the lack of information content in passive cloud observables on cloud vertical structure, beyond cloud-top and thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard is helpful, better honoring inversion structures in the background state.

Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

DOE PAGES

Yang, Fan; Luke, Edward P.; Kollias, Pavlos; ...

2018-04-20

Drizzle plays a crucial role in cloud lifetime and radiation properties of marine stratocumulus clouds. Understanding where drizzle exists in the sub-cloud layer, which depends on drizzle virga depth, can help us better understand where below-cloud scavenging and evaporative cooling and moisturizing occur. In this study, we examine the statistical properties of drizzle frequency and virga depth of marine stratocumulus based on unique ground-based remote sensing data. Results show that marine stratocumulus clouds are drizzling nearly all the time. In addition, we derive a simple scaling analysis between drizzle virga thickness and cloud thickness. Our analytical expression agrees with themore » observational data reasonable well, which suggests that our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in other models.« less

Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

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

Yang, Fan; Luke, Edward P.; Kollias, Pavlos

Drizzle plays a crucial role in cloud lifetime and radiation properties of marine stratocumulus clouds. Understanding where drizzle exists in the sub-cloud layer, which depends on drizzle virga depth, can help us better understand where below-cloud scavenging and evaporative cooling and moisturizing occur. In this study, we examine the statistical properties of drizzle frequency and virga depth of marine stratocumulus based on unique ground-based remote sensing data. Results show that marine stratocumulus clouds are drizzling nearly all the time. In addition, we derive a simple scaling analysis between drizzle virga thickness and cloud thickness. Our analytical expression agrees with themore » observational data reasonable well, which suggests that our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in other models.« less

Detection of coliform bacteria and Escherichia coli by multiplex polymerase chain reaction: comparison with defined substrate and plating methods for water quality monitoring.

PubMed Central

Bej, A K; McCarty, S C; Atlas, R M

1991-01-01

Multiplex polymerase chain reaction (PCR) and gene probe detection of target lacZ and uidA genes were used to detect total coliform bacteria and Escherichia coli, respectively, for determining water quality. In tests of environmental water samples, the lacZ PCR method gave results statistically equivalent to those of the plate count and defined substrate methods accepted by the U.S. Environmental Protection Agency for water quality monitoring and the uidA PCR method was more sensitive than 4-methylumbelliferyl-beta-D-glucuronide-based defined substrate tests for specific detection of E. coli. Images PMID:1768116

Cloud Optical Depth Measured with Ground-Based, Uncooled Infrared Imagers

NASA Technical Reports Server (NTRS)

Shaw, Joseph A.; Nugent, Paul W.; Pust, Nathan J.; Redman, Brian J.; Piazzolla, Sabino

2012-01-01

Recent advances in uncooled, low-cost, long-wave infrared imagers provide excellent opportunities for remotely deployed ground-based remote sensing systems. However, the use of these imagers in demanding atmospheric sensing applications requires that careful attention be paid to characterizing and calibrating the system. We have developed and are using several versions of the ground-based "Infrared Cloud Imager (ICI)" instrument to measure spatial and temporal statistics of clouds and cloud optical depth or attenuation for both climate research and Earth-space optical communications path characterization. In this paper we summarize the ICI instruments and calibration methodology, then show ICI-derived cloud optical depths that are validated using a dual-polarization cloud lidar system for thin clouds (optical depth of approximately 4 or less).

Statistical characteristics of cloud variability. Part 1: Retrieved cloud liquid water path at three ARM sites

NASA Astrophysics Data System (ADS)

Huang, Dong; Campos, Edwin; Liu, Yangang

2014-09-01

Statistical characteristics of cloud variability are examined for their dependence on averaging scales and best representation of probability density function with the decade-long retrieval products of cloud liquid water path (LWP) from the tropical western Pacific (TWP), Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites of the Department of Energy's Atmospheric Radiation Measurement Program. The statistical moments of LWP show some seasonal variation at the SGP and NSA sites but not much at the TWP site. It is found that the standard deviation, relative dispersion (the ratio of the standard deviation to the mean), and skewness all quickly increase with the averaging window size when the window size is small and become more or less flat when the window size exceeds 12 h. On average, the cloud LWP at the TWP site has the largest values of standard deviation, relative dispersion, and skewness, whereas the NSA site exhibits the least. Correlation analysis shows that there is a positive correlation between the mean LWP and the standard deviation. The skewness is found to be closely related to the relative dispersion with a correlation coefficient of 0.6. The comparison further shows that the lognormal, Weibull, and gamma distributions reasonably explain the observed relationship between skewness and relative dispersion over a wide range of scales.

Changes in the type of precipitation and associated cloud types in Eastern Romania (1961-2008)

NASA Astrophysics Data System (ADS)

Manea, Ancuta; Birsan, Marius-Victor; Tudorache, George; Cărbunaru, Felicia

2016-03-01

Recent climate change is characterized (among other things) by changes in the frequency of some meteorological phenomena. This paper deals with the long-term changes in various precipitation types, and the connection between their variability and cloud type frequencies, at 11 meteorological stations from Eastern Romania over 1961-2008. These stations were selected with respect to data record completeness for all considered variables (weather phenomena and cloud type). The meteorological variables involved in the present study are: monthly number of days with rain, snowfall, snow showers, rain and snow (sleet), sleet showers and monthly frequency of the Cumulonimbus, Nimbostratus and Stratus clouds. Our results show that all stations present statistically significant decreasing trends in the number of days with rain in the warm period of the year. Changes in the frequency of days for each precipitation type show statistically significant decreasing trends for non-convective (stratiform) precipitation - rain, drizzle, sleet and snowfall -, while the frequencies of rain shower and snow shower (convective precipitation) are increasing. Cloud types show decreasing trends for Nimbostratus and Stratus, and increasing trends for Cumulonimbus.

Using High-Resolution Satellite Observations for Evaluation of Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations. Part I: South China Sea Monsoon Experiment

NASA Astrophysics Data System (ADS)

Zhou, Y.; Hou, A.; Lau, W. K.; Shie, C.; Tao, W.; Lin, X.; Chou, M.; Olson, W. S.; Grecu, M.

2006-05-01

The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model during the South China Sea Monsoon Experiment (SCSMEX) is compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) radiation and cloud retrievals. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. Mesoscale organization is adequately simulated except when environmental wind shear is very weak. The partitions between convective and stratiform rain are also close to TMI and PR classification. However, the model simulated rain spectrum is quite different from either TMI or PR measurements. The model produces more heavy rains and light rains (less than 0.1 mm/hr) than the observations. The model also produces heavier vertical hydrometer profiles of rain, graupel when compared with TMI retrievals and PR radar reflectivity. Comparing GCE simulated OLR and cloud properties with CERES measurements found that the model has much larger domain averaged OLR due to smaller total cloud fraction and a much skewed distribution of OLR and cloud top than CERES observations, indicating that the model's cloud field is not wide spread, consistent with the model's precipitation activity. These results will be used as guidance for improving the model's microphysics.

Two Years of Global Cirrus Cloud Statistics Using HIRS

NASA Technical Reports Server (NTRS)

Wylie, Donald; Menzel, W. Paul; Woolf, H. M.

1991-01-01

A climatology of upper tropospheric semi-transparent cirrus clouds has been compiled using HIRS multispectral infrared data, sensitive to CO2 absorption, from the NOAA polar orbiting satellites. This is a report on the two years of data analyzed (June 1989 - May 1991). Semi-transparent clouds were found in 36% of the observations. Large seasonal changes were found in these clouds in many geographical areas; large changes occur in areas dominated by the ITCZ, the sub-tropical high pressure systems, and the mid-latitude storm belts. Semi-transparent clouds associated with these features move latitudinally with the seasons. These clouds also are more frequent in the summer hemisphere than the winter hemisphere. They appear to be linked to convective cloud development and the mid-latitudinal frontal weather systems. However, very thin semi-transparent cirrus has less seasonal movement than other cloud forms.

Validation of VIIRS Cloud Base Heights at Night Using Ground and Satellite Measurements over Alaska

NASA Astrophysics Data System (ADS)

NOH, Y. J.; Miller, S. D.; Seaman, C.; Forsythe, J. M.; Brummer, R.; Lindsey, D. T.; Walther, A.; Heidinger, A. K.; Li, Y.

2016-12-01

Knowledge of Cloud Base Height (CBH) is critical to describing cloud radiative feedbacks in numerical models and is of practical significance to aviation communities. We have developed a new CBH algorithm constrained by Cloud Top Height (CTH) and Cloud Water Path (CWP) by performing a statistical analysis of A-Train satellite data. It includes an extinction-based method for thin cirrus. In the algorithm, cloud geometric thickness is derived with upstream CTH and CWP input and subtracted from CTH to generate the topmost layer CBH. The CBH information is a key parameter for an improved Cloud Cover/Layers product. The algorithm has been applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP spacecraft. Nighttime cloud optical properties for CWP are retrieved from the nighttime lunar cloud optical and microphysical properties (NLCOMP) algorithm based on a lunar reflectance model for the VIIRS Day/Night Band (DNB) measuring nighttime visible light such as moonlight. The DNB has innovative capabilities to fill the polar winter and nighttime gap of cloud observations which has been an important shortfall from conventional radiometers. The CBH products have been intensively evaluated against CloudSat data. The results showed the new algorithm yields significantly improved performance over the original VIIRS CBH algorithm. However, since CloudSat is now operational during daytime only due to a battery anomaly, the nighttime performance has not been fully assessed. This presentation will show our approach to assess the performance of the CBH algorithm at night. VIIRS CBHs are retrieved over the Alaska region from October 2015 to April 2016 using the Clouds from AVHRR Extended (CLAVR-x) processing system. Ground-based measurements from ceilometer and micropulse lidar at the Atmospheric Radiation Measurement (ARM) site on the North Slope of Alaska are used for the analysis. Local weather conditions are checked using temperature and precipitation observations at the site. CALIPSO data with near-simultaneous colocation are added for multi-layered cloud cases which may have high clouds aloft beyond the ground measurements. Multi-month statistics of performance and case studies will be shown. Additional efforts for algorithm refinements will be also discussed.

Evaluating NASA S-NPP continuity cloud products for climate research using CALIPSO, CATS and Level-3 analysis

NASA Astrophysics Data System (ADS)

Holz, R.; Platnick, S. E.; Meyer, K.; Frey, R.; Wind, G.; Ackerman, S. A.; Heidinger, A. K.; Botambekov, D.; Yorks, J. E.; McGill, M. J.

2016-12-01

The launch of VIIRS and CrIS on Suomi NPP in the fall of 2011 introduced the next generation of U.S. operational polar orbiting environmental observations. Similar to MODIS, VIIRS provides visible and IR observations at moderate spatial resolution and has a 1:30 pm equatorial crossing time consistent with the MODIS on Aqua platform. However unlike MODIS, VIIRS lacks water vapor and CO2 absorbing channels that are used by the MODIS cloud algorithms for both cloud detection and to retrieve cloud top height and cloud emissivity for ice clouds. Given the different spectral and spatial characteristics of VIIRS, we seek to understand the extent to which the 15-year MODIS climate record can be continued with VIIRS/CrIS observations while maintaining consistent sensitivities across the observational systems. This presentation will focus on the evaluation of the latest version of the NASA funded cloud retrieval algorithms being developed for climate research. We will present collocated inter-comparisons between the imagers (VIIRS and MODIS Aqua) with CALIPSO and Cloud Aerosol Transport System (CATS) lidar observations as well as long term statistics based on a new Level-3 (L3) product being developed as part the project. The CALIPSO inter-comparisons will focus on cloud detection (cloud mask) with a focus on the impact of recent modifications to the cloud mask and how these changes impact the global statistics. For the first time we will provide inter-comparisons between two different cloud lidar systems (CALIOP and CATS) and investigate how the different sensitivities of the lidars impact the cloud mask and cloud comparisons. Using CALIPSO and CATS as the reference, and applying the same algorithms to VIIRS and MODIS, we will discuss the consistency between products from both imagers. The L3 analysis will focus on the regional and seasonal consistency between the suite of MODIS and VIIRS continuity cloud products. Do systematic biases remains when using consistent algorithms but applied to different observations (MODIS or VIIRS)?

Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels.

PubMed

Yu, Chao; Di Girolamo, Larry; Chen, Liangfu; Zhang, Xueying; Liu, Yang

2015-01-01

The spatial and temporal characteristics of fine particulate matter (PM2.5, particulate matter <2.5 μm in aerodynamic diameter) are increasingly being studied from satellite aerosol remote sensing data. However, cloud cover severely limits the coverage of satellite-driven PM2.5 models, and little research has been conducted on the association between cloud properties and PM2.5 levels. In this study, we analyzed the relationships between ground PM2.5 concentrations and two satellite-retrieved cloud parameters using data from the Southeastern Aerosol Research and Characterization (SEARCH) Network during 2000-2010. We found that both satellite-retrieved cloud fraction (CF) and cloud optical thickness (COT) are negatively associated with PM2.5 levels. PM2.5 speciation and meteorological analysis suggested that the main reason for these negative relationships might be the decreased secondary particle generation. Stratified analyses by season, land use type, and site location showed that seasonal impacts on this relationship are significant. These associations do not vary substantially between urban and rural sites or inland and coastal sites. The statistically significant negative associations of PM2.5 mass concentrations with CF and COT suggest that satellite-retrieved cloud parameters have the potential to serve as predictors to fill the data gap left by satellite aerosol optical depth in satellite-driven PM2.5 models.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results

PubMed Central

Norris, Peter M.; da Silva, Arlindo M.

2018-01-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational–Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state. PMID:29618848

Monte Carlo Bayesian Inference on a Statistical Model of Sub-Gridcolumn Moisture Variability Using High-Resolution Cloud Observations. Part 2: Sensitivity Tests and Results

NASA Technical Reports Server (NTRS)

Norris, Peter M.; da Silva, Arlindo M.

2016-01-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.

Monte Carlo Bayesian inference on a statistical model of sub-gridcolumn moisture variability using high-resolution cloud observations. Part 2: Sensitivity tests and results.

PubMed

Norris, Peter M; da Silva, Arlindo M

2016-07-01

Part 1 of this series presented a Monte Carlo Bayesian method for constraining a complex statistical model of global circulation model (GCM) sub-gridcolumn moisture variability using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) cloud data, thereby permitting parameter estimation and cloud data assimilation for large-scale models. This article performs some basic testing of this new approach, verifying that it does indeed reduce mean and standard deviation biases significantly with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud-top pressure and that it also improves the simulated rotational-Raman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the Ozone Monitoring Instrument (OMI). Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows non-gradient-based jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast, where the background state has a clear swath. This article also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in passive-radiometer-retrieved cloud observables on cloud vertical structure, beyond cloud-top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification from Riishojgaard provides some help in this respect, by better honouring inversion structures in the background state.

First X-ray Statistical Tests for Clumpy-Torus Models: Constraints from RXTEmonitoring of Seyfert AGN

NASA Astrophysics Data System (ADS)

Markowitz, Alex; Krumpe, Mirko; Nikutta, R.

2016-06-01

In two papers (Markowitz, Krumpe, & Nikutta 2014, and Nikutta et al., in prep.), we derive the first X-ray statistical constraints for clumpy-torus models in Seyfert AGN by quantifying multi-timescale variability in line of-sight X-ray absorbing gas as a function of optical classification.We systematically search for discrete absorption events in the vast archive of RXTE monitoring of 55 nearby type Is and Compton-thin type IIs. We are sensitive to discrete absorption events due to clouds of full-covering, neutral/mildly ionized gas transiting the line of sight. Our results apply to both dusty and non-dusty clumpy media, and probe model parameter space complementary to that for eclipses observed with XMM-Newton, Suzaku, and Chandra.We detect twelve eclipse events in eight Seyferts, roughly tripling the number previously published from this archive. Event durations span hours to years. Most of our detected clouds are Compton-thin, and most clouds' distances from the black hole are inferred to be commensurate with the outer portions of the BLR or the inner regions of infrared-emitting dusty tori.We present the density profiles of the highest-quality eclipse events; the column density profile for an eclipsing cloud in NGC 3783 is doubly spiked, possibly indicating a cloud that is being tidallysheared. We discuss implications for cloud distributions in the context of clumpy-torus models. We calculate eclipse probabilities for orientation-dependent Type I/II unification schemes.We present constraints on cloud sizes, stability, and radial distribution. We infer that clouds' small angular sizes as seen from the SMBH imply 107 clouds required across the BLR + torus. Cloud size is roughly proportional to distance from the black hole, hinting at the formation processes (e.g., disk fragmentation). All observed clouds are sub-critical with respect to tidal disruption; self-gravity alone cannot contain them. External forces, such as magnetic fields or ambient pressure, are needed to contain them; otherwise, clouds must be short-lived.

Scanning Backscatter Lidar Observations for Characterizing 4-D Cloud and Aerosol Fields to Improve Radiative Transfer Parameterizations

NASA Technical Reports Server (NTRS)

Schwemmer, Geary K.; Miller, David O.

2005-01-01

Clouds have a powerful influence on atmospheric radiative transfer and hence are crucial to understanding and interpreting the exchange of radiation between the Earth's surface, the atmosphere, and space. Because clouds are highly variable in space, time and physical makeup, it is important to be able to observe them in three dimensions (3-D) with sufficient resolution that the data can be used to generate and validate parameterizations of cloud fields at the resolution scale of global climate models (GCMs). Simulation of photon transport in three dimensionally inhomogeneous cloud fields show that spatial inhomogeneities tend to decrease cloud reflection and absorption and increase direct and diffuse transmission, Therefore it is an important task to characterize cloud spatial structures in three dimensions on the scale of GCM grid elements. In order to validate cloud parameterizations that represent the ensemble, or mean and variance of cloud properties within a GCM grid element, measurements of the parameters must be obtained on a much finer scale so that the statistics on those measurements are truly representative. High spatial sampling resolution is required, on the order of 1 km or less. Since the radiation fields respond almost instantaneously to changes in the cloud field, and clouds changes occur on scales of seconds and less when viewed on scales of approximately 100m, the temporal resolution of cloud properties should be measured and characterized on second time scales. GCM time steps are typically on the order of an hour, but in order to obtain sufficient statistical representations of cloud properties in the parameterizations that are used as model inputs, averaged values of cloud properties should be calculated on time scales on the order of 10-100 s. The Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) provides exceptional temporal (100 ms) and spatial (30 m) resolution measurements of aerosol and cloud backscatter in three dimensions. HARLIE was used in a ground-based configuration in several recent field campaigns. Principal data products include aerosol backscatter profiles, boundary layer heights, entrainment zone thickness, cloud fraction as a function of altitude and horizontal wind vector profiles based on correlating the motions of clouds and aerosol structures across portions of the scan. Comparisons will be made between various cloud detecting instruments to develop a baseline performance metric.

JINR cloud infrastructure evolution

NASA Astrophysics Data System (ADS)

Baranov, A. V.; Balashov, N. A.; Kutovskiy, N. A.; Semenov, R. N.

2016-09-01

To fulfil JINR commitments in different national and international projects related to the use of modern information technologies such as cloud and grid computing as well as to provide a modern tool for JINR users for their scientific research a cloud infrastructure was deployed at Laboratory of Information Technologies of Joint Institute for Nuclear Research. OpenNebula software was chosen as a cloud platform. Initially it was set up in simple configuration with single front-end host and a few cloud nodes. Some custom development was done to tune JINR cloud installation to fit local needs: web form in the cloud web-interface for resources request, a menu item with cloud utilization statistics, user authentication via Kerberos, custom driver for OpenVZ containers. Because of high demand in that cloud service and its resources over-utilization it was re-designed to cover increasing users' needs in capacity, availability and reliability. Recently a new cloud instance has been deployed in high-availability configuration with distributed network file system and additional computing power.

Aviation effects on already-existing cirrus clouds

PubMed Central

Tesche, Matthias; Achtert, Peggy; Glantz, Paul; Noone, Kevin J.

2016-01-01

Determining the effects of the formation of contrails within natural cirrus clouds has proven to be challenging. Quantifying any such effects is necessary if we are to properly account for the influence of aviation on climate. Here we quantify the effect of aircraft on the optical thickness of already-existing cirrus clouds by matching actual aircraft flight tracks to satellite lidar measurements. We show that there is a systematic, statistically significant increase in normalized cirrus cloud optical thickness inside mid-latitude flight tracks compared with adjacent areas immediately outside the tracks. PMID:27327838

Aviation effects on already-existing cirrus clouds.

PubMed

Tesche, Matthias; Achtert, Peggy; Glantz, Paul; Noone, Kevin J

2016-06-21

Determining the effects of the formation of contrails within natural cirrus clouds has proven to be challenging. Quantifying any such effects is necessary if we are to properly account for the influence of aviation on climate. Here we quantify the effect of aircraft on the optical thickness of already-existing cirrus clouds by matching actual aircraft flight tracks to satellite lidar measurements. We show that there is a systematic, statistically significant increase in normalized cirrus cloud optical thickness inside mid-latitude flight tracks compared with adjacent areas immediately outside the tracks.

Ship-based Observations of Turbulence and Stratocumulus Cloud Microphysics in the SE Pacific Ocean from the VOCALS Field Program

NASA Astrophysics Data System (ADS)

Fairall, C. W.; Williams, C.; Grachev, A. A.; Brewer, A.; Choukulkar, A.

2013-12-01

The VAMOS (VOCALS) field program involved deployment of several measurement systems based on ships, land and aircraft over the SE Pacific Ocean. The NOAA Ship Ronald H. Brown was the primary platform for surface based measurements which included the High Resolution Doppler Lidar (HRDL) and the motion-stabilized 94-GHz cloud Doppler radar (W-band radar). In this paper, the data from the W-band radar will be used to study the turbulent and microphysical structure of the stratocumulus clouds prevalent in the region. The radar data consists of a 3 Hz time series of radar parameters (backscatter coefficient, mean Doppler shift, and Doppler width) at 175 range gates (25-m spacing). Several statistical methods to de-convolve the turbulent velocity and gravitational settling velocity are examined and an optimized algorithm is developed. 20 days of observations are processed to examine in-cloud profiles of mean turbulent statistics (vertical velocity variance, skewness, dissipation rate) in terms of surface fluxes and estimates of entrainment and cloudtop radiative cooling. The clean separation of turbulent and fall velocities will allow us to compute time-averaged drizzle-drop size spectra within and below the cloud that are significantly superior to previous attempts with surface-based marine cloud radar observations.

Assessment of the Effects of Entrainment and Wind Shear on Nuclear Cloud Rise Modeling

NASA Astrophysics Data System (ADS)

Zalewski, Daniel; Jodoin, Vincent

2001-04-01

Accurate modeling of nuclear cloud rise is critical in hazard prediction following a nuclear detonation. This thesis recommends improvements to the model currently used by DOD. It considers a single-term versus a three-term entrainment equation, the value of the entrainment and eddy viscous drag parameters, as well as the effect of wind shear in the cloud rise following a nuclear detonation. It examines departures from the 1979 version of the Department of Defense Land Fallout Interpretive Code (DELFIC) with the current code used in the Hazard Prediction and Assessment Capability (HPAC) code version 3.2. The recommendation for a single-term entrainment equation, with constant value parameters, without wind shear corrections, and without cloud oscillations is based on both a statistical analysis using 67 U.S. nuclear atmospheric test shots and the physical representation of the modeling. The statistical analysis optimized the parameter values of interest for four cases: the three-term entrainment equation with wind shear and without wind shear as well as the single-term entrainment equation with and without wind shear. The thesis then examines the effect of cloud oscillations as a significant departure in the code. Modifications to user input atmospheric tables are identified as a potential problem in the calculation of stabilized cloud dimensions in HPAC.

Statistical Survey of Icing Data Measured on Scheduled Airline Flights over the United States and Canada from November 1951 to June 1952

NASA Technical Reports Server (NTRS)

Perkins, Porter J

1955-01-01

A statistical survey and a preliminary analysis are made of icing data collected from scheduled flights over the United States and Canada from November 1951 to June 1952 by airline aircraft equipped with NACA pressure-type icing-rate meters. This interim report presents information obtained from a continuing program sponsored by the NACA with the cooperation of the airlines. An analysis of over 600 icing encounters logged by three airlines operating in the United States, one operating in Canada and one operating up the coast to Alaska, is presented. The icing conditions encountered provided relative frequencies of many icing-cloud variables, such as horizontal extent, vertical thickness, temperatures, icing rate, liquid-water content, and total ice accumulation. Liquid-water contents were higher than data from earlier research flights in layer-type clouds but slightly lower than previous data from cumulus clouds. Broken-cloud conditions, indicated by intermittent icing, accounted for nearly one-half of all the icing encounters. About 90 percent of the encounters did not exceed a distance of 120 miles, and continuous icing did not exceed 50 miles for 90 percent of the unbroken conditions. Icing cloud thicknesses measured during climbs and descents were less than 4500 feet for 90 percent of the vertical cloud traverses.

Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3

DOE PAGES

Prather, M. J.

2015-05-27

A new approach for modeling photolysis rates ( J values) in atmospheres with fractional cloud cover has been developed and implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observed statistics for the vertical correlation of cloud layers, Cloud-J 7.3 provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations represented by four quadrature atmospheres produces mean J values in an atmospheric column with root-mean-square errors of 4% or less compared with 10–20% errors using simpler approximations.more » Cloud-J is practical for chemistry-climate models, requiring only an average of 2.8 Fast-J calls per atmosphere, vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections is also incorporated into Cloud-J.« less

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

NASA Technical Reports Server (NTRS)

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.

Probabilistic verification of cloud fraction from three different products with CALIPSO

NASA Astrophysics Data System (ADS)

Jung, B. J.; Descombes, G.; Snyder, C.

2017-12-01

In this study, we present how Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) can be used for probabilistic verification of cloud fraction, and apply this probabilistic approach to three cloud fraction products: a) The Air Force Weather (AFW) World Wide Merged Cloud Analysis (WWMCA), b) Satellite Cloud Observations and Radiative Property retrieval Systems (SatCORPS) from NASA Langley Research Center, and c) Multi-sensor Advection Diffusion nowCast (MADCast) from NCAR. Although they differ in their details, both WWMCA and SatCORPS retrieve cloud fraction from satellite observations, mainly of infrared radiances. MADCast utilizes in addition a short-range forecast of cloud fraction (provided by the Model for Prediction Across Scales, assuming cloud fraction is advected as a tracer) and a column-by-column particle filter implemented within the Gridpoint Statistical Interpolation (GSI) data-assimilation system. The probabilistic verification considers the retrieved or analyzed cloud fractions as predicting the probability of cloud at any location within a grid cell and the 5-km vertical feature mask (VFM) from CALIPSO level-2 products as a point observation of cloud.

Infrared cloud imaging in support of Earth-space optical communication.

PubMed

Nugent, Paul W; Shaw, Joseph A; Piazzolla, Sabino

2009-05-11

The increasing need for high data return from near-Earth and deep-space missions is driving a demand for the establishment of Earth-space optical communication links. These links will require a nearly obstruction-free path to the communication platform, so there is a need to measure spatial and temporal statistics of clouds at potential ground-station sites. A technique is described that uses a ground-based thermal infrared imager to provide continuous day-night cloud detection and classification according to the cloud optical depth and potential communication channel attenuation. The benefit of retrieving cloud optical depth and corresponding attenuation is illustrated through measurements that identify cloudy times when optical communication may still be possible through thin clouds.

Magnetic flux in modeled magnetic clouds at 1 AU and some specific comparisons to associated photospheric flux

NASA Technical Reports Server (NTRS)

Lepping, R. P.; Szabo, A.; DeForest, C. E.; Thompson, B. J.

1997-01-01

In order to better understand the solar origins of magnetic clouds, statistical distributions of the estimated axial magnetic flux of 30 magnetic clouds at 1 AU, separated according to their occurrence during the solar cycle, were obtained and a comparison was made of the magnetic flux of a magnetic cloud to the aggregate flux of apparently associated photospheric magnetic flux tubes, for some specific cases. The 30 magnetic clouds comprise 12 cases from WIND, and the remainder from IMP-8, earlier IMPs, the International Sun-Earth Explorer (ISEE) 3 and HELIOS. The total magnetic flux along the cloud axis was estimated using a constant alpha, cylindrical, force-free flux rope model to determine cloud diameter and axial magentic field strength. The distribution of magentic fluxes for the 30 clouds is shown to be in the form of a skewed Gaussian.

Variability analysis of the reconstructed daily global solar radiation under all-sky and cloud-free conditions in Madrid during the period 1887-1950

NASA Astrophysics Data System (ADS)

Antón, M.; Román, R.; Sanchez-Lorenzo, A.; Calbó, J.; Vaquero, J. M.

2017-07-01

This study focuses on the analysis of the daily global solar radiation (GSR) reconstructed from sunshine duration measurements at Madrid (Spain) from 1887 to 1950. Additionally, cloud cover information recorded simultaneously by human observations for the study period was also analyzed and used to select cloud-free days. First, the day-to-day variability of reconstructed GSR data was evaluated, finding a strong relationship between GSR and cloudiness. The second step was to analyze the long-term evolution of the GSR data which exhibited two clear trends with opposite sign: a marked negative trend of - 36 kJ/m2 per year for 1887-1915 period and a moderate positive trend of + 13 kJ/m2 per year for 1916-1950 period, both statistically significant at the 95% confidence level. Therefore, there is evidence of "early dimming" and "early brightening" periods in the reconstructed GSR data for all-sky conditions in Madrid from the late 19th to the mid-20th centuries. Unlike the long-term evolution of GSR data, cloud cover showed non-statistically significant trends for the two analyzed sub-periods, 1887-1915 and 1916-1950. Finally, GSR trends were analyzed exclusively under cloud-free conditions in summer by means of the determination of the clearness index for those days with all cloud cover observations equal to zero oktas. The long-term evolution of the clearness index was in accordance with the "early dimming" and "early brightening" periods, showing smaller trends but still statistically significant. This result points out that aerosol load variability could have had a non-negligible influence on the long-term evolution of GSR even as far as from the late 19th century.

[The principal components analysis--method to classify the statistical variables with applications in medicine].

PubMed

Dascălu, Cristina Gena; Antohe, Magda Ecaterina

2009-01-01

Based on the eigenvalues and the eigenvectors analysis, the principal component analysis has the purpose to identify the subspace of the main components from a set of parameters, which are enough to characterize the whole set of parameters. Interpreting the data for analysis as a cloud of points, we find through geometrical transformations the directions where the cloud's dispersion is maximal--the lines that pass through the cloud's center of weight and have a maximal density of points around them (by defining an appropriate criteria function and its minimization. This method can be successfully used in order to simplify the statistical analysis on questionnaires--because it helps us to select from a set of items only the most relevant ones, which cover the variations of the whole set of data. For instance, in the presented sample we started from a questionnaire with 28 items and, applying the principal component analysis we identified 7 principal components--or main items--fact that simplifies significantly the further data statistical analysis.

Multiplexed BioCD for prostate specific antigen detection

NASA Astrophysics Data System (ADS)

Wang, Xuefeng; Zhao, Ming; Nolte, David D.

2008-02-01

Specific protein concentrations in human body fluid can serve as diagnostic markers for some diseases, and a quantitative and high-throughput technique for multiplexed protein detection would speed up diagnosis and facilitate medical research. For this purpose, our group developed the BioCD, a spinning-disc interferometric biosensor on which antibody is immobilized. The detection system adopts a common-path scheme making it ultra stable. The scaling mass sensitivity is below 10 pg/mm for protein surface density. A 25000-spot antibody BioCD was fabricated to measure the concentration of prostate specific antigen (PSA), a protein indicating prostate cancer if its level is high. Statistical analysis of our immunoassay results projects that the detection limit of PSA would reach 20 pg/ml in a 2 mg/ml background solution. For future prospects, a multiplexed BioCD can be produced for simultaneous diagnosis of diverse diseases. For instance, 100 markers above 200 pg/ml could be measured on a single disc given that the detection limit is inversely proportional to square root of the number of spots.

The Galactic Distribution of OB Associations in Molecular Clouds

NASA Astrophysics Data System (ADS)

Williams, Jonathan P.; McKee, Christopher F.

1997-02-01

Molecular clouds account for half of the mass of the interstellar medium interior to the solar circle and for all current star formation. Using cloud catalogs of two CO surveys of the first quadrant, we have fitted the mass distribution of molecular clouds to a truncated power law in a similar manner as the luminosity function of OB associations in the companion paper to this work. After extrapolating from the first quadrant to the entire inner Galaxy, we find that the mass of cataloged clouds amounts to only 40% of current estimates of the total Galactic molecular mass. Following Solomon & Rivolo, we have assumed that the remaining molecular gas is in cold clouds, and we normalize the distribution accordingly. The predicted total number of clouds is then shown to be consistent with that observed in the solar neighborhood where cloud catalogs should be more complete. Within the solar circle, the cumulative form of the distribution is \\Nscrc(>M)=105[(Mu/M)0.6-1], where \\Nscrc is the number of clouds, and Mu = 6 × 106 M⊙ is the upper mass limit. The large number of clouds near the upper cutoff to the distribution indicates an underlying physical limit to cloud formation or destruction processes. The slope of the distribution corresponds to d\\Nscrc/dM~M-1.6, implying that although numerically most clouds are of low mass, most of the molecular gas is contained within the most massive clouds. The distribution of cloud masses is then compared to the Galactic distribution of OB association luminosities to obtain statistical estimates of the number of massive stars expected in any given cloud. The likelihood of massive star formation in a cloud is determined, and it is found that the median cloud mass that contains at least one O star is ~105 M⊙. The average star formation efficiency over the lifetime of an association is about 5% but varies by more than 2 orders of magnitude from cloud to cloud and is predicted to increase with cloud mass. O stars photoevaporate their surrounding molecular gas, and even with low rates of formation, they are the principal agents of cloud destruction. Using an improved estimate of the timescale for photoevaporation and our statistics on the expected numbers of stars per cloud, we find that 106 M⊙ giant molecular clouds (GMCs) are expected to survive for about 3 × 107 yr. Smaller clouds are disrupted, rather than photoionized, by photoevaporation. The porosity of H II regions in large GMCs is shown to be of order unity, which is consistent with self-regulation of massive star formation in GMCs. On average, 10% of the mass of a GMC is converted to stars by the time it is destroyed by photoevaporation.

On the Emergent Constraints of Climate Sensitivity [On proposed emergent constraints of climate sensitivity

DOE PAGES

Qu, Xin; Hall, Alex; DeAngelis, Anthony M.; ...

2018-01-11

Differences among climate models in equilibrium climate sensitivity (ECS; the equilibrium surface temperature response to a doubling of atmospheric CO2) remain a significant barrier to the accurate assessment of societally important impacts of climate change. Relationships between ECS and observable metrics of the current climate in model ensembles, so-called emergent constraints, have been used to constrain ECS. Here a statistical method (including a backward selection process) is employed to achieve a better statistical understanding of the connections between four recently proposed emergent constraint metrics and individual feedbacks influencing ECS. The relationship between each metric and ECS is largely attributable tomore » a statistical connection with shortwave low cloud feedback, the leading cause of intermodel ECS spread. This result bolsters confidence in some of the metrics, which had assumed such a connection in the first place. Additional analysis is conducted with a few thousand artificial metrics that are randomly generated but are well correlated with ECS. The relationships between the contrived metrics and ECS can also be linked statistically to shortwave cloud feedback. Thus, any proposed or forthcoming ECS constraint based on the current generation of climate models should be viewed as a potential constraint on shortwave cloud feedback, and physical links with that feedback should be investigated to verify that the constraint is real. Additionally, any proposed ECS constraint should not be taken at face value since other factors influencing ECS besides shortwave cloud feedback could be systematically biased in the models.« less

On the Emergent Constraints of Climate Sensitivity [On proposed emergent constraints of climate sensitivity

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

Qu, Xin; Hall, Alex; DeAngelis, Anthony M.

Differences among climate models in equilibrium climate sensitivity (ECS; the equilibrium surface temperature response to a doubling of atmospheric CO2) remain a significant barrier to the accurate assessment of societally important impacts of climate change. Relationships between ECS and observable metrics of the current climate in model ensembles, so-called emergent constraints, have been used to constrain ECS. Here a statistical method (including a backward selection process) is employed to achieve a better statistical understanding of the connections between four recently proposed emergent constraint metrics and individual feedbacks influencing ECS. The relationship between each metric and ECS is largely attributable tomore » a statistical connection with shortwave low cloud feedback, the leading cause of intermodel ECS spread. This result bolsters confidence in some of the metrics, which had assumed such a connection in the first place. Additional analysis is conducted with a few thousand artificial metrics that are randomly generated but are well correlated with ECS. The relationships between the contrived metrics and ECS can also be linked statistically to shortwave cloud feedback. Thus, any proposed or forthcoming ECS constraint based on the current generation of climate models should be viewed as a potential constraint on shortwave cloud feedback, and physical links with that feedback should be investigated to verify that the constraint is real. Additionally, any proposed ECS constraint should not be taken at face value since other factors influencing ECS besides shortwave cloud feedback could be systematically biased in the models.« less

A self-consistency approach to improve microwave rainfall rate estimation from space

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Mack, Robert A.; Hakkarinen, Ida M.

1989-01-01

A multichannel statistical approach is used to retrieve rainfall rates from the brightness temperature T(B) observed by passive microwave radiometers flown on a high-altitude NASA aircraft. T(B) statistics are based upon data generated by a cloud radiative model. This model simulates variabilities in the underlying geophysical parameters of interest, and computes their associated T(B) in each of the available channels. By further imposing the requirement that the observed T(B) agree with the T(B) values corresponding to the retrieved parameters through the cloud radiative transfer model, the results can be made to agree quite well with coincident radar-derived rainfall rates. Some information regarding the cloud vertical structure is also obtained by such an added requirement. The applicability of this technique to satellite retrievals is also investigated. Data which might be observed by satellite-borne radiometers, including the effects of nonuniformly filled footprints, are simulated by the cloud radiative model for this purpose.

Quantifying spatial variability of AgI cloud seeding benefits and Ag enrichments in snow

NASA Astrophysics Data System (ADS)

Fisher, J.; Benner, S. G.; Lytle, M. L.; Kunkel, M. L.; Blestrud, D.; Holbrook, V. P.; Parkinson, S.; Edwards, R.

2016-12-01

Glaciogenic cloud seeding is an important scientific technology for enhancing water resources across in the Western United States. Cloud seeding enriches super cooled liquid water layers with plumes of silver iodide (AgI), an artificial ice nuclei. Recent studies using target-control regression analysis and modeling estimate glaciogenic cloud seeding increases snow precipitation between 3-15% annually. However, the efficacy of cloud seeding programs is difficult to assess using weather models and statistics alone. This study will supplement precipitation enhancement statistics and Weather Research and Forecasting (WRF) model outputs with ultra-trace chemistry. Combining precipitation enhancement estimates with trace chemistry data (to estimate AgI plume targeting accuracy) may provide a more robust analysis. Precipitation enhancement from the 2016 water year will be modeled two ways. First, by using double-mass curve. Annual SNOTEL data of the cumulative SWE in unseeded areas and cumulative SWE in seeded areas will be compared before, and after, the cloud seeding program's initiation in 2003. Any change in the double-mass curve's slope after 2003 may be attributed to cloud seeding. Second, WRF model estimates of precipitation will be compared to the observed precipitation at SNOTEL sites. The difference between observed and modeled precipitation in AgI seeded regions may also be attributed to cloud seeding (assuming modeled and observed data are comparable at unseeded SNOTEL stations). Ultra-trace snow chemistry data from the 2016 winter season will be used to validate whether estimated precipitation increases are positively correlated with the mass of silver in the snowpack.

Clouds Aerosols Internal Affaires: Increasing Cloud Fraction and Enhancing the Convection

NASA Technical Reports Server (NTRS)

Koren, Ilan; Kaufman, Yoram; Remer, Lorraine; Rosenfeld, Danny; Rudich, Yinon

2004-01-01

Clouds developing in a polluted environment have more numerous, smaller cloud droplets that can increase the cloud lifetime and liquid water content. Such changes in the cloud droplet properties may suppress low precipitation allowing development of a stronger convection and higher freezing level. Delaying the washout of the cloud water (and aerosol), and the stronger convection will result in higher clouds with longer life time and larger anvils. We show these effects by using large statistics of the new, 1km resolution data from MODIS on the Terra satellite. We isolate the aerosol effects from meteorology by regression and showing that aerosol microphysical effects increases cloud fraction by average of 30 presents for all cloud types and increases convective cloud top pressure by average of 35mb. We analyze the aerosol cloud interaction separately for high pressure trade wind cloud systems and separately for deep convective cloud systems. The resultant aerosol radiative effect on climate for the high pressure cloud system is: -10 to -13 W/sq m at the top of the atmosphere (TOA) and -11 to -14 W/sq m at the surface. For deeper convective clouds the forcing is: -4 to -5 W/sq m at the TOA and -6 to -7 W/sq m at the surface.

Characterizing relative humidity with respect to ice in midlatitude cirrus clouds as a function of atmospheric state

NASA Astrophysics Data System (ADS)

Dzambo, Andrew M.; Turner, David D.

2016-10-01

Midlatitude cirrus cloud macrophysical and microphysical properties have been shown in previous studies to vary seasonally and in various large-scale dynamical regimes, but relative humidity with respect to ice (RHI) within cirrus clouds has not been studied extensively in this context. Using a combination of radiosonde and millimeter-wavelength cloud radar data, we identify 1076 cirrus clouds spanning a 7 year period from 2004 to 2011. These data are separated into five classes using a previously published algorithm that is based largely on synoptic conditions. Using these data and classification scheme, we find that RHI in cirrus clouds varies seasonally. Variations in cirrus cloud RHI exist within the prescribed classifications; however, most of the variations are within the measurement uncertainty. Additionally, with the exception of nonsummer class cirrus, these variations are not statistically significant. We also find that cirrus cloud occurrence is not necessarily correlated with higher observed values of RHI. The structure of RHI in cirrus clouds varies more in thicker clouds, which follows previous studies showing that macrophysical and microphysical variability increases in thicker cirrus clouds.

Scalable modulation technology and the tradeoff of reach, spectral efficiency, and complexity

NASA Astrophysics Data System (ADS)

Bosco, Gabriella; Pilori, Dario; Poggiolini, Pierluigi; Carena, Andrea; Guiomar, Fernando

2017-01-01

Bandwidth and capacity demand in metro, regional, and long-haul networks is increasing at several tens of percent per year, driven by video streaming, cloud computing, social media and mobile applications. To sustain this traffic growth, an upgrade of the widely deployed 100-Gbit/s long-haul optical systems, based on polarization multiplexed quadrature phase-shift keying (PM-QPSK) modulation format associated with coherent detection and digital signal processing (DSP), is mandatory. In fact, optical transport techniques enabling a per-channel bit rate beyond 100 Gbit/s have recently been the object of intensive R and D activities, aimed at both improving the spectral efficiency and lowering the cost per bit in fiber transmission systems. In this invited contribution, we review the different available options to scale the per-channel bit-rate to 400 Gbit/s and beyond, i.e. symbol-rate increase, use of higher-order quadrature amplitude modulation (QAM) modulation formats and use of super-channels with DSP-enabled spectral shaping and advanced multiplexing technologies. In this analysis, trade-offs of system reach, spectral efficiency and transceiver complexity are addressed. Besides scalability, next generation optical networks will require a high degree of flexibility in the transponders, which should be able to dynamically adapt the transmission rate and bandwidth occupancy to the light path characteristics. In order to increase the flexibility of these transponders (often referred to as "flexponders"), several advanced modulation techniques have recently been proposed, among which sub-carrier multiplexing, hybrid formats (over time, frequency and polarization), and constellation shaping. We review these techniques, highlighting their limits and potential in terms of performance, complexity and flexibility.

More Than Filaments and Cores: Statistical Study of Structure Formation and Dynamics in Nearby Molecular Clouds

NASA Astrophysics Data System (ADS)

Chen, How-Huan; Goodman, Alyssa

2018-01-01

In the past decade, multiple attempts at understanding the connection between filaments and star forming cores have been made using observations across the entire epectrum. However, the filaments and the cores are usually treated as predefined--and well-defined--entities, instead of structures that often come at different sizes, shapes, with substantially different dynamics, and inter-connected at different scales. In my dissertation, I present an array of studies using different statistical methods, including the dendrogram and the probability distribution function (PDF), of structures at different size scales within nearby molecular clouds. These structures are identified using observations of different density tracers, and where possible, in the multi-dimensional parameter space of key dynamic properties--the LSR velocity, the velocity dispersion, and the column density. The goal is to give an overview of structure formation in nearby star-forming clouds, as well as of the dynamics in these structures. I find that the overall statistical properties of a larger structure is often the summation/superposition of sub-structures within, and that there could be significant variations due to local physical processes. I also find that the star formation process within molecular clouds could in fact take place in a non-monolithic manner, connecting potentially merging and/or transient structures, at different scales.

“Using Statistical Comparisons between SPartICus Cirrus Microphysical Measurements, Detailed Cloud Models, and GCM Cloud Parameterizations to Understand Physical Processes Controlling Cirrus Properties and to Improve the Cloud Parameterizations”

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

Woods, Sarah

2015-12-01

The dual objectives of this project were improving our basic understanding of processes that control cirrus microphysical properties and improvement of the representation of these processes in the parameterizations. A major effort in the proposed research was to integrate, calibrate, and better understand the uncertainties in all of these measurements.

Statistical Study of High-Velocity Compact Clouds Based on the Complete CO Imagings of the Central Molecular Zone

NASA Astrophysics Data System (ADS)

Tokuyama, Sekito; Oka, Tomoharu; Takekawa, Shunya; Yamada, Masaya; Iwata, Yuhei; Tsujimoto, Shiho

2017-01-01

High-velocity compact clouds (HVCCs) is one of the populations of peculiar clouds detected in the Central Molecular Zone (CMZ) of our Galaxy. They have compact appearances (< 5 pc) and large velocity widths (> 50 km s-1). Several explanations for the origin of HVCC were proposed; e.g., a series of supernovae (SN) explosions (Oka et al. 1999) or a gravitational kick by a point-like gravitational source (Oka et al. 2016). To investigate the statistical property of HVCCs, a complete list of them is acutely necessary. However, the previous list is not complete since the identification procedure included automated processes and manual selection (Nagai 2008). Here we developed an automated procedure to identify HVCCs in a spectral line data.

Design, Evaluation and GCM-Performance of a New Parameterization for Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRas)

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.

1998-01-01

A prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) was developed with the aim of improving cloud-microphysics, and cloud-radiation interactions in GCMs. McRAS distinguishes convective, stratiform, and boundary-layer clouds. The convective clouds merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds do so instantly. The cloud condensate transforms into precipitation following the auto-conversion relations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, and diffuse both horizontally and vertically with a fully active cloud-microphysics throughout its life-cycle, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III data has shown that McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. An evaluation with the ARM-CART SCM data in a cloud model intercomparison exercise shows reasonable but not an outstanding accurate simulation. Such a discrepancy is common to almost all models and is related, in part, to the input data quality. McRAS was implemented in the GEOS II GCM. A 50 month integration that was initialized with the ECMWF analysis of observations for January 1, 1987 and forced with the observed sea-surface temperatures and sea-ice distribution and vegetation properties (biomes, and soils), with prognostic soil moisture, snow-cover, and hydrology showed a very realistic simulation of cloud process, incloud water and ice, and cloud-radiative forcing (CRF). The simulated ITCZ showed a realistic time-mean structure and seasonal cycle, while the simulated CRF showed sensitivity to vertical distribution of cloud water which can be easily altered by the choice of time constant and incloud critical cloud water amount regulators for auto-conversion. The CRF and its feedbacks also have a profound effect on the ITCZ. Even though somewhat weaker than observed, the McRAS-GCM simulation produces robust 30-60 day oscillations in the 200 hPa velocity potential. Two ensembles of 4-summer (July, August, September) simulations, one each for 1987 and 1988 show that the McRAS-GCM simulates realistic and statistically significant precipitation differences over India, Central America, and tropical Africa. Several seasonal simulations were performed with McRAS-GEOS II GCM for the summer (June-July- August) and winter (December-January-February) periods to determine how the simulated clouds and CRFs would be affected by: i) advection of clouds; ii) cloud top entrainment instability, iii) cloud water inhomogeneity correction, and (iv) cloud production and dissipation in different cloud-processes. The results show that each of these processes contributes to the simulated cloud-fraction and CRF.

