Detection of morphological changes in cliff face surrounding a waterfall using terrestrial laser scanning and unmanned aerial system

NASA Astrophysics Data System (ADS)

Hayakawa, Yuichi S.; Obanawa, Hiroyuki

2015-04-01

Waterfall or bedrock knickpoint appears as an erosional front in bedrock rivers forming deep v-shaped valley downstream. Following the rapid fluvial erosion of waterfall, rockfalls and gravita-tional collapses often occur in surrounding steep cliffs. Although morphological changes of such steep cliffs are sometimes visually observed, quantitative and precise measurements of their spatio-temporal distribution have been limited due to the difficulties in direct access to such cliffs if with classical measurement methods. However, for the clarification of geomorphological processes oc-curring in the cliffs, multi-temporal mapping of the cliff face at a high resolution is necessary. Re-mote sensing approaches are therefore suitable for the topographic measurements and detection of changes in such inaccessible cliffs. To achieve accurate topographic mapping of cliffs around a wa-terfall, here we perform multi-temporal terrestrial laser scanning (TLS), as well as structure-from-motion multi-view stereo (SfM-MVS) photogrammetry based on unmanned aerial system (UAS). The study site is Kegon Falls in central Japan, having a vertical drop of surface water from top of its overhanging cliff, as well as groundwater outflows from its lower portions. The bedrock is composed of alternate layers of andesite lava and conglomerates. Minor rockfalls in the cliffs are often ob-served by local people. The latest major rockfall occurred in 1986, causing ca. 8-m upstream propa-gation of the waterfall lip. This provides a good opportunity to examine the changes in the surround-ing cliffs following the waterfall recession. Multi-time point clouds were obtained by TLS measure-ment over years, and the three-dimensional changes of the rock surface were detected, uncovering the locus of small rockfalls and gully developments. Erosion seems particularly frequent in relatively weak the conglomerates layer, whereas small rockfalls seems to have occurred in the andesite layers. Also, shadows in the TLS point clouds are effectively filled by complementary data of UAS-based SfM-MVS photogrammetry, which can improve the mapping quality of the cliff morphology. The point clouds are also projected on a vertical plane to generate a digital elevation model (DEM). Cross-sectional profiles extracted from the DEM show the presence of a distinct, 5-10-m depression at the mid of the cliff (bottom of the upper andesite layer), which appears to have been formed by freeze-thaw and/or wet-dry weathering following the waterfall recession in 1986.

Determination of ice water path in ice-over-water cloud systems using combined MODIS and AMSR-E measurements

NASA Astrophysics Data System (ADS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

2006-11-01

To provide more accurate ice cloud microphysical properties, the multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems globally over oceans using combined instrument data from Aqua. The liquid water path (LWP) of lower-layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. The properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements by matching simulated radiances from a two-cloud-layer radiative transfer model. The results show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and IWP retrievals for ice-over-water cloud systems. The mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over oceans from Aqua are 7.6 and 146.4 gm-2, respectively, down from the initial single-layer retrievals of 17.3 and 322.3 gm-2. The mean IWP for actual single-layer clouds is 128.2 gm-2.

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).

Determination of Ice Water Path in Ice-over-Water Cloud Systems Using Combined MODIS and AMSR-E Measurements

NASA Technical Reports Server (NTRS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

2006-01-01

To provide more accurate ice cloud properties for evaluating climate models, the updated version of multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems over global ocean using combined instrument data from the Aqua satellite. The liquid water path (LWP) of lower layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. With the lower layer LWP known, the properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer measurements by matching simulated radiances from a two-cloud layer radiative transfer model. Comparisons with single-layer cirrus systems and surface-based radar retrievals show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and ice water path retrievals for ice over-water cloud systems. During the period from December 2004 through February 2005, the mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over ocean from Aqua are 7.6 and 146.4 gm(sup -2), respectively, significantly less than the initial single layer retrievals of 17.3 and 322.3 gm(sup -2). The mean IWP for actual single-layer clouds was 128.2 gm(sup -2).

Multi-layer Clouds Over the South Indian Ocean

NASA Image and Video Library

2003-05-07

The complex structure and beauty of polar clouds are highlighted by these images acquired by NASA Terra spacecraft on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean,

Merging Sounder and Imager Data for Improved Cloud Depiction on SNPP and JPSS.

NASA Astrophysics Data System (ADS)

Heidinger, A. K.; Holz, R.; Li, Y.; Platnick, S. E.; Wanzong, S.

2017-12-01

Under the NOAA GOES-R Algorithm Working Group (AWG) Program, NOAA supports the development of an Infrared (IR) Optimal Estimation (OE) Cloud Height Algorithm (ACHA). ACHA is an enterprise solution that supports many geostationary and polar orbiting imager sensors. ACHA is operational at NOAA on SNPP VIIRS and has been adopted as the cloud height algorithm for the NASA NPP Atmospheric Suite of products. Being an OE algorithm, ACHA is flexible and capable of using additional observations and constraints. We have modified ACHA to use sounder (CriS) observations to improve the cloud detection, typing and height estimation. Specifically, these improvements include retrievals in multi-layer scenarios and improved performance in polar regions. This presentation will describe the process for merging VIIRS and CrIS and a demonstration of the improvements.

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

MPLNET V3 Cloud and Planetary Boundary Layer Detection

NASA Technical Reports Server (NTRS)

Lewis, Jasper R.; Welton, Ellsworth J.; Campbell, James R.; Haftings, Phillip C.

2016-01-01

The NASA Micropulse Lidar Network Version 3 algorithms for planetary boundary layer and cloud detection are described and differences relative to the previous Version 2 algorithms are highlighted. A year of data from the Goddard Space Flight Center site in Greenbelt, MD consisting of diurnal and seasonal trends is used to demonstrate the results. Both the planetary boundary layer and cloud algorithms show significant improvement of the previous version.

Harmonic regression based multi-temporal cloud filtering algorithm for Landsat 8

NASA Astrophysics Data System (ADS)

Joshi, P.

2015-12-01

Landsat data archive though rich is seen to have missing dates and periods owing to the weather irregularities and inconsistent coverage. The satellite images are further subject to cloud cover effects resulting in erroneous analysis and observations of ground features. In earlier studies the change detection algorithm using statistical control charts on harmonic residuals of multi-temporal Landsat 5 data have been shown to detect few prominent remnant clouds [Brooks, Evan B., et al, 2014]. So, in this work we build on this harmonic regression approach to detect and filter clouds using a multi-temporal series of Landsat 8 images. Firstly, we compute the harmonic coefficients using the fitting models on annual training data. This time series of residuals is further subjected to Shewhart X-bar control charts which signal the deviations of cloud points from the fitted multi-temporal fourier curve. For the process with standard deviation σ we found the second and third order harmonic regression with a x-bar chart control limit [Lσ] ranging between [0.5σ < Lσ < σ] as most efficient in detecting clouds. By implementing second order harmonic regression with successive x-bar chart control limits of L and 0.5 L on the NDVI, NDSI and haze optimized transformation (HOT), and utilizing the seasonal physical properties of these parameters, we have designed a novel multi-temporal algorithm for filtering clouds from Landsat 8 images. The method is applied to Virginia and Alabama in Landsat8 UTM zones 17 and 16 respectively. Our algorithm efficiently filters all types of cloud cover with an overall accuracy greater than 90%. As a result of the multi-temporal operation and the ability to recreate the multi-temporal database of images using only the coefficients of the fourier regression, our algorithm is largely storage and time efficient. The results show a good potential for this multi-temporal approach for cloud detection as a timely and targeted solution for the Landsat 8 research community, catering to the need for innovative processing solutions in the infant stage of the satellite.