Observed Aerosol Influence on Ice Water Content of Arctic Mixed-Phase Clouds

NASA Astrophysics Data System (ADS)

Norgren, M.; de Boer, G.; Shupe, M.

2016-12-01

The response of ice water content (IWC) in Arctic mixed-phase stratocumulus to atmospheric aerosols is observed. IWC retrievals from ground based radars operated by the Atmospheric Radiation Measurement (ARM) program in Barrow, Alaska are used to construct composite profiles of cloud IWC from a 9-year radar record starting in January of 2000. The IWC profiles for high (polluted) and low (clean) aerosol loadings are compared. Generally, we find that clean clouds exhibit statistically significant higher levels of IWC than do polluted clouds by a factor of 2-4 at cloud base. For springtime clouds, with a maximum relative humidity with respect to ice (RHI) above 110% in the cloud layer, the IWC at cloud base was a factor of 3.25 times higher in clean clouds than it was in polluted clouds. We infer that the aerosol loading of the cloud environment alters the liquid drop size distribution within the cloud, with larger drops being more frequent in clean clouds. Larger cloud drops promote riming within the cloud layer, which is one explanation for the higher IWC levels in clean clouds. The drop size distribution may also be a significant control of ice nucleation events within mixed-phase clouds. Whether the high IWC levels in clean clouds are due to increased riming or nucleation events is unclear at this time.

Statistical analysis of multivariate atmospheric variables. [cloud cover

NASA Technical Reports Server (NTRS)

Tubbs, J. D.

1979-01-01

Topics covered include: (1) estimation in discrete multivariate distributions; (2) a procedure to predict cloud cover frequencies in the bivariate case; (3) a program to compute conditional bivariate normal parameters; (4) the transformation of nonnormal multivariate to near-normal; (5) test of fit for the extreme value distribution based upon the generalized minimum chi-square; (6) test of fit for continuous distributions based upon the generalized minimum chi-square; (7) effect of correlated observations on confidence sets based upon chi-square statistics; and (8) generation of random variates from specified distributions.

New Cloud and Precipitation Research Avenues Enabled by low-cost Phased-array Radar Technology

NASA Astrophysics Data System (ADS)

Kollias, P.; Oue, M.; Fridlind, A. M.; Matsui, T.; McLaughlin, D. J.

2017-12-01

For over half a century, radars operating in a wide range of frequencies have been the primary source of observational insights of clouds and precipitation microphysics and dynamics and contributed to numerous significant advancements in the field of cloud and precipitation physics. The development of multi-wavelength and polarization diversity techniques has further strengthened the quality of microphysical and dynamical retrievals from radars and has assisted in overcoming some of the limitations imposed by the physics of scattering. Atmospheric radars have historically employed a mechanically-scanning dish antenna and their ability to point to, survey, and revisit specific points or regions in the atmosphere is limited by mechanical inertia. Electronically scanned, or phased-array, radars capable of high-speed, inertialess beam steering, have been available for several decades, but the cost of this technology has limited its use to military applications. During the last 10 years, lower power and lower-cost versions of electronically scanning radars have been developed, and this presents an attractive and affordable new tool for the atmospheric sciences. The operational and research communities are currently exploring phased array advantages in signal processing (i.e. beam multiplexing, improved clutter rejection, cross beam wind estimation, adaptive sensing) and science applications (i.e. tornadic storm morphology studies). Here, we will present some areas of atmospheric research where inertia-less radars with ability to provide rapid volume imaging offers the potential to advance cloud and precipitation research. We will discuss the added value of single phased-array radars as well as networks of these radars for several problems including: multi-Doppler wind retrieval techniques, cloud lifetime studies and aerosol-convection interactions. The performance of current (dish) and future (e-scan) radar systems for these atmospheric studies will be evaluated using numerical model output and a sophisticated radar simulator package.

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

NASA Astrophysics Data System (ADS)

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.

Application of cloud database in the management of clinical data of patients with skin diseases.

PubMed

Mao, Xiao-fei; Liu, Rui; DU, Wei; Fan, Xue; Chen, Dian; Zuo, Ya-gang; Sun, Qiu-ning

2015-04-01

To evaluate the needs and applications of using cloud database in the daily practice of dermatology department. The cloud database was established for systemic scleroderma and localized scleroderma. Paper forms were used to record the original data including personal information, pictures, specimens, blood biochemical indicators, skin lesions,and scores of self-rating scales. The results were input into the cloud database. The applications of the cloud database in the dermatology department were summarized and analyzed. The personal and clinical information of 215 systemic scleroderma patients and 522 localized scleroderma patients were included and analyzed using the cloud database. The disease status,quality of life, and prognosis were obtained by statistical calculations. The cloud database can efficiently and rapidly store and manage the data of patients with skin diseases. As a simple, prompt, safe, and convenient tool, it can be used in patients information management, clinical decision-making, and scientific research.

Microsecond-scale electric field pulses in cloud lightning discharges

NASA Technical Reports Server (NTRS)

Villanueva, Y.; Rakov, V. A.; Uman, M. A.; Brook, M.

1994-01-01

From wideband electric field records acquired using a 12-bit digitizing system with a 500-ns sampling interval, microsecond-scale pulses in different stages of cloud flashes in Florida and New Mexico are analyzed. Pulse occurrence statistics and waveshape characteristics are presented. The larger pulses tend to occur early in the flash, confirming the results of Bils et al. (1988) and in contrast with the three-stage representation of cloud-discharge electric fields suggested by Kitagawa and Brook (1960). Possible explanations for the discrepancy are discussed. The tendency for the larger pulses to occur early in the cloud flash suggests that they are related to the initial in-cloud channel formation processes and contradicts the common view found in the atmospheric radio-noise literature that the main sources of VLF/LF electromagnetic radiation in cloud flashes are the K processes which occur in the final, or J type, part of the cloud discharge.

Aerosol climatology using a tunable spectral variability cloud screening of AERONET data

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Gobbi, Gian Paolo; Koren, Ilan

2005-01-01

Can cloud screening of an aerosol data set, affect the aerosol optical thickness (AOT) climatology? Aerosols, humidity and clouds are correlated. Therefore, rigorous cloud screening can systematically bias towards less cloudy conditions, underestimating the average AOT. Here, using AERONET data we show that systematic rejection of variable atmospheric optical conditions can generate such bias in the average AOT. Therefore we recommend (1) to introduce more powerful spectral variability cloud screening and (2) to change the philosophy behind present aerosol climatologies: Instead of systematically rejecting all cloud contaminations, we suggest to intentionally allow the presence of cloud contamination, estimate the statistical impact of the contamination and correct for it. The analysis, applied to 10 AERONET stations with approx. 4 years of data, shows almost no change for Rome (Italy), but up to a change in AOT of 0.12 in Beijing (PRC). Similar technique may be explored for satellite analysis, e.g. MODIS.

Structures observed on the spot radiance fields during the FIRE experiment

NASA Technical Reports Server (NTRS)

Seze, Genevieve; Smith, Leonard; Desbois, Michel

1990-01-01

Three Spot images taken during the FIRE experiment on stratocumulus are analyzed. From this high resolution data detailed observations of the true cloud radiance field may be made. The structure and inhomogeneity of these radiance fields hold important implications for the radiation budget, while the fine scale structure in radiance field provides information on cloud dynamics. Wieliki and Welsh, and Parker et al., have quantified the inhomogeneities of the cumulus clouds through a careful examination of the distribution of cloud (and hole) size as functions of an effective cloud diameter and radiance threshold. Cahalan (1988) has compared for different cloud types of (stratocumulus, fair weather cumulus, convective clouds in the ITCZ) the distributions of clouds (and holes) sizes, the relation between the size and the perimeter of these clouds (and holes), and examining the possibility of scale invariance. These results are extended from LANDSAT resolution (57 m and 30 m) to the Spot resolution (10 m) resolution in the case of boundary layer clouds. Particular emphasis is placed on the statistics of zones of high and low reflectivity as a function of a threshold reflectivity.

75 FR 80042 - Information Privacy and Innovation in the Internet Economy

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-21

... statistics that provide evidence of concern--or comments explaining why concerns are unwarranted--about cloud computing data privacy and security in the commercial context. We also seek data that links any such concerns to decisions to adopt, or refrain from adopting, cloud computing services. (41) The Task Force...

An Extension of the Split Window Technique for the Retrieval of Precipitable Water: Experimental Verification

DTIC Science & Technology

1988-09-23

DOWNGRADING SCHEDULE D~istribution Unlimited 4. PERFORMING ORGANIZATiON REPORT NUMVBER(S) 5. MONITORiG ORGANIZATION REPORT NUMBER(S) AFGL-TR-88-0237...Collocations were performed on launch sites of the cloud contamination, aerosol problems, collocation 1200 UT radiosondes on 25 Aug 1987. Statistics were...al (1987) and Thomason, 1987). In this imagery opaque clouds to this problem appear white, low clouds and fog appear bright red against a brown

Linkage analysis of chromosome 22q12-13 in a United Kingdom/Icelandic sample of 23 multiplex schizophrenia families

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

Kalsi, G.; Read, T.; Butler, R.

A possible linkage to a genetic subtype of schizophrenia and related disorders has been reported on the long arm of chromosome 22 at q12-13. However formal statistical tests in a combined sample could not reject homogeneity and prove that there was linked subgroup of families. We have studied 23 schizophrenia pedigrees to test whether some multiplex schizophrenia families may be linked to the microsatellite markers D22S274 and D22S283 which span the 22q12-13 region. Two point followed by multipoint lod and non-parametric linkage analyses under the assumption of heterogeneity provided no evidence for linkage over the relevant region. 16 refs., 4more » tabs.« less

Self-Similar Spin Images for Point Cloud Matching

NASA Astrophysics Data System (ADS)

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 based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.

Cloud Statistics for NASA Climate Change Studies

NASA Technical Reports Server (NTRS)

Wylie, Donald P.

1999-01-01

The Principal Investigator participated in two field experiments and developed a global data set on cirrus cloud frequency and optical depth to aid the development of numerical models of climate. Four papers were published under this grant. The accomplishments are summarized: (1) In SUCCESS (SUbsonic aircraft: Contrail & Cloud Effects Special Study) the Principal Investigator aided weather forecasters in the start of the field program. A paper also was published on the clouds studied in SUCCESS and the use of the satellite stereographic technique to distinguish cloud forms and heights of clouds. (2) In SHEBA (Surface Heat Budget in the Arctic) FIRE/ACE (Arctic Cloud Experiment) the Principal Investigator provided daily weather and cloud forecasts for four research aircraft crews, NASA's ER-2, UCAR's C-130, University of Washington's Convert 580, and the Canadian Atmospheric Environment Service's Convert 580. Approximately 105 forecasts were written. The Principal Investigator also made daily weather summaries with calculations of air trajectories for 54 flight days in the experiment. The trajectories show where the air sampled during the flights came from and will be used in future publications to discuss the origin and history of the air and clouds sampled by the aircraft. A paper discussing how well the FIRE/ACE data represent normal climatic conditions in the arctic is being prepared. (3) The Principal Investigator's web page became the source of information for weather forecasting by the scientists on the SHEBA ship. (4) Global Cirrus frequency and optical depth is a continuing analysis of global cloud cover and frequency distribution are being made from the NOAA polar orbiting weather satellites. This analysis is sensitive to cirrus clouds because of the radiative channels used. During this grant three papers were published which describe cloud frequencies, their optical properties and compare the Wisconsin FM Cloud Analysis to other global cloud data such as the International Satellite Cloud Climatology Program (ISCCP) and the Stratospheric Aerosol and Gas Experiment (SAGE). A summary of eight years of HIRS data will be published in late 1998. Important information from this study are: 1) cirrus clouds cover most of the earth, 2) they are found about 40% of the time globally, 3) in the tropics cirrus cloud frequencies are even higher, from 80-100%, 4) there is slight evidence that cirnis cloud cover is increasing in the northern hemisphere at about 0.5% per year, and 5) cirrus clouds have an average infrared transmittance of about 40% of the terrestrial radiation. (5) Global Cloud Frequency Statistics published on the Principal Investigator's web page have been used in the planning of the future CRYSTAL experiment and have been used for refinements of a global numerical model operated at the Colorado State University.

First X-ray Statistical Tests for Clumpy Torii Models: Constraints from RXTE monitoring of Seyfert AGN

NASA Astrophysics Data System (ADS)

Markowitz, A.

2015-09-01

We summarize two papers providing the first X-ray-derived statistical constraints for both clumpy-torus model parameters and cloud ensemble properties. In Markowitz, Krumpe, & Nikutta (2014), we explored multi-timescale variability in line-of-sight X-ray absorbing gas as a function of optical classification. We examined 55 Seyferts monitored with the Rossi X-ray Timing Explorer, and found in 8 objects a total of 12 eclipses, with durations between hours and years. Most clouds are commensurate with the outer portions of the BLR, or the inner regions of infrared-emitting dusty tori. The detection of eclipses in type Is disfavors sharp-edged tori. We provide probabilities to observe a source undergoing an absorption event for both type Is and IIs, yielding constraints in [N_0, sigma, i] parameter space. In Nikutta et al., in prep., we infer that the small cloud angular sizes, as seen from the SMBH, imply the presence of >10^7 clouds in BLR+torus to explain observed covering factors. Cloud size is roughly proportional to distance from the SMBH, hinting at the formation processes (e.g. disk fragmentation). All observed clouds are sub-critical with respect to tidal disruption; self-gravity alone cannot contain them. External forces (e.g. magnetic fields, ambient pressure) are needed to contain them, or otherwise the clouds must be short-lived. Finally, we infer that the radial cloud density distribution behaves as 1/r^{0.7}, compatible with VLTI observations. Our results span both dusty and non-dusty clumpy media, and probe model parameter space complementary to that for short-term eclipses observed with XMM-Newton, Suzaku, and Chandra.

Statistics Analysis of the Uncertainties in Cloud Optical Depth Retrievals Caused by Three-Dimensional Radiative Effects

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander

2000-01-01

This paper presents a simple approach to estimate the uncertainties that arise in satellite retrievals of cloud optical depth when the retrievals use one-dimensional radiative transfer theory for heterogeneous clouds that have variations in all three dimensions. For the first time, preliminary error bounds are set to estimate the uncertainty of cloud optical depth retrievals. These estimates can help us better understand the nature of uncertainties that three-dimensional effects can introduce into retrievals of this important product of the MODIS instrument. The probability distribution of resulting retrieval errors is examined through theoretical simulations of shortwave cloud reflection for a wide variety of cloud fields. The results are used to illustrate how retrieval uncertainties change with observable and known parameters, such as solar elevation or cloud brightness. Furthermore, the results indicate that a tendency observed in an earlier study, clouds appearing thicker for oblique sun, is indeed caused by three-dimensional radiative effects.

Use of MODIS Cloud Top Pressure to Improve Assimilation Yields of AIRS Radiances in GSI

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Srikishen, Jayanthi

2014-01-01

Radiances from hyperspectral sounders such as the Atmospheric Infrared Sounder (AIRS) are routinely assimilated both globally and regionally in operational numerical weather prediction (NWP) systems using the Gridpoint Statistical Interpolation (GSI) data assimilation system. However, only thinned, cloud-free radiances from a 281-channel subset are used, so the overall percentage of these observations that are assimilated is somewhere on the order of 5%. Cloud checks are performed within GSI to determine which channels peak above cloud top; inaccuracies may lead to less assimilated radiances or introduction of biases from cloud-contaminated radiances.Relatively large footprint from AIRS may not optimally represent small-scale cloud features that might be better resolved by higher-resolution imagers like the Moderate Resolution Imaging Spectroradiometer (MODIS). Objective of this project is to "swap" the MODIS-derived cloud top pressure (CTP) for that designated by the AIRS-only quality control within GSI to test the hypothesis that better representation of cloud features will result in higher assimilated radiance yields and improved forecasts.

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Neural network cloud top pressure and height for MODIS

NASA Astrophysics Data System (ADS)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found to give the most useful information of the spread of the errors. For all descriptive statistics presented MAE, IQR, RMSE (root mean square error), SD, mode, median, bias and percentage of absolute errors above 0.25, 0.5, 1 and 2 km the neural network perform better than the reference algorithms both validated with CALIOP and CPR (CloudSat). The neural networks using the brightness temperatures at 11 and 12 µm show at least 32 % (or 623 m) lower MAE compared to the two operational reference algorithms when validating with CALIOP height. Validation with CPR (CloudSat) height gives at least 25 % (or 430 m) reduction of MAE.

Satellite-Based Assessment of Possible Dust Aerosols Semi-Direct Effect on Cloud Water Path over East Asia

NASA Technical Reports Server (NTRS)

Huang, Jianping; Lin, Bing; Minnis, Patrick; Wang, Tainhe; Wang, Xin; Hu, Yongxiang; Yi, Yuhong; Ayers, J. Kirk

2006-01-01

The semi-direct effects of dust aerosols are analyzed over eastern Asia using 2 years (June 2002 to June 2004) of data from the Clouds and the Earth s Radiant Energy System (CERES) scanning radiometer and MODerate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, and 18 years (1984 to 2001) of International Satellite Cloud Climatology Project (ISCCP) data. The results show that the water path of dust-contaminated clouds is considerably smaller than that of dust-free clouds. The mean ice water path (IWP) and liquid water path (LWP) of dusty clouds are less than their dust-free counterparts by 23.7% and 49.8%, respectively. The long-term statistical relationship derived from ISCCP also confirms that there is significant negative correlation between dust storm index and ISCCP cloud water path. These results suggest that dust aerosols warm clouds, increase the evaporation of cloud droplets and further reduce cloud water path, the so-called semi-direct effect. The semi-direct effect may play a role in cloud development over arid and semi-arid areas of East Asia and contribute to the reduction of precipitation.

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.

2005-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven

2005-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-02-16

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m −2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m −2.« less

Seasonal and Interannual Variations of Top-of-Atmosphere Irradiance and Cloud Cover over Polar Regions Derived from the CERES Data Set

NASA Technical Reports Server (NTRS)

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

2006-01-01

The semi-direct effects of dust aerosols are analyzed over eastern Asia using 2 years (June 2002 to June 2004) of data from the Clouds and the Earth s Radiant Energy System (CERES) scanning radiometer and MODerate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, and 18 years (1984 to 2001) of International Satellite Cloud Climatology Project (ISCCP) data. The results show that the water path of dust-contaminated clouds is considerably smaller than that of dust-free clouds. The mean ice water path (IWP) and liquid water path (LWP) of dusty clouds are less than their dust-free counterparts by 23.7% and 49.8%, respectively. The long-term statistical relationship derived from ISCCP also confirms that there is significant negative correlation between dust storm index and ISCCP cloud water path. These results suggest that dust aerosols warm clouds, increase the evaporation of cloud droplets and further reduce cloud water path, the so-called semi-direct effect. The semi-direct effect may play a role in cloud development over arid and semi-arid areas of East Asia and contribute to the reduction of precipitation.

Evaluation of cloud detection instruments and performance of laminar-flow leading-edge test articles during NASA Leading-Edge Flight-Test Program

NASA Technical Reports Server (NTRS)

Davis, Richard E.; Maddalon, Dal V.; Wagner, Richard D.; Fisher, David F.; Young, Ronald

1989-01-01

Summary evaluations of the performance of laminar-flow control (LFC) leading edge test articles on a NASA JetStar aircraft are presented. Statistics, presented for the test articles' performance in haze and cloud situations, as well as in clear air, show a significant effect of cloud particle concentrations on the extent of laminar flow. The cloud particle environment was monitored by two instruments, a cloud particle spectrometer (Knollenberg probe) and a charging patch. Both instruments are evaluated as diagnostic aids for avoiding laminar-flow detrimental particle concentrations in future LFC aircraft operations. The data base covers 19 flights in the simulated airline service phase of the NASA Leading-Edge Flight-Test (LEFT) Program.

Methods for Discerning Cloud Reflectivity Changes due to the Indirect Effect of Aerosol: A Pilot-study for Triana

NASA Technical Reports Server (NTRS)

Kinne, S.; Wiscombe, Warren; Einaudi, Franco (Technical Monitor)

2001-01-01

Understanding the effect of aerosol on cloud systems is one of the major challenges in atmospheric and climate research. Local studies suggest a multitude of influences on cloud properties. Yet the overall effect on cloud albedo, a critical parameter in climate simulations, remains uncertain. NASA's Triana mission will provide, from its EPIC multi-spectral imager, simultaneous data on aerosol properties and cloud reflectivity. With Triana's unique position in space these data will be available not only globally but also over the entire daytime, well suited to accommodate the often short lifetimes of aerosol and investigations around diurnal cycles. This pilot study explores the ability to detect relationships between aerosol properties and cloud reflectivity with sophisticated statistical methods. Sample results using data from the EOS Terra platform to simulate Triana are presented.

Assessment of dust aerosol effect on cloud properties over Northwest China using CERES SSF data

NASA Astrophysics Data System (ADS)

Huang, J.; Wang, X.; Wang, T.; Su, J.; Minnis, P.; Lin, B.; Hu, Y.; Yi, Y.

Dust aerosols not only have direct effects on the climate through reflection and absorption of the short and long wave radiation but also modify cloud properties such as the number concentration and size of cloud droplets indirect effect and contribute to diabatic heating in the atmosphere that often enhances cloud evaporation and reduces the cloud water path In this study indirect and semi-direct effects of dust aerosols are analyzed over eastern Asia using two years June 2002 to June 2004 of CERES Clouds and the Earth s Radiant Energy Budget Scanner and MODIS MODerate Resolution Imaging Spectroradiometer Aqua Edition 1B SSF Single Scanner Footprint data sets The statistical analysis shows evidence for both indirect and semi-direct effect of Asia dust aerosols The dust appears to reduce the ice cloud effective particle diameter and increase high cloud amount On average ice cloud effective particle diameters of cirrus clouds under dust polluted conditions dusty cloud are 11 smaller than those derived from ice clouds in dust-free atmospheric environments The water paths of dusty clouds are also considerably smaller than those of dust-free clouds Dust aerosols could warm clouds thereby increasing the evaporation of cloud droplets resulting in reduced cloud water path semi-direct effect The semi-direct effect may be dominated the interaction between dust aerosols and clouds over arid and semi-arid areas and partly contribute to reduced precipitation

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

NASA Astrophysics Data System (ADS)

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.

Parameterization of GCM subgrid nonprecipitating cumulus and stratocumulus clouds using stochastic/phenomenological methods. Annual technical progress report, 1 December 1992--30 November 1993

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

Stull, R.B.

1993-08-27

This document is a progress report to the USDOE Atmospheric Radiation and Measurement Program (ARM). The overall project goal is to relate subgrid-cumulus-cloud formation, coverage, and population characteristics to statistical properties of surface-layer air, which in turn are modulated by heterogeneous land-usage within GCM-grid-box-size regions. The motivation is to improve the understanding and prediction of climate change by more accurately describing radiative and cloud processes.

Supernova Driving. IV. The Star-formation Rate of Molecular Clouds

NASA Astrophysics Data System (ADS)

Padoan, Paolo; Haugbølle, Troels; Nordlund, Åke; Frimann, Søren

2017-05-01

We compute the star-formation rate (SFR) in molecular clouds (MCs) that originate ab initio in a new, higher-resolution simulation of supernova-driven turbulence. Because of the large number of well-resolved clouds with self-consistent boundary and initial conditions, we obtain a large range of cloud physical parameters with realistic statistical distributions, which is an unprecedented sample of star-forming regions to test SFR models and to interpret observational surveys. We confirm the dependence of the SFR per free-fall time, SFRff, on the virial parameter, α vir, found in previous simulations, and compare a revised version of our turbulent fragmentation model with the numerical results. The dependences on Mach number, { M }, gas to magnetic pressure ratio, β, and compressive to solenoidal power ratio, χ at fixed α vir are not well constrained, because of random scatter due to time and cloud-to-cloud variations in SFRff. We find that SFRff in MCs can take any value in the range of 0 ≤ SFRff ≲ 0.2, and its probability distribution peaks at a value of SFRff ≈ 0.025, consistent with observations. The values of SFRff and the scatter in the SFRff-α vir relation are consistent with recent measurements in nearby MCs and in clouds near the Galactic center. Although not explicitly modeled by the theory, the scatter is consistent with the physical assumptions of our revised model and may also result in part from a lack of statistical equilibrium of the turbulence, due to the transient nature of MCs.

Cloud cover estimation: Use of GOES imagery in development of cloud cover data base for insolation assessment

NASA Technical Reports Server (NTRS)

Huning, J. R.; Logan, T. L.; Smith, J. H.

1982-01-01

The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics.

Cloud Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)

2001-01-01

Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

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

NASA Astrophysics Data System (ADS)

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.

Why do Tornados and Hail Storms Rest on Weekends?

NASA Technical Reports Server (NTRS)

Rosenfeld, Daniel; Bell, Thomas L.

2010-01-01

When anthropogenic aerosols over the eastern USA during summertime are at their weekly mid-week peak, tornado and hail storm activity there is also near its weekly maximum. The weekly cycle in storm activity is statistically significant and unlikely to be due to natural variability. The pattern of variability supports the hypothesis that air pollution aerosols invigorate deep convective clouds in a moist, unstable atmosphere, to the extent of inducing production of large hailstones and tornados. This is caused by the effect of aerosols on cloud-drop nucleation, making cloud drops smaller, delaying precipitation-forming processes and their evaporation, and hence affecting cloud dynamics.

Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach

NASA Astrophysics Data System (ADS)

Schulz, Hans Martin; Thies, Boris; Chang, Shih-Chieh; Bendix, Jörg

2016-03-01

The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ≈ 40, classification errors significantly increase.

Statistical Study of Aircraft Icing Probabilities at the 700- and 500- Millibar Levels over Ocean Areas in the Northern Hemisphere

NASA Technical Reports Server (NTRS)

Perkins, Porter J.; Lewis, William; Mulholland, Donald R.

1957-01-01

A statistical study is made of icing data reported from weather reconnaissance aircraft flown by Air Weather Service (USAF). The weather missions studied were flown at fixed flight levels of 500 millibars (18,000 ft) and 700 millibars (10,000 ft) over wide areas of the Pacific, Atlantic, and Arctic Oceans. This report is presented as part of a program conducted by the NACA to obtain extensive icing statistics relevant to aircraft design and operation. The thousands of in-flight observations recorded over a 2- to 4-year period provide reliable statistics on icing encounters for the specific areas, altitudes, and seasons included in the data. The relative frequencies of icing occurrence are presented, together with the estimated icing probabilities and the relation of these probabilities to the frequencies of flight in clouds and cloud temperatures. The results show that aircraft operators can expect icing probabilities to vary widely throughout the year from near zero in the cold Arctic areas in winter up to 7 percent in areas where greater cloudiness and warmer temperatures prevail. The data also reveal a general tendency of colder cloud temperatures to reduce the probability of icing in equally cloudy conditions.

Timing the state of light with anomalous dispersion and a gradient echo memory

NASA Astrophysics Data System (ADS)

Clark, Jeremy B.

We study the effects of anomalous dispersion on the continuous-variable entanglement of EPR states (generated using four-wave mixing in 85 Rb) by sending one part of the state through a fast-light medium and measuring the state's quantum mutual information. We observe an advance in the maximum of the quantum mutual information between modes. In contrast, due to uncorrelated noise added by a small phase-insensitive gain, we do not observe any statistically significant advance in the leading edge of the mutual information. We also study the storage and retrieval of multiplexed optical signals in a Gradient Echo Memory (GEM) at relevant four-wave mixing frequencies in 85Rb. Temporal multiplexing capabilities are demonstrated by storing multiple classical images in the memory simultaneously and observing the expected first-in last-out order of recall without obvious cross-talk. We also develop a technique wherein selected portions of an image written into the memory can be spatially targeted for readout and erasure on demand. The effect of diffusion on the quality of the recalled images is characterized. Our results indicate that Raman-based atomic memories may serve as a flexible platform for the storage and retrieval of multiplexed optical signals.

Quantifying the propagation of distress and mental disorders in social networks.

PubMed

Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro

2018-03-22

Heterogeneity of human beings leads to think and react differently to social phenomena. Awareness and homophily drive people to weigh interactions in social multiplex networks, influencing a potential contagion effect. To quantify the impact of heterogeneity on spreading dynamics, we propose a model of coevolution of social contagion and awareness, through the introduction of statistical estimators, in a weighted multiplex network. Multiplexity of networked individuals may trigger propagation enough to produce effects among vulnerable subjects experiencing distress, mental disorder, which represent some of the strongest predictors of suicidal behaviours. The exposure to suicide is emotionally harmful, since talking about it may give support or inadvertently promote it. To disclose the complex effect of the overlapping awareness on suicidal ideation spreading among disordered people, we also introduce a data-driven approach by integrating different types of data. Our modelling approach unveils the relationship between distress and mental disorders propagation and suicidal ideation spreading, shedding light on the role of awareness in a social network for suicide prevention. The proposed model is able to quantify the impact of overlapping awareness on suicidal ideation spreading and our findings demonstrate that it plays a dual role on contagion, either reinforcing or delaying the contagion outbreak.

The local environment of ice particles in arctic mixed-phase clouds

NASA Astrophysics Data System (ADS)

Schlenczek, Oliver; Fugal, Jacob P.; Schledewitz, Waldemar; Borrmann, Stephan

2015-04-01

During the RACEPAC field campaign in April and May 2014, research flights were made with the Polar 5 and Polar 6 aircraft from the Alfred Wegener Institute in Arctic clouds near Inuvik, Northwest Territories, Canada. One flight with the Polar 6 aircraft, done on May 16, 2014, flew under precipitating, stratiform, mid-level clouds with several penetrations through cloud base. Measurements with HALOHolo, an airborne digital in-line holographic instrument for cloud particles, show ice particles in a field of other cloud particles in a local three-dimensional sample volume (~14x19x130 mm3 or ~35 cm^3). Each holographic sample volume is a snapshot of a 3-dimensional piece of cloud at the cm-scale with typically thousands of cloud droplets per sample volume, so each sample volume yields a statistically significant droplet size distribution. Holograms are recorded at a rate of six times per second, which provides one volume sample approx. every 12 meters along the flight path. The size resolution limit for cloud droplets is better than 1 µm due to advanced sizing algorithms. Shown are preliminary results of, (1) the ice/liquid water partitioning at the cloud base and the distribution of water droplets around each ice particle, and (2) spatial and temporal variability of the cloud droplet size distributions at cloud base.

Relating Solar Resource Variability to Cloud Type

NASA Astrophysics Data System (ADS)

Hinkelman, L. M.; Sengupta, M.

2012-12-01

Power production from renewable energy (RE) resources is rapidly increasing. Generation of renewable energy is quite variable since the solar and wind resources that form the inputs are, themselves, inherently variable. There is thus a need to understand the impact of renewable generation on the transmission grid. Such studies require estimates of high temporal and spatial resolution power output under various scenarios, which can be created from corresponding solar resource data. Satellite-based solar resource estimates are the best source of long-term solar irradiance data for the typically large areas covered by transmission studies. As satellite-based resource datasets are generally available at lower temporal and spatial resolution than required, there is, in turn, a need to downscale these resource data. Downscaling in both space and time requires information about solar irradiance variability, which is primarily a function of cloud types and properties. In this study, we analyze the relationship between solar resource variability and satellite-based cloud properties. One-minute resolution surface irradiance data were obtained from a number of stations operated by the National Oceanic and Atmospheric Administration (NOAA) under the Surface Radiation (SURFRAD) and Integrated Surface Irradiance Study (ISIS) networks as well as from NREL's Solar Radiation Research Laboratory (SRRL) in Golden, Colorado. Individual sites were selected so that a range of meteorological conditions would be represented. Cloud information at a nominal 4 km resolution and half hour intervals was derived from NOAA's Geostationary Operation Environmental Satellite (GOES) series of satellites. Cloud class information from the GOES data set was then used to select and composite irradiance data from the measurement sites. The irradiance variability for each cloud classification was characterized using general statistics of the fluxes themselves and their variability in time, as represented by ramps computed for time scales from 10 s to 0.5 hr. The statistical relationships derived using this method will be presented, comparing and contrasting the statistics computed for the different cloud types. The implications for downscaling irradiances from satellites or forecast models will also be discussed.

PRECISE:PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare

PubMed Central

Chen, Feng; Wang, Shuang; Mohammed, Noman; Cheng, Samuel; Jiang, Xiaoqian

2015-01-01

Quality improvement (QI) requires systematic and continuous efforts to enhance healthcare services. A healthcare provider might wish to compare local statistics with those from other institutions in order to identify problems and develop intervention to improve the quality of care. However, the sharing of institution information may be deterred by institutional privacy as publicizing such statistics could lead to embarrassment and even financial damage. In this article, we propose a PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare (PRECISE), which aims at enabling cross-institution comparison of healthcare statistics while protecting privacy. The proposed framework relies on a set of state-of-the-art cryptographic protocols including homomorphic encryption and Yao’s garbled circuit schemes. By securely pooling data from different institutions, PRECISE can rank the encrypted statistics to facilitate QI among participating institutes. We conducted experiments using MIMIC II database and demonstrated the feasibility of the proposed PRECISE framework. PMID:26146645

PRECISE:PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare.

PubMed

Chen, Feng; Wang, Shuang; Mohammed, Noman; Cheng, Samuel; Jiang, Xiaoqian

2014-10-01

Quality improvement (QI) requires systematic and continuous efforts to enhance healthcare services. A healthcare provider might wish to compare local statistics with those from other institutions in order to identify problems and develop intervention to improve the quality of care. However, the sharing of institution information may be deterred by institutional privacy as publicizing such statistics could lead to embarrassment and even financial damage. In this article, we propose a PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare (PRECISE), which aims at enabling cross-institution comparison of healthcare statistics while protecting privacy. The proposed framework relies on a set of state-of-the-art cryptographic protocols including homomorphic encryption and Yao's garbled circuit schemes. By securely pooling data from different institutions, PRECISE can rank the encrypted statistics to facilitate QI among participating institutes. We conducted experiments using MIMIC II database and demonstrated the feasibility of the proposed PRECISE framework.

Cloud cover models derived from satellite radiation measurements

NASA Technical Reports Server (NTRS)

Bean, S. J.; Somerville, P. N.

1979-01-01

Using daily measurement of day and night infrared and incoming and absorbed solar radiation obtained from a TIROS satellite over a period of approximately 45 months, and integrated over 2.5 degree latitude-longitude grids, the proportion of cloud cover over each grid each day was derived for the entire period. For each of four three-month periods, estimates a and b of the two parameters of the best-fit beta distribution were obtained for each grid location. The (a,b) plane was divided into a number of regions. All the geographical locations whose (a,b) estimates were in the same region in the (a,b) plane were said to have the same cloud cover type for that season. For each season, the world was thus divided into separate cloud cover types. Using estimates of mean cloud cover for each season, the world was again divided into separate cloud cover types. The process was repeated for standard deviations. Thus for each season, three separate cloud cover models were obtained using the criteria of shape of frequency distribution, mean cloud cover, and variability of cloud cover. The cloud cover statistics were derived from once-a-day, near-local-noon satellite radiation measurements.

[Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

PubMed

Qu, Wei-ping; Liu, Wen-qing; Liu, Jian-guo; Lu, Yi-huai; Zhu, Jun; Qin, Min; Liu, Cheng

2006-11-01

In satellite remote-sensing detection, cloud as an interference plays a negative role in data retrieval. How to discern the cloud fields with high fidelity thus comes as a need to the following research. A new method rooting in atmospheric radiation characteristics of cloud layer, in the present paper, presents a sort of solution where single-band brightness variance ratio is used to detect the relative intensity of cloud clutter so as to delineate cloud field rapidly and exactly, and the formulae of brightness variance ratio of satellite image, image reflectance variance ratio, and brightness temperature variance ratio of thermal infrared image are also given to enable cloud elimination to produce data free from cloud interference. According to the variance of the penetrating capability for different spectra bands, an objective evaluation is done on cloud penetration of them with the factors that influence penetration effect. Finally, a multi-band data fusion task is completed using the image data of infrared penetration from cirrus nothus. Image data reconstruction is of good quality and exactitude to show the real data of visible band covered by cloud fields. Statistics indicates the consistency of waveband relativity with image data after the data fusion.

Global CALIPSO Observations of Aerosol Changes Near Clouds

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander

2011-01-01

Several recent studies have found that clouds are surrounded by a transition zone of rapidly changing aerosol optical properties and particle size. Characterizing this transition zone is important for better understanding aerosol-cloud interactions and aerosol radiative effects, and also for improving satellite retrievals of aerosol properties. This letter presents a statistical analysis of a monthlong global data set of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observations over oceans. The results show that the transition zone is ubiquitous over all oceans and extends up to 15 km away from clouds. They also show that near-cloud enhancements in backscatter and particle size are strongest at low altitudes, slightly below the top of the nearest clouds. Also, the enhancements are similar near illuminated and shadowy cloud sides, which confirms that the asymmetry of Moderate Resolution Imaging Spectroradiometer reflectances found in an earlier study comes from 3-D radiative processes and not from differences in aerosol properties. Finally, the effects of CALIPSO aerosol detection and cloud identification uncertainties are discussed. The findings underline the importance of accounting for the transition zone to avoid potential biases in studies of satellite aerosol products, aerosol-cloud interactions, and aerosol direct radiative effects.

Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

NASA Technical Reports Server (NTRS)

Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.

2009-01-01

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases

Video traffic characteristics of modern encoding standards: H.264/AVC with SVC and MVC extensions and H.265/HEVC.

PubMed

Seeling, Patrick; Reisslein, Martin

2014-01-01

Video encoding for multimedia services over communication networks has significantly advanced in recent years with the development of the highly efficient and flexible H.264/AVC video coding standard and its SVC extension. The emerging H.265/HEVC video coding standard as well as 3D video coding further advance video coding for multimedia communications. This paper first gives an overview of these new video coding standards and then examines their implications for multimedia communications by studying the traffic characteristics of long videos encoded with the new coding standards. We review video coding advances from MPEG-2 and MPEG-4 Part 2 to H.264/AVC and its SVC and MVC extensions as well as H.265/HEVC. For single-layer (nonscalable) video, we compare H.265/HEVC and H.264/AVC in terms of video traffic and statistical multiplexing characteristics. Our study is the first to examine the H.265/HEVC traffic variability for long videos. We also illustrate the video traffic characteristics and statistical multiplexing of scalable video encoded with the SVC extension of H.264/AVC as well as 3D video encoded with the MVC extension of H.264/AVC.

Video Traffic Characteristics of Modern Encoding Standards: H.264/AVC with SVC and MVC Extensions and H.265/HEVC

PubMed Central

2014-01-01

Video encoding for multimedia services over communication networks has significantly advanced in recent years with the development of the highly efficient and flexible H.264/AVC video coding standard and its SVC extension. The emerging H.265/HEVC video coding standard as well as 3D video coding further advance video coding for multimedia communications. This paper first gives an overview of these new video coding standards and then examines their implications for multimedia communications by studying the traffic characteristics of long videos encoded with the new coding standards. We review video coding advances from MPEG-2 and MPEG-4 Part 2 to H.264/AVC and its SVC and MVC extensions as well as H.265/HEVC. For single-layer (nonscalable) video, we compare H.265/HEVC and H.264/AVC in terms of video traffic and statistical multiplexing characteristics. Our study is the first to examine the H.265/HEVC traffic variability for long videos. We also illustrate the video traffic characteristics and statistical multiplexing of scalable video encoded with the SVC extension of H.264/AVC as well as 3D video encoded with the MVC extension of H.264/AVC. PMID:24701145

Observations of aerosol-induced convective invigoration in the tropical east Atlantic

NASA Astrophysics Data System (ADS)

Storer, R. L.; van den Heever, S. C.; L'Ecuyer, T. S.

2014-04-01

Four years of CloudSat data have been analyzed over a region of the east Atlantic Ocean in order to examine the influence of aerosols on deep convection. The satellite data were combined with information about aerosols taken from the Global and Regional Earth-System Monitoring Using Satellite and In Situ Data model. Only those profiles fitting the definition of deep convective clouds were analyzed. Overall, the cloud center of gravity, cloud top, and rain top were all found to increase with increased aerosol loading. These effects were largely independent of the environment, and the differences between the cleanest and most polluted clouds sampled were found to be statistically significant. When examining an even smaller subset of deep convective clouds likely to be part of the convective core, similar trends were seen. These observations suggest that convective invigoration occurs with increased aerosol loading, leading to deeper, stronger storms in polluted environments.

Midlatitude Cloud Shifts, Their Primary Link to the Hadley Cell, and Their Diverse Radiative Effects

NASA Technical Reports Server (NTRS)

Tselioudis, George; Lipat, Bernard R.; Konsta, Dimitra; Grise, Kevin M.; Polvani, Lorenzo M.

2016-01-01

We investigate the interannual relationship among clouds, their radiative effects, and two key indices of the atmospheric circulation: the latitudinal positions of the Hadley cell edge and the midlatitude jet. From reanalysis data and satellite observations, we find a clear and consistent relationship between the width of the Hadley cell and the high cloud field, statistically significant in nearly all regions and seasons. In contrast, shifts of the midlatitude jet correlate significantly with high cloud shifts only in the North Atlantic region during the winter season. While in that region and season poleward high cloud shifts are associated with shortwave radiative warming, over the Southern Oceans during all seasons they are associated with shortwave radiative cooling. Finally, a trend analysis reveals that poleward high cloud shifts observed over the 1983-2009 period are more likely related to Hadley cell expansion, rather than poleward shifts of the midlatitude jets.

A Mass-Flux Scheme View of a High-Resolution Simulation of a Transition from Shallow to Deep Cumulus Convection.

NASA Astrophysics Data System (ADS)

Kuang, Zhiming; Bretherton, Christopher S.

2006-07-01

In this paper, an idealized, high-resolution simulation of a gradually forced transition from shallow, nonprecipitating to deep, precipitating cumulus convection is described; how the cloud and transport statistics evolve as the convection deepens is explored; and the collected statistics are used to evaluate assumptions in current cumulus schemes. The statistical analysis methodologies that are used do not require tracing the history of individual clouds or air parcels; instead they rely on probing the ensemble characteristics of cumulus convection in the large model dataset. They appear to be an attractive way for analyzing outputs from cloud-resolving numerical experiments. Throughout the simulation, it is found that 1) the initial thermodynamic properties of the updrafts at the cloud base have rather tight distributions; 2) contrary to the assumption made in many cumulus schemes, nearly undiluted air parcels are too infrequent to be relevant to any stage of the simulated convection; and 3) a simple model with a spectrum of entraining plumes appears to reproduce most features of the cloudy updrafts, but significantly overpredicts the mass flux as the updrafts approach their levels of zero buoyancy. A buoyancy-sorting model was suggested as a potential remedy. The organized circulations of cold pools seem to create clouds with larger-sized bases and may correspondingly contribute to their smaller lateral entrainment rates. Our results do not support a mass-flux closure based solely on convective available potential energy (CAPE), and are in general agreement with a convective inhibition (CIN)-based closure. The general similarity in the ensemble characteristics of shallow and deep convection and the continuous evolution of the thermodynamic structure during the transition provide justification for developing a single unified cumulus parameterization that encompasses both shallow and deep convection.

The occurrence of ice production in slightly supercooled Arctic stratiform clouds as observed by ground-based remote sensors at the ARM NSA site

NASA Astrophysics Data System (ADS)

Zhang, Damao; Wang, Zhien; Luo, Tao; Yin, Yan; Flynn, Connor

2017-03-01

Ice particle formation in slightly supercooled stratiform clouds is not well documented or understood. In this study, 4 years of combined lidar depolarization and radar reflectivity (Ze) measurements are analyzed to distinguish between cold drizzle and ice crystal formations in slightly supercooled Arctic stratiform clouds over the Atmospheric Radiation Measurement Program Climate Research Facility North Slope of Alaska Utqiaġvik ("Barrow") site. Ice particles are detected and statistically shown to be responsible for the strong precipitation in slightly supercooled Arctic stratiform clouds at cloud top temperatures as high as -4°C. For ice precipitating Arctic stratiform clouds, the lidar particulate linear depolarization ratio (δpar_lin) correlates well with radar Ze at each temperature range, but the δpar_lin-Ze relationship varies with temperature ranges. In addition, lidar depolarization and radar Ze observations of ice generation characteristics in Arctic stratiform clouds are consistent with laboratory-measured temperature-dependent ice growth habits.

Morphological diagnostics of star formation in molecular clouds

NASA Astrophysics Data System (ADS)

Beaumont, Christopher Norris

Molecular clouds are the birth sites of all star formation in the present-day universe. They represent the initial conditions of star formation, and are the primary medium by which stars transfer energy and momentum back to parsec scales. Yet, the physical evolution of molecular clouds remains poorly understood. This is not due to a lack of observational data, nor is it due to an inability to simulate the conditions inside molecular clouds. Instead, the physics and structure of the interstellar medium are sufficiently complex that interpreting molecular cloud data is very difficult. This dissertation mitigates this problem, by developing more sophisticated ways to interpret morphological information in molecular cloud observations and simulations. In particular, I have focused on leveraging machine learning techniques to identify physically meaningful substructures in the interstellar medium, as well as techniques to inter-compare molecular cloud simulations to observations. These contributions make it easier to understand the interplay between molecular clouds and star formation. Specific contributions include: new insight about the sheet-like geometry of molecular clouds based on observations of stellar bubbles; a new algorithm to disambiguate overlapping yet morphologically distinct cloud structures; a new perspective on the relationship between molecular cloud column density distributions and the sizes of cloud substructures; a quantitative analysis of how projection effects affect measurements of cloud properties; and an automatically generated, statistically-calibrated catalog of bubbles identified from their infrared morphologies.

OMMYDCLD: a New A-train Cloud Product that Co-locates OMI and MODIS Cloud and Radiance Parameters onto the OMI Footprint

NASA Technical Reports Server (NTRS)

Fisher, Brad; Joiner, Joanna; Vasilkov, Alexander; Veefkind, Pepijn; Platnick, Steven; Wind, Galina

2014-01-01

Clouds cover approximately 60% of the earth's surface. When obscuring the satellite's field of view (FOV), clouds complicate the retrieval of ozone, trace gases and aerosols from data collected by earth observing satellites. Cloud properties associated with optical thickness, cloud pressure, water phase, drop size distribution (DSD), cloud fraction, vertical and areal extent can also change significantly over short spatio-temporal scales. The radiative transfer models used to retrieve column estimates of atmospheric constituents typically do not account for all these properties and their variations. The OMI science team is preparing to release a new data product, OMMYDCLD, which combines the cloud information from sensors on board two earth observing satellites in the NASA A-Train: Aura/OMI and Aqua/MODIS. OMMYDCLD co-locates high resolution cloud and radiance information from MODIS onto the much larger OMI pixel and combines it with parameters derived from the two other OMI cloud products: OMCLDRR and OMCLDO2. The product includes histograms for MODIS scientific data sets (SDS) provided at 1 km resolution. The statistics of key data fields - such as effective particle radius, cloud optical thickness and cloud water path - are further separated into liquid and ice categories using the optical and IR phase information. OMMYDCLD offers users of OMI data cloud information that will be useful for carrying out OMI calibration work, multi-year studies of cloud vertical structure and in the identification and classification of multi-layer clouds.

a Probability-Based Statistical Method to Extract Water Body of TM Images with Missing Information

NASA Astrophysics Data System (ADS)

Lian, Shizhong; Chen, Jiangping; Luo, Minghai

2016-06-01

Water information cannot be accurately extracted using TM images because true information is lost in some images because of blocking clouds and missing data stripes, thereby water information cannot be accurately extracted. Water is continuously distributed in natural conditions; thus, this paper proposed a new method of water body extraction based on probability statistics to improve the accuracy of water information extraction of TM images with missing information. Different disturbing information of clouds and missing data stripes are simulated. Water information is extracted using global histogram matching, local histogram matching, and the probability-based statistical method in the simulated images. Experiments show that smaller Areal Error and higher Boundary Recall can be obtained using this method compared with the conventional methods.

Satellite and Surface Data Synergy for Developing a 3D Cloud Structure and Properties Characterization Over the ARM SGP. Stage 1: Cloud Amounts, Optical Depths, and Cloud Heights Reconciliation

NASA Technical Reports Server (NTRS)

Genkova, I.; Long, C. N.; Heck, P. W.; Minnis, P.

2003-01-01

One of the primary Atmospheric Radiation Measurement (ARM) Program objectives is to obtain measurements applicable to the development of models for better understanding of radiative processes in the atmosphere. We address this goal by building a three-dimensional (3D) characterization of the cloud structure and properties over the ARM Southern Great Plains (SGP). We take the approach of juxtaposing the cloud properties as retrieved from independent satellite and ground-based retrievals, and looking at the statistics of the cloud field properties. Once these retrievals are well understood, they will be used to populate the 3D characterization database. As a first step we determine the relationship between surface fractional sky cover and satellite viewing angle dependent cloud fraction (CF). We elaborate on the agreement intercomparing optical depth (OD) datasets from satellite and ground using available retrieval algorithms with relation to the CF, cloud height, multi-layer cloud presence, and solar zenith angle (SZA). For the SGP Central Facility, where output from the active remote sensing cloud layer (ARSCL) valueadded product (VAP) is available, we study the uncertainty of satellite estimated cloud heights and evaluate the impact of this uncertainty for radiative studies.

Cloud Macroscopic Organization: Order Emerging from Randomness

NASA Technical Reports Server (NTRS)

Yuan, Tianle

2011-01-01

Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-07-02

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m -2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m -2.« less

Verification of NWP Cloud Properties using A-Train Satellite Observations

NASA Astrophysics Data System (ADS)

Kucera, P. A.; Weeks, C.; Wolff, C.; Bullock, R.; Brown, B.

2011-12-01

Recently, the NCAR Model Evaluation Tools (MET) has been enhanced to incorporate satellite observations for the verification of Numerical Weather Prediction (NWP) cloud products. We have developed tools that match fields spatially (both in the vertical and horizontal dimensions) to compare NWP products with satellite observations. These matched fields provide diagnostic evaluation of cloud macro attributes such as vertical distribution of clouds, cloud top height, and the spatial and seasonal distribution of cloud fields. For this research study, we have focused on using CloudSat, CALIPSO, and MODIS observations to evaluate cloud fields for a variety of NWP fields and derived products. We have selected cases ranging from large, mid-latitude synoptic systems to well-organized tropical cyclones. For each case, we matched the observed cloud field with gridded model and/or derived product fields. CloudSat and CALIPSO observations and model fields were matched and compared in the vertical along the orbit track. MODIS data and model fields were matched and compared in the horizontal. We then use MET to compute the verification statistics to quantify the performance of the models in representing the cloud fields. In this presentation we will give a summary of our comparison and show verification results for both synoptic and tropical cyclone cases.

A Catalog of Distances to Molecular Clouds from Pan-STARRS1

NASA Astrophysics Data System (ADS)

Schlafly, Eddie; Green, G.; Finkbeiner, D. P.; Rix, H.

2014-01-01

We present a catalog of distances to molecular clouds, derived from PanSTARRS-1 photometry. We simultaneously infer the full probability distribution function of reddening and distance of the stars towards these clouds using the technique of Green et al. (2013) (see neighboring poster). We fit the resulting measurements using a simple dust screen model to infer the distance to each cloud. The result is a large, homogeneous catalog of distances to molecular clouds. For clouds with heliocentric distances greater than about 200 pc, typical statistical uncertainties in the distances are 5%, with systematic uncertainty stemming from the quality of our stellar models of about 10%. We have applied this analysis to many of the most well-studied clouds in the δ > -30° sky, including Orion, California, Taurus, Perseus, and Cepheus. We have also studied the entire catalog of Magnani, Blitz, and Mundy (1985; MBM), though for about half of those clouds we can provide only upper limits on the distances. We compare our distances with distances from the literature, when available, and find good agreement.

How Well Can Infrared Sounders Observe the Atmosphere and Surface Through Clouds?

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, L. Larrabee; Yang, Ping

2010-01-01

Infrared sounders, such as the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared sounder (CrIS), have a cloud-impenetrable disadvantage in observing the atmosphere and surface under opaque cloudy conditions. However, recent studies indicate that hyperspectral, infrared sounders have the ability to detect cloud effective-optical and microphysical properties and to penetrate optically thin clouds in observing the atmosphere and surface to a certain degree. We have developed a retrieval scheme dealing with atmospheric conditions with cloud presence. This scheme can be used to analyze the retrieval accuracy of atmospheric and surface parameters under clear and cloudy conditions. In this paper, we present the surface emissivity results derived from IASI global measurements under both clear and cloudy conditions. The accuracy of surface emissivity derived under cloudy conditions is statistically estimated in comparison with those derived under clear sky conditions. The retrieval error caused by the clouds is shown as a function of cloud optical depth, which helps us to understand how well infrared sounders can observe the atmosphere and surface through clouds.

Precipitation Discrimination from Satellite Infrared Temperatures over the CCOPE Mesonet Region.

NASA Astrophysics Data System (ADS)

Weiss, Mitchell; Smith, Eric A.

1987-06-01

A quantitative investigation of the relationship between satellite-derived cloud-top temperature parameters and the detection of intense convective rainfall is described. The area of study is that of the Cooperative Convective Precipitation Experiment (CCOPE), which was held near Miles City, Montana during the summer of 1981. Cloud-top temperatures, derived from the GOES-West operational satellite, were used to calculate a variety of parameters for objectively quantifying the convective intensity of a storm. A dense network of rainfall provided verification of surface rainfall. The cloud-top temperature field and surface rainfall data were processed into equally sized grid domains in order to best depict the individual samples of instantaneous precipitation.The technique of statistical discriminant analysis was used to determine which combinations of cloud-top temperature parameters best classify rain versus no-rain occurrence using three different rain-rate cutoffs: 1, 4, and 10 mm h1. Time lags within the 30 min rainfall verification were tested to determine the optimum time delay associated with rainfall reaching the ground.A total of six storm cases were used to develop and test the statistical models. Discrimination of rain events was found to be most accurate when using a 10 mm h1 rain-rate cutoff. Use parameters designated as coldest cloud-top temperature, the spatial mean of coldest cloud-top temperature, and change over time of mean coldest cloud-top temperature were found to be the best classifiers of rainfall in this study. Combining both a 10-min time lag (in terms of surface verification) with a 10 mm h1 rain-rate threshold resulted in classifying over 60% of all rain and no-rain cases correctly.

The application of satellite data in the determination of ocean temperatures and cloud characteristics and statistics

NASA Technical Reports Server (NTRS)

Curran, R. J.; Salomonson, V. V.; Shenk, W. (Principal Investigator)

1975-01-01

The author has identified the following significant results. The major shortcoming of the data was the loss of the infrared radiances from the S191 spectrometer. The cloud thermodynamic phase determination procedure was derived and tested with the data collected by the S192 multispectral scanner. Results of the test indicate a large fraction of the data could be classified thermodynamically. An added bonus was the inclusion of snow in the classification approach. The conclusion to be drawn from this portion of the effort is that in most cases considered ice clouds, liquid water droplet clouds, and snow fields can be spectroscopically separated to a high degree of accuracy.

Statistical characterization of the nonlinear noise in 2.8 Tbit/s PDM-16QAM CO-OFDM system.

PubMed

Wang, Zhe; Qiao, Yaojun; Xu, Yanfei; Ji, Yuefeng

2013-07-29

We show for the first time through comprehensive simulations under both uncompensated transmission (UT) and dispersion managed transmission (DMT) systems that the statistical distribution of the nonlinear interference (NLI) within the polarization multiplexed 16-state quadrature amplitude modulation (PM-16QAM) Coherent Optical OFDM (CO-OFDM) system deviates from Gaussian distribution in the absence of amplified spontaneous emission (ASE) noise. We also observe that the dependences of the variance of the NLI noise on both the launch power and the transmission distance (logrithm) seem to be in a simple linear way.

Estimates for the Probabilities of Surface-to-Air Cloud-Free Lines-of-Sight and Low Cloud Statistics from Ship Observations. Part 1. Fifteen Marine Locations.

DTIC Science & Technology

1980-11-24

time before and after) or cumulus fractus of bad weath’er, or both ( pannus ), usually below altostratus or nimbostratus. 8 = Cumulus and stratocumulus...vibrous upper part by cumulus, stratocumulus, stratus or pannus . + . from Surface Marine Observations Tape Deck TDF-11 *Fog All clouds in the 0-50...Fractus of bad weather, cr V both ( pannus ), usually below Alto- stratus or N~imbostratus. The term "bad weather* denotes the conditions which coenerally

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-cloud Aerosols over Ocean Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

2013-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4%. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

2014-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

Application of Seasonal CRM Integrations to Develop Statistics and Improved GCM Parameterization of Subgrid Cloud-Radiation Interactions

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

Xiaoqing Wu; Xin-Zhong Liang; Sunwook Park

2007-01-23

The works supported by this ARM project lay the solid foundation for improving the parameterization of subgrid cloud-radiation interactions in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and concurrent ARM observations to produce long-term, consistent cloud and radiative property datasets at the cloud scale (Wu et al. 2006, 2007). With these datasets, we have investigated the mesoscale enhancement of cloud systems on surface heat fluxes (Wu and Guimond 2006), quantified the effects of cloud horizontal inhomogeneity and vertical overlap on the domain-averaged radiative fluxes (Wu and Liang 2005), and subsequently validatedmore » and improved the physically-based mosaic treatment of subgrid cloud-radiation interactions (Liang and Wu 2005). We have implemented the mosaic treatment into the CCM3. The 5-year (1979-1983) AMIP-type simulation showed significant impacts of subgrid cloud-radiation interaction on the climate simulations (Wu and Liang 2005). We have actively participated in CRM intercomparisons that foster the identification and physical understanding of common errors in cloud-scale modeling (Xie et al. 2005; Xu et al. 2005, Grabowski et al. 2005).« less

Analysis of the VIIRS cloud mask, comparison with the NAVOCEANO cloud mask, and how they complement each other

NASA Astrophysics Data System (ADS)

Cayula, Jean-François P.; May, Douglas A.; McKenzie, Bruce D.

2014-05-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Mask (VCM) Intermediate Product (IP) has been developed for use with Suomi National Polar-orbiting Partnership (NPP) VIIRS Environmental Data Record (EDR) products. In particular, the VIIRS Sea Surface Temperature (SST) EDR relies on VCM to identify cloud contaminated observations. Unfortunately, VCM does not appear to perform as well as cloud detection algorithms for SST. This may be due to similar but different goals of the two algorithms. VCM is concerned with detecting clouds while SST is interested in identifying clear observations. The result is that in undetermined cases VCM defaults to "clear," while the SST cloud detection defaults to "cloud." This problem is further compounded because classic SST cloud detection often flags as "cloud" all types of corrupted data, thus making a comparison with VCM difficult. The Naval Oceanographic Office (NAVOCEANO), which operationally produces a VIIRS SST product, relies on cloud detection from the NAVOCEANO Cloud Mask (NCM), adapted from cloud detection schemes designed for SST processing. To analyze VCM, the NAVOCEANO SST process was modified to attach the VCM flags to all SST retrievals. Global statistics are computed for both day and night data. The cases where NCM and/or VCM tag data as cloud-contaminated or clear can then be investigated. By analyzing the VCM individual test flags in conjunction with the status of NCM, areas where VCM can complement NCM are identified.

Assessing the accuracy of MISR and MISR-simulated cloud top heights using CloudSat- and CALIPSO-retrieved hydrometeor profiles

NASA Astrophysics Data System (ADS)

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.; Mace, Gerald G.; Benson, Sally

2017-03-01

Satellite retrievals of cloud properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of CloudSat, CALIPSO, MODIS, and AMSR-E observations as inputs to the MISR simulator and comparing cloud top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle- and high-altitude topped clouds agrees well between MISR retrievals and the MISR-simulated output, with distributions of middle- and high-topped cloud cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low-topped clouds between MISR retrievals and MISR-simulated output that are due to differences in the detection of low-level clouds between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator cloud top height adjustment. This difference highlights the importance of sensor resolution and boundary layer cloud spatial structure in determining low-altitude cloud cover. The MISR-simulated and MISR-retrieved cloud optical depth also show systematic differences, which are also likely due in part to cloud spatial structure.

Estimating vertical profiles of water-cloud droplet effective radius from SWIR satellite measurements via a statistical model derived from CloudSat observations

NASA Astrophysics Data System (ADS)

Nagao, T. M.; Murakami, H.; Nakajima, T. Y.

2017-12-01

This study proposes an algorithm to estimate vertical profiles of cloud droplet effective radius (CDER-VP) for water clouds from shortwave infrared (SWIR) measurements of Himawari-8/AHI via a statistical model of CDER-VP derived from CloudSat observation. Several similar algorithms in previous studies utilize a spectral radiance matching on the assumption of simultaneous observations of CloudSat and Aqua/MODIS. However, our algorithm does not assume simultaneous observations with CloudSat. First, in advance, a database (DB) of CDER-VP is prepared by the following procedure: TOA radiances at 0.65, 2.3 and 10.4-μm bands of the AHI are simulated using CDER-VP and cloud optical depth vertical profile (COD-VP) contained in the CloudSat 2B-CWC-RVOD and 2B-TAU products. Cloud optical thickness (COT), Column-CDER and cloud top height (CTH) are retrieved from the simulated radiances using a traditional retrieval algorithm with vertically homogeneous cloud model (1-SWIR VHC method). The CDER-VP is added to the DB by using the COT and Column-CDER retrievals as a key of the DB. Then by using principal component (PC) analysis, up to three PC vectors of the CDER-VPs in the DB are extracted. Next, the algorithm retrieves CDER-VP from actual AHI measurements by the following procedure: First, COT, Column-CDER and CTH are retrieved from TOA radiances at 0.65, 2.3 and 10.4-μm bands of the AHI using by 1-SWIR VHC method. Then, the PC vectors of CDER-VP is fetched from the DB using the COT and Column-CDER retrievals as the key of the DB. Finally, using coefficients of the PC vectors of CDER-VP as variables for retrieval, CDER-VP, COT and CTH are retrieved from TOA radiances at 0.65, 1.6, 2.3, 3.9 and 10.4-μm bands of the AHI based on optimal estimation method with iterative radiative transfer calculation. The simulation result showed the CDER-VP retrieval errors were almost smaller than 3 - 4 μm. The CDER retrieval errors at the cloud base were almost larger than the others (e.g. CDER at cloud top), especially when COT and CDER was large. The tendency can be explained by less sensitivities of SWIRs to CDER at cloud base. Additionally, as a case study, this study will attempt to apply the algorithm to the AHI's high-frequency observations, and to interpret the time series of the CDER-VP retrievals in terms of temporal evolution of water clouds.

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

2010-01-01

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

Low-cloud characteristics over the tropical western Pacific from ARM observations and CAM5 simulations

DOE PAGES

Chandra, Arunchandra S.; Zhang, Chidong; Klein, Stephen A.; ...

2015-09-10

Here, this study evaluates the ability of the Community Atmospheric Model version 5 (CAM5) to reproduce low clouds observed by the Atmospheric Radiation Measurement (ARM) cloud radar at Manus Island of the tropical western Pacific during the Years of Tropical Convection. Here low clouds are defined as clouds with their tops below the freezing level and bases within the boundary layer. Low-cloud statistics in CAM5 simulations and ARM observations are compared in terms of their general occurrence, mean vertical profiles, fraction of precipitating versus nonprecipitating events, diurnal cycle, and monthly time series. Other types of clouds are included to putmore » the comparison in a broader context. The comparison shows that the model overproduces total clouds and their precipitation fraction but underestimates low clouds in general. The model, however, produces excessive low clouds in a thin layer between 954 and 930 hPa, which coincides with excessive humidity near the top of the mixed layer. This suggests that the erroneously excessive low clouds stem from parameterization of both cloud and turbulence mixing. The model also fails to produce the observed diurnal cycle in low clouds, not exclusively due to the model coarse grid spacing that does not resolve Manus Island. Lastly, this study demonstrates the utility of ARM long-term cloud observations in the tropical western Pacific in verifying low clouds simulated by global climate models, illustrates issues of using ARM observations in model validation, and provides an example of severe model biases in producing observed low clouds in the tropical western Pacific.« less

Machine learning patterns for neuroimaging-genetic studies in the cloud.

PubMed

Da Mota, Benoit; Tudoran, Radu; Costan, Alexandru; Varoquaux, Gaël; Brasche, Goetz; Conrod, Patricia; Lemaitre, Herve; Paus, Tomas; Rietschel, Marcella; Frouin, Vincent; Poline, Jean-Baptiste; Antoniu, Gabriel; Thirion, Bertrand

2014-01-01

Brain imaging is a natural intermediate phenotype to understand the link between genetic information and behavior or brain pathologies risk factors. Massive efforts have been made in the last few years to acquire high-dimensional neuroimaging and genetic data on large cohorts of subjects. The statistical analysis of such data is carried out with increasingly sophisticated techniques and represents a great computational challenge. Fortunately, increasing computational power in distributed architectures can be harnessed, if new neuroinformatics infrastructures are designed and training to use these new tools is provided. Combining a MapReduce framework (TomusBLOB) with machine learning algorithms (Scikit-learn library), we design a scalable analysis tool that can deal with non-parametric statistics on high-dimensional data. End-users describe the statistical procedure to perform and can then test the model on their own computers before running the very same code in the cloud at a larger scale. We illustrate the potential of our approach on real data with an experiment showing how the functional signal in subcortical brain regions can be significantly fit with genome-wide genotypes. This experiment demonstrates the scalability and the reliability of our framework in the cloud with a 2 weeks deployment on hundreds of virtual machines.

Classification of Arctic, midlatitude and tropical clouds in the mixed-phase temperature regime

NASA Astrophysics Data System (ADS)

Costa, Anja; Meyer, Jessica; Afchine, Armin; Luebke, Anna; Günther, Gebhard; Dorsey, James R.; Gallagher, Martin W.; Ehrlich, Andre; Wendisch, Manfred; Baumgardner, Darrel; Wex, Heike; Krämer, Martina

2017-10-01

The degree of glaciation of mixed-phase clouds constitutes one of the largest uncertainties in climate prediction. In order to better understand cloud glaciation, cloud spectrometer observations are presented in this paper, which were made in the mixed-phase temperature regime between 0 and -38 °C (273 to 235 K), where cloud particles can either be frozen or liquid. The extensive data set covers four airborne field campaigns providing a total of 139 000 1 Hz data points (38.6 h within clouds) over Arctic, midlatitude and tropical regions. We develop algorithms, combining the information on number concentration, size and asphericity of the observed cloud particles to classify four cloud types: liquid clouds, clouds in which liquid droplets and ice crystals coexist, fully glaciated clouds after the Wegener-Bergeron-Findeisen process and clouds where secondary ice formation occurred. We quantify the occurrence of these cloud groups depending on the geographical region and temperature and find that liquid clouds dominate our measurements during the Arctic spring, while clouds dominated by the Wegener-Bergeron-Findeisen process are most common in midlatitude spring. The coexistence of liquid water and ice crystals is found over the whole mixed-phase temperature range in tropical convective towers in the dry season. Secondary ice is found at midlatitudes at -5 to -10 °C (268 to 263 K) and at higher altitudes, i.e. lower temperatures in the tropics. The distribution of the cloud types with decreasing temperature is shown to be consistent with the theory of evolution of mixed-phase clouds. With this study, we aim to contribute to a large statistical database on cloud types in the mixed-phase temperature regime.

Performance analysis of Integrated Communication and Control System networks

NASA Technical Reports Server (NTRS)

Halevi, Y.; Ray, A.

1990-01-01

This paper presents statistical analysis of delays in Integrated Communication and Control System (ICCS) networks that are based on asynchronous time-division multiplexing. The models are obtained in closed form for analyzing control systems with randomly varying delays. The results of this research are applicable to ICCS design for complex dynamical processes like advanced aircraft and spacecraft, autonomous manufacturing plants, and chemical and processing plants.

Analysis of stratocumulus cloud fields using LANDSAT imagery: Size distributions and spatial separations

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1990-01-01

Stratocumulus cloud fields in the FIRE IFO region are analyzed using LANDSAT Thematic Mapper imagery. Structural properties such as cloud cell size distribution, cell horizontal aspect ratio, fractional coverage and fractal dimension are determined. It is found that stratocumulus cloud number densities are represented by a power law. Cell horizontal aspect ratio has a tendency to increase at large cell sizes, and cells are bi-fractal in nature. Using LANDSAT Multispectral Scanner imagery for twelve selected stratocumulus scenes acquired during previous years, similar structural characteristics are obtained. Cloud field spatial organization also is analyzed. Nearest-neighbor spacings are fit with a number of functions, with Weibull and Gamma distributions providing the best fits. Poisson tests show that the spatial separations are not random. Second order statistics are used to examine clustering.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Factor analysis as a tool for spectral line component separation 21cm emission in the direction of L1780

NASA Technical Reports Server (NTRS)

Toth, L. V.; Mattila, K.; Haikala, L.; Balazs, L. G.

1992-01-01

The spectra of the 21cm HI radiation from the direction of L1780, a small high-galactic latitude dark/molecular cloud, were analyzed by multivariate methods. Factor analysis was performed on HI (21cm) spectra in order to separate the different components responsible for the spectral features. The rotated, orthogonal factors explain the spectra as a sum of radiation from the background (an extended HI emission layer), and from the L1780 dark cloud. The coefficients of the cloud-indicator factors were used to locate the HI 'halo' of the molecular cloud. Our statistically derived 'background' and 'cloud' spectral profiles, as well as the spatial distribution of the HI halo emission distribution were compared to the results of a previous study which used conventional methods analyzing nearly the same data set.

Statistical patterns in the location of natural lightning

NASA Astrophysics Data System (ADS)

Zoghzoghy, F. G.; Cohen, M. B.; Said, R. K.; Inan, U. S.

2013-01-01

Lightning discharges are nature's way of neutralizing the electrical buildup in thunderclouds. Thus, if an individual discharge destroys a substantial fraction of the cloud charge, the probability of a subsequent flash is reduced until the cloud charge separation rebuilds. The temporal pattern of lightning activity in a localized region may thus inherently be a proxy measure of the corresponding timescales for charge separation and electric field buildup processes. We present a statistical technique to bring out this effect (as well as the subsequent recovery) using lightning geo-location data, in this case with data from the National Lightning Detection Network (NLDN) and from the GLD360 Network. We use this statistical method to show that a lightning flash can remove an appreciable fraction of the built up charge, affecting the neighboring lightning activity for tens of seconds within a ˜ 10 km radius. We find that our results correlate with timescales of electric field buildup in storms and suggest that the proposed statistical tool could be used to study the electrification of storms on a global scale. We find that this flash suppression effect is a strong function of flash type, flash polarity, cloud-to-ground flash multiplicity, the geographic location of lightning, and is proportional to NLDN model-derived peak stroke current. We characterize the spatial and temporal extent of the suppression effect as a function of these parameters and discuss various applications of our findings.

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

Sena, Elisa T.; McComiskey, Allison; Feingold, Graham

Empirical estimates of the microphysical response of cloud droplet size distribution to aerosol perturbations are commonly used to constrain aerosol–cloud interactions in climate models. Instead of empirical microphysical estimates, here macroscopic variables are analyzed to address the influence of aerosol particles and meteorological descriptors on instantaneous cloud albedo and the radiative effect of shallow liquid water clouds. Long-term ground-based measurements from the Atmospheric Radiation Measurement (ARM) program over the Southern Great Plains are used. A broad statistical analysis was performed on 14 years of coincident measurements of low clouds, aerosol, and meteorological properties. Here two cases representing conflicting results regardingmore » the relationship between the aerosol and the cloud radiative effect were selected and studied in greater detail. Microphysical estimates are shown to be very uncertain and to depend strongly on the methodology, retrieval technique and averaging scale. For this continental site, the results indicate that the influence of the aerosol on the shallow cloud radiative effect and albedo is weak and that macroscopic cloud properties and dynamics play a much larger role in determining the instantaneous cloud radiative effect compared to microphysical effects. On a daily basis, aerosol shows no correlation with cloud radiative properties (correlation = -0.01 ± 0.03), whereas the liquid water path shows a clear signal (correlation = 0.56 ± 0.02).« less

Detection of long duration cloud contamination in hyper-temporal NDVI imagery

NASA Astrophysics Data System (ADS)

Ali, A.; de Bie, C. A. J. M.; Skidmore, A. K.; Scarrott, R. G.

2012-04-01

NDVI time series imagery are commonly used as a reliable source for land use and land cover mapping and monitoring. However long duration cloud can significantly influence its precision in areas where persistent clouds prevails. Therefore quantifying errors related to cloud contamination are essential for accurate land cover mapping and monitoring. This study aims to detect long duration cloud contamination in hyper-temporal NDVI imagery based land cover mapping and monitoring. MODIS-Terra NDVI imagery (250 m; 16-day; Feb'03-Dec'09) were used after necessary pre-processing using quality flags and upper envelope filter (ASAVOGOL). Subsequently stacked MODIS-Terra NDVI image (161 layers) was classified for 10 to 100 clusters using ISODATA. After classifications, 97 clusters image was selected as best classified with the help of divergence statistics. To detect long duration cloud contamination, mean NDVI class profiles of 97 clusters image was analyzed for temporal artifacts. Results showed that long duration clouds affect the normal temporal progression of NDVI and caused anomalies. Out of total 97 clusters, 32 clusters were found with cloud contamination. Cloud contamination was found more prominent in areas where high rainfall occurs. This study can help to stop error propagation in regional land cover mapping and monitoring, caused by long duration cloud contamination.

An imager-based multispectral retrieval of above-cloud absorbing aerosol optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2014-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into imager-based cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced for cloud optical thickness retrievals, which are typically derived from the visible or near-IR wavelength channels (effective particle size retrievals are derived from short and mid-wave IR channels that are less affected by aerosol absorption). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple spectral channels in the visible and near- and shortwave-IR. The technique has been applied to MODIS, and retrieval results and statistics, as well as comparisons with other A-Train sensors, are shown.

The ROSCOE MANUAL. Volume 27. Natural Background Radiation

DTIC Science & Technology

1980-07-01

159 cloud configurations in the statistical cloud model, this distribution function has 160 members for nighttime and 161 mem - bers for daytime: 159...COWA - SIN( ON+DETLAT ) RINOUT 1A5 Q14P - A8S( OETLOW-POSLOW RI NO, T 146 1Ff QNP.GE.PI ) OHP - TWOPI-QNP RINOU!T 1,47 SINOMP -SIN’ ONP ) QRIWfoUT

Classification of clouds sampled at the puy de Dôme (France) based on 10 yr of monitoring of their physicochemical properties

NASA Astrophysics Data System (ADS)

Deguillaume, L.; Charbouillot, T.; Joly, M.; Vaïtilingom, M.; Parazols, M.; Marinoni, A.; Amato, P.; Delort, A.-M.; Vinatier, V.; Flossmann, A.; Chaumerliac, N.; Pichon, J. M.; Houdier, S.; Laj, P.; Sellegri, K.; Colomb, A.; Brigante, M.; Mailhot, G.

2014-02-01

Long-term monitoring of the chemical composition of clouds (73 cloud events representing 199 individual samples) sampled at the puy de Dôme (pdD) station (France) was performed between 2001 and 2011. Physicochemical parameters, as well as the concentrations of the major organic and inorganic constituents, were measured and analyzed by multicomponent statistical analysis. Along with the corresponding back-trajectory plots, this allowed for distinguishing four different categories of air masses reaching the summit of the pdD: polluted, continental, marine and highly marine. The statistical analysis led to the determination of criteria (concentrations of inorganic compounds, pH) that differentiate each category of air masses. Highly marine clouds exhibited high concentrations of Na+ and Cl-; the marine category presented lower concentration of ions but more elevated pH. Finally, the two remaining clusters were classified as "continental" and "polluted"; these clusters had the second-highest and highest levels of NH4+, NO3-, and SO24-, respectively. This unique data set of cloud chemical composition is then discussed as a function of this classification. Total organic carbon (TOC) is significantly higher in polluted air masses than in the other categories, which suggests additional anthropogenic sources. Concentrations of carboxylic acids and carbonyls represent around 10% of the organic matter in all categories of air masses and are studied for their relative importance. Iron concentrations are significantly higher for polluted air masses and iron is mainly present in its oxidation state (+II) in all categories of air masses. Finally, H2O2 concentrations are much more varied in marine and highly marine clouds than in polluted clouds, which are characterized by the lowest average concentration of H2O2. This data set provides concentration ranges of main inorganic and organic compounds for modeling purposes on multiphase cloud chemistry.

Selection of optical model of stereophotography experiment for determination the cloud base height as a problem of testing of statistical hypotheses

NASA Astrophysics Data System (ADS)

Chulichkov, Alexey I.; Nikitin, Stanislav V.; Emilenko, Alexander S.; Medvedev, Andrey P.; Postylyakov, Oleg V.

2017-10-01

Earlier, we developed a method for estimating the height and speed of clouds from cloud images obtained by a pair of digital cameras. The shift of a fragment of the cloud in the right frame relative to its position in the left frame is used to estimate the height of the cloud and its velocity. This shift is estimated by the method of the morphological analysis of images. However, this method requires that the axes of the cameras are parallel. Instead of real adjustment of the axes, we use virtual camera adjustment, namely, a transformation of a real frame, the result of which could be obtained if all the axes were perfectly adjusted. For such adjustment, images of stars as infinitely distant objects were used: on perfectly aligned cameras, images on both the right and left frames should be identical. In this paper, we investigate in more detail possible mathematical models of cloud image deformations caused by the misalignment of the axes of two cameras, as well as their lens aberration. The simplest model follows the paraxial approximation of lens (without lens aberrations) and reduces to an affine transformation of the coordinates of one of the frames. The other two models take into account the lens distortion of the 3rd and 3rd and 5th orders respectively. It is shown that the models differ significantly when converting coordinates near the edges of the frame. Strict statistical criteria allow choosing the most reliable model, which is as much as possible consistent with the measurement data. Further, each of these three models was used to determine parameters of the image deformations. These parameters are used to provide cloud images to mean what they would have when measured using an ideal setup, and then the distance to cloud is calculated. The results were compared with data of a laser range finder.

Microphysics of Clouds with the Relaxed Arakawa-Schubert Scheme (McRAS). Part I: Design and Evaluation with GATE Phase III Data.

NASA Astrophysics Data System (ADS)

Sud, Y. C.; Walker, G. K.

1999-09-01

A prognostic cloud scheme named McRAS (Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme) has been designed and developed with the aim of improving moist processes, microphysics of clouds, and cloud-radiation interactions in GCMs. McRAS distinguishes three types of clouds: convective, stratiform, and boundary layer. The convective clouds transform and merge into stratiform clouds on an hourly timescale, while the boundary layer clouds merge into the stratiform clouds instantly. The cloud condensate converts into precipitation following the autoconversion equations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, as well as diffuse both horizontally and vertically with a fully interactive cloud microphysics throughout the life cycle of the cloud, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry.An evaluation of McRAS in a single-column model (SCM) with the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE) Phase III data has shown that, together with the rest of the model physics, McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. The time history and time mean in-cloud water and ice distribution, fractional cloudiness, cloud optical thickness, origin of precipitation in the convective anvils and towers, and the convective updraft and downdraft velocities and mass fluxes all simulate a realistic behavior. Some of these diagnostics are not verifiable with data on hand. These SCM sensitivity tests show that (i) without clouds the simulated GATE-SCM atmosphere is cooler than observed; (ii) the model's convective scheme, RAS, is an important subparameterization of McRAS; and (iii) advection of cloud water substance is helpful in simulating better cloud distribution and cloud-radiation interaction. An evaluation of the performance of McRAS in the Goddard Earth Observing System II GCM is given in a companion paper (Part II).

A Diagnostic PDF Cloud Scheme to Improve Subtropical Low Clouds in NCAR Community Atmosphere Model (CAM5)

NASA Astrophysics Data System (ADS)

Qin, Yi; Lin, Yanluan; Xu, Shiming; Ma, Hsi-Yen; Xie, Shaocheng

2018-02-01

Low clouds strongly impact the radiation budget of the climate system, but their simulation in most GCMs has remained a challenge, especially over the subtropical stratocumulus region. Assuming a Gaussian distribution for the subgrid-scale total water and liquid water potential temperature, a new statistical cloud scheme is proposed and tested in NCAR Community Atmospheric Model version 5 (CAM5). The subgrid-scale variance is diagnosed from the turbulent and shallow convective processes in CAM5. The approach is able to maintain the consistency between cloud fraction and cloud condensate and thus alleviates the adjustment needed in the default relative humidity-based cloud fraction scheme. Short-term forecast simulations indicate that low cloud fraction and liquid water content, including their diurnal cycle, are improved due to a proper consideration of subgrid-scale variance over the southeastern Pacific Ocean region. Compared with the default cloud scheme, the new approach produced the mean climate reasonably well with improved shortwave cloud forcing (SWCF) due to more reasonable low cloud fraction and liquid water path over regions with predominant low clouds. Meanwhile, the SWCF bias over the tropical land regions is also alleviated. Furthermore, the simulated marine boundary layer clouds with the new approach extend further offshore and agree better with observations. The new approach is able to obtain the top of atmosphere (TOA) radiation balance with a slightly alleviated double ITCZ problem in preliminary coupled simulations. This study implies that a close coupling of cloud processes with other subgrid-scale physical processes is a promising approach to improve cloud simulations.

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

NASA Technical Reports Server (NTRS)

Stubenrauch, C. J.; Rossow, W. B.; Kinne, S.; Ackerman, S.; Cesana, G.; Chepfer, H.; Getzewich, B.; Di Girolamo, L.; Guignard, A.; Heidinger, A.;

GEWEX cloud assessment: A review

NASA Astrophysics Data System (ADS)

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.

Study of wind retrieval from space-borne infrared coherent lidar in cloudy atmosphere.

NASA Astrophysics Data System (ADS)

Baron, Philippe; Ishii, Shoken; Mizutani, Kohei; Okamoto, Kozo; Ochiai, Satoshi

2015-04-01

Future spaceborne tropospheric wind missions using infrared coherent lidar are currently being studied in Japan and in the United States [1,2]. The line-of-sight wind velocity is retrieved from the Doppler shift frequency of the signal returned by aerosol particles. However a large percentage (70-80%) of the measured single-shot intensity profiles are expected to be contaminated by clouds [3]. A large number of cloud contaminated profiles (>40%) will be characterized by a cloud-top signal intensity stronger than the aerosol signal by a factor of one order of magnitude, and by a strong attenuation of the signal backscattered from below the clouds. Profiles including more than one cloud layer are also expected. This work is a simulation study dealing with the impacts of clouds on wind retrieval. We focus on the three following points: 1) definition of an algorithm for optimizing the wind retrieval from the cloud-top signal, 2) assessment of the clouds impact on the measurement performance and, 3) definition of a method for averaging the measurements before the retrieval. The retrieval simulations are conducted considering the instrumental characteristics selected for the Japanese study: wavelength at 2 µm, PRF of 30 Hz, pulse power of 0.125 mJ and platform altitude between 200-400 km. Liquid and ice clouds are considered. The analysis uses data from atmospheric models and statistics of cloud effects derived from CALIPSO measurements such as in [3]. A special focus is put on the average method of the measurements before retrieval. Good retrievals in the mid-upper troposphere implie the average of measured single-range power spectra over large horizontal (100 km) and vertical (1 km) ranges. Large differences of signal intensities due to the presence of clouds and the clouds non-uniform distribution have to be taken into account when averaging the data to optimize the measurement performances. References: [1] S. Ishii, T. Iwasaki, M. Sato, R. Oki, K. Okamoto, T. Ishibashi, P. Baron, and T. Nishizawa: Future Doppler lidar wind measurement from space in Japan, Proc. of SPIE Vol. 8529, 2012 [2] D. Wu, J. Tang, Z. Liu, and Y. Hu: Simulation of coherent doppler wind lidar measurement from space based on CALIPSO lidar global aerosol observations. Journal of Quantitative Spectroscopy and Radiative Transfer, 122(0), 79-86, 2013 [3] G.D Emmitt: CFLOS and cloud statistics from satellite and their impact on future space-based Doppler Wind Lidar development. Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, 2008

Unveiling aerosol-cloud interactions - Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data

NASA Astrophysics Data System (ADS)

Neubauer, David; Christensen, Matthew W.; Poulsen, Caroline A.; Lohmann, Ulrike

2017-11-01

Aerosol-cloud interactions (ACIs) are uncertain and the estimates of the ACI effective radiative forcing (ERFaci) magnitude show a large variability. Within the Aerosol_cci project the susceptibility of cloud properties to changes in aerosol properties is derived from the high-resolution AATSR (Advanced Along-Track Scanning Radiometer) data set using the Cloud-Aerosol Pairing Algorithm (CAPA) (as described in our companion paper) and compared to susceptibilities from the global aerosol climate model ECHAM6-HAM2 and MODIS-CERES (Moderate Resolution Imaging Spectroradiometer - Clouds and the Earth's Radiant Energy System) data. For ECHAM6-HAM2 the dry aerosol is analysed to mimic the effect of CAPA. Furthermore the analysis is done for different environmental regimes. The aerosol-liquid water path relationship in ECHAM6-HAM2 is systematically stronger than in AATSR-CAPA data and cannot be explained by an overestimation of autoconversion when using diagnostic precipitation but rather by aerosol swelling in regions where humidity is high and clouds are present. When aerosol water is removed from the analysis in ECHAM6-HAM2 the strength of the susceptibilities of liquid water path, cloud droplet number concentration and cloud albedo as well as ERFaci agree much better with those of AATSR-CAPA or MODIS-CERES. When comparing satellite-derived to model-derived susceptibilities, this study finds it more appropriate to use dry aerosol in the computation of model susceptibilities. We further find that the statistical relationships inferred from different satellite sensors (AATSR-CAPA vs. MODIS-CERES) as well as from ECHAM6-HAM2 are not always of the same sign for the tested environmental conditions. In particular the susceptibility of the liquid water path is negative in non-raining scenes for MODIS-CERES but positive for AATSR-CAPA and ECHAM6-HAM2. Feedback processes like cloud-top entrainment that are missing or not well represented in the model are therefore not well constrained by satellite observations. In addition to aerosol swelling, wet scavenging and aerosol processing have an impact on liquid water path, cloud albedo and cloud droplet number susceptibilities. Aerosol processing leads to negative liquid water path susceptibilities to changes in aerosol index (AI) in ECHAM6-HAM2, likely due to aerosol-size changes by aerosol processing. Our results indicate that for statistical analysis of aerosol-cloud interactions the unwanted effects of aerosol swelling, wet scavenging and aerosol processing need to be minimised when computing susceptibilities of cloud variables to changes in aerosol.

What is the role of laminar cirrus cloud on regulating the cross-tropopause water vapor transport?

NASA Astrophysics Data System (ADS)

Wu, D. L.; Gong, J.; Tsai, V.

2016-12-01

Laminar cirrus is an extremely thin ice cloud found persistently inhabit in the tropical and subtropical tropopause. Due to its sub-visible optical depth and high formation altitude, knowledge about the characteristics of this special type of cloud is very limited, and debates are ongoing about its role on regulating the cross-tropopause transport of water vapor. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite has been continuously providing us with unprecedented details of the laminar cirrus since its launch in 2006. In this research, we adapted Winker and Trepte (1998)'s eyeball detection method. A JAVA-based applet and graphical user interface (GUI) is developed to manually select the laminar, which then automatically record the cloud properties, such as spatial location, shape, thickness, tilt angle, and whether its isolated or directly above a deep convective cloud. Monthly statistics of the laminar cirrus are then separately analyzed according to the orbit node, isolated/convective, banded/non-banded, etc. Monthly statistics support a diurnal difference in the occurring frequency and formation height of the laminar cirrus. Also, isolated and convective laminars show diverse behaviors (height, location, distribution, etc.), which strongly implies that their formation mechanisms and their roles on depleting the upper troposphere water vapor are distinct. We further study the relationship between laminar characteristics and collocated and coincident water vapor gradient measurements from Aura Microwave Limb Sounder (MLS) observations below and above the laminars. The identified relationship provides a quantitative answer to the role laminar cirrus plays on regulating the water vapor entering the stratosphere.

Clouds vertical properties over the Northern Hemisphere monsoon regions from CloudSat-CALIPSO measurements

NASA Astrophysics Data System (ADS)

Das, Subrata Kumar; Golhait, R. B.; Uma, K. N.

2017-01-01

The CloudSat spaceborne radar and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) space-borne lidar measurements, provide opportunities to understand the intriguing behavior of the vertical structure of monsoon clouds. The combined CloudSat-CALIPSO data products have been used for the summer season (June-August) of 2006-2010 to present the statistics of cloud macrophysical (such as cloud occurrence frequency, distribution of cloud top and base heights, geometrical thickness and cloud types base on occurrence height), and microphysical (such as ice water content, ice water path, and ice effective radius) properties of the Northern Hemisphere (NH) monsoon region. The monsoon regions considered in this work are the North American (NAM), North African (NAF), Indian (IND), East Asian (EAS), and Western North Pacific (WNP). The total cloud fraction over the IND (mostly multiple-layered cloud) appeared to be more frequent as compared to the other monsoon regions. Three distinctive modes of cloud top height distribution are observed over all the monsoon regions. The high-level cloud fraction is comparatively high over the WNP and IND. The ice water content and ice water path over the IND are maximum compared to the other monsoon regions. We found that the ice water content has little variations over the NAM, NAF, IND, and WNP as compared to their macrophysical properties and thus give an impression that the regional differences in dynamics and thermodynamics properties primarily cause changes in the cloud frequency or coverage and only secondary in the cloud ice properties. The background atmospheric dynamics using wind and relative humidity from the ERA-Interim reanalysis data have also been investigated which helps in understanding the variability of the cloud properties over the different monsoon regions.

Topology of Neutral Hydrogen within the Small Magellanic Cloud

NASA Astrophysics Data System (ADS)

Chepurnov, A.; Gordon, J.; Lazarian, A.; Stanimirovic, S.

2008-12-01

In this paper, genus statistics have been applied to an H I column density map of the Small Magellanic Cloud in order to study its topology. To learn how topology changes with the scale of the system, we provide topology studies for column density maps at varying resolutions. To evaluate the statistical error of the genus, we randomly reassign the phases of the Fourier modes while keeping the amplitudes. We find that at the smallest scales studied (40 pc <= λ <= 80 pc), the genus shift is negative in all regions, implying a clump topology. At the larger scales (110 pc <= λ <= 250 pc), the topology shift is detected to be negative (a "meatball" topology) in four cases and positive (a "swiss cheese" topology) in two cases. In four regions, there is no statistically significant topology shift at large scales.

On the Representation of Cloud Phase in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

NASA Astrophysics Data System (ADS)

Storelvmo, Trude; Sagoo, Navjit; Tan, Ivy

2016-04-01

Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

A long-term study of aerosol–cloud interactions and their radiative effect at the Southern Great Plains using ground-based measurements

DOE PAGES

Sena, Elisa T.; McComiskey, Allison; Feingold, Graham

2016-09-13

Empirical estimates of the microphysical response of cloud droplet size distribution to aerosol perturbations are commonly used to constrain aerosol–cloud interactions in climate models. Instead of empirical microphysical estimates, here macroscopic variables are analyzed to address the influence of aerosol particles and meteorological descriptors on instantaneous cloud albedo and the radiative effect of shallow liquid water clouds. Long-term ground-based measurements from the Atmospheric Radiation Measurement (ARM) program over the Southern Great Plains are used. A broad statistical analysis was performed on 14 years of coincident measurements of low clouds, aerosol, and meteorological properties. Here two cases representing conflicting results regardingmore » the relationship between the aerosol and the cloud radiative effect were selected and studied in greater detail. Microphysical estimates are shown to be very uncertain and to depend strongly on the methodology, retrieval technique and averaging scale. For this continental site, the results indicate that the influence of the aerosol on the shallow cloud radiative effect and albedo is weak and that macroscopic cloud properties and dynamics play a much larger role in determining the instantaneous cloud radiative effect compared to microphysical effects. On a daily basis, aerosol shows no correlation with cloud radiative properties (correlation = -0.01 ± 0.03), whereas the liquid water path shows a clear signal (correlation = 0.56 ± 0.02).« less

Splice loss requirements in multi-mode fiber mode-division-multiplex transmission links.

PubMed

Warm, Stefan; Petermann, Klaus

2013-01-14

We investigate numerically the influence of fiber splices and fiber connectors to the statistics of mode dependent loss (MDL) and multiple-input multiple-output (MIMO) outage capacity in mode multiplexed multi-mode fiber links. Our results indicate required splice losses much lower than currently feasible to achieve a reasonable outage capacity in long-haul transmission systems. Splice losses as low as 0.03dB may effectively lead to an outage of MIMO channels after only a few hundred kilometers transmission length. In a first approximation, the relative capacity solely depends on the accumulated splice loss and should be less than ≈ 2dB to ensure a relative capacity of 90%. We also show that discrete mode permutation (mixing) within the transmission line may effectively increase the maximum transmission distance by a factor of 5 for conventional splice losses.

Neurons in Anterior Cingulate Cortex Multiplex Information about Reward and Action

PubMed Central

Hayden, Benjamin Y.; Platt, Michael L.

2010-01-01

The dorsal anterior cingulate cortex (dACC) is thought to play a critical role in forming associations between rewards and actions. Currently available physiological data, however, remain inconclusive regarding the question of whether dACC neurons carry information linking particular actions to reward or, instead, encode abstract reward information independent of specific actions. Here we show that firing rates of a majority of dACC neurons in a population studied in an eight-option variably rewarded choice task were sensitive to both saccade direction and reward value. Furthermore, the influences of reward and saccade direction on neuronal activity were roughly equal in magnitude over the range of rewards tested and were statistically independent. Our results indicate that dACC neurons multiplex information about both reward and action, endorsing the idea that this area links motivational outcomes to behavior and undermining the notion that its neurons solely contribute to reward processing in the abstract. PMID:20203193

Identification of nonclassical properties of light with multiplexing layouts

NASA Astrophysics Data System (ADS)

Sperling, J.; Eckstein, A.; Clements, W. R.; Moore, M.; Renema, J. J.; Kolthammer, W. S.; Nam, S. W.; Lita, A.; Gerrits, T.; Walmsley, I. A.; Agarwal, G. S.; Vogel, W.

2017-07-01

In Sperling et al. [Phys. Rev. Lett. 118, 163602 (2017), 10.1103/PhysRevLett.118.163602], we introduced and applied a detector-independent method to uncover nonclassicality. Here, we extend those techniques and give more details on the performed analysis. We derive a general theory of the positive-operator-valued measure that describes multiplexing layouts with arbitrary detectors. From the resulting quantum version of a multinomial statistics, we infer nonclassicality probes based on a matrix of normally ordered moments. We discuss these criteria and apply the theory to our data which are measured with superconducting transition-edge sensors. Our experiment produces heralded multiphoton states from a parametric down-conversion light source. We show that the known notions of sub-Poisson and sub-binomial light can be deduced from our general approach, and we establish the concept of sub-multinomial light, which is shown to outperform the former two concepts of nonclassicality for our data.

Identification of nonclassical properties of light with multiplexing layouts

PubMed Central

Sperling, J.; Eckstein, A.; Clements, W. R.; Moore, M.; Renema, J. J.; Kolthammer, W. S.; Nam, S. W.; Lita, A.; Gerrits, T.; Walmsley, I. A.; Agarwal, G. S.; Vogel, W.

2018-01-01

In Sperling et al. [Phys. Rev. Lett. 118, 163602 (2017)], we introduced and applied a detector-independent method to uncover nonclassicality. Here, we extend those techniques and give more details on the performed analysis. We derive a general theory of the positive-operator-valued measure that describes multiplexing layouts with arbitrary detectors. From the resulting quantum version of a multinomial statistics, we infer nonclassicality probes based on a matrix of normally ordered moments. We discuss these criteria and apply the theory to our data which are measured with superconducting transition-edge sensors. Our experiment produces heralded multiphoton states from a parametric down-conversion light source. We show that the known notions of sub-Poisson and sub-binomial light can be deduced from our general approach, and we establish the concept of sub-multinomial light, which is shown to outperform the former two concepts of nonclassicality for our data. PMID:29670949

Simultaneous use of multiplex ligation-dependent probe amplification assay and flow cytometric DNA ploidy analysis in patients with acute leukemia.