MOD06 Optical and Microphysical Retrievals

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Arnold, G. T.; Dinsick, J.; Gatebe, C. K.; Gray, M. A.; Hubanks, P. A.; Moody, E. G.; Wind, B.; Wind, G.

2003-01-01

Major efforts over the past six months included: (1) submission of MOD06 Optical and Microphysical Retrieval recompetition proposal, (2) delivery of a MODIS Atmosphere Level-3 update, (3) delivery of the MODIS Atmosphere s new combined Level-2 product, (4) development of an above-cloud precipitable water research algorithm and a multi-layer cloud detection algorithm, (5) continued development of a Fortran 90 version of the retrieval code for use with MAS as well as operational MODIS processing, (6) preliminary analysis of CRYSTAL-FACE field experiment in July 2002, (7) continued analysis of data obtained during the SAFARI 2000 dry season campaign in southern Africa, and the Arctic FIRE-ACE experiment.

Low Cloud Feedback to Surface Warming in the World's First Global Climate Model with Explicit Embedded Boundary Layer Turbulence

NASA Astrophysics Data System (ADS)

Parishani, H.; Pritchard, M. S.; Bretherton, C. S.; Wyant, M. C.; Khairoutdinov, M.; Singh, B.

2017-12-01

Biases and parameterization formulation uncertainties in the representation of boundary layer clouds remain a leading source of possible systematic error in climate projections. Here we show the first results of cloud feedback to +4K SST warming in a new experimental climate model, the ``Ultra-Parameterized (UP)'' Community Atmosphere Model, UPCAM. We have developed UPCAM as an unusually high-resolution implementation of cloud superparameterization (SP) in which a global set of cloud resolving arrays is embedded in a host global climate model. In UP, the cloud-resolving scale includes sufficient internal resolution to explicitly generate the turbulent eddies that form marine stratocumulus and trade cumulus clouds. This is computationally costly but complements other available approaches for studying low clouds and their climate interaction, by avoiding parameterization of the relevant scales. In a recent publication we have shown that UP, while not without its own complexity trade-offs, can produce encouraging improvements in low cloud climatology in multi-month simulations of the present climate and is a promising target for exascale computing (Parishani et al. 2017). Here we show results of its low cloud feedback to warming in multi-year simulations for the first time. References: Parishani, H., M. S. Pritchard, C. S. Bretherton, M. C. Wyant, and M. Khairoutdinov (2017), Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence, J. Adv. Model. Earth Syst., 9, doi:10.1002/2017MS000968.

Complex Clouds

Atmospheric Science Data Center

2013-04-16

... article title:  Multi-layer Clouds Over the South Indian Ocean     View Larger Image ... System-2 path 155. MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission ...

Vertical stratification of forest canopy for segmentation of understory trees within small-footprint airborne LiDAR point clouds

NASA Astrophysics Data System (ADS)

Hamraz, Hamid; Contreras, Marco A.; Zhang, Jun

2017-08-01

Airborne LiDAR point cloud representing a forest contains 3D data, from which vertical stand structure even of understory layers can be derived. This paper presents a tree segmentation approach for multi-story stands that stratifies the point cloud to canopy layers and segments individual tree crowns within each layer using a digital surface model based tree segmentation method. The novelty of the approach is the stratification procedure that separates the point cloud to an overstory and multiple understory tree canopy layers by analyzing vertical distributions of LiDAR points within overlapping locales. The procedure does not make a priori assumptions about the shape and size of the tree crowns and can, independent of the tree segmentation method, be utilized to vertically stratify tree crowns of forest canopies. We applied the proposed approach to the University of Kentucky Robinson Forest - a natural deciduous forest with complex and highly variable terrain and vegetation structure. The segmentation results showed that using the stratification procedure strongly improved detecting understory trees (from 46% to 68%) at the cost of introducing a fair number of over-segmented understory trees (increased from 1% to 16%), while barely affecting the overall segmentation quality of overstory trees. Results of vertical stratification of the canopy showed that the point density of understory canopy layers were suboptimal for performing a reasonable tree segmentation, suggesting that acquiring denser LiDAR point clouds would allow more improvements in segmenting understory trees. As shown by inspecting correlations of the results with forest structure, the segmentation approach is applicable to a variety of forest types.

A New Methodology for Simultaneous Multi-layer Retrievals of Ice and Liquid Water Cloud Properties

NASA Astrophysics Data System (ADS)

Sourdeval, O.; Labonnote, L.; Baran, A. J.; Brogniez, G.

2014-12-01

It is widely recognized that the study of clouds has nowadays become one of the major concern of the climate research community. Consequently, a multitude of retrieval methodologies have been developed during the last decades in order to obtain accurate retrievals of cloud properties that can be supplied to climate models. Most of the current methodologies have proven to be satisfactory for separately retrieving ice or liquid cloud properties, but very few of them have attempted simultaneous retrievals of these two cloud types. Recent studies nevertheless show that the omission of one of these layers can have strong consequences on the retrievals and their accuracy. In this study, a new methodology that simultaneously retrieves the properties of ice and liquid clouds is presented. The optical thickness and the effective radius of up to two liquid cloud layers and the ice water path of one ice cloud layer are simultaneously retrieved, along with an accurate estimation of their uncertainties. Radiometric measurements ranging from the visible to the thermal infrared are used for performing the retrievals. In order to quantify the capabilities and limitations of our methodology, the results of a theoretical information content analysis are first presented. This analysis allows obtaining an a priori understanding of how much information should be expected on each of the retrieval parameters in different atmospheric conditions, and which set of channels is likely to provide this information. After such theoretical considerations, global retrievals corresponding to several months of A-Train data are presented. Comparisons of our retrievals with operational products from active and passive instruments are effectuated and show good global agreements. These comparisons are useful for validating our retrievals but also for testing how operational products can be influenced by multi-layer configurations.

Cloud Detection Using Measured and Modeled State Parameters

NASA Technical Reports Server (NTRS)

Yi, Y.; Minnis, P.; Huang, J.; Ayers, J. K.; Doelling, D. R.; Khaiyer, M. M.; Nordeen, M. L.