PubMed

Reyes-Núñez, Virginia; Galo-Hooker, Evelyn; Pérez-Romano, Beatriz; Duque, Ricardo E; Ruiz-Arguelles, Alejandro; Garcés-Eisele, Javier

2018-01-01

The aim of this work was to simultaneously use multiplex ligation-dependent probe amplification (MLPA) assay and flow cytometric DNA ploidy analysis (FPA) to detect aneuploidy in patients with newly diagnosed acute leukemia. MLPA assay and propidium iodide FPA were used to test samples from 53 consecutive patients with newly diagnosed acute leukemia referred to our laboratory for immunophenotyping. Results were compared by nonparametric statistics. The combined use of both methods significantly increased the rate of detection of aneuploidy as compared to that obtained by each method alone. The limitations of one method are somehow countervailed by the other and vice versa. MPLA and FPA yield different yet complementary information concerning aneuploidy in acute leukemia. The simultaneous use of both methods might be recommended in the clinical setting. © 2017 International Clinical Cytometry Society. © 2017 International Clinical Cytometry Society.

Spatial and Temporal Distribution of Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Ackerman, Steven A.; Hubanks, Paul A.

2012-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched aboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. A comprehensive set of remote sensing algorithms for the retrieval of cloud physical and optical properties have enabled over twelve years of continuous observations of cloud properties from Terra and over nine years from Aqua. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as latitudinal distributions of cloud top pressure and cloud top temperature. MODIS finds the cloud fraction, as derived by the cloud mask, is nearly identical during the day and night, with only modest diurnal variation. Globally, the cloud fraction derived by the MODIS cloud mask is approx.67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, cloud fraction over land is approx.55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Cloud top pressure and temperature have distinct spatial and temporal patterns, and clearly reflect our understanding of the global cloud distribution. High clouds are especially prevalent over the northern hemisphere continents between 30 and 50 . Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to afternoon deep convection. The coldest cloud tops (colder than 230 K) generally occur over Antarctica and the high clouds in the tropics (ITCZ and the deep convective clouds over the western tropical Pacific and Indian sub-continent).

Mitigating randomness of consumer preferences under certain conditional choices

NASA Astrophysics Data System (ADS)

Bothos, John M. A.; Thanos, Konstantinos-Georgios; Papadopoulou, Eirini; Daveas, Stelios; Thomopoulos, Stelios C. A.

2017-05-01

Agent-based crowd behaviour consists a significant field of research that has drawn a lot of attention in recent years. Agent-based crowd simulation techniques have been used excessively to forecast the behaviour of larger or smaller crowds in terms of certain given conditions influenced by specific cognition models and behavioural rules and norms, imposed from the beginning. Our research employs conditional event algebra, statistical methodology and agent-based crowd simulation techniques in developing a behavioural econometric model about the selection of certain economic behaviour by a consumer that faces a spectre of potential choices when moving and acting in a multiplex mall. More specifically we try to analyse the influence of demographic, economic, social and cultural factors on the economic behaviour of a certain individual and then we try to link its behaviour with the general behaviour of the crowds of consumers in multiplex malls using agent-based crowd simulation techniques. We then run our model using Generalized Least Squares and Maximum Likelihood methods to come up with the most probable forecast estimations, regarding the agent's behaviour. Our model is indicative about the formation of consumers' spectre of choices in multiplex malls under the condition of predefined preferences and can be used as a guide for further research in this area.

Vertical transport by convective clouds: Comparisons of three modeling approaches

NASA Technical Reports Server (NTRS)

Pickering, Kenneth E.; Thompson, Anne M.; Tao, Wei-Kuo; Rood, Richard B.; Mcnamara, Donna P.; Molod, Andrea M.

1995-01-01

A preliminary comparison of the GEOS-1 (Goddard Earth Observing System) data assimilation system convective cloud mass fluxes with fluxes from a cloud-resolving model (the Goddard Cumulus Ensemble Model, GCE) is reported. A squall line case study (10-11 June 1985 Oklahoma PRESTORM episode) is the basis of the comparison. Regional (central U. S.) monthly total convective mass flux for June 1985 from GEOS-1 compares favorably with estimates from a statistical/dynamical approach using GCE simulations and satellite-derived cloud observations. The GEOS-1 convective mass fluxes produce reasonable estimates of monthly-averaged regional convective venting of CO from the boundary layer at least in an urban-influenced continental region, suggesting that they can be used in tracer transport simulations.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

NASA Astrophysics Data System (ADS)

Huang, Dong; Liu, Yangang

2014-12-01

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.

Clouds above the Martin Limb: Viking observations

NASA Technical Reports Server (NTRS)

Martin, L. J.; Baum, W. A.; Wasserman, L. H.; Kreidl, T. J.

1984-01-01

Whenever Viking Orbiter images included the limb of Mars, they recorded one or more layers of clouds above the limb. The height above the limb and the brightness (reflectivity) of these clouds were determined in a selected group of these images. Normalized individual brightness profiles of three separate traverses across the limb of each image are shown. The most notable finding is that some of these clouds can be very high. Many reach heights of over 60 km, and several are over 70 km above the limb. Statistically, the reflectivity of the clouds increases with phase angle. Reflectivity and height both appear to vary with season, but the selected images spanned only one Martian year, so the role of seasons cannot be isolated. Limb clouds in red-filter images tend to be brighter than violet-filter images, but both season and phase appear to be more dominant factors. Due to the limited sample available, the possible influences of latitude and longitude are less clear. The layering of these clouds ranges from a single layer to five or more layers. Reflectivity gradients range from smooth and gentle to steep and irregular.

Differences in the Optical Characteristics of Continental US Ground and Cloud Flashes as Observed from Space

NASA Technical Reports Server (NTRS)

Koshak, William

2007-01-01

Continental US lightning flashes observed by the Optical Transient Detector (OTD) are categorized according to flash type (ground or cloud flash) using US National Lightning Detection Network (TM) (NLDN) data. The statistics of the ground and cloud flash optical parameters (e.g., radiance, area, duration, number of optical groups, and number of optical events) are inter-compared. On average, the ground flash cloud-top emissions are more radiant, illuminate a larger area, are longer lasting, and have more optical groups and optical events than those cloud-top emissions associated with cloud flashes. Given these differences, it is suggested that the methods of Bayesian Inference could be used to help discriminate between ground and cloud flashes. The ability to discriminate flash type on-orbit is highly desired since such information would help researchers and operational decision makers better assess the intensification, evolutionary state, and severe weather potential of thunderstorms. This work supports risk reduction activities presently underway for the future launch of the GOES-R Geostationary Lightning Mapper (GLM).

Interannual to decadal climate variability of sea salt aerosols in the coupled climate model CESM1.0: Climate variability of sea salt aerosols

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

Xu, Li; Pierce, David W.; Russell, Lynn M.

This study examines multi-year climate variability associated with sea salt aerosols and their contribution to the variability of shortwave cloud forcing (SWCF) using a 150-year simulation for pre-industrial conditions of the Community Earth System Model version 1.0 (CESM1). The results suggest that changes in sea salt and related cloud and radiative properties on interannual timescales are dominated by the ENSO cycle. Sea salt variability on longer (interdecadal) timescales is associated with low-frequency Pacific ocean variability similar to the interdecadal Pacific Oscillation (IPO), but does not show a statistically significant spectral peak. A multivariate regression suggests that sea salt aerosol variabilitymore » may contribute to SWCF variability in the tropical Pacific, explaining up to 25-35% of the variance in that region. Elsewhere, there is only a small aerosol influence on SWCF through modifying cloud droplet number and liquid water path that contributes to the change of cloud effective radius and cloud optical depth (and hence cloud albedo), producing a multi-year aerosol-cloud-wind interaction.« less

The Experimental Cloud Lidar Pilot Study (ECLIPS) for cloud-radiation research

NASA Technical Reports Server (NTRS)

Platt, C. M.; Young, S. A.; Carswell, A. I.; Pal, S. R.; Mccormick, M. P.; Winker, D. M.; Delguasta, M.; Stefanutti, L.; Eberhard, W. L.; Hardesty, M.

1994-01-01

The Experimental Cloud Lidar Pilot Study (ECLIPS) was initiated to obtain statistics on cloud-base height, extinction, optical depth, cloud brokenness, and surface fluxes. Two observational phases have taken place, in October-December 1989 and April-July 1991, with intensive 30-day periods being selected within the two time intervals. Data are being archived at NASA Langley Research Center and, once there, are readily available to the international scientific community. This article describes the scale of the study in terms of its international involvement and in the range of data being recorded. Lidar observations of cloud height and backscatter coefficient have been taken from a number of ground-based stations spread around the globe. Solar shortwave and infrared longwave fluxes and infrared beam radiance have been measured at the surface wherever possible. The observations have been tailored to occur around the overpass times of the NOAA weather satellites. This article describes in some detail the various retrieval methods used to obtain results on cloud-base height, extinction coefficient, and infrared emittance, paying particular attention to the uncertainties involved.

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

Spatial Distribution of Large Cloud Drops

NASA Technical Reports Server (NTRS)

Marshak, A.; Knyazikhin, Y.; Larsen, M.; Wiscombe, W.

2004-01-01

By analyzing aircraft measurements of individual drop sizes in clouds, we have shown in a companion paper (Knyazikhin et al., 2004) that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)) where 0 less than or equal to D(r) less than or equal to 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast. It also helps explain why remotely sensed cloud drop size is generally biased and why clouds absorb more sunlight than conventional radiative transfer models predict.

Estimation of Cloud Fraction Profile in Shallow Convection Using a Scanning Cloud Radar

DOE PAGES

Oue, Mariko; Kollias, Pavlos; North, Kirk W.; ...

2016-10-18

Large spatial heterogeneities in shallow convection result in uncertainties in estimations of domain-averaged cloud fraction profiles (CFP). This issue is addressed using large eddy simulations of shallow convection over land coupled with a radar simulator. Results indicate that zenith profiling observations are inadequate to provide reliable CFP estimates. Use of Scanning Cloud Radar (SCR), performing a sequence of cross-wind horizon-to-horizon scans, is not straightforward due to the strong dependence of radar sensitivity to target distance. An objective method for estimating domain-averaged CFP is proposed that uses observed statistics of SCR hydrometeor detection with height to estimate optimum sampling regions. Thismore » method shows good agreement with the model CFP. Results indicate that CFP estimates require more than 35 min of SCR scans to converge on the model domain average. Lastly, the proposed technique is expected to improve our ability to compare model output with cloud radar observations in shallow cumulus cloud conditions.« less

Design and Performance of McRas in SCMs and GEOS I/II GCMs

NASA Technical Reports Server (NTRS)

Sud, Yogesh C.; Einaudi, Franco (Technical Monitor)

2000-01-01

The design of a prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) for general circulation models (GCMs) will be discussed. McRAS distinguishes three types of clouds: (1) convective, (2) stratiform, and (3) boundary-layer types. The convective clouds transform and merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds merge into the stratiform clouds instantly. The cloud condensate converts into precipitation following the auto-conversion equations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, as well as diffuse both horizontally and vertically with a fully interactive cloud-microphysics throughout the life-cycle of the cloud, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III and 5-ARN CART datasets has shown that together with the rest of the model physics, McRAS can simulate the observed temperature, humidity, and precipitation without many systematic errors. The time history and time mean incloud water and ice distribution, fractional cloudiness, cloud optical thickness, origin of precipitation in the convective anvil and towers, and the convective updraft and downdraft velocities and mass fluxes all show a realistic behavior. Performance of McRAS in GEOS 11 GCM shows several satisfactory features but some of the remaining deficiencies suggest need for additional research involving convective triggers and inhibitors, provision for continuously detraining updraft, a realistic scheme for cumulus gravity wave drag, and refinements to physical conditions for ascertaining cloud detrainment level.

Spatial and Temporal Distribution of Clouds as Observed by MODIS Onboard the Terra and Aqua Satellites

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, Paul; Ackerman, Steven A.

2006-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24,2000 for Terra and June 24,2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. Over the last year, extensive improvements and enhancements in the global cloud products have been implemented, and reprocessing of all MODIS data on Terra has commenced since first light in February 2000. In the cloud mask algorithm, the most extensive improvements were in distinguishing clouds at nighttime, including the challenging polar darkness regions of the world. Additional improvements have been made to properly distinguish sunglint from clouds in the tropical ocean regions, and to improve the identification of clouds from snow during daytime in Polar Regions. We will show global monthly mean cloud fraction for both Terra and Aqua, and show how similar the global daytime cloud fraction is from these morning and afternoon orbits, respectively. We will also show the zonal distribution of cloud fraction over land and ocean regions for both Terra and Aqua, and show the time series of global cloud fraction from July 2002 through June 2006.

Biogeography, Cloud Base Heights and Cloud Immersion in Tropical Montane Cloud Forests

NASA Astrophysics Data System (ADS)

Welch, R. M.; Asefi, S.; Zeng, J.; Nair, U. S.; Lawton, R. O.; Ray, D. K.; Han, Q.; Manoharan, V. S.

2007-05-01

Tropical Montane Cloud Forests (TMCFs) are ecosystems characterized by frequent and prolonged immersion within orographic clouds. TMCFs often lie at the core of the biological hotspots, areas of high biodiversity, whose conservation is necessary to ensure the preservation of a significant amount of the plant and animal species in the world. TMCFs support islands of endemism dependent on cloud water interception that are extremely susceptible to environmental and climatic changes at regional or global scales. Due to the ecological and hydrological importance of TMCFs it is important to understand the biogeographical distribution of these ecosystems. The best current list of TMCFs is a global atlas compiled by the United Nations Environmental Program (UNEP). However, this list is incomplete, and it does not provide information on cloud immersion, which is the defining characteristic of TMCFs and sorely needed for ecological and hydrological studies. The present study utilizes MODIS satellite data both to determine orographic cloud base heights and then to quantify cloud immersion statistics over TMCFs. Results are validated from surface measurements over Northern Costa Rica for the month of March 2003. Cloud base heights are retrieved with approximately 80m accuracy, as determined at Monteverde, Costa Rica. Cloud immersion derived from MODIS data is also compared to an independent cloud immersion dataset created using a combination of GOES satellite data and RAMS model simulations. Comparison against known locations of cloud forests in Northern Costa Rica shows that the MODIS-derived cloud immersion maps successfully identify these cloud forest locations, including those not included in the UNEP data set. Results also will be shown for cloud immersion in Hawaii. The procedure appears to be ready for global mapping.

Statistical properties of the normalized ice particle size distribution

NASA Astrophysics Data System (ADS)

Delanoë, Julien; Protat, Alain; Testud, Jacques; Bouniol, Dominique; Heymsfield, A. J.; Bansemer, A.; Brown, P. R. A.; Forbes, R. M.

2005-05-01

Testud et al. (2001) have recently developed a formalism, known as the "normalized particle size distribution (PSD)", which consists in scaling the diameter and concentration axes in such a way that the normalized PSDs are independent of water content and mean volume-weighted diameter. In this paper we investigate the statistical properties of the normalized PSD for the particular case of ice clouds, which are known to play a crucial role in the Earth's radiation balance. To do so, an extensive database of airborne in situ microphysical measurements has been constructed. A remarkable stability in shape of the normalized PSD is obtained. The impact of using a single analytical shape to represent all PSDs in the database is estimated through an error analysis on the instrumental (radar reflectivity and attenuation) and cloud (ice water content, effective radius, terminal fall velocity of ice crystals, visible extinction) properties. This resulted in a roughly unbiased estimate of the instrumental and cloud parameters, with small standard deviations ranging from 5 to 12%. This error is found to be roughly independent of the temperature range. This stability in shape and its single analytical approximation implies that two parameters are now sufficient to describe any normalized PSD in ice clouds: the intercept parameter N*0 and the mean volume-weighted diameter Dm. Statistical relationships (parameterizations) between N*0 and Dm have then been evaluated in order to reduce again the number of unknowns. It has been shown that a parameterization of N*0 and Dm by temperature could not be envisaged to retrieve the cloud parameters. Nevertheless, Dm-T and mean maximum dimension diameter -T parameterizations have been derived and compared to the parameterization of Kristjánsson et al. (2000) currently used to characterize particle size in climate models. The new parameterization generally produces larger particle sizes at any temperature than the Kristjánsson et al. (2000) parameterization. These new parameterizations are believed to better represent particle size at global scale, owing to a better representativity of the in situ microphysical database used to derive it. We then evaluated the potential of a direct N*0-Dm relationship. While the model parameterized by temperature produces strong errors on the cloud parameters, the N*0-Dm model parameterized by radar reflectivity produces accurate cloud parameters (less than 3% bias and 16% standard deviation). This result implies that the cloud parameters can be estimated from the estimate of only one parameter of the normalized PSD (N*0 or Dm) and a radar reflectivity measurement.

Aerosol and Cloud Observations and Data Products by the GLAS Polar Orbiting Lidar Instrument

NASA Technical Reports Server (NTRS)

Spinhirne, J. D.; Palm, S. P.; Hlavka, D. L.; Hart, W. D.; Mahesh, A.; Welton, E. J.

2005-01-01

The Geoscience Laser Altimeter System (GLAS) launched in 2003 is the first polar orbiting satellite lidar. The instrument was designed for high performance observations of the distribution and optical scattering cross sections of clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. Both receiver channels meet and exceed their design goals, and beginning with a two month period through October and November 2003, an excellent global lidar data set now exists. The data products for atmospheric observations include the calibrated, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data sets are now in open release through the NASA data distribution system. The initial results on global statistics for cloud and aerosol distribution has been produced and in some cases compared to other satellite observations. The sensitivity of the cloud measurements is such that the 70% global cloud coverage result should be the most accurate to date. Results on the global distribution of aerosol are the first that produce the true height distribution for model inter-comparison.

Implications of the Observed Mesoscale Variations of Clouds for Earth's Radiation Budget

NASA Technical Reports Server (NTRS)

Rossow, William B.; Delo, Carl; Cairns, Brian; Hansen, James E. (Technical Monitor)

2001-01-01

The effect of small-spatial-scale cloud variations on radiative transfer in cloudy atmospheres currently receives a lot of research attention, but the available studies are not very clear about which spatial scales are important and report a very large range of estimates of the magnitude of the effects. Also, there have been no systematic investigations of how to measure and represent these cloud variations. We exploit the cloud climatology produced by the International Satellite Cloud Climatology Project (ISCCP) to: (1) define and test different methods of representing cloud variation statistics, (2) investigate the range of spatial scales that should be included, (3) characterize cloud variations over a range of space and time scales covering mesoscale (30 - 300 km, 3-12 hr) into part of the lower part of the synoptic scale (300 - 3000 km, 1-30 days), (4) obtain a climatology of the optical thickness, emissivity and cloud top temperature variability of clouds that can be used in weather and climate GCMS, together with the parameterization proposed by Cairns et al. (1999), to account for the effects of small-scale cloud variations on radiative fluxes, and (5) evaluate the effect of observed cloud variations on Earth's radiation budget. These results lead to the formulation of a revised conceptual model of clouds for use in radiative transfer calculations in GCMS. The complete variability climatology can be obtained from the ISCCP Web site at http://isccp.giss.nasa.gov.

LACIS-T - A moist air wind tunnel for investigating the interactions between cloud microphysics and turbulence

NASA Astrophysics Data System (ADS)

Niedermeier, Dennis; Voigtländer, Jens; Siebert, Holger; Desai, Neel; Shaw, Raymond; Chang, Kelken; Krueger, Steven; Schumacher, Jörg; Stratmann, Frank

2017-11-01

Turbulence - cloud droplet interaction processes have been investigated primarily through numerical simulation and field measurements over the last ten years. However, only in the laboratory we can be confident in our knowledge of initial and boundary conditions, and are able to measure for extended times under statistically stationary and repeatable conditions. Therefore, the newly built turbulent wind tunnel LACIS-T (Turbulent Leipzig Aerosol Cloud Interaction Simulator) is an ideal facility for pursuing mechanistic understanding of these processes. Within the tunnel we are able to adjust precisely controlled turbulent temperature and humidity fields so as to achieve supersaturation levels allowing for detailed investigations of the interactions between cloud microphysical processes (e.g., cloud droplet activation) and the turbulent flow, under well-defined and reproducible laboratory conditions. We will present the fundamental operating principle, first results from ongoing characterization efforts, numerical simulations as well as first droplet activation experiments.

A Method to Analyze How Various Parts of Clouds Influence Each Other's Brightness

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander; Lau, William (Technical Monitor)

2001-01-01

This paper proposes a method for obtaining new information on 3D radiative effects that arise from horizontal radiative interactions in heterogeneous clouds. Unlike current radiative transfer models, it can not only calculate how 3D effects change radiative quantities at any given point, but can also determine which areas contribute to these 3D effects, to what degree, and through what mechanisms. After describing the proposed method, the paper illustrates its new capabilities both for detailed case studies and for the statistical processing of large datasets. Because the proposed method makes it possible, for the first time, to link a particular change in cloud properties to the resulting 3D effect, in future studies it can be used to develop new radiative transfer parameterizations that would consider 3D effects in practical applications currently limited to 1D theory-such as remote sensing of cloud properties and dynamical cloud modeling.

Cloud and surface textural features in polar regions

NASA Technical Reports Server (NTRS)

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.

Observed and Simulated Radiative and Microphysical Properties of Tropical Convective Storms

NASA Technical Reports Server (NTRS)

DelGenio, Anthony D.; Hansen, James E. (Technical Monitor)

2001-01-01

Increases in the ice content, albedo and cloud cover of tropical convective storms in a warmer climate produce a large negative contribution to cloud feedback in the GISS GCM. Unfortunately, the physics of convective upward water transport, detrainment, and ice sedimentation, and the relationship of microphysical to radiative properties, are all quite uncertain. We apply a clustering algorithm to TRMM satellite microwave rainfall retrievals to identify contiguous deep precipitating storms throughout the tropics. Each storm is characterized according to its size, albedo, OLR, rain rate, microphysical structure, and presence/absence of lightning. A similar analysis is applied to ISCCP data during the TOGA/COARE experiment to identify optically thick deep cloud systems and relate them to large-scale environmental conditions just before storm onset. We examine the statistics of these storms to understand the relative climatic roles of small and large storms and the factors that regulate convective storm size and albedo. The results are compared to GISS GCM simulated statistics of tropical convective storms to identify areas of agreement and disagreement.

Efficient and Flexible Climate Analysis with Python in a Cloud-Based Distributed Computing Framework

NASA Astrophysics Data System (ADS)

Gannon, C.

2017-12-01

As climate models become progressively more advanced, and spatial resolution further improved through various downscaling projects, climate projections at a local level are increasingly insightful and valuable. However, the raw size of climate datasets presents numerous hurdles for analysts wishing to develop customized climate risk metrics or perform site-specific statistical analysis. Four Twenty Seven, a climate risk consultancy, has implemented a Python-based distributed framework to analyze large climate datasets in the cloud. With the freedom afforded by efficiently processing these datasets, we are able to customize and continually develop new climate risk metrics using the most up-to-date data. Here we outline our process for using Python packages such as XArray and Dask to evaluate netCDF files in a distributed framework, StarCluster to operate in a cluster-computing environment, cloud computing services to access publicly hosted datasets, and how this setup is particularly valuable for generating climate change indicators and performing localized statistical analysis.

Clustering, randomness, and regularity in cloud fields: 2. Cumulus cloud fields

NASA Astrophysics Data System (ADS)

Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.

1992-12-01

During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus clouds form in clusters, in which cloud spacing is closer than that found for the overall cloud field and which maintains its identity over many cloud lifetimes. This "mutual protection hypothesis" of Randall and Huffman (1980) has been challenged by the "inhibition hypothesis" of Ramirez et al. (1990) which strongly suggests that the spatial distribution of cumuli must tend toward a regular distribution. A dilemma has resulted because observations have been reported to support both hypotheses. The present work reports a detailed analysis of cumulus cloud field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-cloud cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small clouds are included in the cloud field distribution, the cloud field always has a strong clustering signal. The strength of clustering is largest at cloud diameters of about 200-300 m, diminishing with increasing cloud diameter. In many cases, clusters of small clouds are found which are not closely associated with large clouds. As the small clouds are eliminated from consideration, the cloud field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large clouds. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the cloud size distributions. Since distinct clouds are by definition nonoverlapping, cloud size effects place a restriction upon the possible locations of clouds in the cloud field. The net effect of this analysis is that the large clouds appear to be randomly distributed, with only weak tendencies towards regularity. For clouds less than 1 km in diameter, the average nearest-neighbor distance is equal to 3-7 cloud diameters. For larger clouds, the ratio of cloud nearest-neighbor distance to cloud diameter increases sharply with increasing cloud diameter. This demonstrates that large clouds inhibit the growth of other large clouds in their vicinity. Nevertheless, this leads to random distributions of large clouds, not regularity.

Proteome-wide quantitative multiplexed profiling of protein expression: carbon-source dependency in Saccharomyces cerevisiae

PubMed Central

Paulo, Joao A.; O’Connell, Jeremy D.; Gaun, Aleksandr; Gygi, Steven P.

2015-01-01

The global proteomic alterations in the budding yeast Saccharomyces cerevisiae due to differences in carbon sources can be comprehensively examined using mass spectrometry–based multiplexing strategies. In this study, we investigate changes in the S. cerevisiae proteome resulting from cultures grown in minimal media using galactose, glucose, or raffinose as the carbon source. We used a tandem mass tag 9-plex strategy to determine alterations in relative protein abundance due to a particular carbon source, in triplicate, thereby permitting subsequent statistical analyses. We quantified more than 4700 proteins across all nine samples; 1003 proteins demonstrated statistically significant differences in abundance in at least one condition. The majority of altered proteins were classified as functioning in metabolic processes and as having cellular origins of plasma membrane and mitochondria. In contrast, proteins remaining relatively unchanged in abundance included those having nucleic acid–related processes, such as transcription and RNA processing. In addition, the comprehensiveness of the data set enabled the analysis of subsets of functionally related proteins, such as phosphatases, kinases, and transcription factors. As a resource, these data can be mined further in efforts to understand better the roles of carbon source fermentation in yeast metabolic pathways and the alterations observed therein, potentially for industrial applications, such as biofuel feedstock production. PMID:26399295

The Statistical Value of Raw Fluorescence Signal in Luminex xMAP Based Multiplex Immunoassays

PubMed Central

Breen, Edmond J.; Tan, Woei; Khan, Alamgir

2016-01-01

Tissue samples (plasma, saliva, serum or urine) from 169 patients classified as either normal or having one of seven possible diseases are analysed across three 96-well plates for the presences of 37 analytes using cytokine inflammation multiplexed immunoassay panels. Censoring for concentration data caused problems for analysis of the low abundant analytes. Using fluorescence analysis over concentration based analysis allowed analysis of these low abundant analytes. Mixed-effects analysis on the resulting fluorescence and concentration responses reveals a combination of censoring and mapping the fluorescence responses to concentration values, through a 5PL curve, changed observed analyte concentrations. Simulation verifies this, by showing a dependence on the mean florescence response and its distribution on the observed analyte concentration levels. Differences from normality, in the fluorescence responses, can lead to differences in concentration estimates and unreliable probabilities for treatment effects. It is seen that when fluorescence responses are normally distributed, probabilities of treatment effects for fluorescence based t-tests has greater statistical power than the same probabilities from concentration based t-tests. We add evidence that the fluorescence response, unlike concentration values, doesn’t require censoring and we show with respect to differential analysis on the fluorescence responses that background correction is not required. PMID:27243383

Intra-annual variability of cloud cover over the Mediterranean region based on NCEP/NCAR, MODIS and ECAD data sets

NASA Astrophysics Data System (ADS)

Ioannidis, Eleftherios; Lolis, Christos J.; Papadimas, Christos D.; Hatzianastassiou, Nikolaos; Bartzokas, Aristides

2017-04-01

The seasonal variability of total cloud cover in the Mediterranean region is examined for the period 1948-2014 using a multivariate statistical methodology. The data used consist of: i) daily gridded (1.875°x1.905°) values of total cloud cover over the broader Mediterranean region for the 66-year period 1948-2014, obtained from NCEP/NCAR Reanalysis data set, ii) daily gridded (1°x1°) values of total cloud cover for the period 2003-2014 obtained from the Moderate resolution Imaging Spectroradiometer (MODIS) satellite data set and iii) daily station cloud cover data for the period 2003-2014 obtained from the European Climate Assessment & Dataset (ECA&D). At first, the multivariate statistical method of Factor Analysis (S-mode) with varimax rotation is applied as a dimensionality reduction tool on the mean day to day intra-annual variation of NCEP/NCAR cloud cover for the period 1948-2014. According to the results, three main modes of intra-annual variation of cloud cover are found. The first mode is characterized by a winter maximum and a summer minimum and prevails mainly over the sea; a weak see-saw teleconnection over the Alps represents the opposite intra-annual marching. The second mode presents maxima in early autumn and late spring, and minima in late summer and winter, and prevails over the SW Europe and NW Africa inland regions. The third mode shows a maximum in June and a minimum in October and prevails over the eastern part of central Europe. Next, the mean day to day intra-annual variation of NCEP/NCAR cloud cover over the core regions of the above factors is calculated for the entire period 1948-2014 and the three 22-year sub-periods 1948-70, 1970-92 and 1992-2014. A comparison is carried out between each of the three sub-periods and the total period in order to reveal possible long-term changes in seasonal march of total cloud cover. The results show that cloud cover was reduced above all regions during the last 22-year sub-period 1992-2014 throughout the year, but especially in winter. Finally, given the different nature of the utilized NCEP/NCAR (Reanalysis), MODIS (satellite) and ECAD (stations) cloud cover data sets, an inter-comparison is made among them as it concerns the intra-annual variation of cloud cover for the common period 2003-2014. The results show a nice similarity among the three datasets, with some differences in magnitude during the cold period of the year.

A Climatology of Fair-Weather Cloud Statistics at the Atmospheric Radiation Measurement Program Southern Great Plains Site: Temporal and Spatial Variability

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

Berg, Larry K.; Kassianov, Evgueni I.; Long, Charles N.

2006-03-30

In previous work, Berg and Stull (2005) developed a new parameterization for Fair-Weather Cumuli (FWC). Preliminary testing of the new scheme used data collected during a field experiment conducted during the summer of 1996. This campaign included a few research flights conducted over three locations within the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site. A more comprehensive verification of the new scheme requires a detailed climatology of FWC. Several cloud climatologies have been completed for the ACRF SGP, but these efforts have focused on either broad categories of clouds grouped by height and seasonmore » (e.g., Lazarus et al. 1999) or height and time of day (e.g., Dong et al. 2005). In these two examples, the low clouds were not separated by the type of cloud, either stratiform or cumuliform, nor were the horizontal chord length (the length of the cloud slice that passed directly overhead) or cloud aspect ratio (defined as the ratio of the cloud thickness to the cloud chord length) reported. Lane et al. (2002) presented distributions of cloud chord length, but only for one year. The work presented here addresses these shortcomings by looking explicitly at cases with FWC over five summers. Specifically, we will address the following questions: •Does the cloud fraction (CF), cloud-base height (CBH), and cloud-top height (CTH) of FWC change with the time of day or the year? •What is the distribution of FWC chord lengths? •Is there a relationship between the cloud chord length and the cloud thickness?« less

Effects of Cloud Properties on PM2.5 Levels in the Southeastern United States

NASA Astrophysics Data System (ADS)

Yu, C.; Zhang, X.; Liu, Y.

2012-12-01

The spatial and temporal characteristics of fine particulate matter (PM2.5) are increasingly being derived from satellite aerosol remote sensing data. A major concern of satellite-derived PM2.5 information is cloud cover, i.e., PM2.5 mass concentrations cannot be estimated from satellite observations under cloudy conditions. There has been little research on the effects of cloud properties on PM2.5 levels. In this study, we performed a statistical analysis of relationships between various cloud parameters and PM2.5 concentrations. We used 2005-2010 PM2.5 observations from 8 sites in the Southeastern Aerosol Research and Characterization (SEARCH) Network, and cloud parameters from MODIS cloud product retrievals from Terra and Aqua satellites. We find that cloud fraction (CF) is generally negatively correlated with the mean value of PM2.5 mass concentration. However, the largest mean value occurs when the cloud fraction is between 10% and 30% instead of lower cloud cover (CF < 10%). The mean value of PM2.5 decreased from 14.3μg/m3 during 10%~30% cloud fraction to 9.3μg/m3 in cloudy days (CF=100%), and the negative correlation is more significant during the summer and fall than spring and winter. In addition, Cloud top pressure (CTP) and cloud optical thickness (COT) also influence PM2.5 mass concentration, with CTP being positively correlated with PM2.5 while COT being negatively correlated. These results suggest that cloud parameters may be used as predictor variables in satellite models of PM2.5.

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

NASA Astrophysics Data System (ADS)

Lohmann, U.; Stier, P.; Hoose, C.; Ferrachat, S.; Kloster, S.; Roeckner, E.; Zhang, J.

2007-07-01

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.

Improvements to the CERES Cloud Detection Algorithm using Himawari 8 Data and Validation using CALIPSO and CATS Lidar Observations

NASA Astrophysics Data System (ADS)

Trepte, Q.; Minnis, P.; Palikonda, R.; Yost, C. R.; Rodier, S. D.; Trepte, C. R.; McGill, M. J.

2016-12-01

Geostationary satellites provide continuous cloud and meteorological observations important for weather forecasting and for understanding climate processes. The Himawari-8 satellite represents a new generation of measurement capabilities with significantly improved resolution and enhanced spectral information. The satellite was launched in October 2014 by the Japanese Meteorological Agency and is centered at 140° E to provide coverage over eastern Asia and the western Pacific region. A cloud detection algorithm was developed as part of the CERES Cloud Mask algorithm using the Advanced Himawari Imager (AHI), a 16 channel multi-spectral imager. The algorithm was originally designed for use with Meteosat Second Generation (MSG) data and has been adapted for Himawari-8 AHI measurements. This paper will describe the improvements in the Himawari cloud mask including daytime ocean low cloud and aerosol discrimination, nighttime thin cirrus detection, and Australian desert and coastal cloud detection. The statistics from matched CERES Himawari cloud mask results with CALIPSO lidar data and with new observations from the CATS lidar will also be presented. A feature of the CATS instrument on board the International Space Station is that it gives information at different solar viewing times to examine the diurnal variation of clouds and this provides an ability to evaluate the performance of the cloud mask for different sun angles.

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

PubMed

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Mid-infrared interferometry of AGNs: A statistical view into the dusty nuclear environment of the Seyfert Galaxies.

NASA Astrophysics Data System (ADS)

Lopez-Gonzaga, N.

2015-09-01

The high resolution achieved by the instrument MIDI at the VLTI allowed to obtain more detail information about the geometry and structure of the nuclear mid-infrared emission of AGNs, but due to the lack of real images, the interpretation of the results is not an easy task. To profit more from the high resolution data, we developed a statistical tool that allows interpret these data using clumpy torus models. A statistical approach is needed to overcome effects such as, the randomness in the position of the clouds and the uncertainty of the true position angle on the sky. Our results, obtained by studying the mid-infrared emission at the highest resolution currently available, suggest that the dusty environment of Type I objects is formed by a lower number of clouds than Type II objects.

The statistical distribution of aerosol properties in sourthern West Africa

NASA Astrophysics Data System (ADS)

Haslett, Sophie; Taylor, Jonathan; Flynn, Michael; Bower, Keith; Dorsey, James; Crawford, Ian; Brito, Joel; Denjean, Cyrielle; Bourrianne, Thierry; Burnet, Frederic; Batenburg, Anneke; Schulz, Christiane; Schneider, Johannes; Borrmann, Stephan; Sauer, Daniel; Duplissy, Jonathan; Lee, James; Vaughan, Adam; Coe, Hugh

2017-04-01

The population and economy in southern West Africa have been growing at an exceptional rate in recent years and this trend is expected to continue, with the population projected to more than double to 800 million by 2050. This will result in a dramatic increase in anthropogenic pollutants, already estimated to have tripled between 1950 and 2000 (Lamarque et al., 2010). It is known that aerosols can modify the radiative properties of clouds. As such, the entrainment of anthropogenic aerosol into the large banks of clouds forming during the onset of the West African Monsoon could have a substantial impact on the region's response to climate change. Such projections, however, are greatly limited by the scarcity of observations in this part of the world. As part of the Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA) project, three research aircraft were deployed, each carrying equipment capable of measuring aerosol properties in-situ. Instrumentation included Aerosol Mass Spectrometers (AMS), Single Particle Soot Photometers (SP2), Condensation Particle Counters (CPC) and Scanning Mobility Particle Sizers (SMPS). Throughout the intensive aircraft campaign, 155 hours of scientific flights covered an area including large parts of Benin, Togo, Ghana and parts of Côte D'Ivoire. Approximately 70 hours were dedicated to the measurement of cloud-aerosol interactions, with many other flights producing data contributing towards this objective. Using datasets collected during this campaign period, it is possible to build a robust statistical understanding of aerosol properties in this region for the first time, including size distributions and optical and chemical properties. Here, we describe preliminary results from aerosol measurements on board the three aircraft. These have been used to describe aerosol properties throughout the region and time period encompassed by the DACCIWA aircraft campaign. Such statistics will be invaluable for improving future projections of cloud properties and radiative effects in the region.

The role of the GABRA2 polymorphism in multiplex alcohol dependence families with minimal comorbidity: within-family association and linkage analyses.

PubMed

Matthews, Abigail G; Hoffman, Eric K; Zezza, Nicholas; Stiffler, Scott; Hill, Shirley Y

2007-09-01

The genes encoding the gamma-aminobutyric acid(A) (GABA(A)) receptor have been the focus of several recent studies investigating the genetic etiology of alcohol dependence. Analyses of multiplex families found a particular gene, GABRA2, to be highly associated with alcohol dependence, using within-family association tests and other methods. Results were confirmed in three case-control studies. The objective of this study was to investigate the GABRA2 gene in another collection of multiplex families. Analyses were based on phenotypic and genotypic data available for 330 individuals from 65 bigenerational pedigrees with a total of 232 alcohol-dependent subjects. A proband pair of same-sex siblings meeting Diagnostic and Statistical Manual of Mental Disorders, Third Edition, criteria for alcohol dependence was required for entry of a family into the study. One member of the proband pair was identified while in treatment for alcohol dependence. Linkage and association of GABRA2 and alcohol dependence were evaluated using SIBPAL (a nonparametric linkage package) and both the Pedigree Disequilibrium Test and the Family-Based Association Test, respectively. We find no evidence of a relationship between GABRA2 and alcohol dependence. Linkage analyses exhibited no linkage using affected/affected, affected/unaffected, and unaffected/unaffected sib pairs (all p's < .13). There was no evidence of a within-family association (all p's > .39). Comorbidity may explain why our results differ from those in the literature. The presence of primary drug dependence and/or other psychiatric disorders is minimal in our pedigrees, although several of the other previously published multiplex family analyses exhibit a greater degree of comorbidity.

Phase division multiplexed EIT for enhanced temporal resolution.

PubMed

Dowrick, T; Holder, D

2018-03-29

The most commonly used EIT paradigm (time division multiplexing) limits the temporal resolution of impedance images due to the need to switch between injection electrodes. Advances have previously been made using frequency division multiplexing (FDM) to increase temporal resolution, but in cases where a fixed range of frequencies is available, such as imaging fast neural activity, an upper limit is placed on the total number of simultaneous injections. The use of phase division multiplexing (PDM) where multiple out of phase signals can be injected at each frequency is investigated to increase temporal resolution. TDM, FDM and PDM were compared in head tank experiments, to compare transfer impedance measurements and spatial resolution between the three techniques. A resistor phantom paradigm was established to investigate the imaging of one-off impedance changes, of magnitude 1% and with durations as low as 500 µs (similar to those seen in nerve bundles), using both PDM and TDM approaches. In head tank experiments, a strong correlation (r  >  0.85 and p  <  0.001) was present between the three sets of measured transfer impedances, and no statistically significant difference was found in reconstructed image quality. PDM was able to image impedance changes down to 500 µs in the phantom experiments, while the minimum duration imaged using TDM was 5 ms. PDM offers a possible solution to the imaging of fast moving impedance changes (such as in nerves), where the use of triggering or coherent averaging is not possible. The temporal resolution presents an order of magnitude improvement of the TDM approach, and the approach addresses the limited spatial resolution of FDM by increasing the number of simultaneous EIT injections.

Life Cycle of Tropical Convection and Anvil in Observations and Models

NASA Astrophysics Data System (ADS)

McFarlane, S. A.; Hagos, S. M.; Comstock, J. M.

2011-12-01

Tropical convective clouds are important elements of the hydrological cycle and produce extensive cirrus anvils that strongly affect the tropical radiative energy balance. To improve simulations of the global water and energy cycles and accurately predict both precipitation and cloud radiative feedbacks, models need to realistically simulate the lifecycle of tropical convection, including the formation and radiative properties of ice anvil clouds. By combining remote sensing datasets from precipitation and cloud radars at the Atmospheric Radiation Measurement (ARM) Darwin site with geostationary satellite data, we can develop observational understanding of the lifetime of convective systems and the links between the properties of convective systems and their associated anvil clouds. The relationships between convection and anvil in model simulations can then be compared to those seen in the observations to identify areas for improvement in the model simulations. We identify and track tropical convective systems in the Tropical Western Pacific using geostationary satellite observations. We present statistics of the tropical convective systems including size, age, and intensity and classify the lifecycle stage of each system as developing, mature, or dissipating. For systems that cross over the ARM Darwin site, information on convective intensity and anvil properties are obtained from the C-Pol precipitation radar and MMCR cloud radar, respectively, and are examined as a function of the system lifecycle. Initial results from applying the convective identification and tracking algorithm to a tropical simulation from the Weather Research and Forecasting (WRF) model run show that the model produces reasonable overall statistics of convective systems, but details of the life cycle (such as diurnal cycle, system tracks) differ from the observations. Further work will focus on the role of atmospheric temperature and moisture profiles in the model's convective life cycle.

FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption

PubMed Central

2015-01-01

Background The increasing availability of genome data motivates massive research studies in personalized treatment and precision medicine. Public cloud services provide a flexible way to mitigate the storage and computation burden in conducting genome-wide association studies (GWAS). However, data privacy has been widely concerned when sharing the sensitive information in a cloud environment. Methods We presented a novel framework (FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption) to fully outsource GWAS (i.e., chi-square statistic computation) using homomorphic encryption. The proposed framework enables secure divisions over encrypted data. We introduced two division protocols (i.e., secure errorless division and secure approximation division) with a trade-off between complexity and accuracy in computing chi-square statistics. Results The proposed framework was evaluated for the task of chi-square statistic computation with two case-control datasets from the 2015 iDASH genome privacy protection challenge. Experimental results show that the performance of FORESEE can be significantly improved through algorithmic optimization and parallel computation. Remarkably, the secure approximation division provides significant performance gain, but without missing any significance SNPs in the chi-square association test using the aforementioned datasets. Conclusions Unlike many existing HME based studies, in which final results need to be computed by the data owner due to the lack of the secure division operation, the proposed FORESEE framework support complete outsourcing to the cloud and output the final encrypted chi-square statistics. PMID:26733391

FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption.

PubMed

Zhang, Yuchen; Dai, Wenrui; Jiang, Xiaoqian; Xiong, Hongkai; Wang, Shuang

2015-01-01

The increasing availability of genome data motivates massive research studies in personalized treatment and precision medicine. Public cloud services provide a flexible way to mitigate the storage and computation burden in conducting genome-wide association studies (GWAS). However, data privacy has been widely concerned when sharing the sensitive information in a cloud environment. We presented a novel framework (FORESEE: Fully Outsourced secuRe gEnome Study basEd on homomorphic Encryption) to fully outsource GWAS (i.e., chi-square statistic computation) using homomorphic encryption. The proposed framework enables secure divisions over encrypted data. We introduced two division protocols (i.e., secure errorless division and secure approximation division) with a trade-off between complexity and accuracy in computing chi-square statistics. The proposed framework was evaluated for the task of chi-square statistic computation with two case-control datasets from the 2015 iDASH genome privacy protection challenge. Experimental results show that the performance of FORESEE can be significantly improved through algorithmic optimization and parallel computation. Remarkably, the secure approximation division provides significant performance gain, but without missing any significance SNPs in the chi-square association test using the aforementioned datasets. Unlike many existing HME based studies, in which final results need to be computed by the data owner due to the lack of the secure division operation, the proposed FORESEE framework support complete outsourcing to the cloud and output the final encrypted chi-square statistics.

16 year climatology of cirrus clouds over a tropical station in southern India using ground and space-based lidar observations

NASA Astrophysics Data System (ADS)

Pandit, A. K.; Gadhavi, H. S.; Venkat Ratnam, M.; Raghunath, K.; Rao, S. V. B.; Jayaraman, A.

2015-06-01

16 year (1998-2013) climatology of cirrus clouds and their macrophysical (base height, top height and geometrical thickness) and optical properties (cloud optical thickness) observed using a ground-based lidar over Gadanki (13.5° N, 79.2° E), India, is presented. The climatology obtained from the ground-based lidar is compared with the climatology obtained from seven and half years (June 2006-December 2013) of Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) observations. A very good agreement is found between the two climatologies in spite of their opposite viewing geometries and difference in sampling frequencies. Nearly 50-55% of cirrus clouds were found to possess geometrical thickness less than 2 km. Ground-based lidar is found to detect more number of sub-visible clouds than CALIOP which has implications for global warming studies as sub-visible cirrus clouds have significant positive radiative forcing. Cirrus clouds with mid-cloud temperatures between -50 to -70 °C have a mean geometrical thickness greater than 2 km in contrast to the earlier reported value of 1.7 km. Trend analyses reveal a statistically significant increase in the altitude of sub-visible cirrus clouds which is consistent with the recent climate model simulations. Also, the fraction of sub-visible cirrus cloud is found to be increasing during the last sixteen years (1998 to 2013) which has implications to the temperature and water vapour budget in the tropical tropopause layer.

HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

NASA Astrophysics Data System (ADS)

Beck, Alexander; Henneberger, Jan; Schöpfer, Sarah; Fugal, Jacob; Lohmann, Ulrike

2017-02-01

In situ observations of cloud properties in complex alpine terrain where research aircraft cannot sample are commonly conducted at mountain-top research stations and limited to single-point measurements. The HoloGondel platform overcomes this limitation by using a cable car to obtain vertical profiles of the microphysical and meteorological cloud parameters. The main component of the HoloGondel platform is the HOLographic Imager for Microscopic Objects (HOLIMO 3G), which uses digital in-line holography to image cloud particles. Based on two-dimensional images the microphysical cloud parameters for the size range from small cloud particles to large precipitation particles are obtained for the liquid and ice phase. The low traveling velocity of a cable car on the order of 10 m s-1 allows measurements with high spatial resolution; however, at the same time it leads to an unstable air speed towards the HoloGondel platform. Holographic cloud imagers, which have a sample volume that is independent of the air speed, are therefore well suited for measurements on a cable car. Example measurements of the vertical profiles observed in a liquid cloud and a mixed-phase cloud at the Eggishorn in the Swiss Alps in the winters 2015 and 2016 are presented. The HoloGondel platform reliably observes cloud droplets larger than 6.5 µm, partitions between cloud droplets and ice crystals for a size larger than 25 µm and obtains a statistically significantly size distribution for every 5 m in vertical ascent.

Architecture Design and Experimental Platform Demonstration of Optical Network based on OpenFlow Protocol

NASA Astrophysics Data System (ADS)

Xing, Fangyuan; Wang, Honghuan; Yin, Hongxi; Li, Ming; Luo, Shenzi; Wu, Chenguang

2016-02-01

With the extensive application of cloud computing and data centres, as well as the constantly emerging services, the big data with the burst characteristic has brought huge challenges to optical networks. Consequently, the software defined optical network (SDON) that combines optical networks with software defined network (SDN), has attracted much attention. In this paper, an OpenFlow-enabled optical node employed in optical cross-connect (OXC) and reconfigurable optical add/drop multiplexer (ROADM), is proposed. An open source OpenFlow controller is extended on routing strategies. In addition, the experiment platform based on OpenFlow protocol for software defined optical network, is designed. The feasibility and availability of the OpenFlow-enabled optical nodes and the extended OpenFlow controller are validated by the connectivity test, protection switching and load balancing experiments in this test platform.

A multilinear regression methodology to analyze the effect of atmospheric and surface forcing on Arctic clouds

NASA Astrophysics Data System (ADS)

Boeke, R.; Taylor, P. C.; Li, Y.