2004-01-01

In this study, hourly RUC analyses were used to examine the differences between RH and temperature values from RUC reanalysis data and from radiosonde atmospheric profiles obtained at the ARM SCF. The results show that the temperature observations from the SONDE and RUC are highly correlated. The RHs are also well-correlated, but the SONDE values generally exceed those from RUC. Inside cloud layers, the RH from RUC is 2-14% lower than the RH from SONDE for all RUC layers. Although the layer mean RH within clouds is much greater than the layer mean RH outside cloud or in the clear-sky, RH thresholds chosen as a function of temperature can more accurately diagnose cloud occurrence for either dataset. For overcast clouds, it was found that the 50% probability RH threshold for diagnosing a cloud, within a given upper tropospheric layer is roughly 90% for the Vaisala RS80-15LH radisonde and 80% for RUC data. While for the partial cloud (cloud amount is less than 90%), the RH thresholds of SONDE are close to RUC for a given probability in upper tropospheric layers. The probabilities of detecting clouds at a given RH and temperature should be useful for a variety of application such as the development of new cloud parameterizations or for estimating the vertical profile of cloudiness underneath a given cloud observed from the satellite to construct a 3-D cloud data set for computing atmospheric radiative heating profiles or determining potential aircraft icing conditions.

Preliminary Analysis of X-Band and Ka-Band Radar for Use in the Detection of Icing Conditions Aloft

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Koenig, George G.

2004-01-01

NASA and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) have an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. Radar has been identified as a strong tool for this work. However, since the remote detection of icing conditions with the intent to identify areas of icing hazard is a new and evolving capability, there are no set requirements for radar sensitivity. This work is an initial attempt to quantify, through analysis, the sensitivity requirements for an icing remote sensing radar. The primary radar of interest for cloud measurements is Ka-band, however, since NASA is currently using an X-band unit, this frequency is also examined. Several aspects of radar signal analysis were examined. Cloud reflectivity was calculated for several forms of cloud using two different techniques. The Air Force Geophysical Laboratory (AFGL) cloud models, with different drop spectra represented by a modified gamma distribution, were utilized to examine several categories of cloud formation. Also a fundamental methods approach was used to allow manipulation of the cloud droplet size spectra. And an analytical icing radar simulator was developed to examine the complete radar system response to a configurable multi-layer cloud environment. Also discussed is the NASA vertical pointing X-band radar. The radar and its data system are described, and several summer weather events are reviewed.

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths With GOSE Data Over ARM/SGP Site

NASA Technical Reports Server (NTRS)

Kawamoto, Kazuaki; Minnis, Patrick; Smith, William L., Jr.

2001-01-01

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the capability of detecting overlapping clouds

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths with GOES Data Over ARM/SGP Site

NASA Technical Reports Server (NTRS)

Kawamoto, K.; Minnis, P.; Smith, W. L., Jr.

2001-01-01

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.

Improving the Accuracy of Cloud Detection Using Machine Learning

NASA Astrophysics Data System (ADS)

Craddock, M. E.; Alliss, R. J.; Mason, M.

2017-12-01

Cloud detection from geostationary satellite imagery has long been accomplished through multi-spectral channel differencing in comparison to the Earth's surface. The distinction of clear/cloud is then determined by comparing these differences to empirical thresholds. Using this methodology, the probability of detecting clouds exceeds 90% but performance varies seasonally, regionally and temporally. The Cloud Mask Generator (CMG) database developed under this effort, consists of 20 years of 4 km, 15minute clear/cloud images based on GOES data over CONUS and Hawaii. The algorithms to determine cloudy pixels in the imagery are based on well-known multi-spectral techniques and defined thresholds. These thresholds were produced by manually studying thousands of images and thousands of man-hours to determine the success and failure of the algorithms to fine tune the thresholds. This study aims to investigate the potential of improving cloud detection by using Random Forest (RF) ensemble classification. RF is the ideal methodology to employ for cloud detection as it runs efficiently on large datasets, is robust to outliers and noise and is able to deal with highly correlated predictors, such as multi-spectral satellite imagery. The RF code was developed using Python in about 4 weeks. The region of focus selected was Hawaii and includes the use of visible and infrared imagery, topography and multi-spectral image products as predictors. The development of the cloud detection technique is realized in three steps. First, tuning of the RF models is completed to identify the optimal values of the number of trees and number of predictors to employ for both day and night scenes. Second, the RF models are trained using the optimal number of trees and a select number of random predictors identified during the tuning phase. Lastly, the model is used to predict clouds for an independent time period than used during training and compared to truth, the CMG cloud mask. Initial results show 97% accuracy during the daytime, 94% accuracy at night, and 95% accuracy for all times. The total time to train, tune and test was approximately one week. The improved performance and reduced time to produce results is testament to improved computer technology and the use of machine learning as a more efficient and accurate methodology of cloud detection.

Validation of a radiosonde-based cloud layer detection method against a ground-based remote sensing method at multiple ARM sites

NASA Astrophysics Data System (ADS)

Zhang, Jinqiang; Li, Zhanqing; Chen, Hongbin; Cribb, Maureen

2013-01-01

Cloud vertical structure is a key quantity in meteorological and climate studies, but it is also among the most difficult quantities to observe. In this study, we develop a long-term (10 years) radiosonde-based cloud profile product for the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP), Tropical Western Pacific (TWP), and North Slope of Alaska (NSA) sites and a shorter-term product for the ARM Mobile Facility (AMF) deployed in Shouxian, Anhui Province, China (AMF-China). The AMF-China site was in operation from 14 May to 28 December 2008; the ARM sites have been collecting data for over 15 years. The Active Remote Sensing of Cloud (ARSCL) value-added product (VAP), which combines data from the 95-GHz W-band ARM Cloud Radar (WACR) and/or the 35-GHz Millimeter Microwave Cloud Radar (MMCR), is used in this study to validate the radiosonde-based cloud layer retrieval method. The performance of the radiosonde-based cloud layer retrieval method applied to data from different climate regimes is evaluated. Overall, cloud layers derived from the ARSCL VAP and radiosonde data agree very well at the SGP and AMF-China sites. At the TWP and NSA sites, the radiosonde tends to detect more cloud layers in the upper troposphere.

Comparison of the MODIS Multilayer Cloud Detection and Thermodynamic Phase Products with CALIPSO and CloudSat

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Gala; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.

2008-01-01

CALIPSO and CloudSat, launched in June 2006, provide global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the "Collection 5" stream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 h resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, and CloudSat radar measurements, we investigate the global performance of the thermodynamic phase and multilayer cloud detection algorithms.

Trade cumulus clouds embedded in a deep regional haze: Results from Indian Ocean CARDEX experiment

NASA Astrophysics Data System (ADS)

Wilcox, E. M.; Thomas, R. M.; Praveen, P. S.; Pistone, K.; Bender, F.; Feng, Y.; Ramanathan, V.

2013-12-01

During the winter monsoon, trade cumulus clouds over the North Indian Ocean are embedded within a deep regional haze described as an atmospheric brown cloud. While the trade-cu clouds are largely confined to the marine boundary layer, the sooty brown cloud extends from the boundary layer to as high as 3 km; well above the tops of the cumulus. The boundary layer pollution is persistent and limits drizzle in the cumulus over a period of greater than a month at the Maldives Climate Observatory located at Hanimaadhoo Island. The elevated haze from 1 to 3 km altitude is episodic and strongly modulated by synoptic variability in the 700 hPa flow. The elevated plume enhances heating above the marine boundary layer through daytime absorption of sunlight by the haze particles. The interplay between the microphysical modification of clouds by boundary layer pollution and the episodic elevated heating by the atmospheric brown cloud are explored in in-situ observations from UAVs and surface remote sensing during the CARDEX field campaign of winter 2012 and supported by multi-year analysis of satellite remote sensing observations. These observations document the variability in pollution at the surface and above the marine boundary layer and the effects of pollution on the microphysics of the trade-cu clouds, the depth of the marine boundary layer, the liquid water path of trade-cu clouds, and the profile of turbulent moisture flux through the boundary layer. The consequences of these effects for the radiative forcing of regional climate will be discussed.

The role of ice nuclei recycling in the maintenance of cloud ice in Arctic mixed-phase stratocumulus

DOE PAGES

Solomon, Amy; Feingold, G.; Shupe, M. D.

2015-09-25

This study investigates the maintenance of cloud ice production in Arctic mixed-phase stratocumulus in large eddy simulations that include a prognostic ice nuclei (IN) formulation and a diurnal cycle. Balances derived from a mixed-layer model and phase analyses are used to provide insight into buffering mechanisms that maintain ice in these cloud systems. We find that, for the case under investigation, IN recycling through subcloud sublimation considerably prolongs ice production over a multi-day integration. This effective source of IN to the cloud dominates over mixing sources from above or below the cloud-driven mixed layer. Competing feedbacks between dynamical mixing andmore » recycling are found to slow the rate of ice lost from the mixed layer when a diurnal cycle is simulated. Furthermore, the results of this study have important implications for maintaining phase partitioning of cloud ice and liquid that determine the radiative forcing of Arctic mixed-phase clouds.« less

The role of ice nuclei recycling in the maintenance of cloud ice in Arctic mixed-phase stratocumulus

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

Solomon, Amy; Feingold, G.; Shupe, M. D.

This study investigates the maintenance of cloud ice production in Arctic mixed-phase stratocumulus in large eddy simulations that include a prognostic ice nuclei (IN) formulation and a diurnal cycle. Balances derived from a mixed-layer model and phase analyses are used to provide insight into buffering mechanisms that maintain ice in these cloud systems. We find that, for the case under investigation, IN recycling through subcloud sublimation considerably prolongs ice production over a multi-day integration. This effective source of IN to the cloud dominates over mixing sources from above or below the cloud-driven mixed layer. Competing feedbacks between dynamical mixing andmore » recycling are found to slow the rate of ice lost from the mixed layer when a diurnal cycle is simulated. Furthermore, the results of this study have important implications for maintaining phase partitioning of cloud ice and liquid that determine the radiative forcing of Arctic mixed-phase clouds.« less

Examining the Impact of Overlying Aerosols on the Retrieval of Cloud Optical Properties from Passive Remote Sensing

NASA Technical Reports Server (NTRS)

Coddington, O. M.; Pilewskie, P.; Redemann, J.; Platnick, S.; Russell, P. B.; Schmidt, K. S.; Gore, W. J.; Livingston, J.; Wind, G.; Vukicevic, T.

2010-01-01

Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space ]based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below ]aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol ]induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 microns) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS ]retrieved cloud optical thickness and effective radius can reach values of 10 and 10 microns, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

Global Distribution and Vertical Structure of Clouds Revealed by CALIPSO

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

[CII] observations of H2 molecular layers in transition clouds

NASA Astrophysics Data System (ADS)

Velusamy, T.; Langer, W. D.; Pineda, J. L.; Goldsmith, P. F.; Li, D.; Yorke, H. W.

2010-10-01

We present the first results on the diffuse transition clouds observed in [CII] line emission at 158 μm (1.9 THz) towards Galactic longitudes near 340° (5 LOSs) & 20° (11 LOSs) as part of the HIFI tests and GOT C+ survey. Out of the total 146 [CII] velocity components detected by profile fitting we identify 53 as diffuse molecular clouds with associated 12CO emission but without 13CO emission and characterized by AV < 5 mag. We estimate the fraction of the [CII] emission in the diffuse HI layer in each cloud and then determine the [CII] emitted from the molecular layers in the cloud. We show that the excess [CII] intensities detected in a few clouds is indicative of a thick H2 layer around the CO core. The wide range of clouds in our sample with thin to thick H2 layers suggests that these are at various evolutionary states characterized by the formation of H2 and CO layers from HI and C+, respectively. In about 30% of the clouds the H2 column densities (“dark gas”) traced by the [CII] is 50% or more than that traced by 12CO emission. On the average ~25% of the total H2 in these clouds is in an H2 layer which is not traced by CO. We use the HI, [CII], and 12CO intensities in each cloud along with simple chemical models to obtain constraints on the FUV fields and cosmic ray ionization rates. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

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

NASA Astrophysics Data System (ADS)

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

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

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.

Comparison of the MODIS Collection 5 Multilayer Cloud Detection Product with CALIPSO

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Gala; King, Michael D.; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.

2010-01-01

CALIPSO, launched in June 2006, provides global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the Collection 5 scream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 km resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, we investigate the global performance of multilayer cloud detection algorithms (and thermodynamic phase).

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

Height Distribution Between Cloud and Aerosol Layers from the GLAS Spaceborne Lidar in the Indian Ocean Region

NASA Technical Reports Server (NTRS)

Hart, William D.; Spinhirne, James D.; Palm, Steven P.; Hlavka, Dennis L.

2005-01-01

The Geoscience Laser Altimeter System (GLAS), a nadir pointing lidar on the Ice Cloud and land Elevation Satellite (ICESat) launched in 2003, now provides important new global measurements of the relationship between the height distribution of cloud and aerosol layers. GLAS data have the capability to detect, locate, and distinguish between cloud and aerosol layers in the atmosphere up to 40 km altitude. The data product algorithm tests the product of the maximum attenuated backscatter coefficient b'(r) and the vertical gradient of b'(r) within a layer against a predetermined threshold. An initial case result for the critical Indian Ocean region is presented. From the results the relative height distribution between collocated aerosol and cloud shows extensive regions where cloud formation is well within dense aerosol scattering layers at the surface. Citation: Hart, W. D., J. D. Spinhime, S. P. Palm, and D. L. Hlavka (2005), Height distribution between cloud and aerosol layers from the GLAS spaceborne lidar in the Indian Ocean region,

A Radiative Analysis of Angular Signatures and Oblique Radiance Retrievals over the Polar Regions from the Multi-Angle Imaging Spectroradiometer

ERIC Educational Resources Information Center

Wilson, Michael Jason

2009-01-01

This dissertation studies clouds over the polar regions using the Multi-angle Imaging SpectroRadiometer (MISR) on-board EOS-Terra. Historically, low thin clouds have been problematic for satellite detection, because these clouds have similar brightness and temperature properties to the surface they overlay. However, the oblique angles of MISR…

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Global Single and Multiple Cloud Classification with a Fuzzy Logic Expert System

NASA Technical Reports Server (NTRS)

Welch, Ronald M.; Tovinkere, Vasanth; Titlow, James; Baum, Bryan A.

1996-01-01

An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.

RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

NASA Technical Reports Server (NTRS)

Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; Fridlind, Ann; Endo, Satoshi; Song, Hua; Feng, Sha; Toto, Tami; Li, Zhijin; Zhang, Minghua

2015-01-01

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

RACORO continental boundary layer cloud investigations. 3. Separation of parameterization biases in single-column model CAM5 simulations of shallow cumulus

DOE PAGES

Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; ...