2017-12-01

Arctic cloud amount as simulated in CMIP5 models displays large intermodel spread- models disagree on the processes important for cloud formation as well as the radiative impact of clouds. The radiative response to cloud forcing can be better assessed when the drivers of Arctic cloud formation are known. Arctic cloud amount (CA) is a function of both atmospheric and surface conditions, and it is crucial to separate the influences of unique processes to understand why the models are different. This study uses a multilinear regression methodology to determine cloud changes using 3 variables as predictors: lower tropospheric stability (LTS), 500-hPa vertical velocity (ω500), and sea ice concentration (SIC). These three explanatory variables were chosen because their effects on clouds can be attributed to unique climate processes: LTS is a thermodynamic indicator of the relationship between clouds and atmospheric stability, SIC determines the interaction between clouds and the surface, and ω500 is a metric for dynamical change. Vertical, seasonal profiles of necessary variables are obtained from the Coupled Model Intercomparison Project 5 (CMIP5) historical simulation, an ocean-atmosphere couple model forced with the best-estimate natural and anthropogenic radiative forcing from 1850-2005, and statistical significance tests are used to confirm the regression equation. A unique heuristic model will be constructed for each climate model and for observations, and models will be tested by their ability to capture the observed cloud amount and behavior. Lastly, the intermodel spread in Arctic cloud amount will be attributed to individual processes, ranking the relative contributions of each factor to shed light on emergent constraints in the Arctic cloud radiative effect.

Machine learning based cloud mask algorithm driven by radiative transfer modeling

NASA Astrophysics Data System (ADS)

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.

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

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

Huang, Dong; Liu, Yangang

2014-12-18

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost,more » allowing for more realistic representation of cloud radiation interactions in large-scale models.« less

Addressing scale dependence in roughness and morphometric statistics derived from point cloud data.

NASA Astrophysics Data System (ADS)

Buscombe, D.; Wheaton, J. M.; Hensleigh, J.; Grams, P. E.; Welcker, C. W.; Anderson, K.; Kaplinski, M. A.

2015-12-01

The heights of natural surfaces can be measured with such spatial density that almost the entire spectrum of physical roughness scales can be characterized, down to the morphological form and grain scales. With an ability to measure 'microtopography' comes a demand for analytical/computational tools for spatially explicit statistical characterization of surface roughness. Detrended standard deviation of surface heights is a popular means to create continuous maps of roughness from point cloud data, using moving windows and reporting window-centered statistics of variations from a trend surface. If 'roughness' is the statistical variation in the distribution of relief of a surface, then 'texture' is the frequency of change and spatial arrangement of roughness. The variance in surface height as a function of frequency obeys a power law. In consequence, roughness is dependent on the window size through which it is examined, which has a number of potential disadvantages: 1) the choice of window size becomes crucial, and obstructs comparisons between data; 2) if windows are large relative to multiple roughness scales, it is harder to discriminate between those scales; 3) if roughness is not scaled by the texture length scale, information on the spacing and clustering of roughness `elements' can be lost; and 4) such practice is not amenable to models describing the scattering of light and sound from rough natural surfaces. We discuss the relationship between roughness and texture. Some useful parameters which scale vertical roughness to characteristic horizontal length scales are suggested, with examples of bathymetric point clouds obtained using multibeam from two contrasting riverbeds, namely those of the Colorado River in Grand Canyon, and the Snake River in Hells Canyon. Such work, aside from automated texture characterization and texture segmentation, roughness and grain size calculation, might also be useful for feature detection and classification from point clouds.

Are CO Observations of Interstellar Clouds Tracing the H2?

NASA Astrophysics Data System (ADS)

Federrath, Christoph; Glover, S. C. O.; Klessen, R. S.; Mac Low, M.

2010-01-01

Interstellar clouds are commonly observed through the emission of rotational transitions from carbon monoxide (CO). However, the abundance ratio of CO to molecular hydrogen (H2), which is the most abundant molecule in molecular clouds is only about 10-4. This raises the important question of whether the observed CO emission is actually tracing the bulk of the gas in these clouds, and whether it can be used to derive quantities like the total mass of the cloud, the gas density distribution function, the fractal dimension, and the velocity dispersion--size relation. To evaluate the usability and accuracy of CO as a tracer for H2 gas, we generate synthetic observations of hydrodynamical models that include a detailed chemical network to follow the formation and photo-dissociation of H2 and CO. These three-dimensional models of turbulent interstellar cloud formation self-consistently follow the coupled thermal, dynamical and chemical evolution of 32 species, with a particular focus on H2 and CO (Glover et al. 2009). We find that CO primarily traces the dense gas in the clouds, however, with a significant scatter due to turbulent mixing and self-shielding of H2 and CO. The H2 probability distribution function (PDF) is well-described by a log-normal distribution. In contrast, the CO column density PDF has a strongly non-Gaussian low-density wing, not at all consistent with a log-normal distribution. Centroid velocity statistics show that CO is more intermittent than H2, leading to an overestimate of the velocity scaling exponent in the velocity dispersion--size relation. With our systematic comparison of H2 and CO data from the numerical models, we hope to provide a statistical formula to correct for the bias of CO observations. CF acknowledges financial support from a Kade Fellowship of the American Museum of Natural History.

Effects of atmospheric dynamics and aerosols on the fraction of supercooled water clouds

NASA Astrophysics Data System (ADS)

Li, Jiming; Lv, Qiaoyi; Zhang, Min; Wang, Tianhe; Kawamoto, Kazuaki; Chen, Siyu; Zhang, Beidou

2017-02-01

Based on 8 years of (January 2008-December 2015) cloud phase information from the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP), aerosol products from CALIPSO and meteorological parameters from the ERA-Interim products, the present study investigates the effects of atmospheric dynamics on the supercooled liquid cloud fraction (SCF) during nighttime under different aerosol loadings at global scale to better understand the conditions of supercooled liquid water gradually transforming to ice phase. Statistical results indicate that aerosols' effect on nucleation cannot fully explain all SCF changes, especially in those regions where aerosols' effect on nucleation is not a first-order influence (e.g., due to low ice nuclei aerosol frequency). By performing the temporal and spatial correlations between SCFs and different meteorological factors, this study presents specifically the relationship between SCF and different meteorological parameters under different aerosol loadings on a global scale. We find that the SCFs almost decrease with increasing of aerosol loading, and the SCF variation is closely related to the meteorological parameters but their temporal relationship is not stable and varies with the different regions, seasons and isotherm levels. Obviously negative temporal correlations between SCFs versus vertical velocity and relative humidity indicate that the higher vertical velocity and relative humidity the smaller SCFs. However, the patterns of temporal correlation for lower-tropospheric static stability, skin temperature and horizontal wind are relatively more complex than those of vertical velocity and humidity. For example, their close correlations are predominantly located in middle and high latitudes and vary with latitude or surface type. Although these statistical correlations have not been used to establish a certain causal relationship, our results may provide a unique point of view on the phase change of mixed-phase cloud and have potential implications for further improving the parameterization of the cloud phase and determining the climate feedbacks.

Planck intermediate results: XXXV. Probing the role of the magnetic field in the formation of structure in molecular clouds

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Alves, M. I. R.; ...

2016-02-09

Within ten nearby (d < 450 pc) Gould belt molecular clouds we evaluate in this paper statistically the relative orientation between the magnetic field projected on the plane of sky, inferred from the polarized thermal emission of Galactic dust observed by Planck at 353 GHz, and the gas column density structures, quantified by the gradient of the column density, N H. The selected regions, covering several degrees in size, are analysed at an effective angular resolution of 10' FWHM, thus sampling physical scales from 0.4 to 40 pc in the nearest cloud. The column densities in the selected regions rangemore » from N H≈ 10 21 to10 23 cm -2, and hence they correspond to the bulk of the molecular clouds. The relative orientation is evaluated pixel by pixel and analysed in bins of column density using the novel statistical tool called “histogram of relative orientations”. Throughout this study, we assume that the polarized emission observed by Planck at 353 GHz is representative of the projected morphology of the magnetic field in each region, i.e., we assume a constant dust grain alignment efficiency, independent of the local environment. Within most clouds we find that the relative orientation changes progressively with increasing N H, from mostly parallel or having no preferred orientation to mostly perpendicular. In simulations of magnetohydrodynamic turbulence in molecular clouds this trend in relative orientation is a signature of Alfvénic or sub-Alfvénic turbulence, implying that the magnetic field is significant for the gas dynamics at the scales probed by Planck. Finally, we compare the deduced magnetic field strength with estimates we obtain from other methods and discuss the implications of the Planck observations for the general picture of molecular cloud formation and evolution.« less

Are ship tracks useful analogs for studying the aerosol indirect effect?

NASA Astrophysics Data System (ADS)

Christensen, M.; Toll, V.; Stephens, G. L.

2017-12-01

Vessels transiting the ocean sometimes leave their mark on the clouds - leaving behind reflective cloud lines, known as ship tracks. Ship tracks have been looked upon by some as a possible Rosetta Stone connecting the effects of changing aerosol over the ocean and cloud albedo effects on climate (Porch et al. 1990, Atmos. Enviorn., 1051-1059). In this research, we establish whether ship tracks, and volcano tracks - a natural analog, can be used to relate these cloud-scale perturbations to the aerosol effects occurring at larger regional-scales. Two databases containing over 1,500 ship and 900 volcano tracks, all carefully hand-selected from satellite imagery, are utilized; showing that ship tracks exhibit very similar cloud albedo effect responses to that of volcano tracks. For comparison, our global dataset utilises over 7 million CloudSat profiles consisting of single-layer marine warm cloud in which the retrievals are co-located with the MODerate Imaging Spectroradiometer (MODIS) product so that statistical relationships between aerosol and cloud can be computed over 4x4 degree regions. All datasets show the same key physical processes that govern the cloud-aerosol indirect effect, namely, the strong negative responses in cloud droplet size and the bidirectional responses in liquid water path and cloud albedo depending on the meteorological conditions. Finally, this analysis is extended to a comparison against several general circulation models where it is suggested that key processes such as cloud-top entrainment and evaporation that regulates against strong liquid water path responses are likely underrepresented in most models.

Long-term observation of aerosol cloud relationships in the Mid-Atlantic region

NASA Astrophysics Data System (ADS)

Li, S.; Joseph, E.; Min, Q.; Yin, B.

2013-12-01

Long-term ground-based observations of aerosol and cloud properties derived from measurements of Multifilter Rotating Shadow Band Radiometer and microwave radiometer at an atmospheric measurement field station in the Baltimore-Washington corridor operated by Howard University are used to examine the temporal variation of aerosol and cloud properties and moreover aerosol indirect effect on clouds. Through statistical analysis of five years (from 2006 to 2010) of these observations, the proportion of polluted cases is found larger in 2006 and 2007 and the proportion of optically thick clouds cases is also larger in 2006 and 2007 than that in 2008, 2009 and 2010. Both the mean aerosol optical depth (AOD) and cloud optical depth (COD) are observed decreasing from 2006 to 2010 but there is no obvious trend observed on cloud liquid water path (LWP). Because of the limit of AOD retrievals under cloudy conditions surface measurements of fine particle particulate matter 2.5 (PM2.5) were used for assessing aerosol indirect effect. A positive relationship between LWP and cloud droplets effective radius (Re) and a negative relationship between PM2.5 and Re are observed based on a stringent case selection method which is used to reduce the uncertainties from retrieval and meteorological impacts. The total 5 years summer time observations are segregated according to the value of PM2.5. Examination of distributions of COD, cloud condensation nuclei (CCN), cloud droplets effective radius and LWP under polluted and pristine conditions further confirm that the high aerosol loading decreases cloud droplets effective radius and increases cloud optical depth.

Beyond multi-fractals: surrogate time series and fields

NASA Astrophysics Data System (ADS)

Venema, V.; Simmer, C.

2007-12-01

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

A Spread-Spectrum SQUID Multiplexer

NASA Astrophysics Data System (ADS)

Irwin, K. D.; Chaudhuri, S.; Cho, H.-M.; Dawson, C.; Kuenstner, S.; Li, D.; Titus, C. J.; Young, B. A.

2018-06-01

The transition-edge sensor (TES) is a mature, high-resolution x-ray spectrometer technology that provides a much higher efficiency than dispersive spectrometers such as gratings and crystal spectrometers. As larger arrays are developed, time-division multiplexing schemes operating at MHz frequencies are being replaced by microwave SQUID multiplexers using frequency-division multiplexing at GHz frequencies. However, the multiplexing factor achievable with microwave SQUIDs is limited by the high slew rate on the leading edge of x-ray pulses. In this paper, we propose a new multiplexing scheme for high-slew-rate TES x-ray calorimeters: the spread-spectrum SQUID multiplexer, which has the potential to enable higher multiplexing factors, especially in applications with lower photon-arrival rates.

Lagrangian large eddy simulations of boundary layer clouds on ERA-Interim and ERA5 trajectories

NASA Astrophysics Data System (ADS)

Kazil, J.; Feingold, G.; Yamaguchi, T.

2017-12-01

This exploratory study examines Lagrangian large eddy simulations of boundary layer clouds along wind trajectories from the ERA-Interim and ERA5 reanalyses. The study is motivated by the need for statistically representative sets of high resolution simulations of cloud field evolution in realistic meteorological conditions. The study will serve as a foundation for the investigation of biomass burning effects on the transition from stratocumulus to shallow cumulus clouds in the South-East Atlantic. Trajectories that pass through a location with radiosonde data (St. Helena) and which exhibit a well-defined cloud structure and evolution were identified in satellite imagery, and sea surface temperature and atmospheric vertical profiles along the trajectories were extracted from the reanalysis data sets. The System for Atmospheric Modeling (SAM) simulated boundary layer turbulence and cloud properties along the trajectories. Mean temperature and moisture (in the free troposphere) and mean wind speed (at all levels) were nudged towards the reanalysis data. Atmospheric and cloud properties in the large eddy simulations were compared with those from the reanalysis products, and evaluated with satellite imagery and radiosonde data. Simulations using ERA-Interim data and the higher resolution ERA5 data are contrasted.

Arctic Clouds Infrared Imaging Field Campaign Report

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

Shaw, J. A.

2016-03-01

The Infrared Cloud Imager (ICI), a passive thermal imaging system, was deployed at the North Slope of Alaska site in Barrow, Alaska, from July 2012 to July 2014 for measuring spatial-temporal cloud statistics. Thermal imaging of the sky from the ground provides high radiometric contrast during night and polar winter when visible sensors and downward-viewing thermal sensors experience low contrast. In addition to demonstrating successful operation in the Arctic for an extended period and providing data for Arctic cloud studies, a primary objective of this deployment was to validate novel instrument calibration algorithms that will allow more compact ICI instrumentsmore » to be deployed without the added expense, weight, size, and operational difficulty of a large-aperture onboard blackbody calibration source. This objective was successfully completed with a comparison of the two-year data set calibrated with and without the onboard blackbody. The two different calibration methods produced daily-average cloud amount data sets with correlation coefficient = 0.99, mean difference = 0.0029 (i.e., 0.29% cloudiness), and a difference standard deviation = 0.054. Finally, the ICI instrument generally detected more thin clouds than reported by other ARM cloud products available as of late 2015.« less

Clouds in GEOS-5

NASA Technical Reports Server (NTRS)

Bacmeister, Julio; Rienecker, Michele; Suarez, Max; Norris, Peter

2007-01-01

The GEOS-5 atmospheric model is being developed as a weather-and-climate capable model. It must perform well in assimilation mode as well as in weather and climate simulations and forecasts and in coupled chemistry-climate simulations. In developing GEOS-5, attention has focused on the representation of moist processes. The moist physics package uses a single phase prognostic condensate and a prognostic cloud fraction. Two separate cloud types are distinguished by their source: "anvil" cloud originates in detraining convection, and large-scale cloud originates in a PDF-based condensation calculation. Ice and liquid phases for each cloud type are considered. Once created, condensate and fraction from the anvil and statistical cloud types experience the same loss processes: evaporation of condensate and fraction, auto-conversion of liquid or mixed phase condensate, sedimentation of frozen condensate, and accretion of condensate by falling precipitation. The convective parameterization scheme is the Relaxed Arakawa-Schubert, or RAS, scheme. Satellite data are used to evaluate the performance of the moist physics packages and help in their tuning. In addition, analysis of and comparisons to cloud-resolving models such as the Goddard Cumulus Ensemble model are used to help improve the PDFs used in the moist physics. The presentation will show some of our evaluations including precipitation diagnostics.

Multiplexed image storage by electromagnetically induced transparency in a solid

NASA Astrophysics Data System (ADS)

Heinze, G.; Rentzsch, N.; Halfmann, T.

2012-11-01

We report on frequency- and angle-multiplexed image storage by electromagnetically induced transparency (EIT) in a Pr3+:Y2SiO5 crystal. Frequency multiplexing by EIT relies on simultaneous storage of light pulses in atomic coherences, driven in different frequency ensembles of the inhomogeneously broadened solid medium. Angular multiplexing by EIT relies on phase matching of the driving laser beams, which permits simultaneous storage of light pulses propagating under different angles into the crystal. We apply the multiplexing techniques to increase the storage capacity of the EIT-driven optical memory, in particular to implement multiplexed storage of larger two-dimensional amounts of data (images). We demonstrate selective storage and readout of images by frequency-multiplexed EIT and angular-multiplexed EIT, as well as the potential to combine both multiplexing approaches towards further enhanced storage capacities.

Discrimination Between Clouds and Snow in Landsat 8 Imagery: an Assessment of Current Methods and a New Approach

NASA Astrophysics Data System (ADS)

Stillinger, T.; Dozier, J.; Phares, N.; Rittger, K.

2015-12-01

Discrimination between snow and clouds poses a serious but tractable challenge to the consistent delivery of high-quality information on mountain snow from remote sensing. Clouds obstruct the surface from the sensor's view, and the similar optical properties of clouds and snow make accurate discrimination difficult. We assess the performance of the current Landsat 8 operational snow and cloud mask products (LDCM CCA and CFmask), along with a new method, using over one million manually identified snow and clouds pixels in Landsat 8 scenes. The new method uses physically based scattering models to generate spectra in each Landsat 8 band, at that scene's solar illumination, for snow and cloud particle sizes that cover the plausible range for each. The modeled spectra are compared to pixels' spectra via several independent ways to identify snow and clouds. The results are synthesized to create a final snow/cloud mask, and the method can be applied to any multispectral imager with bands covering the visible, near-infrared, and shortwave-infrared regions. Each algorithm we tested misidentifies snow and clouds in both directions to varying degrees. We assess performance with measures of Precision, Recall, and the F statistic, which are based on counts of true and false positives and negatives. Tests for significance in differences between spectra in the measured and modeled values among incorrectly identified pixels help ascertain reasons for misidentification. A cloud mask specifically designed to separate snow from clouds is a valuable tool for those interested in remotely sensing snow cover. Given freely available remote sensing datasets and computational tools to feasibly process entire mission histories for an area of interest, enabling researchers to reliably identify and separate snow and clouds increases the usability of the data for hydrological and climatological studies.

View-angle-dependent AIRS Cloudiness and Radiance Variance: Analysis and Interpretation

NASA Technical Reports Server (NTRS)

Gong, Jie; Wu, Dong L.

2013-01-01

Upper tropospheric clouds play an important role in the global energy budget and hydrological cycle. Significant view-angle asymmetry has been observed in upper-level tropical clouds derived from eight years of Atmospheric Infrared Sounder (AIRS) 15 um radiances. Here, we find that the asymmetry also exists in the extra-tropics. It is larger during day than that during night, more prominent near elevated terrain, and closely associated with deep convection and wind shear. The cloud radiance variance, a proxy for cloud inhomogeneity, has consistent characteristics of the asymmetry to those in the AIRS cloudiness. The leading causes of the view-dependent cloudiness asymmetry are the local time difference and small-scale organized cloud structures. The local time difference (1-1.5 hr) of upper-level (UL) clouds between two AIRS outermost views can create parts of the observed asymmetry. On the other hand, small-scale tilted and banded structures of the UL clouds can induce about half of the observed view-angle dependent differences in the AIRS cloud radiances and their variances. This estimate is inferred from analogous study using Microwave Humidity Sounder (MHS) radiances observed during the period of time when there were simultaneous measurements at two different view-angles from NOAA-18 and -19 satellites. The existence of tilted cloud structures and asymmetric 15 um and 6.7 um cloud radiances implies that cloud statistics would be view-angle dependent, and should be taken into account in radiative transfer calculations, measurement uncertainty evaluations and cloud climatology investigations. In addition, the momentum forcing in the upper troposphere from tilted clouds is also likely asymmetric, which can affect atmospheric circulation anisotropically.

Cloud Coverage and Height Distribution from the GLAS Polar Orbiting Lidar: Comparison to Passive Cloud Retrievals

NASA Technical Reports Server (NTRS)

Spinhime, J. D.; Palm, S. P.; Hlavka, D. L.; Hart, W. D.; Mahesh, A.

2004-01-01

The Geoscience Laser Altimeter System (GLAS) began full on orbit operations in September 2003. A main application of the two-wavelength GLAS lidar is highly accurate detection and profiling of global cloud cover. Initial analysis indicates that cloud and aerosol layers are consistently detected on a global basis to cross-sections down to 10(exp -6) per meter. Images of the lidar data dramatically and accurately show the vertical structure of cloud and aerosol to the limit of signal attenuation. The GLAS lidar has made the most accurate measurement of global cloud coverage and height to date. In addition to the calibrated lidar signal, GLAS data products include multi level boundaries and optical depth of all transmissive layers. Processing includes a multi-variable separation of cloud and aerosol layers. An initial application of the data results is to compare monthly cloud means from several months of GLAS observations in 2003 to existing cloud climatologies from other satellite measurement. In some cases direct comparison to passive cloud retrievals is possible. A limitation of the lidar measurements is nadir only sampling. However monthly means exhibit reasonably good global statistics and coverage results, at other than polar regions, compare well with other measurements but show significant differences in height distribution. For polar regions where passive cloud retrievals are problematic and where orbit track density is greatest, the GLAS results are particularly an advance in cloud cover information. Direct comparison to MODIS retrievals show a better than 90% agreement in cloud detection for daytime, but less than 60% at night. Height retrievals are in much less agreement. GLAS is a part of the NASA EOS project and data products are thus openly available to the science community (see http://glo.gsfc.nasa.gov).

Normalized vertical ice mass flux profiles from vertically pointing 8-mm-wavelength Doppler radar

NASA Technical Reports Server (NTRS)

Orr, Brad W.; Kropfli, Robert A.

1993-01-01

During the FIRE 2 (First International Satellite Cloud Climatology Project Regional Experiment) project, NOAA's Wave Propagation Laboratory (WPL) operated its 8-mm wavelength Doppler radar extensively in the vertically pointing mode. This allowed for the calculation of a number of important cirrus cloud parameters, including cloud boundary statistics, cloud particle characteristic sizes and concentrations, and ice mass content (imc). The flux of imc, or, alternatively, ice mass flux (imf), is also an important parameter of a cirrus cloud system. Ice mass flux is important in the vertical redistribution of water substance and thus, in part, determines the cloud evolution. It is important for the development of cloud parameterizations to be able to define the essential physical characteristics of large populations of clouds in the simplest possible way. One method would be to normalize profiles of observed cloud properties, such as those mentioned above, in ways similar to those used in the convective boundary layer. The height then scales from 0.0 at cloud base to 1.0 at cloud top, and the measured cloud parameter scales by its maximum value so that all normalized profiles have 1.0 as their maximum value. The goal is that there will be a 'universal' shape to profiles of the normalized data. This idea was applied to estimates of imf calculated from data obtained by the WPL cloud radar during FIRE II. Other quantities such as median particle diameter, concentration, and ice mass content can also be estimated with this radar, and we expect to also examine normalized profiles of these quantities in time for the 1993 FIRE II meeting.

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

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

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

NASA Astrophysics Data System (ADS)

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 (Bz<0) and the By component duskward (By>0). 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.

Cloud regimes as phase transitions

NASA Astrophysics Data System (ADS)

Stechmann, Samuel; Hottovy, Scott

2017-11-01

Clouds are repeatedly identified as a leading source of uncertainty in future climate predictions. Of particular importance are stratocumulus clouds, which can appear as either (i) closed cells that reflect solar radiation back to space or (ii) open cells that allow solar radiation to reach the Earth's surface. Here we show that these clouds regimes - open versus closed cells - fit the paradigm of a phase transition. In addition, this paradigm characterizes pockets of open cells (POCs) as the interface between the open- and closed-cell regimes, and it identifies shallow cumulus clouds as a regime of higher variability. This behavior can be understood using an idealized model for the dynamics of atmospheric water as a stochastic diffusion process. Similar viewpoints of deep convection and self-organized criticality will also be discussed. With these new conceptual viewpoints, ideas from statistical mechanics could potentially be used for understanding uncertainties related to clouds in the climate system and climate predictions. The research of S.N.S. is partially supported by a Sloan Research Fellowship, ONR Young Investigator Award N00014-12-1-0744, and ONR MURI Grant N00014-12-1-0912.

Power availability at terrestrial receptor sites for laser-power transmission from the satellite power system

NASA Technical Reports Server (NTRS)

Beverly, R. E., III

1982-01-01

A statistical model was developed for relating the temporal transmission parameters of a laser beam from a solar power satellite to observable meteorological data to determine the influence of weather on power reception at the earth-based receiver. Sites within 100 miles of existing high voltage transmission lines were examined and the model was developed for clear-sky and clouded conditions. The cases of total transmission through clouds at certain wavelengths, no transmission, and partial transmission were calculated for the cloud portion of the model. The study covered cirriform, stratiform, cumiliform, and mixed type clouds and the possibility of boring holes through the clouds with the beam. Utilization of weapons-quality beams for hole boring, was found to yield power availability increases of 9-33%, although no beneficial effects could be predicted in regions of persistent cloud cover. An efficiency of 80% was determined as possible if several receptor sites were available within 200-300 miles of each other, thereby allowing changes of reception point in cases of unacceptable meteorological conditions.

23 Years of Cloud Statistics Using HIRS Over Australia

NASA Astrophysics Data System (ADS)

Chedzey, H. C.; Menzel, W. P.; Lynch, M. J.; McGann, B. T.

2004-05-01

Clouds are an integral factor in the Earth's water and radiation budgets. Observations and improvements to the accuracy of measurements of cloud properties are crucial in supporting global climate change studies. Regional studies are also of interest and analysis of regional climate variability provides an insight into local weather systems. HIRS is the High-Resolution Infrared Radiation Sounder aboard polar orbiting satellites operated by NOAA (National Oceanographic and Atmospheric Administration). An archive of HIRS data obtained between 1979 (NOAA-5) through to 2001 (NOAA-16) was made available by CIMSS (Cooperative Institute for Meteorological Satellite Studies) at the University of Wisconsin-Madison. The data is obtained from near nadir and frequencies of observations are converted into percentages based on total number of observations for each 1 by 1 degree cell. An assessment of cloud frequency percentages for a region including areas of the Indian Ocean and Australia (0\\deg - 60\\deg S; 80\\deg E - 170\\deg E) will be presented. Climate variability and possible associations with future work to be conducted into cloud frequency and rainfall of North West Cloud Bands using MODIS data will also be covered.

Remote sensing data from CLARET: A prototype CART data set

NASA Technical Reports Server (NTRS)

Eberhard, Wynn L.; Uttal, Taneil; Clark, Kurt A.; Cupp, Richard E.; Dutton, Ellsworth G.; Fedor, Leonard, S.; Intrieri, Janet M.; Matrosov, Sergey Y.; Snider, Jack B.; Willis, Ron J.

1992-01-01

The data set containing radiation, meteorological , and cloud sensor observations is documented. It was prepared for use by the Department of Energy's Atmospheric Radiation Measurement (ARM) Program and other interested scientists. These data are a precursor of the types of data that ARM Cloud And Radiation Testbed (CART) sites will provide. The data are from the Cloud Lidar And Radar Exploratory Test (CLARET) conducted by the Wave Propagation Laboratory during autumn 1989 in the Denver-Boulder area of Colorado primarily for the purpose of developing new cloud-sensing techniques on cirrus. After becoming aware of the experiment, ARM scientists requested archival of subsets of the data to assist in the developing ARM program. Five CLARET cases were selected: two with cirrus, one with stratus, one with mixed-phase clouds, and one with clear skies. Satellite data from the stratus case and one cirrus case were analyzed for statistics on cloud cover and top height. The main body of the selected data are available on diskette from the Wave Propagation Laboratory or Los Alamos National Laboratory.

A statistical comparison of cirrus particle size distributions measured using the 2-D stereo probe during the TC4, SPARTICUS, and MACPEX flight campaigns with historical cirrus datasets

NASA Astrophysics Data System (ADS)

Schwartz, M. Christian

2017-08-01

This paper addresses two straightforward questions. First, how similar are the statistics of cirrus particle size distribution (PSD) datasets collected using the Two-Dimensional Stereo (2D-S) probe to cirrus PSD datasets collected using older Particle Measuring Systems (PMS) 2-D Cloud (2DC) and 2-D Precipitation (2DP) probes? Second, how similar are the datasets when shatter-correcting post-processing is applied to the 2DC datasets? To answer these questions, a database of measured and parameterized cirrus PSDs - constructed from measurements taken during the Small Particles in Cirrus (SPARTICUS); Mid-latitude Airborne Cirrus Properties Experiment (MACPEX); and Tropical Composition, Cloud, and Climate Coupling (TC4) flight campaigns - is used.Bulk cloud quantities are computed from the 2D-S database in three ways: first, directly from the 2D-S data; second, by applying the 2D-S data to ice PSD parameterizations developed using sets of cirrus measurements collected using the older PMS probes; and third, by applying the 2D-S data to a similar parameterization developed using the 2D-S data themselves. This is done so that measurements of the same cloud volumes by parameterized versions of the 2DC and 2D-S can be compared with one another. It is thereby seen - given the same cloud field and given the same assumptions concerning ice crystal cross-sectional area, density, and radar cross section - that the parameterized 2D-S and the parameterized 2DC predict similar distributions of inferred shortwave extinction coefficient, ice water content, and 94 GHz radar reflectivity. However, the parameterization of the 2DC based on uncorrected data predicts a statistically significantly higher number of total ice crystals and a larger ratio of small ice crystals to large ice crystals than does the parameterized 2D-S. The 2DC parameterization based on shatter-corrected data also predicts statistically different numbers of ice crystals than does the parameterized 2D-S, but the comparison between the two is nevertheless more favorable. It is concluded that the older datasets continue to be useful for scientific purposes, with certain caveats, and that continuing field investigations of cirrus with more modern probes is desirable.

Reconfigurable data path processor

NASA Technical Reports Server (NTRS)

Donohoe, Gregory (Inventor)

2005-01-01

A reconfigurable data path processor comprises a plurality of independent processing elements. Each of the processing elements advantageously comprising an identical architecture. Each processing element comprises a plurality of data processing means for generating a potential output. Each processor is also capable of through-putting an input as a potential output with little or no processing. Each processing element comprises a conditional multiplexer having a first conditional multiplexer input, a second conditional multiplexer input and a conditional multiplexer output. A first potential output value is transmitted to the first conditional multiplexer input, and a second potential output value is transmitted to the second conditional multiplexer output. The conditional multiplexer couples either the first conditional multiplexer input or the second conditional multiplexer input to the conditional multiplexer output, according to an output control command. The output control command is generated by processing a set of arithmetic status-bits through a logical mask. The conditional multiplexer output is coupled to a first processing element output. A first set of arithmetic bits are generated according to the processing of the first processable value. A second set of arithmetic bits may be generated from a second processing operation. The selection of the arithmetic status-bits is performed by an arithmetic-status bit multiplexer selects the desired set of arithmetic status bits from among the first and second set of arithmetic status bits. The conditional multiplexer evaluates the select arithmetic status bits according to logical mask defining an algorithm for evaluating the arithmetic status bits.

The Use of Satellite Observed Cloud Patterns in Northern Hemisphere 300 mb and 1000/300 mb Numerical Analysis.

DTIC Science & Technology

1984-02-01

prediction Extratropical cyclones Objective analysis Bogus techniques 20. ABSTRACT (Continue on reverse aide If necooearn mid Identify by block number) Jh A...quasi-objective statistical method for deriving 300 mb geopotential heights and 1000/300 mb thicknesses in the vicinity of extratropical cyclones 0I...with the aid of satellite imagery is presented. The technique utilizes satellite observed extratropical spiral cloud pattern parameters in conjunction

Galactic cold cores. IX. Column density structures and radiative-transfer modelling

NASA Astrophysics Data System (ADS)

Juvela, M.; Malinen, J.; Montillaud, J.; Pelkonen, V.-M.; Ristorcelli, I.; Tóth, L. V.

2018-06-01

Context. The Galactic Cold Cores (GCC) project has made Herschel photometric observations of interstellar clouds where Planck detected compact sources of cold dust emission. The fields are in different environments and stages of star formation. Aims: Our aim is to characterise the structure of the clumps and their parent clouds, and to study the connections between the environment and the formation of gravitationally bound objects. We also examine the accuracy to which the structure of dense clumps can be determined from sub-millimetre data. Methods: We use standard statistical methods to characterise the GCC fields. Individual clumps are extracted using column density thresholding. Based on sub-millimetre measurements, we construct a three-dimensional radiative transfer (RT) model for each field. These are used to estimate the relative radiation field intensities, to probe the clump stability, and to examine the uncertainty of column density estimates. We examine the structural parameters of the clumps, including their radial column density profiles. Results: In the GCC fields, the structure noise follows the relations previously established at larger scales and in lower-density clouds. The fractal dimension has no significant dependence on column density and the values DP = 1.25 ± 0.07 are only slightly lower than in typical molecular clouds. The column density probability density functions (PDFs) exhibit large variations, for example, in the case of externally compressed clouds. At scales r > 0.1 pc, the radial column density distributions of the clouds follow an average relation of N r-1. In spite of a great variety of clump morphologies (and a typical aspect ratio of 1.5), clumps tend to follow a similar N r-1 relation below r 0.1 pc. RT calculations indicate only factor 2.5 variation in the local radiation field intensity. The fraction of gravitationally bound clumps increases significantly in regions with AV > 5 mag but most bound objects appear to be pressure-confined. Conclusions: The host clouds of the cold clumps in the GCC sample have statistical properties similar to general molecular clouds. The gravitational stability, peak column density, and clump orientation are connected to the cloud background while most other statistical clump properties (e.g. DP and radial profiles) are insensitive to the environment. The study of clump morphology should be continued with a comparison with numerical simulations. Planck (http://www.esa.int/Planck) is a project of the European Space Agency (ESA) with instruments provided by two scientific consortia funded by ESA member states (in particular the lead countries: France and Italy) with contributions from NASA (USA), and telescope reflectors provided in a collaboration between ESA and a scientific consortium led and funded by Denmark.Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

PROGRESS REPORT OF FY 2004 ACTIVITIES: IMPROVED WATER VAPOR AND CLOUD RETRIEVALS AT THE NSA/AAO

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

E. R. Westwater; V. V. Leuskiy; M. Klein

2004-11-01

The basic goals of the research are to develop and test algorithms and deploy instruments that improve measurements of water vapor, cloud liquid, and cloud coverage, with a focus on the Arctic conditions of cold temperatures and low concentrations of water vapor. The importance of accurate measurements of column amounts of water vapor and cloud liquid has been well documented by scientists within the Atmospheric Radiation Measurement Program. Although several technologies have been investigated to measure these column amounts, microwave radiometers (MWR) have been used operationally by the ARM program for passive retrievals of these quantities: precipitable water vapor (PWV)more » and integrated water liquid (IWL). The technology of PWV and IWL retrievals has advanced steadily since the basic 2-channel MWR was first deployed at ARM CART sites Important advances are the development and refinement of the tipcal calibration method [1,2], and improvement of forward model radiative transfer algorithms [3,4]. However, the concern still remains that current instruments deployed by ARM may be inadequate to measure low amounts of PWV and IWL. In the case of water vapor, this is especially important because of the possibility of scaling and/or quality control of radiosondes by the water amount. Extremely dry conditions, with PWV less than 3 mm, commonly occur in Polar Regions during the winter months. Accurate measurements of the PWV during such dry conditions are needed to improve our understanding of the regional radiation energy budgets. The results of a 1999 experiment conducted at the ARM North Slope of Alaska/Adjacent Arctic Ocean (NSA/AAO) site during March of 1999 [5] have shown that the strength associated with the 183 GHz water vapor absorption line makes radiometry in this frequency regime suitable for measuring low amounts of PWV. As a portion of our research, we conducted another millimeter wave radiometric experiment at the NSA/AAO in March-April 2004. This experiment relied heavily on our experiences of the 1999 experiment. Particular attention was paid to issues of radiometric calibration and radiosonde intercomparisons. Our theoretical and experimental work also supplements efforts by industry (F. Solheim, Private Communication) to develop sub-millimeter radiometers for ARM deployment. In addition to quantitative improvement of water vapor measurements at cold temperature, the impact of adding millimeter-wave window channels to improve the sensitivity to arctic clouds was studied. We also deployed an Infrared Cloud Imager (ICI) during this experiment, both for measuring continuous day-night statistics of the study of cloud coverage and identifying conditions suitable for tipcal analysis. This system provided the first capability of determining spatial cloud statistics continuously in both day and night at the NSA site and has been used to demonstrate that biases exist in inferring cloud statistics from either zenith-pointing active sensors (lidars or radars) or sky imagers that rely on scattered sunlight in daytime and star maps at night [6].« less

On the capacity of MIMO-OFDM based diversity and spatial multiplexing in Radio-over-Fiber system

NASA Astrophysics Data System (ADS)

El Yahyaoui, Moussa; El Moussati, Ali; El Zein, Ghaïs

2017-11-01

This paper proposes a realistic and global simulation to predict the behavior of a Radio over Fiber (RoF) system before its realization. In this work we consider a 2 × 2 Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) RoF system at 60 GHz. This system is based on Spatial Diversity (SD) which increases reliability (decreases probability of error) and Spatial Multiplexing (SMX) which increases data rate, but not necessarily reliability. The 60 GHz MIMO channel model employed in this work based on a lot of measured data and statistical analysis named Triple-S and Valenzuela (TSV) model. To the authors best knowledge; it is the first time that this type of TSV channel model has been employed for 60 GHz MIMO-RoF system. We have evaluated and compared the performance of this system according to the diversity technique, modulation schemes, and channel coding rate for Line-Of-Sight (LOS) desktop environment. The SMX coded is proposed as an intermediate system to improve the Signal to Noise Ratio (SNR) and the data rate. The resulting 2 × 2 MIMO-OFDM SMX system achieves a higher data rate up to 70 Gb/s with 64QAM and Forward Error Correction (FEC) limit of 10-3 over 25-km fiber transmission followed by 3-m wireless transmission using 7 GHz bandwidth of millimeter wave band.

On the Representation of Ice Nucleation in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

NASA Astrophysics Data System (ADS)

Storelvmo, T.

2015-12-01

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. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.

"Black cloud" vs. "white cloud" physicians - Myth or reality in apheresis medicine?

PubMed

Pham, Huy P; Raju, Dheeraj; Jiang, Ning; Williams, Lance A

2017-08-01

Many practitioners believe in the phenomenon of either being labeled a "black cloud" or "white cloud" while on-call. A "white-cloud" physician is one who usually gets fewer cases. A "black-cloud" is one who often has more cases. It is unclear if the designation is only superstitious or if there is some merit. Our aim is to objectively assess this phenomenon in apheresis medicine at our center. A one-year prospective study from 12/2014 to 11/2015 was designed to evaluate the number of times apheresis physicians and nurses were involved with emergent apheresis procedures between the hours from 10 PM and 7 AM. Other parameters collected include the names of the physician, apheresis nurse, type of emergent apheresis procedure, day of the week, and season of the year. During the study period, 32 emergent procedures (or "black-cloud" events) occurred. The median time between two consecutive events was 8 days (range: 1-34 days). We found no statistically significant association between the "black-cloud" events and attending physicians, nurses, day of the week, or season of the year by Chi-square and Fisher's analyses. However, exploratory analysis using association rule demonstrated that "black-cloud" events were more likely to happen on Thursday (2.19 times), with attending physician 2 (1.18 times), and during winter (1.15 times). The results of this pilot study may support the common perception that some physicians or nurses are either "black cloud" or "white cloud". A larger, multi-center study population is needed to validate the results of this pilot study. © 2016 Wiley Periodicals, Inc.

Covariance Between Arctic Sea Ice and Clouds Within Atmospheric State Regimes at the Satellite Footprint Level

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.; Kato, Seiji; Xu, Kuan-Man; Cai, Ming

2015-01-01

Understanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice-cloud relationship in the Arctic using a satellite footprint-level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A-Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and mid-tropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest-magnitude cloud-sea ice covariance occurs between 500m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near-surface static stability is found at larger sea ice concentrations.

Effective cloud optical depth and enhancement effects for broken liquid water clouds in Valencia (Spain)

NASA Astrophysics Data System (ADS)

Marín, M. J.; Serrano, D.; Utrillas, M. P.; Núñez, M.; Martínez-Lozano, J. A.

2017-10-01

Partly cloudy skies with liquid water clouds have been analysed, founding that it is essential to distinguish data if the Sun is obstructed or not by clouds. Both cases can be separated considering simultaneously the Cloud Modification Factor (CMF) and the clearness index (kt). For partly cloudy skies and the Sun obstructed the effective cloud optical depth (τ) has been obtained by the minimization method for overcast skies. This method was previously developed by the authors but, in this case, taking into account partial cloud cover. This study has been conducted for the years 2011-2015 with the multiple scattering model SBDART and irradiance measurements for the UV Erythemal Radiation (UVER) and the broadband ranges. Afterwards a statistical analysis of τ has shown that the maximum value is much lower than for overcast skies and there is more discrepancy between the two spectral ranges regarding the results for overcast skies. In order to validate these results the effective cloud optical depth has been correlated with several transmission factors, giving similar fit parameters to those obtained for overcast skies except for the clearness index in the UVER range. As our method is not applicable for partly cloudy skies with the visible Sun, the enhancement of radiation caused by clouds when the Sun is visible has been studied. Results show that the average enhancement CMF values are the same for both ranges although enhancement is more frequent for low cloud cover in the UVER and medium-high cloud cover in the broadband range and it does not depend on the solar zenith angle.

Covariance between Arctic sea ice and clouds within atmospheric state regimes at the satellite footprint level.

PubMed

Taylor, Patrick C; Kato, Seiji; Xu, Kuan-Man; Cai, Ming

2015-12-27

Understanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice-cloud relationship in the Arctic using a satellite footprint-level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A-Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and midtropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest-magnitude cloud-sea ice covariance occurs between 500 m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near-surface static stability is found at larger sea ice concentrations.

Automated cloud classification using a ground based infra-red camera and texture analysis techniques

NASA Astrophysics Data System (ADS)

Rumi, Emal; Kerr, David; Coupland, Jeremy M.; Sandford, Andrew P.; Brettle, Mike J.

2013-10-01

Clouds play an important role in influencing the dynamics of local and global weather and climate conditions. Continuous monitoring of clouds is vital for weather forecasting and for air-traffic control. Convective clouds such as Towering Cumulus (TCU) and Cumulonimbus clouds (CB) are associated with thunderstorms, turbulence and atmospheric instability. Human observers periodically report the presence of CB and TCU clouds during operational hours at airports and observatories; however such observations are expensive and time limited. Robust, automatic classification of cloud type using infrared ground-based instrumentation offers the advantage of continuous, real-time (24/7) data capture and the representation of cloud structure in the form of a thermal map, which can greatly help to characterise certain cloud formations. The work presented here utilised a ground based infrared (8-14 μm) imaging device mounted on a pan/tilt unit for capturing high spatial resolution sky images. These images were processed to extract 45 separate textural features using statistical and spatial frequency based analytical techniques. These features were used to train a weighted k-nearest neighbour (KNN) classifier in order to determine cloud type. Ground truth data were obtained by inspection of images captured simultaneously from a visible wavelength colour camera at the same installation, with approximately the same field of view as the infrared device. These images were classified by a trained cloud observer. Results from the KNN classifier gave an encouraging success rate. A Probability of Detection (POD) of up to 90% with a Probability of False Alarm (POFA) as low as 16% was achieved.

Multiplexer and time duration measuring circuit

DOEpatents

Gray, Jr., James

1980-01-01

A multiplexer device is provided for multiplexing data in the form of randomly developed, variable width pulses from a plurality of pulse sources to a master storage. The device includes a first multiplexer unit which includes a plurality of input circuits each coupled to one of the pulse sources, with all input circuits being disabled when one input circuit receives an input pulse so that only one input pulse is multiplexed by the multiplexer unit at any one time.

On the performance of metrics to predict quality in point cloud representations

NASA Astrophysics Data System (ADS)

Alexiou, Evangelos; Ebrahimi, Touradj

2017-09-01

Point clouds are a promising alternative for immersive representation of visual contents. Recently, an increased interest has been observed in the acquisition, processing and rendering of this modality. Although subjective and objective evaluations are critical in order to assess the visual quality of media content, they still remain open problems for point cloud representation. In this paper we focus our efforts on subjective quality assessment of point cloud geometry, subject to typical types of impairments such as noise corruption and compression-like distortions. In particular, we propose a subjective methodology that is closer to real-life scenarios of point cloud visualization. The performance of the state-of-the-art objective metrics is assessed by considering the subjective scores as the ground truth. Moreover, we investigate the impact of adopting different test methodologies by comparing them. Advantages and drawbacks of every approach are reported, based on statistical analysis. The results and conclusions of this work provide useful insights that could be considered in future experimentation.

Cost Savings Associated with the Adoption of a Cloud Computing Data Transfer System for Trauma Patients.

PubMed

Feeney, James M; Montgomery, Stephanie C; Wolf, Laura; Jayaraman, Vijay; Twohig, Michael

2016-09-01

Among transferred trauma patients, challenges with the transfer of radiographic studies include problems loading or viewing the studies at the receiving hospitals, and problems manipulating, reconstructing, or evalu- ating the transferred images. Cloud-based image transfer systems may address some ofthese problems. We reviewed the charts of patients trans- ferred during one year surrounding the adoption of a cloud computing data transfer system. We compared the rates of repeat imaging before (precloud) and af- ter (postcloud) the adoption of the cloud-based data transfer system. During the precloud period, 28 out of 100 patients required 90 repeat studies. With the cloud computing transfer system in place, three out of 134 patients required seven repeat films. There was a statistically significant decrease in the proportion of patients requiring repeat films (28% to 2.2%, P < .0001). Based on an annualized volume of 200 trauma patient transfers, the cost savings estimated using three methods of cost analysis, is between $30,272 and $192,453.

Changes in thunderstorm characteristics due to feeder cloud merging

NASA Astrophysics Data System (ADS)

Sinkevich, Andrei A.; Krauss, Terrence W.

2014-06-01

Cumulus cloud merging is a complex dynamical and microphysical process in which two convective cells merge into a single cell. Previous radar observations and numerical simulations have shown a substantial increase in the maximum area, maximum echo top and maximum reflectivity as a result of the merging process. Although the qualitative aspects of merging have been well documented, the quantitative effects on storm properties remain less defined. Therefore, a statistical assessment of changes in storm characteristics due to merging is of importance. Further investigation into the effects of cloud merging on precipitation flux (Pflux) in a statistical manner provided the motivation for this study in the Asir region of Saudi Arabia. It was confirmed that merging has a strong effect on storm development in this region. The data analysis shows that an increase in the median of the distribution of maximum reflectivity was observed just after merging and was equal to 3.9 dBZ. A detailed analysis of the individual merge cases compared the merged storm Pflux and mass to the sum of the individual Feeder and Storm portions just before merging for each case. The merged storm Pflux increased an average of 106% over the 20-min period after merging, and the mass increased on average 143%. The merged storm clearly became larger and more severe than the sum of the two parts prior to merging. One consequence of this study is that any attempts to evaluate the precipitation enhancement effects of cloud seeding must also include the issue of cloud mergers because merging can have a significant effect on the results.

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

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

Evans, Stuart; Marchand, Roger; Ackerman, Thomas

In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

NASA Astrophysics Data System (ADS)

Evans, Stuart; Marchand, Roger; Ackerman, Thomas; Donner, Leo; Golaz, Jean-Christophe; Seman, Charles

2017-12-01

We define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, and high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. We find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

DOE PAGES

Evans, Stuart; Marchand, Roger; Ackerman, Thomas; ...

2017-11-16

In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less

Aerosol and Cloud Interaction Observed From High Spectral Resolution Lidar Data

NASA Technical Reports Server (NTRS)

Su, Wenying; Schuster, Gregory L.; Loeb, Norman G.; Rogers, Raymond R.; Ferrare, Richard A.; Hostetler, Chris A.; Hair, Johnathan W.; Obland, Michael D.