2015-06-19

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) project has constructed case studies from the Atmospheric Radiation Measurement (ARM) Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only amore » relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.« less

Evaluation of Satellite-Based Upper Troposphere Cloud Top Height Retrievals in Multilayer Cloud Conditions During TC4

NASA Technical Reports Server (NTRS)

Chang, Fu-Lung; Minnis, Patrick; Ayers, J. Kirk; McGill, Matthew J.; Palikonda, Rabindra; Spangenberg, Douglas A.; Smith, William L., Jr.; Yost, Christopher R.

2010-01-01

Upper troposphere cloud top heights (CTHs), restricted to cloud top pressures (CTPs) less than 500 hPa, inferred using four satellite retrieval methods applied to Twelfth Geostationary Operational Environmental Satellite (GOES-12) data are evaluated using measurements during the July August 2007 Tropical Composition, Cloud and Climate Coupling Experiment (TC4). The four methods are the single-layer CO2-absorption technique (SCO2AT), a modified CO2-absorption technique (MCO2AT) developed for improving both single-layered and multilayered cloud retrievals, a standard version of the Visible Infrared Solar-infrared Split-window Technique (old VISST), and a new version of VISST (new VISST) recently developed to improve cloud property retrievals. They are evaluated by comparing with ER-2 aircraft-based Cloud Physics Lidar (CPL) data taken during 9 days having extensive upper troposphere cirrus, anvil, and convective clouds. Compared to the 89% coverage by upper tropospheric clouds detected by the CPL, the SCO2AT, MCO2AT, old VISST, and new VISST retrieved CTPs less than 500 hPa in 76, 76, 69, and 74% of the matched pixels, respectively. Most of the differences are due to subvisible and optically thin cirrus clouds occurring near the tropopause that were detected only by the CPL. The mean upper tropospheric CTHs for the 9 days are 14.2 (+/- 2.1) km from the CPL and 10.7 (+/- 2.1), 12.1 (+/- 1.6), 9.7 (+/- 2.9), and 11.4 (+/- 2.8) km from the SCO2AT, MCO2AT, old VISST, and new VISST, respectively. Compared to the CPL, the MCO2AT CTHs had the smallest mean biases for semitransparent high clouds in both single-layered and multilayered situations whereas the new VISST CTHs had the smallest mean biases when upper clouds were opaque and optically thick. The biases for all techniques increased with increasing numbers of cloud layers. The transparency of the upper layer clouds tends to increase with the numbers of cloud layers.

Developing Present-day Proxy Cases Based on NARVAL Data for Investigating Low Level Cloud Responses to Future Climate Change.

NASA Astrophysics Data System (ADS)

Reilly, Stephanie

2017-04-01

The energy budget of the entire global climate is significantly influenced by the presence of boundary layer clouds. The main aim of the High Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) project is to improve climate model predictions by means of process studies of clouds and precipitation. This study makes use of observed elevated moisture layers as a proxy of future changes in tropospheric humidity. The associated impact on radiative transfer triggers fast responses in boundary layer clouds, providing a framework for investigating this phenomenon. The investigation will be carried out using data gathered during the Next-generation Aircraft Remote-sensing for VALidation (NARVAL) South campaigns. Observational data will be combined with ECMWF reanalysis data to derive the large scale forcings for the Large Eddy Simulations (LES). Simulations will be generated for a range of elevated moisture layers, spanning a multi-dimensional phase space in depth, amplitude, elevation, and cloudiness. The NARVAL locations will function as anchor-points. The results of the large eddy simulations and the observations will be studied and compared in an attempt to determine how simulated boundary layer clouds react to changes in radiative transfer from the free troposphere. Preliminary LES results will be presented and discussed.

The Mixed-Phase Arctic Cloud Experiment (M-PACE)

NASA Technical Reports Server (NTRS)

Verlinde, J.; Harrington, J. Y.; McFarquhar, G. M.; Yannuzzi, V. T.; Avramov, A.; Greenberg, S.; Johnson, N.; Zhang, G.; Poellot, M. R.; Mather, J. H.;

Multi-Layer Arctic Mixed-Phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity Experiments

NASA Technical Reports Server (NTRS)

Luo, Yali; Xu, Kuan-Man; Morrison, Hugh; McFarquhar, Greg M.; Wang, Zhien; Zhang, Gong

2007-01-01

A cloud-resolving model (CRM) is used to simulate the multiple-layer mixed-phase stratiform (MPS) clouds that occurred during a three-and-a-half day subperiod of the Department of Energy-Atmospheric Radiation Measurement Program s Mixed-Phase Arctic Cloud Experiment (M-PACE). The CRM is implemented with an advanced two-moment microphysics scheme, a state-of-the-art radiative transfer scheme, and a complicated third-order turbulence closure. Concurrent meteorological, aerosol, and ice nucleus measurements are used to initialize the CRM. The CRM is prescribed by time-varying large-scale advective tendencies of temperature and moisture and surface turbulent fluxes of sensible and latent heat. The CRM reproduces the occurrences of the single- and double-layer MPS clouds as revealed by the M-PACE observations. However, the simulated first cloud layer is lower and the second cloud layer thicker compared to observations. The magnitude of the simulated liquid water path agrees with that observed, but its temporal variation is more pronounced than that observed. As in an earlier study of single-layer cloud, the CRM also captures the major characteristics in the vertical distributions and temporal variations of liquid water content (LWC), total ice water content (IWC), droplet number concentration and ice crystal number concentration (nis) as suggested by the aircraft observations. However, the simulated mean values differ significantly from the observed. The magnitude of nis is especially underestimated by one order of magnitude. Sensitivity experiments suggest that the lower cloud layer is closely related to the surface fluxes of sensible and latent heat; the upper cloud layer is probably initialized by the large-scale advective cooling/moistening and maintained through the strong longwave (LW) radiative cooling near the cloud top which enhances the dynamical circulation; artificially turning off all ice-phase microphysical processes results in an increase in LWP by a factor of 3 due to interactions between the excessive LW radiative cooling and extra cloud water; heating caused by phase change of hydrometeors could affect the LWC and cloud top height by partially canceling out the LW radiative cooling. It is further shown that the resolved dynamical circulation appears to contribute more greatly to the evolution of the MPS cloud layers than the parameterized subgrid-scale circulation.

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.

Absolute calibration of the Jenoptik CHM15k-x ceilometer and its applicability for quantitative aerosol monitoring

NASA Astrophysics Data System (ADS)

Geiß, Alexander; Wiegner, Matthias

2014-05-01

The knowledge of the spatiotemporal distribution of atmospheric aerosols and its optical characterization is essential for the understanding of the radiation budget, air quality, and climate. For this purpose, lidar is an excellent system as it is an active remote sensing technique. As multi-wavelength research lidars with depolarization channels are quite complex and cost-expensive, increasing attention is paid to so-called ceilometers. They are simple one-wavelength backscatter lidars with low pulse energy for eye-safe operation. As maintenance costs are low and continuous and unattended measurements can be performed, they are suitable for long-term aerosol monitoring in a network. However, the signal-to-noise ratio is low, and the signals are not calibrated. The only optical property that can be derived from a ceilometer is the particle backscatter coefficient, but even this quantity requires a calibration of the signals. With four years of measurements from a Jenoptik ceilometer CHM15k-x, we developed two methods for an absolute calibration on this system. This advantage of our approach is that only a few days with favorable meteorological conditions are required where Rayleigh-calibration and comparison with our research lidar is possible to estimate the lidar constant. This method enables us to derive the particle backscatter coefficient at 1064 nm, and we retrieved for the first time profiles in near real-time within an accuracy of 10 %. If an appropriate lidar ratio is assumed the aerosol optical depth of e.g. the mixing layer can be determined with an accuracy depending on the accuracy of the lidar ratio estimate. Even for 'simple' applications, e.g. assessment of the mixing layer height, cloud detection, detection of elevated aerosol layers, the particle backscatter coefficient has significant advantages over the measured (uncalibrated) attenuated backscatter. The possibility of continuous operation under nearly any meteorological condition with temporal resolution in the order of 30 seconds makes it also possible to apply time-height-tracking methods for detecting mixing layer heights. The combination of methods for edge detection (e.g. wavelet covariance transform, gradient method, variance method) and edge tracking techniques is used to increase the reliability of the layer detection and attribution. Thus, a feature mask of aerosols and clouds can be derived. Four years of measurements constitute an excellent basis for a climatology including a homogeneous time series of mixing layer heights, aerosol layers and cloud base heights of the troposphere. With a low overlap region of 180 m of the Jenoptik CHM15k-x even very narrow mixing layers, typical for winter conditions, can be considered.

A multi-spectral approach to simultaneously retrieve above-cloud smoke optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds using MODIS

NASA Astrophysics Data System (ADS)

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

2013-12-01

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 the standard MODIS cloud optical and microphysical 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 μm (effective particle size retrievals are derived from the short and mid-wave IR channels at 1.6, 2.1, and 3.7 μm). 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 MODIS spectral channels in the visible and near- and shortwave-infrared. Preliminary retrieval results are shown, as are comparisons with other A-Train sensors.

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

Riihimaki, L.; McFarlane, S.; Sivaraman, C.

The ndrop_mfrsr value-added product (VAP) provides an estimate of the cloud droplet number concentration of overcast water clouds retrieved from cloud optical depth from the multi-filter rotating shadowband radiometer (MFRSR) instrument and liquid water path (LWP) retrieved from the microwave radiometer (MWR). When cloud layer information is available from vertically pointing lidar and radars in the Active Remote Sensing of Clouds (ARSCL) product, the VAP also provides estimates of the adiabatic LWP and an adiabatic parameter (beta) that indicates how divergent the LWP is from the adiabatic case. quality control (QC) flags (qc_drop_number_conc), an uncertainty estimate (drop_number_conc_toterr), and a cloudmore » layer type flag (cloud_base_type) are useful indicators of the quality and accuracy of any given value of the retrieval. Examples of these major input and output variables are given in sample plots in section 6.0.« less

Super-cooled liquid water topped sub-arctic clouds and precipitation - investigation based on combination of ground-based in-situ and remote-sensing observations

NASA Astrophysics Data System (ADS)

Hirsikko, Anne; Brus, David; O'Connor, Ewan J.; Filioglou, Maria; Komppula, Mika; Romakkaniemi, Sami

2017-04-01

In the high and mid latitudes super-cooled liquid water layers are frequently observed on top of clouds. These layers are difficult to forecast with numerical weather prediction models, even though, they have strong influence on atmospheric radiative properties, cloud microphysical properties, and subsequently, precipitation. This work investigates properties of super-cooled liquid water layer topped sub-arctic clouds and precipitation observed with ground-based in-situ (cloud probes) and remote-sensing (a cloud radar, Doppler and multi-wavelength lidars) instrumentation during two-month long Pallas Cloud Experiment (PaCE 2015) in autumn 2015. Analysis is based on standard Cloudnet scheme supplemented with new retrieval products of the specific clouds and their properties. Combination of two scales of observation provides new information on properties of clouds and precipitation in the sub-arctic Pallas region. Current status of results will be presented during the conference. The authors acknowledge financial support by the Academy of Finland (Centre of Excellence Programme, grant no 272041; and ICINA project, grant no 285068), the ACTRIS2 - European Union's Horizon 2020 research and innovation programme under grant agreement No 654109, the KONE foundation, and the EU FP7 project BACCHUS (grant no 603445).

Passive and Active Detection of Clouds: Comparisons between MODIS and GLAS Observations

NASA Technical Reports Server (NTRS)

Mahesh, Ashwin; Gray, Mark A.; Palm, Stephen P.; Hart, William D.; Spinhirne, James D.

2003-01-01

The Geoscience Laser Altimeter System (GLAS), launched on board the Ice, Cloud and Land Elevation Satellite in January 2003 provides space-borne laser observations of atmospheric layers. GLAS provides opportunities to validate passive observations of the atmosphere for the first time from space with an active optical instrument. Data from the Moderate Resolution Imaging Spectrometer aboard the Aqua satellite is examined along with GLAS observations of cloud layers. In more than three-quarters of the cases, MODIS scene identification from spectral radiances agrees with GLAS. Disagreement between the two platforms is most significant over snow-covered surfaces in the northern hemisphere. Daytime clouds detected by GLAS are also more easily seen in the MODIS data as well, compared to observations made at night. These comparisons illustrate the capabilities of active remote sensing to validate and assess passive measurements, and also to complement them in studies of atmospheric layers.

Using deep recurrent neural network for direct beam solar irradiance cloud screening

NASA Astrophysics Data System (ADS)

Chen, Maosi; Davis, John M.; Liu, Chaoshun; Sun, Zhibin; Zempila, Melina Maria; Gao, Wei

2017-09-01

Cloud screening is an essential procedure for in-situ calibration and atmospheric properties retrieval on (UV-)MultiFilter Rotating Shadowband Radiometer [(UV-)MFRSR]. Previous study has explored a cloud screening algorithm for direct-beam (UV-)MFRSR voltage measurements based on the stability assumption on a long time period (typically a half day or a whole day). To design such an algorithm requires in-depth understanding of radiative transfer and delicate data manipulation. Recent rapid developments on deep neural network and computation hardware have opened a window for modeling complicated End-to-End systems with a standardized strategy. In this study, a multi-layer dynamic bidirectional recurrent neural network is built for determining the cloudiness on each time point with a 17-year training dataset and tested with another 1-year dataset. The dataset is the daily 3-minute cosine corrected voltages, airmasses, and the corresponding cloud/clear-sky labels at two stations of the USDA UV-B Monitoring and Research Program. The results show that the optimized neural network model (3-layer, 250 hidden units, and 80 epochs of training) has an overall test accuracy of 97.87% (97.56% for the Oklahoma site and 98.16% for the Hawaii site). Generally, the neural network model grasps the key concept of the original model to use data in the entire day rather than short nearby measurements to perform cloud screening. A scrutiny of the logits layer suggests that the neural network model automatically learns a way to calculate a quantity similar to total optical depth and finds an appropriate threshold for cloud screening.