2008-01-01

Recent studies utilizing satellite retrievals have shown a strong correlation between aerosol optical depth (AOD) and cloud cover. However, these retrievals from passive sensors are subject to many limitations, including cloud adjacency (or 3D) effects, possible cloud contamination, uncertainty in the AOD retrieval. Some of these limitations do not exist in High Spectral Resolution Lidar (HSRL) observations; for instance, HSRL observations are not a ected by cloud adjacency effects, are less prone to cloud contamination, and offer accurate aerosol property measurements (backscatter coefficient, extinction coefficient, lidar ratio, backscatter Angstrom exponent,and aerosol optical depth) at a neospatial resolution (less than 100 m) in the vicinity of clouds. Hence, the HSRL provides an important dataset for studying aerosol and cloud interaction. In this study, we statistically analyze aircraft-based HSRL profiles according to their distance from the nearest cloud, assuring that all profile comparisons are subject to the same large-scale meteorological conditions. Our results indicate that AODs from HSRL are about 17% higher in the proximity of clouds (approximately 100 m) than far away from clouds (4.5 km), which is much smaller than the reported cloud 3D effect on AOD retrievals. The backscatter and extinction coefficients also systematically increase in the vicinity of clouds, which can be explained by aerosol swelling in the high relative humidity (RH) environment and/or aerosol growth through in cloud processing (albeit not conclusively). On the other hand, we do not observe a systematic trend in lidar ratio; we hypothesize that this is caused by the opposite effects of aerosol swelling and aerosol in-cloud processing on the lidar ratio. Finally, the observed backscatter Angstrom exponent (BAE) does not show a consistent trend because of the complicated relationship between BAE and RH. We demonstrate that BAE should not be used as a surrogate for Angstrom exponent, especially at high RH.

Wiener filter preprocessing for OFDM systems in the presence of both nonstationary and stationary phase noises

NASA Astrophysics Data System (ADS)

Zhong, Ke; Lei, Xia; Li, Shaoqian

2013-12-01

Statistics-based intercarrier interference (ICI) mitigation algorithm is proposed for orthogonal frequency division multiplexing systems in presence of both nonstationary and stationary phase noises. By utilizing the statistics of phase noise, which can be obtained from measurements or data sheets, a Wiener filter preprocessing algorithm for ICI mitigation is proposed. The proposed algorithm can be regarded as a performance-improving technique for the previous researches on phase noise cancelation. Simulation results show that the proposed algorithm can effectively mitigate ICI and lower the error floor, and therefore significantly improve the performances of previous researches on phase noise cancelation, especially in the presence of severe phase noise.

Hierarchical patch-based co-registration of differently stained histopathology slides

NASA Astrophysics Data System (ADS)

Yigitsoy, Mehmet; Schmidt, Günter

2017-03-01

Over the past decades, digital pathology has emerged as an alternative way of looking at the tissue at subcellular level. It enables multiplexed analysis of different cell types at micron level. Information about cell types can be extracted by staining sections of a tissue block using different markers. However, robust fusion of structural and functional information from different stains is necessary for reproducible multiplexed analysis. Such a fusion can be obtained via image co-registration by establishing spatial correspondences between tissue sections. Spatial correspondences can then be used to transfer various statistics about cell types between sections. However, the multi-modal nature of images and sparse distribution of interesting cell types pose several challenges for the registration of differently stained tissue sections. In this work, we propose a co-registration framework that efficiently addresses such challenges. We present a hierarchical patch-based registration of intensity normalized tissue sections. Preliminary experiments demonstrate the potential of the proposed technique for the fusion of multi-modal information from differently stained digital histopathology sections.

A new IPQAM modulator with high integrated degree for digital TV

NASA Astrophysics Data System (ADS)

He, Yejun; Liu, Deming; Zhu, Guangxi; Jiang, Tao; Sun, Gongxian

2008-12-01

As video on demand (VOD) services are deployed, cable operators will experience a fundamental shift in their business, moving from broadcast to unicast content delivery. Another significant change is the introduction of Gigabit Ethernet into their network, which is providing an unprecedented opportunity to turn the cable operator's infrastructure into a sustainable competitive advantage. However, Gigabit Ethernet is more than just transport; it's the foundation of the Next-Generation Digital Video Network. IPQAM modulator, which is a main equipment, aren't made in China so far. It is the first time that we did design IPQAM modulator and will apply it to interactive TV based on DWDM (dense wavelength-division multiplexing). This paper introduces the principle of IPQAM modulator and transmission approach. The differences between IPQAM and conventional QAM are analysed. Some key techniques such as scrambling, statistical multiplexing, Data over Cable Service Interface Specification (DOCSIS) 3.0, software defined radio as well as DVB simulcrypt are also studied.

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

Hornemann, Andrea, E-mail: andrea.hornemann@ptb.de; Hoehl, Arne, E-mail: arne.hoehl@ptb.de; Ulm, Gerhard, E-mail: gerhard.ulm@ptb.de

Bio-diagnostic assays of high complexity rely on nanoscaled assay recognition elements that can provide unique selectivity and design-enhanced sensitivity features. High throughput performance requires the simultaneous detection of various analytes combined with appropriate bioassay components. Nanoparticle induced sensitivity enhancement, and subsequent multiplexed capability Surface-Enhanced InfraRed Absorption (SEIRA) assay formats are fitting well these purposes. SEIRA constitutes an ideal platform to isolate the vibrational signatures of targeted bioassay and active molecules. The potential of several targeted biolabels, here fluorophore-labeled antibody conjugates, chemisorbed onto low-cost biocompatible gold nano-aggregates substrates have been explored for their use in assay platforms. Dried films were analyzedmore » by synchrotron radiation based FTIR/SEIRA spectro-microscopy and the resulting complex hyperspectral datasets were submitted to automated statistical analysis, namely Principal Components Analysis (PCA). The relationships between molecular fingerprints were put in evidence to highlight their spectral discrimination capabilities. We demonstrate that robust spectral encoding via SEIRA fingerprints opens up new opportunities for fast, reliable and multiplexed high-end screening not only in biodiagnostics but also in vitro biochemical imaging.« less

A scoring strategy combining statistics and functional genomics supports a possible role for common polygenic variation in autism

PubMed Central

Carayol, Jérôme; Schellenberg, Gerard D.; Dombroski, Beth; Amiet, Claire; Génin, Bérengère; Fontaine, Karine; Rousseau, Francis; Vazart, Céline; Cohen, David; Frazier, Thomas W.; Hardan, Antonio Y.; Dawson, Geraldine; Rio Frio, Thomas

2014-01-01

Autism spectrum disorders (ASD) are highly heritable complex neurodevelopmental disorders with a 4:1 male: female ratio. Common genetic variation could explain 40–60% of the variance in liability to autism. Because of their small effect, genome-wide association studies (GWASs) have only identified a small number of individual single-nucleotide polymorphisms (SNPs). To increase the power of GWASs in complex disorders, methods like convergent functional genomics (CFG) have emerged to extract true association signals from noise and to identify and prioritize genes from SNPs using a scoring strategy combining statistics and functional genomics. We adapted and applied this approach to analyze data from a GWAS performed on families with multiple children affected with autism from Autism Speaks Autism Genetic Resource Exchange (AGRE). We identified a set of 133 candidate markers that were localized in or close to genes with functional relevance in ASD from a discovery population (545 multiplex families); a gender specific genetic score (GS) based on these common variants explained 1% (P = 0.01 in males) and 5% (P = 8.7 × 10−7 in females) of genetic variance in an independent sample of multiplex families. Overall, our work demonstrates that prioritization of GWAS data based on functional genomics identified common variants associated with autism and provided additional support for a common polygenic background in autism. PMID:24600472

Cloud Structure of Galactic OB Cluster-forming Regions from Combining Ground- and Space-based Bolometric Observations

NASA Astrophysics Data System (ADS)

Lin, Yuxin; Liu, Hauyu Baobab; Li, Di; Zhang, Zhi-Yu; Ginsburg, Adam; Pineda, Jaime E.; Qian, Lei; Galván-Madrid, Roberto; McLeod, Anna Faye; Rosolowsky, Erik; Dale, James E.; Immer, Katharina; Koch, Eric; Longmore, Steve; Walker, Daniel; Testi, Leonardo

2016-09-01

We have developed an iterative procedure to systematically combine the millimeter and submillimeter images of OB cluster-forming molecular clouds, which were taken by ground-based (CSO, JCMT, APEX, and IRAM-30 m) and space telescopes (Herschel and Planck). For the seven luminous (L\\gt {10}6 L ⊙) Galactic OB cluster-forming molecular clouds selected for our analyses, namely W49A, W43-Main, W43-South, W33, G10.6-0.4, G10.2-0.3, and G10.3-0.1, we have performed single-component, modified blackbody fits to each pixel of the combined (sub)millimeter images, and the Herschel PACS and SPIRE images at shorter wavelengths. The ˜10″ resolution dust column density and temperature maps of these sources revealed dramatically different morphologies, indicating very different modes of OB cluster-formation, or parent molecular cloud structures in different evolutionary stages. The molecular clouds W49A, W33, and G10.6-0.4 show centrally concentrated massive molecular clumps that are connected with approximately radially orientated molecular gas filaments. The W43-Main and W43-South molecular cloud complexes, which are located at the intersection of the Galactic near 3 kpc (or Scutum) arm and the Galactic bar, show a widely scattered distribution of dense molecular clumps/cores over the observed ˜10 pc spatial scale. The relatively evolved sources G10.2-0.3 and G10.3-0.1 appear to be affected by stellar feedback, and show a complicated cloud morphology embedded with abundant dense molecular clumps/cores. We find that with the high angular resolution we achieved, our visual classification of cloud morphology can be linked to the systematically derived statistical quantities (I.e., the enclosed mass profile, the column density probability distribution function (N-PDF), the two-point correlation function of column density, and the probability distribution function of clump/core separations). In particular, the massive molecular gas clumps located at the center of G10.6-0.4 and W49A, which contribute to a considerable fraction of their overall cloud masses, may be special OB cluster-forming environments as a direct consequence of global cloud collapse. These centralized massive molecular gas clumps also uniquely occupy much higher column densities than what is determined by the overall fit of power-law N-PDF. We have made efforts to archive the derived statistical quantities of individual target sources, to permit comparisons with theoretical frameworks, numerical simulations, and other observations in the future.

Why do tornados and hailstorms rest on weekends?

NASA Astrophysics Data System (ADS)

Rosenfeld, Daniel; Bell, Thomas L.

2011-10-01

This study shows for the first time statistical evidence that when anthropogenic aerosols over the eastern United States during summertime are at their weekly mid-week peak, tornado and hailstorm activity there is also near its weekly maximum. The weekly cycle in summertime storm activity for 1995-2009 was found to be statistically significant and unlikely to be due to natural variability. It correlates well with previously observed weekly cycles of other measures of storm activity. The pattern of variability supports the hypothesis that air pollution aerosols invigorate deep convective clouds in a moist, unstable atmosphere, to the extent of inducing production of large hailstones and tornados. This is caused by the effect of aerosols on cloud drop nucleation, making cloud drops smaller and hydrometeors larger. According to simulations, the larger ice hydrometeors contribute to more hail. The reduced evaporation from the larger hydrometeors produces weaker cold pools. Simulations have shown that too cold and fast-expanding pools inhibit the formation of tornados. The statistical observations suggest that this might be the mechanism by which the weekly modulation in pollution aerosols is causing the weekly cycle in severe convective storms during summer over the eastern United States. Although we focus here on the role of aerosols, they are not a primary atmospheric driver of tornados and hailstorms but rather modulate them in certain conditions.

Alpha1 LASSO data bundles Lamont, OK

DOE Data Explorer

Gustafson, William Jr; Vogelmann, Andrew; Endo, Satoshi; Toto, Tami; Xiao, Heng; Li, Zhijin; Cheng, Xiaoping; Krishna, Bhargavi (ORCID:000000018828528X)

2016-08-03

A data bundle is a unified package consisting of LASSO LES input and output, observations, evaluation diagnostics, and model skill scores. LES input includes model configuration information and forcing data. LES output includes profile statistics and full domain fields of cloud and environmental variables. Model evaluation data consists of LES output and ARM observations co-registered on the same grid and sampling frequency. Model performance is quantified by skill scores and diagnostics in terms of cloud and environmental variables.

Communication Systems through Artificial Earth Satellites (Selected Pages)

DTIC Science & Technology

1987-02-05

A. The speaking currents of this subscriber from equipment AP come through AC only into the two-wire circuit, but also are branched/ shunted to AY, and...distribution of cloud cover. The evaluation, based on the statistic study of clouds [3.3) and rains of South England, at A=50 at the frequency of 4 GHz... Studies of conditions for passage of radio waves through disturbed ionosphere showed [3.16] that aurorae polares increase speed of fadings and are

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

NASA Technical Reports Server (NTRS)

Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.;

Gridding Cloud and Irradiance to Quantify Variability at the ARM Southern Great Plains Site

NASA Astrophysics Data System (ADS)

Riihimaki, L.; Long, C. N.; Gaustad, K.

2017-12-01

Ground-based radiometers provide the most accurate measurements of surface irradiance. However, geometry differences between surface point measurements and large area climate model grid boxes or satellite-based footprints can cause systematic differences in surface irradiance comparisons. In this work, irradiance measurements from a network of ground stations around Kansas and Oklahoma at the US Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains facility are examined. Upwelling and downwelling broadband shortwave and longwave radiometer measurements are available at each site as well as surface meteorological measurements. In addition to the measured irradiances, clear sky irradiance and cloud fraction estimates are analyzed using well established methods based on empirical fits to measured clear sky irradiances. Measurements are interpolated onto a 0.25 degree latitude and longitude grid using a Gaussian weight scheme in order to provide a more accurate statistical comparison between ground measurements and a larger area such as that used in climate models, plane parallel radiative transfer calculations, and other statistical and climatological research. Validation of the gridded product will be shown, as well as analysis that quantifies the impact of site location, cloud type, and other factors on the resulting surface irradiance estimates. The results of this work are being incorporated into the Surface Cloud Grid operational data product produced by ARM, and will be made publicly available for use by others.

Cloud Compute for Global Climate Station Summaries

NASA Astrophysics Data System (ADS)

Baldwin, R.; May, B.; Cogbill, P.

2017-12-01

Global Climate Station Summaries are simple indicators of observational normals which include climatic data summarizations and frequency distributions. These typically are statistical analyses of station data over 5-, 10-, 20-, 30-year or longer time periods. The summaries are computed from the global surface hourly dataset. This dataset totaling over 500 gigabytes is comprised of 40 different types of weather observations with 20,000 stations worldwide. NCEI and the U.S. Navy developed these value added products in the form of hourly summaries from many of these observations. Enabling this compute functionality in the cloud is the focus of the project. An overview of approach and challenges associated with application transition to the cloud will be presented.

Stochastic growth of cloud droplets by collisions during settling

NASA Astrophysics Data System (ADS)

Madival, Deepak G.

2018-04-01

In the last stage of droplet growth in clouds which leads to drizzle formation, larger droplets begin to settle under gravity and collide and coalesce with smaller droplets in their path. In this article, we shall deal with the simplified problem of a large drop settling amidst a population of identical smaller droplets. We present an expression for the probability that a given large drop suffers a given number of collisions, for a general statistically homogeneous distribution of droplets. We hope that our approach will serve as a valuable tool in dealing with droplet distribution in real clouds, which has been found to deviate from the idealized Poisson distribution due to mechanisms such as inertial clustering.

Final Report on DOE Project entitled Dynamic Optimized Advanced Scheduling of Bandwidth Demands for Large-Scale Science Applications

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

Ramamurthy, Byravamurthy

2014-05-05

In this project, developed scheduling frameworks for dynamic bandwidth demands for large-scale science applications. In particular, we developed scheduling algorithms for dynamic bandwidth demands in this project. Apart from theoretical approaches such as Integer Linear Programming, Tabu Search and Genetic Algorithm heuristics, we have utilized practical data from ESnet OSCARS project (from our DOE lab partners) to conduct realistic simulations of our approaches. We have disseminated our work through conference paper presentations and journal papers and a book chapter. In this project we addressed the problem of scheduling of lightpaths over optical wavelength division multiplexed (WDM) networks. We published severalmore » conference papers and journal papers on this topic. We also addressed the problems of joint allocation of computing, storage and networking resources in Grid/Cloud networks and proposed energy-efficient mechanisms for operatin optical WDM networks.« less

Available number of multiplexed holograms based on signal-to-noise ratio analysis in reflection-type holographic memory using three-dimensional speckle-shift multiplexing.

PubMed

Nishizaki, Tatsuya; Matoba, Osamu; Nitta, Kouichi

2014-09-01

The recording properties of three-dimensional speckle-shift multiplexing in reflection-type holographic memory are analyzed numerically. Three-dimensional recording can increase the number of multiplexed holograms by suppressing the cross-talk noise from adjacent holograms by using depth-direction multiplexing rather than in-plane multiplexing. Numerical results indicate that the number of multiplexed holograms in three-layer recording can be increased by 1.44 times as large as that of a single-layer recording when an acceptable signal-to-noise ratio is set to be 2 when NA=0.43 and the thickness of the recording medium is 0.5 mm.

Self-calibrating multiplexer circuit

DOEpatents

Wahl, Chris P.

1997-01-01

A time domain multiplexer system with automatic determination of acceptable multiplexer output limits, error determination, or correction is comprised of a time domain multiplexer, a computer, a constant current source capable of at least three distinct current levels, and two series resistances employed for calibration and testing. A two point linear calibration curve defining acceptable multiplexer voltage limits may be defined by the computer by determining the voltage output of the multiplexer to very accurately known input signals developed from predetermined current levels across the series resistances. Drift in the multiplexer may be detected by the computer when the output voltage limits, expected during normal operation, are exceeded, or the relationship defined by the calibration curve is invalidated.

Literature Review of Cloud Based E-learning Adoption by Students: State of the Art and Direction for Future Work

NASA Astrophysics Data System (ADS)

Hassan Kayali, Mohammad; Safie, Nurhizam; Mukhtar, Muriati

2016-11-01

Cloud computing is a new paradigm shift in information technology. Most of the studies in the cloud are business related while the studies in cloud based e-learning are few. The field is still in its infancy and researchers have used several adoption theories to discover the dimensions of this field. The purpose of this paper is to review and integrate the literature to understand the current situation of the cloud based e-learning adoption. A total of 312 articles were extracted from Science direct, emerald, and IEEE. Screening processes were applied to select only the articles that are related to the cloud based e-learning. A total of 231 removed because they are related to business organization. Next, a total of 63 articles were removed because they are technical articles. A total of 18 articles were included in this paper. A frequency analysis was conducted on the paper to identify the most frequent factors, theories, statistical software, respondents, and countries of the studies. The findings showed that usefulness and ease of use are the most frequent factors. TAM is the most prevalent adoption theories in the literature. The mean of the respondents in the reviewed studies is 377 and Malaysia is the most researched countries in terms of cloud based e-learning. Studies of cloud based e-learning are few and more empirical studies are needed.

Multiplex PCR Tests for Detection of Pathogens Associated with Gastroenteritis

PubMed Central

Zhang, Hongwei; Morrison, Scott; Tang, Yi-Wei

2016-01-01

Synopsis A wide range of enteric pathogens can cause infectious gastroenteritis. Conventional diagnostic algorithms including culture, biochemical identification, immunoassay and microscopic examination are time consuming and often lack sensitivity and specificity. Advances in molecular technology have as allowed its use as clinical diagnostic tools. Multiplex PCR based testing has made its way to gastroenterology diagnostic arena in recent years. In this article we present a review of recent laboratory developed multiplex PCR tests and current commercial multiplex gastrointestinal pathogen tests. We will focus on two FDA cleared commercial syndromic multiplex tests: Luminex xTAG GPP and Biofire FimArray GI test. These multiplex tests can detect and identify multiple enteric pathogens in one test and provide results within hours. Multiplex PCR tests have shown superior sensitivity to conventional methods for detection of most pathogens. The high negative predictive value of these multiplex tests has led to the suggestion that they be used as screening tools especially in outbreaks. Although the clinical utility and benefit of multiplex PCR test are to be further investigated, implementing these multiplex PCR tests in gastroenterology diagnostic algorithm has the potential to improve diagnosis of infectious gastroenteritis. PMID:26004652

Features of clouds and convection during the pre- and post-onset periods of the Asian summer monsoon

NASA Astrophysics Data System (ADS)

Wang, Yi; Wang, Chenghai

2016-02-01

The statistical characteristics of the vertical structure of clouds in the Asian summer monsoon region are investigated using two CloudSat standard products (Geometrical Profiling Product (GEOPROF) and GEOPROF-lidar) during the pre- and post-onset periods of the Asian summer monsoon, from April to August in 2007-2010. The characteristics of the vertical structure of clouds are analyzed and compared for different underlying surfaces in four subregions during this period. Also analyzed are the evolution of precipitation and hydrometeors with the northward advance of the Asian summer monsoon, and different hydrometeor characteristics attributed to the underlying surface features. The results indicate that the vertical cloud amounts increase significantly after the summer monsoon onset; this increase occurs first in the upper troposphere and then at lower altitudes over tropical regions (South Asian and tropical Northwest Pacific regions). The heights of the cloud top ascend, and the vertical height between the top and the base of the whole cloud increases. Single-layer (SL) and double-layer (DL) hydrometeors contribute over half and one third of the cloudiness in these 5 months (April to August), respectively. The multilayer frequencies increase in four different regions, and cloud layer depths (CLD) increase after the summer monsoon onset. These changes are stronger in tropical regions than in subtropical regions, while the vertical distance between cloud layers (VDCL) deceases in tropical regions and increases in subtropical regions.

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

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

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

2010-02-22

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

A Method for Obtaining High Frequency, Global, IR-Based Convective Cloud Tops for Studies of the TTL

NASA Technical Reports Server (NTRS)

Pfister, Leonhard; Ueyama, Rei; Jensen, Eric; Schoeberl, Mark

2017-01-01

Models of varying complexity that simulate water vapor and clouds in the Tropical Tropopause Layer (TTL) show that including convection directly is essential to properly simulating the water vapor and cloud distribution. In boreal winter, for example, simulations without convection yield a water vapor distribution that is too uniform with longitude, as well as minimal cloud distributions. Two things are important for convective simulations. First, it is important to get the convective cloud top potential temperature correctly, since unrealistically high values (reaching above the cold point tropopause too frequently) will cause excessive hydration of the stratosphere. Second, one must capture the time variation as well, since hydration by convection depends on the local relative humidity (temperature), which has substantial variation on synoptic time scales in the TTL. This paper describes a method for obtaining high frequency (3-hourly) global convective cloud top distributions which can be used in trajectory models. The method uses rainfall thresholds, standard IR brightness temperatures, meteorological temperature analyses, and physically realistic and documented corrections IR brightness temperature corrections to derive cloud top altitudes and potential temperatures. The cloud top altitudes compare well with combined CLOUDSAT and CALIPSO data, both in time-averaged overall vertical and horizontal distributions and in individual cases (correlations of .65-.7). An important finding is that there is significant uncertainty (nearly .5 km) in evaluating the statistical distribution of convective cloud tops even using lidar. Deep convection whose tops are in regions of high relative humidity (such as much of the TTL), will cause clouds to form above the actual convection. It is often difficult to distinguish these clouds from the actual convective cloud due to the uncertainties of evaluating ice water content from lidar measurements. Comparison with models show that calculated cloud top altitudes are generally higher than those calculated by global analyses (e.g., MERRA). Interannual variability in the distribution of convective cloud top altitudes is also investigated.

Equivalence of time-multiplexed and frequency-multiplexed signals in digital communications.

NASA Technical Reports Server (NTRS)

Timor, U.

1972-01-01

In comparing different techniques for multiplexing N binary data signals into a single channel, time-division multiplexing (TDM) is known to have a theoretic efficiency of 100 percent (neglecting sync power) and thus seems to outperform frequency-division multiplexing systems (FDM). By considering more general FDM systems, we will show that both TDM and FDM are equivalent and have an efficiency of 100 percent. The difference between the systems is in the multiplexing and demultiplexing subsystems, but not in the performance or in the generated waveforms.

MODIS Retrievals of Cloud Optical Thickness and Particle Radius

NASA Technical Reports Server (NTRS)

Platnick, S.; King, M. D.; Ackerman, S. A.; Gray, M.; Moody, E.; Arnold, G. T.; Einaudi, Franco (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides an unprecedented opportunity for global cloud studies with 36 spectral bands from the visible through the infrared, and spatial resolution from 250 m to 1 km at nadir. In particular, all solar window bands useful for simultaneous retrievals of cloud optical thickness and particle size (0.67, 0.86, 1.2, 1.6, 2.1, and 3.7 micron bands) are now available on a single satellite instrument/platform for the first time. An operational algorithm for the retrieval of these optical and cloud physical properties (including water path) have been developed for both liquid and ice phase clouds. The product is archived into two categories: pixel-level retrievals at 1 km spatial resolution (referred to as a Level-2 product) and global gridded statistics (Level-3 product). An overview of the MODIS cloud retrieval algorithm and early level-2 and -3 results will be presented. A number of MODIS cloud validation activities are being planned, including the recent Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign conducted in August/September 2000. The later part of the experiment concentrated on MODIS validation in the Namibian stratocumulus regime off the southwest coast of Africa. Early retrieval results from this regime will be discussed.

How to assess the impact of a physical parameterization in simulations of moist convection?

NASA Astrophysics Data System (ADS)

Grabowski, Wojciech

2017-04-01

A numerical model capable in simulating moist convection (e.g., cloud-resolving model or large-eddy simulation model) consists of a fluid flow solver combined with required representations (i.e., parameterizations) of physical processes. The later typically include cloud microphysics, radiative transfer, and unresolved turbulent transport. Traditional approaches to investigate impacts of such parameterizations on convective dynamics involve parallel simulations with different parameterization schemes or with different scheme parameters. Such methodologies are not reliable because of the natural variability of a cloud field that is affected by the feedback between the physics and dynamics. For instance, changing the cloud microphysics typically leads to a different realization of the cloud-scale flow, and separating dynamical and microphysical impacts is difficult. This presentation will present a novel modeling methodology, the piggybacking, that allows studying the impact of a physical parameterization on cloud dynamics with confidence. The focus will be on the impact of cloud microphysics parameterization. Specific examples of the piggybacking approach will include simulations concerning the hypothesized deep convection invigoration in polluted environments, the validity of the saturation adjustment in modeling condensation in moist convection, and separation of physical impacts from statistical uncertainty in simulations applying particle-based Lagrangian microphysics, the super-droplet method.

An improvement of the retrieval of temperature and relative humidity profiles from a combination of active and passive remote sensing

NASA Astrophysics Data System (ADS)

Che, Yunfei; Ma, Shuqing; Xing, Fenghua; Li, Siteng; Dai, Yaru

2018-03-01

This paper focuses on an improvement of the retrieval of atmospheric temperature and relative humidity profiles through combining active and passive remote sensing. Ground-based microwave radiometer and millimeter-wavelength cloud radar were used to acquire the observations. Cloud base height and cloud thickness determinations from cloud radar were added into the atmospheric profile retrieval process, and a back-propagation neural network method was used as the retrieval tool. Because a substantial amount of data are required to train a neural network, and as microwave radiometer data are insufficient for this purpose, 8 years of radiosonde data from Beijing were used as the database. The monochromatic radiative transfer model was used to calculate the brightness temperatures in the same channels as the microwave radiometer. Parts of the cloud base heights and cloud thicknesses in the training data set were also estimated using the radiosonde data. The accuracy of the results was analyzed through a comparison with L-band sounding radar data and quantified using the mean bias, root-mean-square error (RMSE), and correlation coefficient. The statistical results showed that an inversion with cloud information was the optimal method. Compared with the inversion profiles without cloud information, the RMSE values after adding cloud information reduced to varying degrees for the vast majority of height layers. These reductions were particularly clear in layers with clouds. The maximum reduction in the RMSE for the temperature profile was 2.2 K, while that for the humidity profile was 16%.

The effect of different spectral shape parameterizations of cloud droplet size distribution on first and second aerosol indirect effects in NACR CAM5 and evaluation with satellite data

NASA Astrophysics Data System (ADS)

Wang, M.; Peng, Y.; Xie, X.; Liu, Y.

2017-12-01

Aerosol cloud interaction continues to constitute one of the most significant uncertainties for anthropogenic climate perturbations. The parameterization of cloud droplet size distribution and autoconversion process from large scale cloud to rain can influence the estimation of first and second aerosol indirect effects in global climate models. We design a series of experiments focusing on the microphysical cloud scheme of NCAR CAM5 (Community Atmospheric Model Version 5) in transient historical run with realistic sea surface temperature and sea ice. We investigate the effect of three empirical, two semi-empirical and one analytical expressions for droplet size distribution on cloud properties and explore the statistical relationships between aerosol optical thickness (AOT) and simulated cloud variables, including cloud top droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP). We also introduce the droplet spectral shape parameter into the autoconversion process to incorporate the effect of droplet size distribution on second aerosol indirect effect. Three satellite datasets (MODIS Terra/ MODIS Aqua/ AVHRR) are used to evaluate the simulated aerosol indirect effect from the model. Evident CDER decreasing with significant AOT increasing is found in the east coast of China to the North Pacific Ocean and the east coast of USA to the North Atlantic Ocean. Analytical and semi-empirical expressions for spectral shape parameterization show stronger first aerosol indirect effect but weaker second aerosol indirect effect than empirical expressions because of the narrower droplet size distribution.

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

PubMed Central

Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei

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, ~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. PMID:29057838

Uncertainties in Ice-Sheet Altimetry from a Spaceborne 1064-nm Single-Channel Lidar Due to Undetected Thin Clouds

NASA Technical Reports Server (NTRS)

Yang, Yuekui; Marshak, Alexander; Varnai, Tamas; Wiscombe, Warren; Yang, Ping

2010-01-01

In support of the Ice, Cloud, and land Elevation Satellite (ICESat)-II mission, this paper studies the bias in surface-elevation measurements caused by undetected thin clouds. The ICESat-II satellite may only have a 1064-nm single-channel lidar onboard. Less sensitive to clouds than the 532-nm channel, the 1064-nm channel tends to miss thin clouds. Previous studies have demonstrated that scattering by cloud particles increases the photon-path length, thus resulting in biases in ice-sheet-elevation measurements from spaceborne lidars. This effect is referred to as atmospheric path delay. This paper complements previous studies in the following ways: First, atmospheric path delay is estimated over the ice sheets based on cloud statistics from the Geoscience Laser Altimeter System onboard ICESat and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua. Second, the effect of cloud particle size and shape is studied with the state-of-the-art phase functions developed for MODIS cirrus- cloud microphysical model. Third, the contribution of various orders of scattering events to the path delay is studied, and an analytical model of the first-order scattering contribution is developed. This paper focuses on the path delay as a function of telescope field of view (FOV). The results show that reducing telescope FOV can significantly reduce the expected path delay. As an example, the average path delays for FOV = 167 microrad (a 100-m-diameter circle on the surface) caused by thin undetected clouds by the 1064-nm channel over Greenland and East Antarctica are illustrated.

Covariance between Arctic sea ice and clouds within atmospheric state regimes at the satellite footprint level

PubMed Central

Kato, Seiji; Xu, Kuan‐Man; Cai, Ming

2015-01-01

Abstract Understanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice‐cloud relationship in the Arctic using a satellite footprint‐level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A‐Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and midtropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest‐magnitude cloud‐sea ice covariance occurs between 500 m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near‐surface static stability is found at larger sea ice concentrations. PMID:27818851

Determinants of Low Cloud Properties - An Artificial Neural Network Approach Using Observation Data Sets

NASA Astrophysics Data System (ADS)

Andersen, Hendrik; Cermak, Jan

2015-04-01

This contribution studies the determinants of low cloud properties based on the application of various global observation data sets in machine learning algorithms. Clouds play a crucial role in the climate system as their radiative properties and precipitation patterns significantly impact the Earth's energy balance. Cloud properties are determined by environmental conditions, as cloud formation requires the availability of water vapour ("precipitable water") and condensation nuclei in sufficiently saturated conditions. A main challenge in the research of aerosol-cloud interactions is the separation of aerosol effects from meteorological influence. To gain understanding of the processes that govern low cloud properties in order to increase accuracy of climate models and predictions of future changes in the climate system is thus of great importance. In this study, artificial neural networks are used to relate a selection of predictors (meteorological parameters, aerosol loading) to a set of predictands (cloud microphysical and optical properties). As meteorological parameters, wind direction and velocity, sea level pressure, static stability of the lower troposphere, atmospheric water vapour and temperature at the surface are used (re-analysis data by the European Centre for Medium-Range Weather Forecasts). In addition to meteorological conditions, aerosol loading is used as a predictor of cloud properties (MODIS collection 6 aerosol optical depth). The statistical model reveals significant relationships between predictors and predictands and is able to represent the aerosol-cloud-meteorology system better than frequently used bivariate relationships. The most important predictors can be identified by the additional error when excluding one predictor at a time. The sensitivity of each predictand to each of the predictors is analyzed.

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

NASA Technical Reports Server (NTRS)

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.

PubMed

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

2017-10-18

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM 2.5 ) 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 PM 2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM 2.5 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 PM 2.5 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 PM 2.5 concentrations.

The influence of Cloud Longwave Scattering together with a state-of-the-art Ice Longwave Optical Parameterization in Climate Model Simulations

NASA Astrophysics Data System (ADS)

Chen, Y. H.; Kuo, C. P.; Huang, X.; Yang, P.

2017-12-01

Clouds play an important role in the Earth's radiation budget, and thus realistic and comprehensive treatments of cloud optical properties and cloud-sky radiative transfer are crucial for simulating weather and climate. However, most GCMs neglect LW scattering effects by clouds and tend to use inconsistent cloud SW and LW optical parameterizations. Recently, co-authors of this study have developed a new LW optical properties parameterization for ice clouds, which is based on ice cloud particle statistics from MODIS measurements and state-of-the-art scattering calculation. A two-stream multiple-scattering scheme has also been implemented into the RRTMG_LW, a widely used longwave radiation scheme by climate modeling centers. This study is to integrate both the new LW cloud-radiation scheme for ice clouds and the modified RRTMG_LW with scattering capability into the NCAR CESM to improve the cloud longwave radiation treatment. A number of single column model (SCM) simulations using the observation from the ARM SGP site on July 18 to August 4 in 1995 are carried out to assess the impact of new LW optical properties of clouds and scattering-enabled radiation scheme on simulated radiation budget and cloud radiative effect (CRE). The SCM simulation allows interaction between cloud and radiation schemes with other parameterizations, but the large-scale forcing is prescribed or nudged. Comparing to the results from the SCM of the standard CESM, the new ice cloud optical properties alone leads to an increase of LW CRE by 26.85 W m-2 in average, as well as an increase of the downward LW flux at surface by 6.48 W m-2. Enabling LW cloud scattering further increases the LW CRE by another 3.57 W m-2 and the downward LW flux at the surface by 0.2 W m-2. The change of LW CRE is mainly due to an increase of cloud top height, which enhances the LW CRE. A long-term simulation of CESM will be carried out to further understand the impact of such changes on simulated climates.

Infrared Cloud Imager Development for Atmospheric Optical Communication Characterization, and Measurements at the JPL Table Mountain Facility

NASA Astrophysics Data System (ADS)

Nugent, P. W.; Shaw, J. A.; Piazzolla, S.

2013-02-01

The continuous demand for high data return in deep space and near-Earth satellite missions has led NASA and international institutions to consider alternative technologies for high-data-rate communications. One solution is the establishment of wide-bandwidth Earth-space optical communication links, which require (among other things) a nearly obstruction-free atmospheric path. Considering the atmospheric channel, the most common and most apparent impairments on Earth-space optical communication paths arise from clouds. Therefore, the characterization of the statistical behavior of cloud coverage for optical communication ground station candidate sites is of vital importance. In this article, we describe the development and deployment of a ground-based, long-wavelength infrared cloud imaging system able to monitor and characterize the cloud coverage. This system is based on a commercially available camera with a 62-deg diagonal field of view. A novel internal-shutter-based calibration technique allows radiometric calibration of the camera, which operates without a thermoelectric cooler. This cloud imaging system provides continuous day-night cloud detection with constant sensitivity. The cloud imaging system also includes data-processing algorithms that calculate and remove atmospheric emission to isolate cloud signatures, and enable classification of clouds according to their optical attenuation. Measurements of long-wavelength infrared cloud radiance are used to retrieve the optical attenuation (cloud optical depth due to absorption and scattering) in the wavelength range of interest from visible to near-infrared, where the cloud attenuation is quite constant. This article addresses the specifics of the operation, calibration, and data processing of the imaging system that was deployed at the NASA/JPL Table Mountain Facility (TMF) in California. Data are reported from July 2008 to July 2010. These data describe seasonal variability in cloud cover at the TMF site, with cloud amount (percentage of cloudy pixels) peaking at just over 51 percent during February, of which more than 60 percent had optical attenuation exceeding 12 dB at wavelengths in the range from the visible to the near-infrared. The lowest cloud amount was found during August, averaging 19.6 percent, and these clouds were mostly optically thin, with low attenuation.

TES Detector Noise Limited Readout Using SQUID Multiplexers

NASA Technical Reports Server (NTRS)

Staguhn, J. G.; Benford, D. J.; Chervenak, J. A.; Khan, S. A.; Moseley, S. H.; Shafer, R. A.; Deiker, S.; Grossman, E. N.; Hilton, G. C.; Irwin, K. D.

2004-01-01

The availability of superconducting Transition Edge Sensors (TES) with large numbers of individual detector pixels requires multiplexers for efficient readout. The use of multiplexers reduces the number of wires needed between the cryogenic electronics and the room temperature electronics and cuts the number of required cryogenic amplifiers. We are using an 8 channel SQUID multiplexer to read out one-dimensional TES arrays which are used for submillimeter astronomical observations. We present results from test measurements which show that the low noise level of the SQUID multiplexers allows accurate measurements of the TES Johnson noise, and that in operation, the readout noise is dominated by the detector noise. Multiplexers for large number of channels require a large bandwidth for the multiplexed readout signal. We discuss the resulting implications for the noise performance of these multiplexers which will be used for the readout of two dimensional TES arrays in next generation instruments.

Extracting information from multiplex networks

NASA Astrophysics Data System (ADS)

Iacovacci, Jacopo; Bianconi, Ginestra

2016-06-01

Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ ˜ S for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

Advanced Code-Division Multiplexers for Superconducting Detector Arrays

NASA Astrophysics Data System (ADS)

Irwin, K. D.; Cho, H. M.; Doriese, W. B.; Fowler, J. W.; Hilton, G. C.; Niemack, M. D.; Reintsema, C. D.; Schmidt, D. R.; Ullom, J. N.; Vale, L. R.

2012-06-01

Multiplexers based on the modulation of superconducting quantum interference devices are now regularly used in multi-kilopixel arrays of superconducting detectors for astrophysics, cosmology, and materials analysis. Over the next decade, much larger arrays will be needed. These larger arrays require new modulation techniques and compact multiplexer elements that fit within each pixel. We present a new in-focal-plane code-division multiplexer that provides multiplexing elements with the required scalability. This code-division multiplexer uses compact lithographic modulation elements that simultaneously multiplex both signal outputs and superconducting transition-edge sensor (TES) detector bias voltages. It eliminates the shunt resistor used to voltage bias TES detectors, greatly reduces power dissipation, allows different dc bias voltages for each TES, and makes all elements sufficiently compact to fit inside the detector pixel area. These in-focal plane code-division multiplexers can be combined with multi-GHz readout based on superconducting microresonators to scale to even larger arrays.

Three-mode all-optical (de)multiplexing on a SOI chip

NASA Astrophysics Data System (ADS)

Le, Yan-Si; Wang, Zhi; Li, Zhi-Yong; Li, Ying; Li, Qiang; Cui, Can; Wu, Chong-Qing

2018-01-01

An on-chip three-mode division multiplexing circuit using a simple ADC-based TE0 & TE1 & TE2 (de)multiplexer is demonstrated to improve the link capacity of on-chip optical interconnects. The proposed (de)multiplexer does not contain any tapered waveguide which is different from the previous mode (de)multiplexer based on ADCs. Here, we choose multimode waveguide width first and then confirm corresponding width of the other two waveguides. Thus the bus waveguide without any tapers can not only reduce complexity of (de)multiplexer but also reduce difficulty of the fabrication. Our simulation results show that the hybrid multiplexer has relatively low loss and low crosstalk about -40 dB, -26.99 dB and -28.72 dB for each mode around 1550 nm with a width-variation w =± 25 nm. These properties make the proposed mode-(de)multiplexer suitable for application in high-capacity data transmission.

The Effects of an Absorbing Smoke Layer on MODIS Marine Boundary Layer Cloud Optical Property Retrievals and Radiative Forcing

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Platnick, Steven

2012-01-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer . (MBL) clouds off the southern Atlantic coast of Africa and the effects on MODIS cloud optical property retrievals (MOD06) of an overlying absorbing smoke layer. During much of August and September, a persistent smoke layer resides over this region, produced from extensive biomass burning throughout the southern African savanna. The resulting absorption, which increases with decreasing wavelength, potentially introduces biases into the MODIS cloud optical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 micron (effective particle size retrievals are derived from the longer-wavelength near-IR channels at 1.6, 2.1, and 3.7 microns). Here, the spatial distributions of the scalar statistics of both the cloud and aerosol layers are first determined from the CALIOP 5 km layer products. Next, the MOD06 look-up tables (LUTs) are adjusted by inserting an absorbing smoke layer of varying optical thickness over the cloud. Retrievals are subsequently performed for a subset of MODIS pixels collocated with the CALIOP ground track, using smoke optical thickness from the CALIOP 5km aerosol layer product to select the appropriate LUT. The resulting differences in cloud optical property retrievals due to the inclusion of the smoke layer in the LUTs will be examined. In addition, the direct radiative forcing of this smoke layer will be investigated from the perspective of the cloud optical property retrieval differences.

Evaluating the Performance of the Goddard Multi-Scale Modeling Framework against GPM, TRMM and CloudSat/CALIPSO Products

NASA Astrophysics Data System (ADS)

Chern, J. D.; Tao, W. K.; Lang, S. E.; Matsui, T.; Mohr, K. I.

2014-12-01

Four six-month (March-August 2014) experiments with the Goddard Multi-scale Modeling Framework (MMF) were performed to study the impacts of different Goddard one-moment bulk microphysical schemes and large-scale forcings on the performance of the MMF. Recently a new Goddard one-moment bulk microphysics with four-ice classes (cloud ice, snow, graupel, and frozen drops/hail) has been developed based on cloud-resolving model simulations with large-scale forcings from field campaign observations. The new scheme has been successfully implemented to the MMF and two MMF experiments were carried out with this new scheme and the old three-ice classes (cloud ice, snow graupel) scheme. The MMF has global coverage and can rigorously evaluate microphysics performance for different cloud regimes. The results show MMF with the new scheme outperformed the old one. The MMF simulations are also strongly affected by the interaction between large-scale and cloud-scale processes. Two MMF sensitivity experiments with and without nudging large-scale forcings to those of ERA-Interim reanalysis were carried out to study the impacts of large-scale forcings. The model simulated mean and variability of surface precipitation, cloud types, cloud properties such as cloud amount, hydrometeors vertical profiles, and cloud water contents, etc. in different geographic locations and climate regimes are evaluated against GPM, TRMM, CloudSat/CALIPSO satellite observations. The Goddard MMF has also been coupled with the Goddard Satellite Data Simulation Unit (G-SDSU), a system with multi-satellite, multi-sensor, and multi-spectrum satellite simulators. The statistics of MMF simulated radiances and backscattering can be directly compared with satellite observations to assess the strengths and/or deficiencies of MMF simulations and provide guidance on how to improve the MMF and microphysics.

Galactic cold cores. IV. Cold submillimetre sources: catalogue and statistical analysis

NASA Astrophysics Data System (ADS)

Montillaud, J.; Juvela, M.; Rivera-Ingraham, A.; Malinen, J.; Pelkonen, V.-M.; Ristorcelli, I.; Montier, L.; Marshall, D. J.; Marton, G.; Pagani, L.; Toth, L. V.; Zahorecz, S.; Ysard, N.; McGehee, P.; Paladini, R.; Falgarone, E.; Bernard, J.-P.; Motte, F.; Zavagno, A.; Doi, Y.

2015-12-01

Context. For the project Galactic cold cores, Herschel photometric observations were carried out as a follow-up of cold regions of interstellar clouds previously identified with the Planck satellite. The aim of the project is to derive the physical properties of the population of cold sources and to study its connection to ongoing and future star formation. Aims: We build a catalogue of cold sources within the clouds in 116 fields observed with the Herschel PACS and SPIRE instruments. We wish to determine the general physical characteristics of the cold sources and to examine the correlations with their host cloud properties. Methods: From Herschel data, we computed colour temperature and column density maps of the fields. We estimated the distance to the target clouds and provide both uncertainties and reliability flags for the distances. The getsources multiwavelength source extraction algorithm was employed to build a catalogue of several thousand cold sources. Mid-infrared data were used, along with colour and position criteria, to separate starless and protostellar sources. We also propose another classification method based on submillimetre temperature profiles. We analysed the statistical distributions of the physical properties of the source samples. Results: We provide a catalogue of ~4000 cold sources within or near star forming clouds, most of which are located either in nearby molecular complexes (≲1 kpc) or in star forming regions of the nearby galactic arms (~2 kpc). About 70% of the sources have a size compatible with an individual core, and 35% of those sources are likely to be gravitationally bound. Significant statistical differences in physical properties are found between starless and protostellar sources, in column density versus dust temperature, mass versus size, and mass versus dust temperature diagrams. The core mass functions are very similar to those previously reported for other regions. On statistical grounds we find that gravitationally bound sources have higher background column densities (median Nbg(H2) ~ 5 × 1021 cm-2) than unbound sources (median Nbg(H2) ~ 3 × 1021 cm-2). These values of Nbg(H2) are higher for higher dust temperatures of the external layers of the parent cloud. However, only in a few cases do we find clear Nbg(H2) thresholds for the presence of cores. The dust temperatures of cloud external layers show clear variations with galactic location, as may the source temperatures. Conclusions: Our data support a more complex view of star formation than in the simple idea of a column density threshold. They show a clear influence of the surrounding UV-visible radiation on how cores distribute in their host clouds with possible variations on the Galactic scale. Planck (http://www.esa.int/Planck) is a project of the European Space Agency - ESA - with instruments provided by two scientific consortia funded by ESA member states (in particular the lead countries: France and Italy) with contributions from NASA (USA), and telescope reflectors provided in a collaboration between ESA and a scientific consortium led and funded by Denmark.Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.Full Table B.1 is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/584/A92

“Lidar Investigations of Aerosol, Cloud, and Boundary Layer Properties Over the ARM ACRF Sites”

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

Ferrare, Richard; Turner, David

2015-01-13

Project goals; Characterize the aerosol and ice vertical distributions over the ARM NSA site, and in particular to discriminate between elevated aerosol layers and ice clouds in optically thin scattering layers; Characterize the water vapor and aerosol vertical distributions over the ARM Darwin site, how these distributions vary seasonally, and quantify the amount of water vapor and aerosol that is above the boundary layer; Use the high temporal resolution Raman lidar data to examine how aerosol properties vary near clouds; Use the high temporal resolution Raman lidar and Atmospheric Emitted Radiance Interferometer (AERI) data to quantify entrainment in optically thinmore » continental cumulus clouds; and Use the high temporal Raman lidar data to continue to characterize the turbulence within the convective boundary layer and how the turbulence statistics (e.g., variance, skewness) is correlated with larger scale variables predicted by models.« less

Observations of Cirrus Clouds over the Pacific Region by the NASA Multiwavelength Lidar System

NASA Technical Reports Server (NTRS)

Ismail, Syed; Browell, Edward V.; Fenn, Marta A.; Nowicki, Greg D.

1992-01-01

As part of the Pacific Exploratory Mission-West Campaign that took place during 16 Sep. - 21 Oct. 1991, lidar measurements were made from the ARC DC-8 aircraft at an altitude of approximately 9 km. This mission provided a unique opportunity to make cirrus cloud observations around the Pacific region covering the latitude range from 5 to 55 deg N and the longitude range from -114 to 120 deg E. Cirrus clouds were observed on most of these flights providing a unique data base. The latitudinal coverage of cirrus observations was further extended to -5 deg S from observations on 30 Jan. 1992 as part of the Airborne Arctic Stratospheric Expedition 2. During this latter mission, aerosol depolarizations at 622 and 1064 nm were also measured. The optical characteristics and statistics related to these cirrus cloud observations are summarized.