Phase-partitioning in mixed-phase clouds - An approach to characterize the entire vertical column

NASA Astrophysics Data System (ADS)

Kalesse, H.; Luke, E. P.; Seifert, P.

2017-12-01

The characterization of the entire vertical profile of phase-partitioning in mixed-phase clouds is a challenge which can be addressed by synergistic profiling measurements with ground-based polarization lidars and cloud radars. While lidars are sensitive to small particles and can thus detect supercooled liquid (SCL) layers, cloud radar returns are dominated by larger particles (like ice crystals). The maximum lidar observation height is determined by complete signal attenuation at a penetrated optical depth of about three. In contrast, cloud radars are able to penetrate multiple liquid layers and can thus be used to expand the identification of cloud phase to the entire vertical column beyond the lidar extinction height, if morphological features in the radar Doppler spectrum can be related to the existence of SCL. Relevant spectral signatures such as bimodalities and spectral skewness can be related to cloud phase by training a neural network appropriately in a supervised learning scheme, with lidar measurements functioning as supervisor. The neural network output (prediction of SCL location) derived using cloud radar Doppler spectra can be evaluated with several parameters such as liquid water path (LWP) detected by microwave radiometer (MWR) and (liquid) cloud base detected by ceilometer or Raman lidar. The technique has been previously tested on data from Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) instruments in Barrow, Alaska and is in this study utilized for observations from the Leipzig Aerosol and Cloud Remote Observations System (LACROS) during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) field experiment in Cabauw, Netherlands in Fall 2014. Comparisons to supercooled-liquid layers as classified by CLOUDNET are provided.

Multi-sensor quantification of aerosol-induced variability in warm clouds over eastern China

NASA Astrophysics Data System (ADS)

Wang, Fu; Guo, Jianping; Zhang, Jiahua; Huang, Jingfeng; Min, Min; Chen, Tianmeng; Liu, Huan; Deng, Minjun; Li, Xiaowen

2015-07-01

Aerosol-cloud (AC) interactions remain uncharacterized due to difficulties in obtaining accurate aerosol and cloud observations. In this study, we quantified the aerosol indirect effects (AIE) on warm clouds over Eastern China based on near-simultaneous retrievals from MODIS/AQUA, CALIOP/CALIPSO, and CPR/CLOUDSAT between June 2006 and December 2010. The seasonality of aerosols from ground-based PM10 (aerosol particles with diameter of 10 μm or less) significantly differed from that estimated using MODIS aerosol optical depth (AOD). This result was supported by the lower level frequency profile of aerosol occurrence from CALIOP, indicative of the significant role of CALIOP in the AC interaction. To focus on warm clouds, cloud layers with base (top) altitudes above 7 (10) km were excluded. The combination of CALIOP and CPR was applied to determine the exact position of warm clouds relative to aerosols out of the following six scenarios in terms of AC mixing states: 1) aerosol only (AO); 2) cloud only (CO); 3) single aerosol layer-single cloud layer (SASC); 4) single aerosol layer-double cloud layers (SADC); 5) double aerosol layers - single cloud layer (DASC); and 6) others. The cases with vertical distance between aerosol and cloud layer less (more) than 100 m (700 m) were marked mixed (separated), and the rest as uncertain. Results showed that only 8.95% (7.53%) belonged to the mixed (separated and uncertain) state among all of the collocated AC overlapping cases, including SASC, SADC, and DASC. Under mixed conditions, the cloud droplet effective radius (CDR) decreased with increasing AOD at moderate aerosol loading (AOD<0.4), and then became saturated at an AOD of around 0.5, followed by an increase in CDR with increasing AOD, known as boomerang shape. Under separated conditions, no apparent changes in CDR with AOD were observed. We categorized the AC dataset into summer- and winter-season subsets to determine how the boomerang shape varied with season. The response of CDR to AOD in summer exhibited similar but much more deepened boomerang shape, as compared with the all year round case. In contrast, CDR in winter did not follow the boomerang shape for its continued decreasing with increasing AOD, even after the saturation zone (AOD around 0.5) of a cloud droplet.

Geometric and optical properties of cirrus clouds inferred from three-year ground-based lidar and CALIOP measurements over Seoul, Korea

NASA Astrophysics Data System (ADS)

Kim, Yumi; Kim, Sang-Woo; Kim, Man-Hae; Yoon, Soon-Chang

2014-03-01

This study examines cirrus cloud top and bottom heights (CTH and CBH, respectively) and the associated optical properties revealed by ground-based lidar in Seoul (SNU-L), Korea, and space-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), which were obtained during a three-year measurement period between July 2006 and June 2009. From two selected cases, we determined good agreement in CTH and CBH with cirrus cloud optical depth (COD) between ground-based lidar and space-borne CALIOP. In particular, CODs at a wavelength of 532 nm calculated from the three years of SNU-L and CALIOP measurements were 0.417 ± 0.394 and 0.425 ± 0.479, respectively. The fraction of COD lower than 0.1 was approximately 17% and 25% of the total SNU-L and CALIOP profiles, respectively, and approximately 50% of both lidar profiles were classified as sub-visual or optically thin such that COD was < 0.3. The mean depolarization ratio was estimated to be 0.30 ± 0.06 for SNU-L and 0.34 ± 0.08 for CALIOP. The monthly variation of CODs from SNU-L and CALIOP measurements was not distinct, whereas cirrus altitudes from both SNU-L and CALIOP showed distinct monthly variation. CALIOP observations showed that cirrus clouds reached the tropopause level in all months, whereas the up-looking SNU-L did not detect cirrus clouds near the tropopause in summer due to signal attenuation by underlying optically thick clouds. The cloud layer thickness (CLT) and COD showed a distinct linear relationship up to approximately 2 km of the CLT; however, the COD did not increase, but remained constant when the CLT was greater than 2.0 km. The ice crystal content, lidar signal attenuation, and the presence of multi-layered cirrus clouds may have contributed to this tendency.

3D cloud detection and tracking system for solar forecast using multiple sky imagers

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2015-06-23

We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

Overlap Properties of Clouds Generated by a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Oreopoulos, L.; Khairoutdinov, M.

2002-01-01

In order for General Circulation Models (GCMs), one of our most important tools to predict future climate, to correctly describe the propagation of solar and thermal radiation through the cloudy atmosphere a realistic description of the vertical distribution of cloud amount is needed. Actually, one needs not only the cloud amounts at different levels of the atmosphere, but also how these cloud amounts are related, in other words, how they overlap. Currently GCMs make some idealized assumptions about cloud overlap, for example that contiguous cloud layers overlap maximally and non-contiguous cloud layers overlap in a random fashion. Since there are difficulties in obtaining the vertical profile of cloud amount from observations, the realism of the overlap assumptions made in GCMs has not been yet rigorously investigated. Recently however, cloud observations from a relatively new type of ground radar have been used to examine the vertical distribution of cloudiness. These observations suggest that the GCM overlap assumptions are dubious. Our study uses cloud fields from sophisticated models dedicated to simulate cloud formation, maintenance, and dissipation called Cloud Resolving Models . These models are generally considered capable of producing realistic three-dimensional representation of cloudiness. Using numerous cloud fields produced by such a CRM we show that the degree of overlap between cloud layers is a function of their separation distance, and is in general described by a combination of the maximum and random overlap assumption, with random overlap dominating as separation distances increase. We show that it is possible to parameterize this behavior in a way that can eventually be incorporated in GCMs. Our results seem to have a significant resemblance to the results from the radar observations despite the completely different nature of the datasets. This consistency is encouraging and will promote development of new radiative transfer codes that will estimate the radiation effects of multi-layer cloud fields more accurately.