The Impact of Horizontal and Temporal Resolution on Convection and Precipitation with High-Resolution GEOS-5

NASA Technical Reports Server (NTRS)

Putman, William P.

2012-01-01

Using a high-resolution non-hydrostatic version of GEOS-5 with the cubed-sphere finite-volume dynamical core, the impact of spatial and temporal resolution on cloud properties will be evaluated. There are indications from examining convective cluster development in high resolution GEOS-5 forecasts that the temporal resolution within the model may playas significant a role as horizontal resolution. Comparing modeled convective cloud clusters versus satellite observations of brightness temperature, we have found that improved. temporal resolution in GEOS-S accounts for a significant portion of the improvements in the statistical distribution of convective cloud clusters. Using satellite simulators in GEOS-S we will compare the cloud optical properties of GEOS-S at various spatial and temporal resolutions with those observed from MODIS. The potential impact of these results on tropical cyclone formation and intensity will be examined as well.

A curvature-based weighted fuzzy c-means algorithm for point clouds de-noising

NASA Astrophysics Data System (ADS)

Cui, Xin; Li, Shipeng; Yan, Xiutian; He, Xinhua

2018-04-01

In order to remove the noise of three-dimensional scattered point cloud and smooth the data without damnify the sharp geometric feature simultaneity, a novel algorithm is proposed in this paper. The feature-preserving weight is added to fuzzy c-means algorithm which invented a curvature weighted fuzzy c-means clustering algorithm. Firstly, the large-scale outliers are removed by the statistics of r radius neighboring points. Then, the algorithm estimates the curvature of the point cloud data by using conicoid parabolic fitting method and calculates the curvature feature value. Finally, the proposed clustering algorithm is adapted to calculate the weighted cluster centers. The cluster centers are regarded as the new points. The experimental results show that this approach is efficient to different scale and intensities of noise in point cloud with a high precision, and perform a feature-preserving nature at the same time. Also it is robust enough to different noise model.

Insights from modeling and observational evaluation of a precipitating continental cumulus event observed during the MC3E field campaign

DOE PAGES

Mechem, David B.; Giangrande, Scott E.; Wittman, Carly S.; ...

2015-03-13

A case of shallow cumulus and precipitating cumulus congestus sampled at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) supersite is analyzed using a multi-sensor observational approach and numerical simulation. Observations from a new radar suite surrounding the facility are used to characterize the evolving statistical behavior of the precipitating cloud system. This is accomplished using distributions of different measures of cloud geometry and precipitation properties. Large-eddy simulation (LES) with size-resolved (bin) microphysics is employed to determine the forcings most important in producing the salient aspects of the cloud system captured in the radar observations. Our emphasis ismore » on assessing the importance of time-varying vs. steady-state large-scale forcing on the model's ability to reproduce the evolutionary behavior of the cloud system. Additional consideration is given to how the characteristic spatial scale and homogeneity of the forcing imposed on the simulation influences the evolution of cloud system properties. Results indicate that several new scanning radar estimates such as distributions of cloud top are useful to differentiate the value of time-varying (or at least temporally well-matched) forcing on LES solution fidelity.« less

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

Zhang, Damao; Wang, Zhien; Heymsfield, Andrew J.

Measurement of ice number concentration in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving ice number concentration from remote sensing measurements. The simple ice generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer ice number concentration quantitatively. To understand the strong temperature dependency of ice habit and growth rate quantitatively, we develop a 1-D ice growth model to calculate the ice diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of ice crystals calculatedmore » from the 1-D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D ice growth model simulations, we develop a method to retrieve the ice number concentrations in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved ice concentrations in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved ice number concentrations are within an uncertainty of a factor of 2, statistically.« less

Two space scatterer formalism calculation of bulk parameters of thunderclouds

NASA Technical Reports Server (NTRS)

Phanord, Dieudonne D.

1994-01-01

In a previous study, we used a modified two-space scatterer formalism of Twersky to establish for a cloud modeled as a statistically homogeneous distribution of spherical water droplets, the dispersion relations that determine its bulk propagation numbers and bulk indexes of refraction in terms of the vector equivalent scattering amplitude and the dyadic scattering amplitude of the single water droplet in isolation. The results were specialized to the forward direction of scattering while demanding that the scatterers preserve the incident polarization. We apply this approach to obtain specific numerical values for the macroscopic parameters of the cloud. We work with a cloud of density rho = 100 cm(exp -3), a wavelength lambda = 0.7774 microns, and with spherical water droplets of common radius alpha = 10 microns. In addition, the scattering medium is divided into three parts, the medium outside the cloud, moist air (the medium inside the cloud but outside the droplets), and the medium inside the spherical water droplets. The results of this report are applicable to a cloud of any geometry since the boundary does not interfere with the calculations. Also, it is important to notice the plane wave nature of the incidence wave in the moist atmosphere.

Ultra-Parameterized CAM: Progress Towards Low-Cloud Permitting Superparameterization

NASA Astrophysics Data System (ADS)

Parishani, H.; Pritchard, M. S.; Bretherton, C. S.; Khairoutdinov, M.; Wyant, M. C.; Singh, B.

2016-12-01

A leading source of uncertainty in climate feedback arises from the representation of low clouds, which are not resolved but depend on small-scale physical processes (e.g. entrainment, boundary layer turbulence) that are heavily parameterized. We show results from recent attempts to achieve an explicit representation of low clouds by pushing the computational limits of cloud superparameterization to resolve boundary-layer eddy scales relevant to marine stratocumulus (250m horizontal and 20m vertical length scales). This extreme configuration is called "ultraparameterization". Effects of varying horizontal vs. vertical resolution are analyzed in the context of altered constraints on the turbulent kinetic energy statistics of the marine boundary layer. We show that 250m embedded horizontal resolution leads to a more realistic boundary layer vertical structure, but also to an unrealistic cloud pulsation that cannibalizes time mean LWP. We explore the hypothesis that feedbacks involving horizontal advection (not typically encountered in offline LES that neglect this degree of freedom) may conspire to produce such effects and present strategies to compensate. The results are relevant to understanding the emergent behavior of quasi-resolved low cloud decks in a multi-scale modeling framework within a previously unencountered grey zone of better resolved boundary-layer turbulence.

The simulation of molecular clouds formation in the Milky Way

NASA Astrophysics Data System (ADS)

Khoperskov, S. A.; Vasiliev, E. O.; Sobolev, A. M.; Khoperskov, A. V.

2013-01-01

Using 3D hydrodynamic calculations we simulate formation of molecular clouds in the Galaxy. The simulations take into account molecular hydrogen chemical kinetics, cooling and heating processes. Comprehensive gravitational potential accounts for contributions from the stellar bulge, two- and four-armed spiral structure, stellar disc, dark halo and takes into account self-gravitation of the gaseous component. Gas clouds in our model form in the spiral arms due to shear and wiggle instabilities and turn into molecular clouds after t ≳ 100 Myr. At the times t ˜ 100-300 Myr the clouds form hierarchical structures and agglomerations with the sizes of 100 pc and greater. We analyse physical properties of the simulated clouds and find that synthetic statistical distributions like mass spectrum, `mass-size' relation and velocity dispersion are close to those observed in the Galaxy. The synthetic l-v (galactic longitude-radial velocity) diagram of the simulated molecular gas distribution resembles observed one and displays a structure with appearance similar to molecular ring of the Galaxy. Existence of this structure in our modelling can be explained by superposition of emission from the galactic bar and the spiral arms at ˜3-4 kpc.

Aerosol-cloud interactions in mixed-phase convective clouds - Part 1: Aerosol perturbations

NASA Astrophysics Data System (ADS)

Miltenberger, Annette K.; Field, Paul R.; Hill, Adrian A.; Rosenberg, Phil; Shipway, Ben J.; Wilkinson, Jonathan M.; Scovell, Robert; Blyth, Alan M.

2018-03-01

Changes induced by perturbed aerosol conditions in moderately deep mixed-phase convective clouds (cloud top height ˜ 5 km) developing along sea-breeze convergence lines are investigated with high-resolution numerical model simulations. The simulations utilise the newly developed Cloud-AeroSol Interacting Microphysics (CASIM) module for the Unified Model (UM), which allows for the representation of the two-way interaction between cloud and aerosol fields. Simulations are evaluated against observations collected during the COnvective Precipitation Experiment (COPE) field campaign over the southwestern peninsula of the UK in 2013. The simulations compare favourably with observed thermodynamic profiles, cloud base cloud droplet number concentrations (CDNC), cloud depth, and radar reflectivity statistics. Including the modification of aerosol fields by cloud microphysical processes improves the correspondence with observed CDNC values and spatial variability, but reduces the agreement with observations for average cloud size and cloud top height. Accumulated precipitation is suppressed for higher-aerosol conditions before clouds become organised along the sea-breeze convergence lines. Changes in precipitation are smaller in simulations with aerosol processing. The precipitation suppression is due to less efficient precipitation production by warm-phase microphysics, consistent with parcel model predictions. In contrast, after convective cells organise along the sea-breeze convergence zone, accumulated precipitation increases with aerosol concentrations. Condensate production increases with the aerosol concentrations due to higher vertical velocities in the convective cores and higher cloud top heights. However, for the highest-aerosol scenarios, no further increase in the condensate production occurs, as clouds grow into an upper-level stable layer. In these cases, the reduced precipitation efficiency (PE) dominates the precipitation response and no further precipitation enhancement occurs. Previous studies of deep convective clouds have related larger vertical velocities under high-aerosol conditions to enhanced latent heating from freezing. In the presented simulations changes in latent heating above the 0°C are negligible, but latent heating from condensation increases with aerosol concentrations. It is hypothesised that this increase is related to changes in the cloud field structure reducing the mixing of environmental air into the convective core. The precipitation response of the deeper mixed-phase clouds along well-established convergence lines can be the opposite of predictions from parcel models. This occurs when clouds interact with a pre-existing thermodynamic environment and cloud field structural changes occur that are not captured by simple parcel model approaches.

Stochasticity of convection in Giga-LES data

NASA Astrophysics Data System (ADS)

De La Chevrotière, Michèle; Khouider, Boualem; Majda, Andrew J.

2016-09-01

The poor representation of tropical convection in general circulation models (GCMs) is believed to be responsible for much of the uncertainty in the predictions of weather and climate in the tropics. The stochastic multicloud model (SMCM) was recently developed by Khouider et al. (Commun Math Sci 8(1):187-216, 2010) to represent the missing variability in GCMs due to unresolved features of organized tropical convection. The SMCM is based on three cloud types (congestus, deep and stratiform), and transitions between these cloud types are formalized in terms of probability rules that are functions of the large-scale environment convective state and a set of seven arbitrary cloud timescale parameters. Here, a statistical inference method based on the Bayesian paradigm is applied to estimate these key cloud timescales from the Giga-LES dataset, a 24-h large-eddy simulation (LES) of deep tropical convection (Khairoutdinov et al. in J Adv Model Earth Syst 1(12), 2009) over a domain comparable to a GCM gridbox. A sequential learning strategy is used where the Giga-LES domain is partitioned into a few subdomains, and atmospheric time series obtained on each subdomain are used to train the Bayesian procedure incrementally. Convergence of the marginal posterior densities for all seven parameters is demonstrated for two different grid partitions, and sensitivity tests to other model parameters are also presented. A single column model simulation using the SMCM parameterization with the Giga-LES inferred parameters reproduces many important statistical features of the Giga-LES run, without any further tuning. In particular it exhibits intermittent dynamical behavior in both the stochastic cloud fractions and the large scale dynamics, with periods of dry phases followed by a coherent sequence of congestus, deep, and stratiform convection, varying on timescales of a few hours consistent with the Giga-LES time series. The chaotic variations of the cloud area fractions were captured fairly well both qualitatively and quantitatively demonstrating the stochastic nature of convection in the Giga-LES simulation.

Icing Frequencies Experienced During Climb and Descent by Fighter-Interceptor Aircraft

NASA Technical Reports Server (NTRS)

Perkins, Porter J.

1958-01-01

Data and analyses are presented on the relative frequencies of occurrence and severity of icing cloud layers encountered by jet aircraft in the climb and descent phases of flights to high altitudes. Fighter-interceptor aircraft operated by the Air Defense Command (USAF) at bases in the Duluth and Seattle areas collected the data with icing meters installed for a l-year period. The project was part of an extensive program conducted by the NACA to collect Icing cloud data for evaluating the icing problem relevant to routine operations. The average frequency of occurrence of icing was found to be about 5 percent of the number of climbs and descents during 1 year of operations The icing encounters were predominantly in the low and middle cloud layers, decreasing above 15,000 feet to practically none above 25,000 feet. The greatest thickness of ice that would accumulate on any aircraft component (as indicated by the accretion on a small object) was measured with the icing meters. The ice thicknesses on a small sensing probe averaged less than 1/32 inch and did not exceed 1/2 inch. Such accumulations are relatively small when compared with those that can form during horizontal flight in icing clouds. The light accretions resulted from relatively steep angles of flight through generally thin cloud layers. Because of the limited statistical reliability of the results, an analysis was made using previous statistics on icing clouds below an altitude of 20,000 feet to determine the general icing severity probabilities. The calculations were made using adiabatic lifting as a basis to establish the liquid-water content. Probabilities of over-all ice accretions on a small object as a function of airspeed and rate of climb were computed from the derived water contents. These results were then combined with the probability of occurrence of icing in order to give the icing severity that can be expected for routine aircraft operations.

76 FR 48169 - Advancing Regulatory Science for Highly Multiplexed Microbiology/Medical Countermeasure Devices...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-08

...] Advancing Regulatory Science for Highly Multiplexed Microbiology/ Medical Countermeasure Devices; Public... Regulatory Science for Highly Multiplexed Microbiology/Medical Countermeasure Devices.'' The purpose of the public meeting is to discuss performance evaluation of highly multiplexed microbiology/medical...

Interlaboratory study of DNA extraction from multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for individual kernel detection system of genetically modified maize.

PubMed

Akiyama, Hiroshi; Sakata, Kozue; Makiyma, Daiki; Nakamura, Kosuke; Teshima, Reiko; Nakashima, Akie; Ogawa, Asako; Yamagishi, Toru; Futo, Satoshi; Oguchi, Taichi; Mano, Junichi; Kitta, Kazumi

2011-01-01

In many countries, the labeling of grains, feed, and foodstuff is mandatory if the genetically modified (GM) organism content exceeds a certain level of approved GM varieties. We previously developed an individual kernel detection system consisting of grinding individual kernels, DNA extraction from the individually ground kernels, GM detection using multiplex real-time PCR, and GM event detection using multiplex qualitative PCR to analyze the precise commingling level and varieties of GM maize in real sample grains. We performed the interlaboratory study of the DNA extraction with multiple ground samples, multiplex real-time PCR detection, and multiplex qualitative PCR detection to evaluate its applicability, practicality, and ruggedness for the individual kernel detection system of GM maize. DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR were evaluated by five laboratories in Japan, and all results from these laboratories were consistent with the expected results in terms of the commingling level and event analysis. Thus, the DNA extraction with multiple ground samples, multiplex real-time PCR, and multiplex qualitative PCR for the individual kernel detection system is applicable and practicable in a laboratory to regulate the commingling level of GM maize grain for GM samples, including stacked GM maize.

Cloud and boundary layer interactions over the Arctic sea-ice in late summer

NASA Astrophysics Data System (ADS)

Shupe, M. D.; Persson, P. O. G.; Brooks, I. M.; Tjernström, M.; Sedlar, J.; Mauritsen, T.; Sjogren, S.; Leck, C.

2013-05-01

Observations from the Arctic Summer Cloud Ocean Study (ASCOS), in the central Arctic sea-ice pack in late summer 2008, provide a detailed view of cloud-atmosphere-surface interactions and vertical mixing processes over the sea-ice environment. Measurements from a suite of ground-based remote sensors, near surface meteorological and aerosol instruments, and profiles from radiosondes and a helicopter are combined to characterize a week-long period dominated by low-level, mixed-phase, stratocumulus clouds. Detailed case studies and statistical analyses are used to develop a conceptual model for the cloud and atmosphere structure and their interactions in this environment. Clouds were persistent during the period of study, having qualities that suggest they were sustained through a combination of advective influences and in-cloud processes, with little contribution from the surface. Radiative cooling near cloud top produced buoyancy-driven, turbulent eddies that contributed to cloud formation and created a cloud-driven mixed layer. The depth of this mixed layer was related to the amount of turbulence and condensed cloud water. Coupling of this cloud-driven mixed layer to the surface boundary layer was primarily determined by proximity. For 75% of the period of study, the primary stratocumulus cloud-driven mixed layer was decoupled from the surface and typically at a warmer potential temperature. Since the near-surface temperature was constrained by the ocean-ice mixture, warm temperatures aloft suggest that these air masses had not significantly interacted with the sea-ice surface. Instead, back trajectory analyses suggest that these warm airmasses advected into the central Arctic Basin from lower latitudes. Moisture and aerosol particles likely accompanied these airmasses, providing necessary support for cloud formation. On the occasions when cloud-surface coupling did occur, back trajectories indicated that these air masses advected at low levels, while mixing processes kept the mixed layer in equilibrium with the near-surface environment. Rather than contributing buoyancy forcing for the mixed-layer dynamics, the surface instead simply appeared to respond to the mixed-layer processes aloft. Clouds in these cases often contained slightly higher condensed water amounts, potentially due to additional moisture sources from below.

Cloud and boundary layer interactions over the Arctic sea ice in late summer

NASA Astrophysics Data System (ADS)

Shupe, M. D.; Persson, P. O. G.; Brooks, I. M.; Tjernström, M.; Sedlar, J.; Mauritsen, T.; Sjogren, S.; Leck, C.

2013-09-01

Observations from the Arctic Summer Cloud Ocean Study (ASCOS), in the central Arctic sea-ice pack in late summer 2008, provide a detailed view of cloud-atmosphere-surface interactions and vertical mixing processes over the sea-ice environment. Measurements from a suite of ground-based remote sensors, near-surface meteorological and aerosol instruments, and profiles from radiosondes and a helicopter are combined to characterize a week-long period dominated by low-level, mixed-phase, stratocumulus clouds. Detailed case studies and statistical analyses are used to develop a conceptual model for the cloud and atmosphere structure and their interactions in this environment. Clouds were persistent during the period of study, having qualities that suggest they were sustained through a combination of advective influences and in-cloud processes, with little contribution from the surface. Radiative cooling near cloud top produced buoyancy-driven, turbulent eddies that contributed to cloud formation and created a cloud-driven mixed layer. The depth of this mixed layer was related to the amount of turbulence and condensed cloud water. Coupling of this cloud-driven mixed layer to the surface boundary layer was primarily determined by proximity. For 75% of the period of study, the primary stratocumulus cloud-driven mixed layer was decoupled from the surface and typically at a warmer potential temperature. Since the near-surface temperature was constrained by the ocean-ice mixture, warm temperatures aloft suggest that these air masses had not significantly interacted with the sea-ice surface. Instead, back-trajectory analyses suggest that these warm air masses advected into the central Arctic Basin from lower latitudes. Moisture and aerosol particles likely accompanied these air masses, providing necessary support for cloud formation. On the occasions when cloud-surface coupling did occur, back trajectories indicated that these air masses advected at low levels, while mixing processes kept the mixed layer in equilibrium with the near-surface environment. Rather than contributing buoyancy forcing for the mixed-layer dynamics, the surface instead simply appeared to respond to the mixed-layer processes aloft. Clouds in these cases often contained slightly higher condensed water amounts, potentially due to additional moisture sources from below.

Constraining the models' response of tropical low clouds to SST forcings using CALIPSO observations

NASA Astrophysics Data System (ADS)

Cesana, G.; Del Genio, A. D.; Ackerman, A. S.; Brient, F.; Fridlind, A. M.; Kelley, M.; Elsaesser, G.

2017-12-01

Low-cloud response to a warmer climate is still pointed out as being the largest source of uncertainty in the last generation of climate models. To date there is no consensus among the models on whether the tropical low cloudiness would increase or decrease in a warmer climate. In addition, it has been shown that - depending on their climate sensitivity - the models either predict deeper or shallower low clouds. Recently, several relationships between inter-model characteristics of the present-day climate and future climate changes have been highlighted. These so-called emergent constraints aim to target relevant model improvements and to constrain models' projections based on current climate observations. Here we propose to use - for the first time - 10 years of CALIPSO cloud statistics to assess the ability of the models to represent the vertical structure of tropical low clouds for abnormally warm SST. We use a simulator approach to compare observations and simulations and focus on the low-layered clouds (i.e. z < 3.2km) as well the more detailed level perspective of clouds (40 levels from 0 to 19km). Results show that in most models an increase of the SST leads to a decrease of the low-layer cloud fraction. Vertically, the clouds deepen namely by decreasing the cloud fraction in the lowest levels and increasing it around the top of the boundary-layer. This feature is coincident with an increase of the high-level cloud fraction (z > 6.5km). Although the models' spread is large, the multi-model mean captures the observed variations but with a smaller amplitude. We then employ the GISS model to investigate how changes in cloud parameterizations affect the response of low clouds to warmer SSTs on the one hand; and how they affect the variations of the model's cloud profiles with respect to environmental parameters on the other hand. Finally, we use CALIPSO observations to constrain the model by determining i) what set of parameters allows reproducing the observed relationships and ii) what are the consequences on the cloud feedbacks. These results point toward process-oriented constraints of low-cloud responses to surface warming and environmental parameters.

Excursion set mass functions for hierarchical Gaussian fluctuations

NASA Technical Reports Server (NTRS)

Bond, J. R.; Kaiser, N.; Cole, S.; Efstathiou, G.

1991-01-01

It is pointed out that most schemes for determining the mass function of virialized objects from the statistics of the initial density perturbation field suffer from the cloud-in-cloud problem of miscounting the number of low-mass clumps, many of which would have been subsumed into larger objects. The paper proposes a solution based on the theory of the excursion sets of F(r, R sub f), the four-dimensional initial density perturbation field smoothed with a continuous hierarchy of filters of radii R sub f.

Costs of cloud computing for a biometry department. A case study.

PubMed

Knaus, J; Hieke, S; Binder, H; Schwarzer, G

2013-01-01

"Cloud" computing providers, such as the Amazon Web Services (AWS), offer stable and scalable computational resources based on hardware virtualization, with short, usually hourly, billing periods. The idea of pay-as-you-use seems appealing for biometry research units which have only limited access to university or corporate data center resources or grids. This case study compares the costs of an existing heterogeneous on-site hardware pool in a Medical Biometry and Statistics department to a comparable AWS offer. The "total cost of ownership", including all direct costs, is determined for the on-site hardware, and hourly prices are derived, based on actual system utilization during the year 2011. Indirect costs, which are difficult to quantify are not included in this comparison, but nevertheless some rough guidance from our experience is given. To indicate the scale of costs for a methodological research project, a simulation study of a permutation-based statistical approach is performed using AWS and on-site hardware. In the presented case, with a system utilization of 25-30 percent and 3-5-year amortization, on-site hardware can result in smaller costs, compared to hourly rental in the cloud dependent on the instance chosen. Renting cloud instances with sufficient main memory is a deciding factor in this comparison. Costs for on-site hardware may vary, depending on the specific infrastructure at a research unit, but have only moderate impact on the overall comparison and subsequent decision for obtaining affordable scientific computing resources. Overall utilization has a much stronger impact as it determines the actual computing hours needed per year. Taking this into ac count, cloud computing might still be a viable option for projects with limited maturity, or as a supplement for short peaks in demand.

76 FR 71982 - Advancing Regulatory Science for Highly Multiplexed Microbiology/Medical Countermeasure Devices...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-21

...] Advancing Regulatory Science for Highly Multiplexed Microbiology/ Medical Countermeasure Devices; Public... Multiplexed Microbiology/ Medical Countermeasure Devices'' that published in the Federal Register of August 8... the October 13, 2011, meeting, including the performance evaluation of highly multiplexed microbiology...

Results of the Thailand Warm-Cloud Hygroscopic Particle Seeding Experiment.

NASA Astrophysics Data System (ADS)

Silverman, Bernard A.; Sukarnjanaset, Wathana

2000-07-01

A randomized, warm-rain enhancement experiment was carried out during 1995-98 in the Bhumibol catchment area in northwestern Thailand. The experiment was conducted in accordance with a randomized, floating single-target design. The seeding targets were semi-isolated, warm convective clouds, contained within a well-defined experimental unit, that, upon qualification, were selected for seeding or not seeding with calcium chloride particles in a random manner. The seeding was done by dispensing the calcium chloride particles at an average rate of 21 kg km1 per seeding pass into the updrafts of growing warm convective clouds (about 1-2 km above cloud base) that have not yet developed or, at most, have just started to develop a precipitation radar echo. The experiment was carried out by the Bureau of Royal Rainmaking and Agricultural Aviation (BRRAA) of the Ministry of Agriculture and Cooperatives as part of its Applied Atmospheric Resources Research Program, Phase 2.During the 4 yr of the experiment, a total of 67 experimental units (34 seeded and 33 nonseeded units) were qualified in accordance with the experimental design. Volume-scan data from a 10-cm Doppler radar at 5-min intervals were used to track each experimental unit, from which various radar-estimated properties of the experimental units were obtained. The statistical evaluation of the experiment was based on a rerandomization analysis of the single ratio of seeded to unseeded experimental unit lifetime properties. In 1997, the BRRAA acquired two sophisticated King Air 350 cloud-physics aircraft, providing the opportunity to obtain physical measurements of the aerosol characteristics of the environment in which the warm clouds grow, of the hydrometeor characteristics of seeded and unseeded clouds, and of the calcium chloride seeding plume dimensions and particle size distribution-information directly related to the effectiveness of the seeding conceptual model that was not directly available up to then.The evaluation of the Thailand warm-rain enhancement experiment has provided statistically significant evidence and supporting physical evidence that the seeding of warm convective clouds with calcium chloride particles produced more rain than was produced by their unseeded counterparts. An exploratory analysis of the time evolution of the seeding effects resulted in a significant revision to the seeding conceptual model.

Statistical properties of the ice particle distribution in stratiform clouds

NASA Astrophysics Data System (ADS)

Delanoe, J.; Tinel, C.; Testud, J.

2003-04-01

This paper presents an extensive analysis of several microphysical data bases CEPEX, EUCREX, CLARE and CARL to determine statistical properties of the Particle Size Distribution (PSD). The data base covers different type of stratiform clouds : tropical cirrus (CEPEX), mid-latitude cirrus (EUCREX) and mid-latitude cirrus and stratus (CARL,CLARE) The approach for analysis uses the concept of normalisation of the PSD developed by Testud et al. (2001). The normalization aims at isolating three independent characteristics of the PSD : its "intrinsic" shape, the "average size" of the spectrum and the ice water content IWC, "average size" is meant the mean mass weighted diameter. It is shown that concentration should be normalized by N_0^* proportional to IWC/D_m^4. The "intrinsic" shape is defined as F(Deq/D_m)=N(Deq)/N_0^* where Deq is the equivalent melted diameter. The "intrinsic" shape is found to be very stable in the range 001.5, more scatter is observed, but future analysis should decide if it is representative of real physical variation or statistical "error" due to counting problem. Considering an overall statistics over the full data base, a large scatter of the N_0^* against Dm plot is found. But in the case of a particular event or a particular leg of a flight, the N_0^* vs. Dm plot is much less scattered and shows a systematic trend for decaying of N_0^* when Dm increases. This trend is interpreted as the manifestation of the predominance of the aggregation process. Finally an important point for cloud remote sensing is investigated : the normalised relationships IWC/N_0^* against Z/N_0^* is much less scattered that the classical IWC against Z the radar reflectivity factor.

The application of multiplex fluorimetric sensor for the analysis of flavonoids content in the medicinal herbs family Asteraceae, Lamiaceae, Rosaceae.

PubMed

Sytar, Oksana; Bruckova, Klaudia; Hunkova, Elena; Zivcak, Marek; Konate, Kiessoun; Brestic, Marian

2015-01-16

The aim of our research work was to quantify total flavonoid contents in the leaves of 13 plant species family Asteraceae, 8 representatives of family Lamiaceae and 9 plant species belonging to family Rosaceae, using the multiplex fluorimetric sensor. Fluorescence was measured using optical fluorescence apparatus Multiplex(R) 3 (Force-A, France) for non-destructive flavonoids estimation. The content of total flavonoids was estimated by FLAV index (expressed in relative units), that is deduced from flavonoids UV absorbing properties. Among observed plant species, the highest amount of total flavonoids has been found in leaves of Helianthus multiflorus (1.65 RU) and Echinops ritro (1.27 RU), Rudbeckia fulgida (1.13 RU) belonging to the family Asteraceae. Lowest flavonoid content has been observed in the leaves of marigold (Calendula officinalis) (0.14 RU) also belonging to family Asteraceae. The highest content of flavonoids among experimental plants of family Rosaceae has been estimated in the leaves of Rosa canina (1.18 RU) and among plant species of family Lamiaceae in the leaves of Coleus blumei (0.90 RU). This research work was done as pre-screening of flavonoids content in the leaves of plant species belonging to family Asteraceae, Lamiaceae and Rosaceae. Results indicated that statistically significant differences (P > 0.05) in flavonoids content were observed not only between families, but also among individual plant species within one family.

Interannual and Diurnal Variability in Water Ice Clouds Observed from MSL Over Two Martian Years

NASA Astrophysics Data System (ADS)

Kloos, J. L.; Moores, J. E.; Whiteway, J. A.; Aggarwal, M.

2018-01-01

We update the results of cloud imaging sequences from the Mars Science Laboratory (MSL) rover Curiosity to complete two Mars years of observations (LS=160° of Mars year (MY) 31 to LS=160° of MY 33). Relatively good seasonal coverage is achieved within the study period, with just over 500 observations obtained, averaging one observation every 2-3 sols. Cloud opacity measurements are made using differential photometry and a simplified radiative transfer method. These opacity measurements are used to assess the interannual variability of the aphelion cloud belt (ACB) for MY 32 and 33. Upon accounting for a statistical bias in the data set, the variation is found to be <30% within uncertainty. Diurnal variation of the ACB is also able to be examined in MY 33 owing to an increased number of early morning observations in this year. Although a gap in data around local noon prevents a complete assessment, we find that cloud opacity is moderately increased in the morning hours (07:00-09:00) compared to the late afternoon (15:00-17:00).

The Feasibility of 3d Point Cloud Generation from Smartphones

NASA Astrophysics Data System (ADS)

Alsubaie, N.; El-Sheimy, N.

2016-06-01

This paper proposes a new technique for increasing the accuracy of direct geo-referenced image-based 3D point cloud generated from low-cost sensors in smartphones. The smartphone's motion sensors are used to directly acquire the Exterior Orientation Parameters (EOPs) of the captured images. These EOPs, along with the Interior Orientation Parameters (IOPs) of the camera/ phone, are used to reconstruct the image-based 3D point cloud. However, because smartphone motion sensors suffer from poor GPS accuracy, accumulated drift and high signal noise, inaccurate 3D mapping solutions often result. Therefore, horizontal and vertical linear features, visible in each image, are extracted and used as constraints in the bundle adjustment procedure. These constraints correct the relative position and orientation of the 3D mapping solution. Once the enhanced EOPs are estimated, the semi-global matching algorithm (SGM) is used to generate the image-based dense 3D point cloud. Statistical analysis and assessment are implemented herein, in order to demonstrate the feasibility of 3D point cloud generation from the consumer-grade sensors in smartphones.

Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements

NASA Astrophysics Data System (ADS)

Coddington, O. M.; Vukicevic, T.; Schmidt, K. S.; Platnick, S.

2017-08-01

We rigorously quantify the probability of liquid or ice thermodynamic phase using only shortwave spectral channels specific to the National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer, Visible Infrared Imaging Radiometer Suite, and the notional future Plankton, Aerosol, Cloud, ocean Ecosystem imager. The results show that two shortwave-infrared channels (2135 and 2250 nm) provide more information on cloud thermodynamic phase than either channel alone; in one case, the probability of ice phase retrieval increases from 65 to 82% by combining 2135 and 2250 nm channels. The analysis is performed with a nonlinear statistical estimation approach, the GEneralized Nonlinear Retrieval Analysis (GENRA). The GENRA technique has previously been used to quantify the retrieval of cloud optical properties from passive shortwave observations, for an assumed thermodynamic phase. Here we present the methodology needed to extend the utility of GENRA to a binary thermodynamic phase space (i.e., liquid or ice). We apply formal information content metrics to quantify our results; two of these (mutual and conditional information) have not previously been used in the field of cloud studies.

Creating User-Friendly Tools for Data Analysis and Visualization in K-12 Classrooms: A Fortran Dinosaur Meets Generation Y

NASA Technical Reports Server (NTRS)

Chambers, L. H.; Chaudhury, S.; Page, M. T.; Lankey, A. J.; Doughty, J.; Kern, Steven; Rogerson, Tina M.

2008-01-01

During the summer of 2007, as part of the second year of a NASA-funded project in partnership with Christopher Newport University called SPHERE (Students as Professionals Helping Educators Research the Earth), a group of undergraduate students spent 8 weeks in a research internship at or near NASA Langley Research Center. Three students from this group formed the Clouds group along with a NASA mentor (Chambers), and the brief addition of a local high school student fulfilling a mentorship requirement. The Clouds group was given the task of exploring and analyzing ground-based cloud observations obtained by K-12 students as part of the Students' Cloud Observations On-Line (S'COOL) Project, and the corresponding satellite data. This project began in 1997. The primary analysis tools developed for it were in FORTRAN, a computer language none of the students were familiar with. While they persevered through computer challenges and picky syntax, it eventually became obvious that this was not the most fruitful approach for a project aimed at motivating K-12 students to do their own data analysis. Thus, about halfway through the summer the group shifted its focus to more modern data analysis and visualization tools, namely spreadsheets and Google(tm) Earth. The result of their efforts, so far, is two different Excel spreadsheets and a Google(tm) Earth file. The spreadsheets are set up to allow participating classrooms to paste in a particular dataset of interest, using the standard S'COOL format, and easily perform a variety of analyses and comparisons of the ground cloud observation reports and their correspondence with the satellite data. This includes summarizing cloud occurrence and cloud cover statistics, and comparing cloud cover measurements from the two points of view. A visual classification tool is also provided to compare the cloud levels reported from the two viewpoints. This provides a statistical counterpart to the existing S'COOL data visualization tool, which is used for individual ground-to-satellite correspondences. The Google(tm) Earth file contains a set of placemarks and ground overlays to show participating students the area around their school that the satellite is measuring. This approach will be automated and made interactive by the S'COOL database expert and will also be used to help refine the latitude/longitude location of the participating schools. Once complete, these new data analysis tools will be posted on the S'COOL website for use by the project participants in schools around the US and the world.

Effects of Cloud on Goddard Lidar Observatory for Wind (GLOW) Performance and Analysis of Associated Errors

NASA Astrophysics Data System (ADS)

Bacha, Tulu

The Goddard Lidar Observatory for Wind (GLOW), a mobile direct detection Doppler LIDAR based on molecular backscattering for measurement of wind in the troposphere and lower stratosphere region of atmosphere is operated and its errors characterized. It was operated at Howard University Beltsville Center for Climate Observation System (BCCOS) side by side with other operating instruments: the NASA/Langely Research Center Validation Lidar (VALIDAR), Leosphere WLS70, and other standard wind sensing instruments. The performance of Goddard Lidar Observatory for Wind (GLOW) is presented for various optical thicknesses of cloud conditions. It was also compared to VALIDAR under various conditions. These conditions include clear and cloudy sky regions. The performance degradation due to the presence of cirrus clouds is quantified by comparing the wind speed error to cloud thickness. The cloud thickness is quantified in terms of aerosol backscatter ratio (ASR) and cloud optical depth (COD). ASR and COD are determined from Howard University Raman Lidar (HURL) operating at the same station as GLOW. The wind speed error of GLOW was correlated with COD and aerosol backscatter ratio (ASR) which are determined from HURL data. The correlation related in a weak linear relationship. Finally, the wind speed measurements of GLOW were corrected using the quantitative relation from the correlation relations. Using ASR reduced the GLOW wind error from 19% to 8% in a thin cirrus cloud and from 58% to 28% in a relatively thick cloud. After correcting for cloud induced error, the remaining error is due to shot noise and atmospheric variability. Shot-noise error is the statistical random error of backscattered photons detected by photon multiplier tube (PMT) can only be minimized by averaging large number of data recorded. The atmospheric backscatter measured by GLOW along its line-of-sight direction is also used to analyze error due to atmospheric variability within the volume of measurement. GLOW scans in five different directions (vertical and at elevation angles of 45° in north, south, east, and west) to generate wind profiles. The non-uniformity of the atmosphere in all scanning directions is a factor contributing to the measurement error of GLOW. The atmospheric variability in the scanning region leads to difference in the intensity of backscattered signals for scanning directions. Taking the ratio of the north (east) to south (west) and comparing the statistical differences lead to a weak linear relation between atmospheric variability and line-of-sights wind speed differences. This relation was used to make correction which reduced by about 50%.

Multiplex transcriptional analysis of paraffin-embedded liver needle biopsy from patients with liver fibrosis

PubMed Central

2012-01-01

Background The possibility of extracting RNA and measuring RNA expression from paraffin sections can allow extensive investigations on stored paraffin samples obtained from diseased livers and could help with studies of the natural history of liver fibrosis and inflammation, and in particular, correlate basic mechanisms to clinical outcomes. Results To address this issue, a pilot study of multiplex gene expression using branched-chain DNA technology was conducted to directly measure mRNA expression in formalin-fixed paraffin-embedded needle biopsy samples of human liver. Twenty-five genes were selected for evaluation based on evidence obtained from human fibrotic liver, a rat BDL model and in vitro cultures of immortalized human hepatic stellate cells. The expression levels of these 25 genes were then correlated with liver fibrosis and inflammation activity scores. Statistical analysis revealed that three genes (COL3A1, KRT18, and TUBB) could separate fibrotic from non-fibrotic samples and that the expression of ten genes (ANXA2, TIMP1, CTGF, COL4A1, KRT18, COL1A1, COL3A1, ACTA2, TGFB1, LOXL2) were positively correlated with the level of liver inflammation activity. Conclusion This is the first report describing this multiplex technique for liver fibrosis and has provided the proof of concept of the suitability of RNA extracted from paraffin sections for investigating the modulation of a panel of proinflammatory and profibrogenic genes. This pilot study suggests that this technique will allow extensive investigations on paraffin samples from diseased livers and possibly from any other tissue. Using identical or other genes, this multiplex expression technique could be applied to samples obtained from extensive patient cohorts with stored paraffin samples in order to correlate gene expression with valuable clinically relevant information. This method could be used to provide a better understanding of the mechanisms of liver fibrosis and inflammation, its progression, and help development of new therapeutic approaches for this indication. PMID:23270325

Preliminary study of visual effect of multiplex hologram

NASA Astrophysics Data System (ADS)

Fu, Huaiping; Xiong, Bingheng; Yang, Hong; Zhang, Xueguo

2004-06-01

The process of any movement of real object can be recorded and displayed by a multiplex holographic stereogram. An embossing multiplex holographic stereogram and a multiplex rainbow holographic stereogram have been made by us, the multiplex rainbow holographic stereogram reconstructs the dynamic 2D line drawing of speech organs, the embossing multiplex holographic stereogram reconstructs the process of an old man drinking water. In this paper, we studied the visual result of an embossing multiplex holographic stereogram made with 80 films of 2-D pictures. Forty-eight persons of aged from 13 to 67 were asked to see the hologram and then to answer some questions about the feeling of viewing. The results indicate that this kind of holograms could be accepted by human visual sense organ without any problem. This paper also discusses visual effect of the multiplex holography stereograms base on visual perceptual psychology. It is open out that the planar multiplex holograms can be recorded and present the movement of real animal and object. Not only have the human visual perceptual constancy for shape, just as that size, color, etc... but also have visual perceptual constancy for binocular parallax.

Aerosol indirect effects -- general circulation model intercomparison and evaluation with satellite data

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

Quaas, Johannes; Ming, Yi; Menon, Surabi

2009-04-10

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterizes aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (Ta) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found thatmore » the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between Ta and liquid water path is simulated much too strongly by the models. It is shown that this is partly related to the representation of the second aerosol indirect effect in terms of autoconversion. A positive relationship between total cloud fraction (fcld) and Ta as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld - Ta relationship, our results indicate that none can be identified as unique explanation. Relationships similar to the ones found in satellite data between Ta and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - Ta relationship show a strong positive correlation between Ta and fcld The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of Ta, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5+-0.5 Wm-2. An alternative estimate obtained by scaling the simulated clear- and cloudy-sky forcings with estimates of anthropogenic Ta and satellite-retrieved Nd - Ta regression slopes, respectively, yields a global annual mean clear-sky (aerosol direct effect) estimate of -0.4+-0.2 Wm-2 and a cloudy-sky (aerosol indirect effect) estimate of -0.7+-0.5 Wm-2, with a total estimate of -1.2+-0.4 Wm-2.« less

Aerosol-cloud interactions in a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Lin, G.; Ghan, S. J.

2017-12-01

Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations.

The Effect of Cumulus Cloud Field Anisotropy on Domain-Averaged Solar Fluxes and Atmospheric Heating Rates

NASA Technical Reports Server (NTRS)

Hinkelman, Laura M.; Evans, K. Franklin; Clothiaux, Eugene E.; Ackerman, Thomas P.; Stackhouse, Paul W., Jr.

2006-01-01

Cumulus clouds can become tilted or elongated in the presence of wind shear. Nevertheless, most studies of the interaction of cumulus clouds and radiation have assumed these clouds to be isotropic. This paper describes an investigation of the effect of fair-weather cumulus cloud field anisotropy on domain-averaged solar fluxes and atmospheric heating rate profiles. A stochastic field generation algorithm was used to produce twenty three-dimensional liquid water content fields based on the statistical properties of cloud scenes from a large eddy simulation. Progressively greater degrees of x-z plane tilting and horizontal stretching were imposed on each of these scenes, so that an ensemble of scenes was produced for each level of distortion. The resulting scenes were used as input to a three-dimensional Monte Carlo radiative transfer model. Domain-average transmission, reflection, and absorption of broadband solar radiation were computed for each scene along with the average heating rate profile. Both tilt and horizontal stretching were found to significantly affect calculated fluxes, with the amount and sign of flux differences depending strongly on sun position relative to cloud distortion geometry. The mechanisms by which anisotropy interacts with solar fluxes were investigated by comparisons to independent pixel approximation and tilted independent pixel approximation computations for the same scenes. Cumulus anisotropy was found to most strongly impact solar radiative transfer by changing the effective cloud fraction, i.e., the cloud fraction when the field is projected on a surface perpendicular to the direction of the incident solar beam.

Does a Relationship Between Arctic Low Clouds and Sea Ice Matter?

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.

2016-01-01

Arctic low clouds strongly affect the Arctic surface energy budget. Through this impact Arctic low clouds influence important aspects of the Arctic climate system, namely surface and atmospheric temperature, sea ice extent and thickness, and atmospheric circulation. Arctic clouds are in turn influenced by these elements of the Arctic climate system, and these interactions create the potential for Arctic cloud-climate feedbacks. To further our understanding of potential Arctic cloudclimate feedbacks, the goal of this paper is to quantify the influence of atmospheric state on the surface cloud radiative effect (CRE) and its covariation with sea ice concentration (SIC). We build on previous research using instantaneous, active remote sensing satellite footprint data from the NASA A-Train. First, the results indicate significant differences in the surface CRE when stratified by atmospheric state. Second, there is a weak covariation between CRE and SIC for most atmospheric conditions. Third, the results show statistically significant differences in the average surface CRE under different SIC values in fall indicating a 3-5 W m(exp -2) larger LW CRE in 0% versus 100% SIC footprints. Because systematic changes on the order of 1 W m(exp -2) are sufficient to explain the observed long-term reductions in sea ice extent, our results indicate a potentially significant amplifying sea ice-cloud feedback, under certain meteorological conditions, that could delay the fall freeze-up and influence the variability in sea ice extent and volume. Lastly, a small change in the frequency of occurrence of atmosphere states may yield a larger Arctic cloud feedback than any cloud response to sea ice.

An eight-month climatology of marine stratocumulus cloud fraction, albedo, and integrated liquid water

NASA Technical Reports Server (NTRS)

Fairall, C. W.; Hare, J. E.; Snider, Jack B.

1990-01-01

As part of the FIRE/Extended Time Observations (ETO) program, extended time observations were made at San Nicolas Island (SNI) from March to October, 1987. Hourly averages of air temperature, relative humidity, wind speed and direction, solar irradiance, and downward longwave irradiance were recorded. The radiation sensors were standard Eppley pyranometers (shortwave) and pyrgeometers (longwave). The SNI data were processed in several ways to deduce properties of the stratocumulus covered marine boundary layer (MBL). For example, from the temperature and humidity the lifting condensation level, which is an estimate of the height of the cloud bottom, can be computed. A combination of longwave irradiance statistics can be used to estimate fractional cloud cover. An analysis technique used to estimate the integrated cloud liquid water content (W) and the cloud albedo from the measured solar irradiance is also described. In this approach, the cloud transmittance is computed by dividing the irradiance measured at some time by a clear sky value obtained at the same hour on a cloudless day. From the transmittance and the zenith angle, values of cloud albedo and W are computed using the radiative transfer parameterizations of Stephens (1978). These analysis algorithms were evaluated with 17 days of simultaneous and colocated mm-wave (20.6 and 31.65 GHz) radiometer measurements of W and lidar ceilometer measurements of cloud fraction and cloudbase height made during the FIRE IFO. The algorithms are then applied to the entire data set to produce a climatology of these cloud properties for the eight month period.

Retrieving the Polar Mixed-Phase Cloud Liquid Water Path by Combining CALIOP and IIR Measurements

NASA Astrophysics Data System (ADS)

Luo, Tao; Wang, Zhien; Li, Xuebin; Deng, Shumei; Huang, Yong; Wang, Yingjian

2018-02-01

Mixed-phase cloud (MC) is the dominant cloud type over the polar region, and there are challenging conditions for remote sensing and in situ measurements. In this study, a new methodology of retrieving the stratiform MC liquid water path (LWP) by combining Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and infrared imaging radiometer (IIR) measurements was developed and evaluated. This new methodology takes the advantage of reliable cloud-phase discrimination by combining lidar and radar measurements. An improved multiple-scattering effect correction method for lidar signals was implemented to provide reliable cloud extinction near cloud top. Then with the adiabatic cloud assumption, the MC LWP can be retrieved by a lookup-table-based method. Simulations with error-free inputs showed that the mean bias and the root mean squared error of the LWP derived from the new method are -0.23 ± 2.63 g/m2, with the mean absolute relative error of 4%. Simulations with erroneous inputs suggested that the new methodology could provide reliable retrieval of LWP to support the statistical or climatology analysis. Two-month A-train satellite retrievals over Arctic region showed that the new method can produce very similar cloud top temperature (CTT) dependence of LWP to the ground-based microwave radiometer measurements, with a bias of -0.78 g/m2 and a correlation coefficient of 0.95 between the two mean CTT-LWP relationships. The new approach can also produce reasonable pattern and value of LWP in spatial distribution over the Arctic region.

Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx

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

Saide, Pablo; Spak, S. N.; Carmichael, Gregory

2012-03-30

We evaluate a regional-scale simulation with the WRF-Chem model for the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx), which sampled the Southeast Pacific's persistent stratocumulus deck. Evaluation of VOCALS-REx ship-based and aircraft observations focuses on analyzing how aerosol loading affects marine boundary layer (MBL) dynamics and cloud microphysics. We compare local time series and campaign averaged longitudinal gradients, and highlight differences in model simulations with (W) and without wet (NW) deposition processes. The higher aerosol loadings in the NW case produce considerable changes in MBL dynamics and cloud microphysics, in accordance with the established conceptualmore » model of aerosol indirect effects. These include increase in cloud albedo, increase in MBL and cloud heights, drizzle suppression, increase in liquid water content, and increase in cloud lifetime. Moreover, better statistical representation of aerosol mass and number concentration improves model fidelity in reproducing observed spatial and temporal variability in cloud properties, including top and base height, droplet concentration, water content, rain rate, optical depth (COD) and liquid water path (LWP). Together, these help to quantify confidence in WRF-Chem's modeled aerosol-cloud interactions, while identifying structural and parametric uncertainties including: irreversibility in rain wet removal; overestimation of marine DMS and sea salt emissions and accelerated aqueous sulfate conversion. Our findings suggest that WRF-Chem simulates marine cloud-aerosol interactions at a level sufficient for applications in forecasting weather and air quality and studying aerosol climate forcing, including the reliability required for policy analysis and geo-engineering applications.« less

A Study of Rapidly Developing Low Cloud Ceilings in a Stable Atmosphere at the Florida Spaceport

NASA Technical Reports Server (NTRS)

Wheeler, Mark M.; Case, Jonathan L.; Baggett, G. Wayne

2006-01-01

Forecasters at the Space Meteorology Group (SMG) issue 30 to 90 minute forecasts for low cloud ceilings at the Shuttle Landing Facility (KTTS) in Kennedy Space Center, FL for all Space Shuttle missions. Mission verification statistics have shown cloud ceilings to be the biggest forecast challenge. SMG forecasters are especially concerned with rapidly developing cloud ceilings below 8000 ft. in a stable, capped thermodynamic environment because ceilings below 8000 ft restrict Shuttle landing operations and are the most challenging to predict accurately. This project involves the development of a database of these cases over east-central Florida in order to identify the onset, location, and if possible, dissipation times of rapidly-developing low cloud ceilings. Another goal is to document the atmospheric regimes favoring this type of cloud development to improve forecast skill of such events during Space Shuttle launch and landing operations. A 10-year database of stable, rapid low cloud development days during the daylight hours was compiled for the Florida cool-season months by examining the Cape Canaveral Air Force Station sounding data, and identifying days that had high boundary layer relative humidity associated with a thermally-capped environment below 8000 ft. Archived hourly surface observations from KTTS and Melbourne, Orlando, Sanford, and Ocala, FL were then examined for the onset of cloud ceilings below 8000 ft between 1100 and 2000 UTC. Once the database was supplemented with the hourly surface cloud observations, visible satellite imagery was examined in 30-minute intervals to confirm event occurrences. This paper will present results from some of the rapidly developing cloud ceiling cases and the prevailing meteorological conditions associated with these events, focusing on potential pre-curser information that may help improve their prediction.

The Impact of Assimilating Precipitation-affected Radiance on Cloud and Precipitation in Goddard WRF-EDAS Analyses

NASA Technical Reports Server (NTRS)

Lin, Xin; Zhang, Sara Q.; Zupanski, M.; Hou, Arthur Y.; Zhang, J.

2015-01-01

High-frequency TMI and AMSR-E radiances, which are sensitive to precipitation over land, are assimilated into the Goddard Weather Research and Forecasting Model- Ensemble Data Assimilation System (WRF-EDAS) for a few heavy rain events over the continental US. Independent observations from surface rainfall, satellite IR brightness temperatures, as well as ground-radar reflectivity profiles are used to evaluate the impact of assimilating rain-sensitive radiances on cloud and precipitation within WRF-EDAS. The evaluations go beyond comparisons of forecast skills and domain-mean statistics, and focus on studying the cloud and precipitation features in the jointed rainradiance and rain-cloud space, with particular attentions on vertical distributions of height-dependent cloud types and collective effect of cloud hydrometers. Such a methodology is very helpful to understand limitations and sources of errors in rainaffected radiance assimilations. It is found that the assimilation of rain-sensitive radiances can reduce the mismatch between model analyses and observations by reasonably enhancing/reducing convective intensity over areas where the observation indicates precipitation, and suppressing convection over areas where the model forecast indicates rain but the observation does not. It is also noted that instead of generating sufficient low-level warmrain clouds as in observations, the model analysis tends to produce many spurious upperlevel clouds containing small amount of ice water content. This discrepancy is associated with insufficient information in ice-water-sensitive radiances to address the vertical distribution of clouds with small amount of ice water content. Such a problem will likely be mitigated when multi-channel multi-frequency radiances/reflectivity are assimilated over land along with sufficiently accurate surface emissivity information to better constrain the vertical distribution of cloud hydrometers.

Large Eddy Simulations of Continental Boundary Layer Clouds Observed during the RACORO Field Campaign

NASA Astrophysics Data System (ADS)

Endo, S.; Fridlind, A. M.; Lin, W.; Vogelmann, A. M.; Toto, T.; Liu, Y.

2013-12-01

Three cases of boundary layer clouds are analyzed in the FAst-physics System TEstbed and Research (FASTER) project, based on continental boundary-layer-cloud observations during the RACORO Campaign [Routine Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations] at the ARM Climate Research Facility's Southern Great Plains (SGP) site. The three 60-hour case study periods are selected to capture the temporal evolution of cumulus, stratiform, and drizzling boundary-layer cloud systems under a range of conditions, intentionally including those that are relatively more mixed or transitional in nature versus being of a purely canonical type. Multi-modal and temporally varying aerosol number size distribution profiles are derived from aircraft observations. Large eddy simulations (LESs) are performed for the three case study periods using the GISS Distributed Hydrodynamic Aerosol and Radiative Modeling Application (DHARMA) model and the WRF-FASTER model, which is the Weather Research and Forecasting (WRF) model implemented with forcing ingestion and other functions to constitute a flexible LES. The two LES models commonly capture the significant transitions of cloud-topped boundary layers in the three periods: diurnal evolution of cumulus layers repeating over multiple days, nighttime evolution/daytime diminution of thick stratus, and daytime breakup of stratus and stratocumulus clouds. Simulated transitions of thermodynamic structures of the cloud-topped boundary layers are examined by balloon-borne soundings and ground-based remote sensors. Aircraft observations are then used to statistically evaluate the predicted cloud droplet number size distributions under varying aerosol and cloud conditions. An ensemble approach is used to refine the model configuration for the combined use of observations with parallel LES and single-column model simulations. See Lin et al. poster for single-column model investigation.

Strategy for long-term 3D cloud-resolving simulations over the ARM SGP site and preliminary results

NASA Astrophysics Data System (ADS)

Lin, W.; Liu, Y.; Song, H.; Endo, S.

2011-12-01

Parametric representations of cloud/precipitation processes continue having to be adopted in climate simulations with increasingly higher spatial resolution or with emerging adaptive mesh framework; and it is only becoming more critical that such parameterizations have to be scale aware. Continuous cloud measurements at DOE's ARM sites have provided a strong observational basis for novel cloud parameterization research at various scales. Despite significant progress in our observational ability, there are important cloud-scale physical and dynamical quantities that are either not currently observable or insufficiently sampled. To complement the long-term ARM measurements, we have explored an optimal strategy to carry out long-term 3-D cloud-resolving simulations over the ARM SGP site using Weather Research and Forecasting (WRF) model with multi-domain nesting. The factors that are considered to have important influences on the simulated cloud fields include domain size, spatial resolution, model top, forcing data set, model physics and the growth of model errors. The hydrometeor advection that may play a significant role in hydrological process within the observational domain but is often lacking, and the limitations due to the constraint of domain-wide uniform forcing in conventional cloud system-resolving model simulations, are at least partly accounted for in our approach. Conventional and probabilistic verification approaches are employed first for selected cases to optimize the model's capability of faithfully reproducing the observed mean and statistical distributions of cloud-scale quantities. This then forms the basis of our setup for long-term cloud-resolving simulations over the ARM SGP site. The model results will facilitate parameterization research, as well as understanding and dissecting parameterization deficiencies in climate models.

Allowing for Horizontally Heterogeneous Clouds and Generalized Overlap in an Atmospheric GCM

NASA Technical Reports Server (NTRS)

Lee, D.; Oreopoulos, L.; Suarez, M.

2011-01-01

While fully accounting for 3D effects in Global Climate Models (GCMs) appears not realistic at the present time for a variety of reasons such as computational cost and unavailability of 3D cloud structure in the models, incorporation in radiation schemes of subgrid cloud variability described by one-point statistics is now considered feasible and is being actively pursued. This development has gained momentum once it was demonstrated that CPU-intensive spectrally explicit Independent Column Approximation (lCA) can be substituted by stochastic Monte Carlo ICA (McICA) calculations where spectral integration is accomplished in a manner that produces relatively benign random noise. The McICA approach has been implemented in Goddard's GEOS-5 atmospheric GCM as part of the implementation of the RRTMG radiation package. GEOS-5 with McICA and RRTMG can handle horizontally variable clouds which can be set via a cloud generator to arbitrarily overlap within the full spectrum of maximum and random both in terms of cloud fraction and layer condensate distributions. In our presentation we will show radiative and other impacts of the combined horizontal and vertical cloud variability on multi-year simulations of an otherwise untuned GEOS-5 with fixed SSTs. Introducing cloud horizontal heterogeneity without changing the mean amounts of condensate reduces reflected solar and increases thermal radiation to space, but disproportionate changes may increase the radiative imbalance at TOA. The net radiation at TOA can be modulated by allowing the parameters of the generalized overlap and heterogeneity scheme to vary, a dependence whose behavior we will discuss. The sensitivity of the cloud radiative forcing to the parameters of cloud horizontal heterogeneity and comparisons of CERES-derived forcing will be shown.

The effect of smoke, dust, and pollution aerosol on shallow cloud development over the Atlantic Ocean

PubMed Central

Kaufman, Yoram J.; Koren, Ilan; Remer, Lorraine A.; Rosenfeld, Daniel; Rudich, Yinon

2005-01-01

Clouds developing in a polluted environment tend to have more numerous but smaller droplets. This property may lead to suppression of precipitation and longer cloud lifetime. Absorption of incoming solar radiation by aerosols, however, can reduce the cloud cover. The net aerosol effect on clouds is currently the largest uncertainty in evaluating climate forcing. Using large statistics of 1-km resolution MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data, we study the aerosol effect on shallow water clouds, separately in four regions of the Atlantic Ocean, for June through August 2002: marine aerosol (30°S–20°S), smoke (20°S–5°N), mineral dust (5°N–25°N), and pollution aerosols (30°N– 60°N). All four aerosol types affect the cloud droplet size. We also find that the coverage of shallow clouds increases in all of the cases by 0.2–0.4 from clean to polluted, smoky, or dusty conditions. Covariability analysis with meteorological parameters associates most of this change to aerosol, for each of the four regions and 3 months studied. In our opinion, there is low probability that the net aerosol effect can be explained by coincidental, unresolved, changes in meteorological conditions that also accumulate aerosol, or errors in the data, although further in situ measurements and model developments are needed to fully understand the processes. The radiative effect at the top of the atmosphere incurred by the aerosol effect on the shallow clouds and solar radiation is –11 ± 3 W/m2 for the 3 months studied; 2/3 of it is due to the aerosol-induced cloud changes, and 1/3 is due to aerosol direct radiative effect. PMID:16076949

Black Clouds vs Random Variation in Hospital Admissions.

PubMed

Ong, Luei Wern; Dawson, Jeffrey D; Ely, John W

2018-06-01

Physicians often accuse their peers of being "black clouds" if they repeatedly have more than the average number of hospital admissions while on call. Our purpose was to determine whether the black-cloud phenomenon is real or explainable by random variation. We analyzed hospital admissions to the University of Iowa family medicine service from July 1, 2010 to June 30, 2015. Analyses were stratified by peer group (eg, night shift attending physicians, day shift senior residents). We analyzed admission numbers to find evidence of black-cloud physicians (those with significantly more admissions than their peers) and white-cloud physicians (those with significantly fewer admissions). The statistical significance of whether there were actual differences across physicians was tested with mixed-effects negative binomial regression. The 5-year study included 96 physicians and 6,194 admissions. The number of daytime admissions ranged from 0 to 10 (mean 2.17, SD 1.63). Night admissions ranged from 0 to 11 (mean 1.23, SD 1.22). Admissions increased from 1,016 in the first year to 1,523 in the fifth year. We found 18 white-cloud and 16 black-cloud physicians in simple regression models that did not control for this upward trend. After including study year and other potential confounding variables in the regression models, there were no significant associations between physicians and admission numbers and therefore no true black or white clouds. In this study, apparent black-cloud and white-cloud physicians could be explained by random variation in hospital admissions. However, this randomness incorporated a wide range in workload among physicians, with potential impact on resident education at the low end and patient safety at the high end.

47 CFR 73.319 - FM multiplex subcarrier technical standards.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 4 2011-10-01 2011-10-01 false FM multiplex subcarrier technical standards. 73... SERVICES RADIO BROADCAST SERVICES FM Broadcast Stations § 73.319 FM multiplex subcarrier technical standards. (a) The technical specifications in this Section apply to all transmissions of FM multiplex...

Measuring and modeling correlations in multiplex networks.

PubMed

Nicosia, Vincenzo; Latora, Vito

2015-09-01

The interactions among the elementary components of many complex systems can be qualitatively different. Such systems are therefore naturally described in terms of multiplex or multilayer networks, i.e., networks where each layer stands for a different type of interaction between the same set of nodes. There is today a growing interest in understanding when and why a description in terms of a multiplex network is necessary and more informative than a single-layer projection. Here we contribute to this debate by presenting a comprehensive study of correlations in multiplex networks. Correlations in node properties, especially degree-degree correlations, have been thoroughly studied in single-layer networks. Here we extend this idea to investigate and characterize correlations between the different layers of a multiplex network. Such correlations are intrinsically multiplex, and we first study them empirically by constructing and analyzing several multiplex networks from the real world. In particular, we introduce various measures to characterize correlations in the activity of the nodes and in their degree at the different layers and between activities and degrees. We show that real-world networks exhibit indeed nontrivial multiplex correlations. For instance, we find cases where two layers of the same multiplex network are positively correlated in terms of node degrees, while other two layers are negatively correlated. We then focus on constructing synthetic multiplex networks, proposing a series of models to reproduce the correlations observed empirically and/or to assess their relevance.

Satellite-based estimation of cloud-base updrafts for convective clouds and stratocumulus

NASA Astrophysics Data System (ADS)

Zheng, Y.; Rosenfeld, D.; Li, Z.

2017-12-01

Updraft speeds of thermals have always been notoriously difficult to measure, despite significant roles they play in transporting pollutants and in cloud formation and precipitation. To our knowledge, no attempt to date has been made to estimate updraft speed from satellite information. In this study, we introduce three methods of retrieving updraft speeds at cloud base () for convective clouds and marine stratocumulus with VIIRS onboard Suomi-NPP satellite. The first method uses ground-air temperature difference to characterize the surface sensible heat flux, which is found to be correlated with updraft speeds measured by the Doppler lidar over the Southern Great Plains (SGP). Based on the relationship, we use the satellite-retrieved surface skin temperature and reanalysis surface air temperature to estimate the updrafts. The second method is based on a good linear correlation between cloud base height and updrafts, which was found over the SGP, the central Amazon, and on board a ship sailing between Honolulu and Los Angeles. We found a universal relationship for both land and ocean. The third method is for marine stratocumulus. A statistically significant relationship between Wb and cloud-top radiative cooling rate (CTRC) is found from measurements over northeastern Pacific and Atlantic. Based on this relation, satellite- and reanalysis-derived CTRC is utilized to infer the Wb of stratocumulus clouds. Evaluations against ground-based Doppler lidar measurements show estimation errors of 24%, 21% and 22% for the three methods, respectively.

CALIPSO Overview and Early Results

NASA Astrophysics Data System (ADS)

McCormick, M. P.

2008-05-01

The CALIPSO spacecraft was co-manifested with the CloudSat spacecraft and launched by a Boeing Delta~II rocket from Vandenberg Air Force Base, California on April~28,~2006. CALIPSO is the acronym for Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations. CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) is a three-channel lidar on board that uses a Nd:YAG laser emitting pulses at 1064 and 532~nm. The receiver uses a 1-meter diameter telescope and photomultipliers in the two 532~nm channels; one for parallel-polarized backscatter, and the other for perpendicular-polarized backscatter. The 1064~nm channel uses an APD for measuring the total backscatter at this wavelength. CALIPSO is in a near-circular sunsynchronous polar 705-km orbit with a 1:30~PM ascending node, and is flying in formation with CloudSat, Aura, Aqua and PARASOL. CALIPSO and CloudSat are flying 15~seconds apart in the formation. This talk will present an overview of the CALIPSO mission and details of CALIOP and the rest of the payload. It will show typical results from measurements of clouds, details on cirrus cloud statistics for the first year of data, a characterization of Polar Stratospheric Clouds over the Artic and Antarctic during local winters and early springs, and some general atmospheric events like hurricanes and aerosols from minor volcanic eruptions, desert dust events, and smoke from fires and their transport. The presentation will end with a look toward the future of spaceborne lidars.

Comparison of CERES-MODIS cloud microphysical properties with surface observations over Loess Plateau

NASA Astrophysics Data System (ADS)

Yan, Hongru; Huang, Jianping; Minnis, Patrick; Yi, Yuhong; Sun-Mack, Sunny; Wang, Tianhe; Nakajima, Takashi Y.

2015-03-01

To enhance the utility of satellite-derived cloud properties for studying the role of clouds in climate change and the hydrological cycle in semi-arid areas, it is necessary to know their uncertainties. This paper estimates the uncertainties of several cloud properties by comparing those derived over the China Loess Plateau from the MODerate-resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua by the Clouds and Earth's Radiant Energy System (CERES) with surface observations at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL). The comparisons use data from January 2008 to June 2010 limited to single layer and overcast stratus conditions during daytime. Cloud optical depths (τ) and liquid water paths (LWP) from both Terra and Aqua generally track the variation of the surface counterparts with modest correlation, while cloud effective radius (re) is only weakly correlated with the surface retrievals. The mean differences between Terra and the SACOL retrievals are -4.7±12.9, 2.1±3.2 μm and 30.2±85.3 g m-2 for τ, re and LWP, respectively. The corresponding differences for Aqua are 2.1±8.4, 1.2±2.9 μm and 47.4±79.6 g m-2, respectively. Possible causes for biases of satellite retrievals are discussed through statistical analysis and case studies. Generally, the CERES-MODIS cloud properties have a bit larger biases over the Loess Plateau than those in previous studies over other locations.

Simultaneous readout of 128 X-ray and gamma-ray transition-edge microcalorimeters using microwave SQUID multiplexing

NASA Astrophysics Data System (ADS)

Mates, J. A. B.; Becker, D. T.; Bennett, D. A.; Dober, B. J.; Gard, J. D.; Hays-Wehle, J. P.; Fowler, J. W.; Hilton, G. C.; Reintsema, C. D.; Schmidt, D. R.; Swetz, D. S.; Vale, L. R.; Ullom, J. N.

2017-08-01

The number of elements in most cryogenic sensor arrays is limited by the technology available to multiplex signals from the arrays into a smaller number of wires and readout amplifiers. The largest demonstrated arrays of transition-edge sensor (TES) microcalorimeters contain roughly 250 detectors and use time-division multiplexing with Superconducting Quantum Interference Devices (SQUIDs). The bandwidth limits of this technology constrain the number of sensors per amplifier chain, a quantity known as the multiplexing factor, to several 10s. With microwave SQUID multiplexing, we can expand the readout bandwidth and enable much larger multiplexing factors. While microwave SQUID multiplexing of TES microcalorimeters has been previously demonstrated with small numbers of detectors, we now present a fully scalable demonstration in which 128 TES detectors are read out on a single pair of coaxial cables.

Simultaneous detection of papaya ringspot virus, papaya leaf distortion mosaic virus, and papaya mosaic virus by multiplex real-time reverse transcription PCR.

PubMed

Huo, P; Shen, W T; Yan, P; Tuo, D C; Li, X Y; Zhou, P

2015-12-01

Both the single infection of papaya ringspot virus (PRSV), papaya leaf distortion mosaic virus (PLDMV) or papaya mosaic virus (PapMV) and double infection of PRSV and PLDMV or PapMV which cause indistinguishable symptoms, threaten the papaya industry in Hainan Island, China. In this study, a multiplex real-time reverse transcription PCR (RT-PCR) was developed to detect simultaneously the three viruses based on their distinctive melting temperatures (Tms): 81.0±0.8°C for PRSV, 84.7±0.6°C for PLDMV, and 88.7±0.4°C for PapMV. The multiplex real-time RT-PCR method was specific and sensitive in detecting the three viruses, with a detection limit of 1.0×10(1), 1.0×10(2), and 1.0×10(2) copies for PRSV, PLDMV, and PapMV, respectively. Indeed, the reaction was 100 times more sensitive than the multiplex RT-PCR for PRSV, and 10 times more sensitive than multiplex RT-PCR for PLDMV. Field application of the multiplex real-time RT-PCR demonstrated that some non-symptomatic samples were positive for PLDMV by multiplex real-time RT-PCR but negative by multiplex RT-PCR, whereas some samples were positive for both PRSV and PLDMV by multiplex real-time RT-PCR assay but only positive for PLDMV by multiplex RT-PCR. Therefore, this multiplex real-time RT-PCR assay provides a more rapid, sensitive and reliable method for simultaneous detection of PRSV, PLDMV, PapMV and their mixed infections in papaya.

Determination of precipitation profiles from airborne passive microwave radiometric measurements

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Hakkarinen, Ida M.; Pierce, Harold F.; Weinman, James A.

1991-01-01

This study presents the first quantitative retrievals of vertical profiles of precipitation derived from multispectral passive microwave radiometry. Measurements of microwave brightness temperature (Tb) obtained by a NASA high-altitude research aircraft are related to profiles of rainfall rate through a multichannel piecewise-linear statistical regression procedure. Statistics for Tb are obtained from a set of cloud radiative models representing a wide variety of convective, stratiform, and anvil structures. The retrieval scheme itself determines which cloud model best fits the observed meteorological conditions. Retrieved rainfall rate profiles are converted to equivalent radar reflectivity for comparison with observed reflectivities from a ground-based research radar. Results for two case studies, a stratiform rain situation and an intense convective thunderstorm, show that the radiometrically derived profiles capture the major features of the observed vertical structure of hydrometer density.

Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. I - Brightness-temperature properties of a time-dependent cloud-radiation model

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Mugnai, Alberto; Cooper, Harry J.; Tripoli, Gregory J.; Xiang, Xuwu

1992-01-01

The relationship between emerging microwave brightness temperatures (T(B)s) and vertically distributed mixtures of liquid and frozen hydrometeors was investigated, using a cloud-radiation model, in order to establish the framework for a hybrid statistical-physical rainfall retrieval algorithm. Although strong relationships were found between the T(B) values and various rain parameters, these correlations are misleading in that the T(B)s are largely controlled by fluctuations in the ice-particle mixing ratios, which in turn are highly correlated to fluctuations in liquid-particle mixing ratios. However, the empirically based T(B)-rain-rate (T(B)-RR) algorithms can still be used as tools for estimating precipitation if the hydrometeor profiles used for T(B)-RR algorithms are not specified in an ad hoc fashion.

A statistical data analysis and plotting program for cloud microphysics experiments

NASA Technical Reports Server (NTRS)

Jordan, A. J.

1981-01-01

The analysis software developed for atmospheric cloud microphysics experiments conducted in the laboratory as well as aboard a KC-135 aircraft is described. A group of four programs was developed and implemented on a Hewlett Packard 1000 series F minicomputer running under HP's RTE-IVB operating system. The programs control and read data from a MEMODYNE Model 3765-8BV cassette recorder, format the data on the Hewlett Packard disk subsystem, and generate statistical data (mean, variance, standard deviation) and voltage and engineering unit plots on a user selected plotting device. The programs are written in HP FORTRAN IV and HP ASSEMBLY Language with the graphics software using the HP 1000 Graphics. The supported plotting devices are the HP 2647A graphics terminal, the HP 9872B four color pen plotter, and the HP 2608A matrix line printer.

Statistical Analysis of Hubble /WFC3 Transit Spectroscopy of Extrasolar Planets

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

Fu, Guangwei; Deming, Drake; Knutson, Heather

2017-10-01

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST /WFC3 transit spectra for 1.1–1.65 μ m water vapor absorption and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-transmit code. We express the magnitude ofmore » the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.« less

Statistical Analysis of Hubble/WFC3 Transit Spectroscopy of Extrasolar Planets

NASA Astrophysics Data System (ADS)

Fu, Guangwei; Deming, Drake; Knutson, Heather; Madhusudhan, Nikku; Mandell, Avi; Fraine, Jonathan

2018-01-01

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST/WFC3 transit spectra for 1.1-1.65 micron water vapor absorption, and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-Transmit code. We express the magnitude of the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.

Statistical Analysis of Hubble/WFC3 Transit Spectroscopy of Extrasolar Planets

NASA Astrophysics Data System (ADS)

Fu, Guangwei; Deming, Drake; Knutson, Heather; Madhusudhan, Nikku; Mandell, Avi; Fraine, Jonathan

2017-10-01

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST/WFC3 transit spectra for 1.1-1.65 μm water vapor absorption and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-transmit code. We express the magnitude of the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.

21 CFR 862.2570 - Instrumentation for clinical multiplex test systems.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Instrumentation for clinical multiplex test... Laboratory Instruments § 862.2570 Instrumentation for clinical multiplex test systems. (a) Identification. Instrumentation for clinical multiplex test systems is a device intended to measure and sort multiple signals...

21 CFR 862.2570 - Instrumentation for clinical multiplex test systems.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Instrumentation for clinical multiplex test... Laboratory Instruments § 862.2570 Instrumentation for clinical multiplex test systems. (a) Identification. Instrumentation for clinical multiplex test systems is a device intended to measure and sort multiple signals...

21 CFR 862.2570 - Instrumentation for clinical multiplex test systems.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Instrumentation for clinical multiplex test... Laboratory Instruments § 862.2570 Instrumentation for clinical multiplex test systems. (a) Identification. Instrumentation for clinical multiplex test systems is a device intended to measure and sort multiple signals...

21 CFR 862.2570 - Instrumentation for clinical multiplex test systems.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Instrumentation for clinical multiplex test... Laboratory Instruments § 862.2570 Instrumentation for clinical multiplex test systems. (a) Identification. Instrumentation for clinical multiplex test systems is a device intended to measure and sort multiple signals...

Effect of Amazon Smoke on Cloud Microphysics and Albedo-Analysis from Satellite Imagery.

NASA Astrophysics Data System (ADS)

Kaufman, Yoram J.; Nakajima, Teruyuki

1993-04-01

NOAA Advanced Very High Resolution Radiometer images taken over the Brazilian Amazon Basin during the biomass burning season of 1987 are used to study the effect of smoke aerosol particles on the properties of low cumulus and stratocumulus clouds. The reflectance at a wavelength of 0.64 µm and the drop size, derived from the cloud reflectance at 3.75 µm, are studied for tens of thousands of clouds. The opacity of the smoke layer adjacent to each cloud is also monitored simultaneously. Though from satellite data it is impossible to derive all the parameters that influence cloud properties and smoke cloud interaction (e.g., detailed aerosol particles size distribution and chemistry, liquid water content, etc.); satellite data can be used to generate large-scale statistics of the properties of clouds and surrounding aerosol (e.g., smoke optical thickness, cloud-drop size, and cloud reflection of solar radiation) from which the interaction of aerosol with clouds can be surmised. In order to minimize the effect of variations in the precipitable water vapor and in other smoke and cloud properties, biomass burning in the tropics is chosen as the study topic, and the results are averaged for numerous clouds with the same ambient smoke optical thickness.It is shown in this study that the presence of dense smoke (an increase in the optical thickness from 0.1 to 2.0) can reduce the remotely sensed drop size of continental cloud drops from 15 to 9 µm. Due to both the high initial reflectance of clouds in the visible part of the spectrum and the presence of graphitic carbon, the average cloud reflectance at 0.64 µm is reduced from 0.71 to 0.68 for an increase in smoke optical thickness from 0.1 to 2.0. The measurements are compared to results from other years, and it is found that, as predicted, high concentration of aerosol particles causes a decrease in the cloud-drop size and that smoke darkens the bright Amazonian clouds. Comparison with theoretical computations based on Twomey's model show that by using the measured reduction in the cloud-drop size due to the presence of smoke it is possible to explain the reduction in the cloud reflectance at 0.64 µm for smoke imagery index of 0.02 to 0.03.Smoke particles are hygroscopic and have a similar size distribution to maritime and anthropogenic sulfuric aerosol particles. Therefore, these results may also be representative of the interaction of sulfuric particles with clouds.

Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions

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

McFarquhar, Greg

We proposed to analyze in-situ cloud data collected during ARM/ASR field campaigns to create databases of cloud microphysical properties and their uncertainties as needed for the development of improved cloud parameterizations for models and remote sensing retrievals, and for evaluation of model simulations and retrievals. In particular, we proposed to analyze data collected over the Southern Great Plains (SGP) during the Mid-latitude Continental Convective Clouds Experiment (MC3E), the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX), the Small Particles in Cirrus (SPARTICUS) Experiment and the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign,more » over the North Slope of Alaska during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) and the Mixed-Phase Arctic Cloud Experiment (M-PACE), and over the Tropical Western Pacific (TWP) during The Tropical Warm Pool International Cloud Experiment (TWP-ICE), to meet the following 3 objectives; derive statistical databases of single ice particle properties (aspect ratio AR, dominant habit, mass, projected area) and distributions of ice crystals (size distributions SDs, mass-dimension m-D, area-dimension A-D relations, mass-weighted fall speeds, single-scattering properties, total concentrations N, ice mass contents IWC), complete with uncertainty estimates; assess processes by which aerosols modulate cloud properties in arctic stratus and mid-latitude cumuli, and quantify aerosol’s influence in context of varying meteorological and surface conditions; and determine how ice cloud microphysical, single-scattering and fall-out properties and contributions of small ice crystals to such properties vary according to location, environment, surface, meteorological and aerosol conditions, and develop parameterizations of such effects.In this report we describe the accomplishments that we made on all 3 research objectives.« less

Deep convective clouds at the tropopause

NASA Astrophysics Data System (ADS)

Aumann, H. H.; Desouza-Machado, S. G.

2010-07-01

Data from the Advanced Infrared Sounder (AIRS) on the EOS Aqua spacecraft identify thousands of cloud tops colder than 225 K, loosely referred to as Deep Convective Clouds (DCC). Many of these cloud tops have "inverted" spectra, i.e. areas of strong water vapor, CO2 and ozone opacity, normally seen in absorption, are now seen in emission. We refer to these inverted spectra as DCCi. They are found in about 0.4% of all spectra from the tropical oceans excluding the Western Tropical Pacific (WTP), 1.1% in the WTP. The cold clouds are the anvils capping thunderstorms and consist of optically thick cirrus ice clouds. The precipitation rate associated with DCCi suggests that imbedded in these clouds, protruding above them, and not spatially resolved by the AIRS 15 km FOV, are even colder bubbles, where strong convection pushes clouds to within 5 hPa of the pressure level of the tropopause cold point. Associated with DCCi is a local upward displacement of the tropopause, a cold "bulge", which can be seen directly in the brightness temperatures of AIRS and AMSU channels with weighting function peaking between 40 and 2 hPa, without the need for a formal temperature retrieval. The bulge is not resolved by the analysis in numerical weather prediction models. The locally cold cloud tops relative to the analysis give the appearance (in the sense of an "illusion") of clouds overshooting the tropopause and penetrating into the stratosphere. Based on a simple model of optically thick cirrus clouds, the spectral inversions seen in the AIRS data do not require these clouds to penetrate into the stratosphere. However, the contents of the cold bulge may be left in the lower stratosphere as soon as the strong convection subsides. The heavy precipitation and the distortion of the temperature structure near the tropopause indicate that DCCi are associated with intense storms. Significant long-term trends in the statistical properties of DCCi could be interesting indicators of climate change.

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

NASA Astrophysics Data System (ADS)

Lohmann, U.; Stier, P.; Hoose, C.; Ferrachat, S.; Roeckner, E.; Zhang, J.

2007-03-01

The double-moment cloud microphysics scheme from ECHAM4 has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass and number concentrations and the aerosol mixing state. This results in a much better agreement with observed vertical profiles of the black carbon and aerosol mass mixing ratios than with the previous version ECHAM4, where only the different aerosol mass mixing ratios were predicted. Also, 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 -1.8 W m-2 in ECHAM5, when a relative humidity dependent cloud cover scheme and present-day aerosol emissions representative for the year 2000 are used. It is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed.

Applying analytic hierarchy process to assess healthcare-oriented cloud computing service systems.

PubMed

Liao, Wen-Hwa; Qiu, Wan-Li

2016-01-01

Numerous differences exist between the healthcare industry and other industries. Difficulties in the business operation of the healthcare industry have continually increased because of the volatility and importance of health care, changes to and requirements of health insurance policies, and the statuses of healthcare providers, which are typically considered not-for-profit organizations. Moreover, because of the financial risks associated with constant changes in healthcare payment methods and constantly evolving information technology, healthcare organizations must continually adjust their business operation objectives; therefore, cloud computing presents both a challenge and an opportunity. As a response to aging populations and the prevalence of the Internet in fast-paced contemporary societies, cloud computing can be used to facilitate the task of balancing the quality and costs of health care. To evaluate cloud computing service systems for use in health care, providing decision makers with a comprehensive assessment method for prioritizing decision-making factors is highly beneficial. Hence, this study applied the analytic hierarchy process, compared items related to cloud computing and health care, executed a questionnaire survey, and then classified the critical factors influencing healthcare cloud computing service systems on the basis of statistical analyses of the questionnaire results. The results indicate that the primary factor affecting the design or implementation of optimal cloud computing healthcare service systems is cost effectiveness, with the secondary factors being practical considerations such as software design and system architecture.

Spatial and Temporal Distribution of Cloud Properties Observed by MODIS: Preliminary Level-3 Results from the Collection 5 Reprocessing

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Hubanks, Paul; Pincus, Robert

2006-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of operational algorithms for the retrieval of cloud physical and optical properties (optical thickness, effective particle radius, water path, thermodynamic phase) have recently been updated and are being used in the new "Collection 5" processing stream being produced by the MODIS Adaptive Processing System (MODAPS) at NASA GSFC. All Terra and Aqua data are undergoing Collection 5 reprocessing with an expected completion date by the end of 2006. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. The cloud products have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In this talk, we will summarize the available Level-3 cloud properties and their associated statistical data sets, and show preliminary Terra and Aqua results from the available Collection 5 reprocessing effort. Anticipated results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

On a report that the 2012 M 6.0 earthquake in Italy was predicted after seeing an unusual cloud formation

USGS Publications Warehouse

Thomas, J.N.; Masci, F; Love, Jeffrey J.

2015-01-01

Several recently published reports have suggested that semi-stationary linear-cloud formations might be causally precursory to earthquakes. We examine the report of Guangmeng and Jie (2013), who claim to have predicted the 2012 M 6.0 earthquake in the Po Valley of northern Italy after seeing a satellite photograph (a digital image) showing a linear-cloud formation over the eastern Apennine Mountains of central Italy. From inspection of 4 years of satellite images we find numerous examples of linear-cloud formations over Italy. A simple test shows no obvious statistical relationship between the occurrence of these cloud formations and earthquakes that occurred in and around Italy. All of the linear-cloud formations we have identified in satellite images, including that which Guangmeng and Jie (2013) claim to have used to predict the 2012 earthquake, appear to be orographic – formed by the interaction of moisture-laden wind flowing over mountains. Guangmeng and Jie (2013) have not clearly stated how linear-cloud formations can be used to predict the size, location, and time of an earthquake, and they have not published an account of all of their predictions (including any unsuccessful predictions). We are skeptical of the validity of the claim by Guangmeng and Jie (2013) that they have managed to predict any earthquakes.

A new design approach to MMI-based (de)multiplexers

NASA Astrophysics Data System (ADS)

Yueyu, Xiao; Sailing, He

2004-09-01

A novel design method of the wavelength (de)multiplexer is presented. The output spectral response of a (de)multiplexer is designed from the view of FIR filters. Avoiding laborious mathematic analysis, the (de)multiplexer is analyzed and designed in this explicit and simple method. A four channel (de)multiplexer based on multimode interference (MMI) is designed as an example. The result obtained agrees with that of the commonly used method, and is verified by a finite difference beam propagation method (FDBPM) simulation.

Parallel excitation-emission multiplexed fluorescence lifetime confocal microscopy for live cell imaging.

PubMed

Zhao, Ming; Li, Yu; Peng, Leilei

2014-05-05

We present a novel excitation-emission multiplexed fluorescence lifetime microscopy (FLIM) method that surpasses current FLIM techniques in multiplexing capability. The method employs Fourier multiplexing to simultaneously acquire confocal fluorescence lifetime images of multiple excitation wavelength and emission color combinations at 44,000 pixels/sec. The system is built with low-cost CW laser sources and standard PMTs with versatile spectral configuration, which can be implemented as an add-on to commercial confocal microscopes. The Fourier lifetime confocal method allows fast multiplexed FLIM imaging, which makes it possible to monitor multiple biological processes in live cells. The low cost and compatibility with commercial systems could also make multiplexed FLIM more accessible to biological research community.

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

NASA Technical Reports Server (NTRS)

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

Analysis of Co-Located MODIS and CALIPSO Observations Near Clouds

NASA Technical Reports Server (NTRS)

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 closer than 5 km to clouds implies that pronounced near-cloud changes in aerosol properties have significant implications for overall clear-sky characteristics, including the radiative impact of aerosols.

Apperception of Clouds in AIRS Data

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Smith, William L.

2005-01-01

Our capacity to simulate the radiative characteristics of the Earth system has advanced greatly over the past decade. However, new space based measurements show that idealized simulations might not adequately represent the complexity of nature. For example, AIRS simulated multi-layer cloud clearing research provides an excellent groundwork for early Atmospheric Infra-Red Sounder (AIRS) operational cloud clearing and atmospheric profile retrieval. However, it doesn't reflect the complicated reality of clouds over land and coastal areas. Thus far, operational AIRS/AMSU (Advanced Microwave Sounding Unit) cloud clearing is not only of low yield but also of unsatisfying quality. This is not an argument for avoiding this challenging task, rather a powerful argument for exploring other synergistic approaches, and for adapting these strategies toward improving both indirect and direct use of cloudy infrared sounding data. Ample evidence is shown in this paper that the indirect use of cloudy sounding data by way of cloud clearing is sub-optimal for data assimilation. Improvements are needed in quality control, retrieval yield, and overall cloud clearing retrieval performance. For example, cloud clearing over land, especially over the desert surface, has led to much degraded retrieval quality and often a very low yield of quality controlled cloud cleared radiances. If these indirect cloud cleared radiances are instead to be directly assimilated into NWP models, great caution must be used. Our limited and preliminary cloud clearing results from AIRS/AMSU (with the use of MODIS data) and an AIRS/MODIS synergistic approach have, however, shown that higher spatial resolution multispectral imagery data can provide much needed quality control of the AIRS/AMSU cloud clearing retrieval. When AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) are used synergistically, a higher spatial resolution over difficult terrain (especially desert areas) can be achieved and with a much improved accuracy. Preliminary statistical analyses of cloud cleared radiances derived from (1) operational AIRS/AMSU, (2) operational AIRS/AMSU plus the use of MODIS data as quality control, and (3) AIRS/MODIS synergistic single channel and two field of views cloud clearing are Our capacity to simulate the radiative characteristics of the Earth system has

A color-corrected strategy for information multiplexed Fourier ptychographic imaging

NASA Astrophysics Data System (ADS)

Wang, Mingqun; Zhang, Yuzhen; Chen, Qian; Sun, Jiasong; Fan, Yao; Zuo, Chao

2017-12-01

Fourier ptychography (FP) is a novel computational imaging technique that provides both wide field of view (FoV) and high-resolution (HR) imaging capacity for biomedical imaging. Combined with information multiplexing technology, wavelength multiplexed (or color multiplexed) FP imaging can be implemented by lighting up R/G/B LED units simultaneously. Furthermore, a HR image can be recovered at each wavelength from the multiplexed dataset. This enhances the efficiency of data acquisition. However, since the same dataset of intensity measurement is used to recover the HR image at each wavelength, the mean value in each channel would converge to the same value. In this paper, a color correction strategy embedded in the multiplexing FP scheme is demonstrated, which is termed as color corrected wavelength multiplexed Fourier ptychography (CWMFP). Three images captured by turning on a LED array in R/G/B are required as priori knowledge to improve the accuracy of reconstruction in the recovery process. Using the reported technique, the redundancy requirement of information multiplexed FP is reduced. Moreover, the accuracy of reconstruction at each channel is improved with correct color reproduction of the specimen.

Transmission of multiplexed video signals in multimode optical fiber systems

NASA Technical Reports Server (NTRS)

White, Preston, III

1988-01-01

Kennedy Space Center has the need for economical transmission of two multiplexed video signals along multimode fiberoptic systems. These systems must span unusual distances and must meet RS-250B short-haul standards after reception. Bandwidth is a major problem and studies of the installed fibers, available LEDs and PINFETs led to the choice of 100 MHz as the upper limit for the system bandwidth. Optical multiplexing and digital transmission were deemed inappropriate. Three electrical multiplexing schemes were chosen for further study. Each of the multiplexing schemes included an FM stage to help meet the stringent S/N specification. Both FM and AM frequency division multiplexing methods were investigated theoretically and these results were validated with laboratory tests. The novel application of quadrature amplitude multiplexing was also considered. Frequency division multiplexing of two wideband FM video signal appears the most promising scheme although this application requires high power highly linear LED transmitters. Futher studies are necessary to determine if LEDs of appropriate quality exist and to better quantify performance of QAM in this application.

Turbulence mitigation scheme based on spatial diversity in orbital-angular-momentum multiplexed system

NASA Astrophysics Data System (ADS)

Zou, Li; Wang, Le; Zhao, Shengmei

2017-10-01

Atmospheric turbulence (AT) induced crosstalk can significantly impair the performance of free-space optical (FSO) communication link using orbital angular momentum (OAM) multiplexing. In this paper, we propose a spatial diversity (SD) turbulence mitigation scheme in an OAM-multiplexed FSO communication link. First, we present a SD mitigation model for the OAM-multiplexed FSO communication link under AT. Then we present a SD combining technique based on equal gain to enhance AT tolerance of the OAM-multiplexed FSO communication link. The numerical results show that performance of the OAM-multiplexed communication link has greatly improved by the proposed scheme. When the turbulence strength Cn2 is 5 × 10-15m - 2 / 3, the transmission distance is 1000 m and the channel signal-to-noise ratio (SNR) is 20 dB, the bit-error-rate (BER) performance of four spatial multiplexed OAM modes lm = + 1 , + 2 , + 3 , + 4 are 3 fold increase in comparison with those results without the proposed scheme. The proposed scheme is a promising direction for compensating the interference caused by AT in the OAM-multiplexed FSO communication link.

Development of a low-flow multiplexed interface for capillary electrophoresis/electrospray ion trap mass spectrometry using sequential spray.

PubMed

Chen, Chao-Jung; Li, Fu-An; Her, Guor-Rong

2008-05-01

A multiplexed CE-MS interface using four low-flow sheath liquid ESI sprayers has been developed. Because of the limited space between the low-flow sprayers and the entrance aperture of the ESI source, multichannel analysis is difficult using conventional rotating plate approaches. Instead, a multiplexed low-flow system was achieved by applying an ESI potential sequentially to the four low-flow sprayers, resulting in only one sprayer being sprayed at any given time. The synchronization of the scan event and the voltage relays was accomplished by using the data acquisition signal from the IT mass spectrometer. This synchronization resulted in the ESI voltage being sequentially applied to each of the four sprayers according to the corresponding scan event. With this design, a four-fold increase in analytical throughput was achieved. Because of the use of low-flow interfaces, this multiplexed system has superior sensitivity than a rotating plate design using conventional sheath liquid interfaces. The multiplexed design presented has the potential to be applied to other low-flow multiplexed systems, such as multiplexed capillary LC and multiplexed CEC.

Cloud Radiative Effect in dependence on Cloud Type

NASA Astrophysics Data System (ADS)

Aebi, Christine; Gröbner, Julian; Kämpfer, Niklaus; Vuilleumier, Laurent

2015-04-01

Radiative transfer of energy in the atmosphere and the influence of clouds on the radiation budget remain the greatest sources of uncertainty in the simulation of climate change. Small changes in cloudiness and radiation can have large impacts on the Earth's climate. In order to assess the opposing effects of clouds on the radiation budget and the corresponding changes, frequent and more precise radiation and cloud observations are necessary. The role of clouds on the surface radiation budget is studied in order to quantify the longwave, shortwave and the total cloud radiative forcing in dependence on the atmospheric composition and cloud type. The study is performed for three different sites in Switzerland at three different altitude levels: Payerne (490 m asl), Davos (1'560 m asl) and Jungfraujoch (3'580 m asl). On the basis of data of visible all-sky camera systems at the three aforementioned stations in Switzerland, up to six different cloud types are distinguished (Cirrus-Cirrostratus, Cirrocumulus-Altocumulus, Stratus-Altostratus, Cumulus, Stratocumulus and Cumulonimbus-Nimbostratus). These cloud types are classified with a modified algorithm of Heinle et al. (2010). This cloud type classifying algorithm is based on a set of statistical features describing the color (spectral features) and the texture of an image (textural features) (Wacker et al. (2015)). The calculation of the fractional cloud cover information is based on spectral information of the all-sky camera data. The radiation data are taken from measurements with pyranometers and pyrgeometers at the different stations. A climatology of a whole year of the shortwave, longwave and total cloud radiative effect and its sensitivity to integrated water vapor, cloud cover and cloud type will be calculated for the three above-mentioned stations in Switzerland. For the calculation of the shortwave and longwave cloud radiative effect the corresponding cloud-free reference models developed at PMOD/WRC will be used (Wacker et al. (2013)). References: Heinle, A., A. Macke and A. Srivastav (2010) Automatic cloud classification of whole sky images, Atmospheric Measurement Techniques. Wacker, S., J. Gröbner and L. Vuilleumier (2013) A method to calculate cloud-free long-wave irradiance at the surface based on radiative transfer modeling and temperature lapse rate estimates, Theoretical and Applied Climatology. Wacker, S., J. Gröbner, C. Zysset, L. Diener, P. Tzoumanikis, A. Kazantzidis, L. Vuilleumier, R. Stöckli, S. Nyeki, and N. Kämpfer (2015) Cloud observations in Switzerland using hemispherical sky cameras, Journal of Geophysical Research.

Cloud field classification based on textural features

NASA Technical Reports Server (NTRS)

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 of features. Preliminary results based on the GLDV textural features alone look promising.

Multiplex Real-Time PCR for Detection of Staphylococcus aureus, mecA and Panton-Valentine Leukocidin (PVL) Genes from Selective Enrichments from Animals and Retail Meat

PubMed Central

Velasco, Valeria; Sherwood, Julie S.; Rojas-García, Pedro P.; Logue, Catherine M.

2014-01-01

The aim of this study was to compare a real-time PCR assay, with a conventional culture/PCR method, to detect S. aureus, mecA and Panton-Valentine Leukocidin (PVL) genes in animals and retail meat, using a two-step selective enrichment protocol. A total of 234 samples were examined (77 animal nasal swabs, 112 retail raw meat, and 45 deli meat). The multiplex real-time PCR targeted the genes: nuc (identification of S. aureus), mecA (associated with methicillin resistance) and PVL (virulence factor), and the primary and secondary enrichment samples were assessed. The conventional culture/PCR method included the two-step selective enrichment, selective plating, biochemical testing, and multiplex PCR for confirmation. The conventional culture/PCR method recovered 95/234 positive S. aureus samples. Application of real-time PCR on samples following primary and secondary enrichment detected S. aureus in 111/234 and 120/234 samples respectively. For detection of S. aureus, the kappa statistic was 0.68–0.88 (from substantial to almost perfect agreement) and 0.29–0.77 (from fair to substantial agreement) for primary and secondary enrichments, using real-time PCR. For detection of mecA gene, the kappa statistic was 0–0.49 (from no agreement beyond that expected by chance to moderate agreement) for primary and secondary enrichment samples. Two pork samples were mecA gene positive by all methods. The real-time PCR assay detected the mecA gene in samples that were negative for S. aureus, but positive for Staphylococcus spp. The PVL gene was not detected in any sample by the conventional culture/PCR method or the real-time PCR assay. Among S. aureus isolated by conventional culture/PCR method, the sequence type ST398, and multi-drug resistant strains were found in animals and raw meat samples. The real-time PCR assay may be recommended as a rapid method for detection of S. aureus and the mecA gene, with further confirmation of methicillin-resistant S. aureus (MRSA) using the standard culture method. PMID:24849624