THOR: Cloud Thickness from Off beam Lidar Returns

NASA Technical Reports Server (NTRS)

Cahalan, Robert F.; McGill, Matthew; Kolasinski, John; Varnai, Tamas; Yetzer, Ken

2004-01-01

Conventional wisdom is that lidar pulses do not significantly penetrate clouds having optical thickness exceeding about tau = 2, and that no returns are detectable from more than a shallow skin depth. Yet optically thicker clouds of tau much greater than 2 reflect a larger fraction of visible photons, and account for much of Earth s global average albedo. As cloud layer thickness grows, an increasing fraction of reflected photons are scattered multiple times within the cloud, and return from a diffuse concentric halo that grows around the incident pulse, increasing in horizontal area with layer physical thickness. The reflected halo is largely undetected by narrow field-of-view (FoV) receivers commonly used in lidar applications. THOR - Thickness from Off-beam Returns - is an airborne wide-angle detection system with multiple FoVs, capable of observing the diffuse halo, detecting wide-angle signal from which physical thickness of optically thick clouds can be retrieved. In this paper we describe the THOR system, demonstrate that the halo signal is stronger for thicker clouds, and validate physical thickness retrievals for clouds having z > 20, from NASA P-3B flights over the Department of Energy/Atmospheric Radiation Measurement/Southern Great Plains site, using the lidar, radar and other ancillary ground-based data.

A Marine Boundary Layer Water Vapor Climatology Derived from Microwave and Near-Infrared Imagery

NASA Astrophysics Data System (ADS)

Millan Valle, L. F.; Lebsock, M. D.; Teixeira, J.

2017-12-01

The synergy of the collocated Advanced Microwave Scanning Radiometer (AMSR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global estimates of partial marine planetary boundary layer water vapor. AMSR microwave radiometry provides the total column water vapor, while MODIS near-infrared imagery provides the water vapor above the cloud layers. The difference between the two gives the vapor between the surface and the cloud top, which may be interpreted as the boundary layer water vapor. Comparisons against radiosondes, and GPS-Radio occultation data demonstrate the robustness of these boundary layer water vapor estimates. We exploit the 14 years of AMSR-MODIS synergy to investigate the spatial, seasonal, and inter-annual variations of the boundary layer water vapor. Last, it is shown that the measured AMSR-MODIS partial boundary layer water vapor can be generally prescribed using sea surface temperature, cloud top pressure and the lifting condensation level. The multi-sensor nature of the analysis demonstrates that there exists more information on boundary layer water vapor structure in the satellite observing system than is commonly assumed when considering the capabilities of single instruments. 2017 California Institute of Technology. U.S. Government sponsorship acknowledged.

Ice Cloud Properties in Ice-Over-Water Cloud Systems Using TRMM VIRS and TMI Data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Huang, Jianping; Lin, Bing; Yi, Yuhong; Arduini, Robert F.; Fan, Tai-Fang; Ayers, J. Kirk; Mace, Gerald G.

2007-01-01

A multi-layered cloud retrieval system (MCRS) is updated and used to estimate ice water path in maritime ice-over-water clouds using Visible and Infrared Scanner (VIRS) and TRMM Microwave Imager (TMI) measurements from the Tropical Rainfall Measuring Mission spacecraft between January and August 1998. Lookup tables of top-of-atmosphere 0.65- m reflectance are developed for ice-over-water cloud systems using radiative transfer calculations with various combinations of ice-over-water cloud layers. The liquid and ice water paths, LWP and IWP, respectively, are determined with the MCRS using these lookup tables with a combination of microwave (MW), visible (VIS), and infrared (IR) data. LWP, determined directly from the TMI MW data, is used to define the lower-level cloud properties to select the proper lookup table. The properties of the upper-level ice clouds, such as optical depth and effective size, are then derived using the Visible Infrared Solar-infrared Split-window Technique (VISST), which matches the VIRS IR, 3.9- m, and VIS data to the multilayer-cloud lookup table reflectances and a set of emittance parameterizations. Initial comparisons with surface-based radar retrievals suggest that this enhanced MCRS can significantly improve the accuracy and decrease the IWP in overlapped clouds by 42% and 13% compared to using the single-layer VISST and an earlier simplified MW-VIS-IR (MVI) differencing method, respectively, for ice-over-water cloud systems. The tropical distribution of ice-over-water clouds is the same as derived earlier from combined TMI and VIRS data, but the new values of IWP and optical depth are slightly larger than the older MVI values, and exceed those of single-layered layered clouds by 7% and 11%, respectively. The mean IWP from the MCRS is 8-14% greater than that retrieved from radar retrievals of overlapped clouds over two surface sites and the standard deviations of the differences are similar to those for single-layered clouds. Examples of a method for applying the MCRS over land without microwave data yield similar differences with the surface retrievals. By combining the MCRS with other techniques that focus primarily on optically thin cirrus over low water clouds, it will be possible to more fully assess the IWP in all conditions over ocean except for precipitating systems.

Detection of single and multilayer clouds in an artificial neural network approach

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Hong, Gang; Chen, Yan

2017-10-01

Determining whether a scene observed with a satellite imager is composed of a thin cirrus over a water cloud or thick cirrus contiguous with underlying layers of ice and water clouds is often difficult because of similarities in the observed radiance values. In this paper an artificial neural network (ANN) algorithm, employing several Aqua MODIS infrared channels and the retrieved total cloud visible optical depth, is trained to detect multilayer ice-over-water cloud systems as identified by matched April 2009 CloudSat and CALIPSO (CC) data. The CC lidar and radar profiles provide the vertical structure that serves as output truth for a multilayer ANN, or MLANN, algorithm. Applying the trained MLANN to independent July 2008 MODIS data resulted in a combined ML and single layer hit rate of 75% (72%) for nonpolar regions during the day (night). The results are comparable to or more accurate than currently available methods. Areas of improvement are identified and will be addressed in future versions of the MLANN.

Powerful Hurricane Irma Seen in 3D by NASA's CloudSat

NASA Image and Video Library

2017-09-08

NASA's CloudSat satellite flew over Hurricane Irma on Sept. 6, 2017 at 1:45 p.m. EDT (17:45 UTC) as the storm was approaching Puerto Rico in the Atlantic Ocean. Hurricane Irma contained estimated maximum sustained winds of 185 miles per hour (160 knots) with a minimum pressure of 918 millibars. CloudSat transected the eastern edge of Hurricane Irma's eyewall, revealing details of the storm's cloud structure beneath its thick canopy of cirrus clouds. The CloudSat Cloud Profiling Radar excels in detecting the organization and placement of cloud layers beneath a storm's cirrus canopy, which are not readily detected by other satellite sensors. The CloudSat overpass reveals the inner details beneath the cloud tops of this large system; intense areas of convection with moderate to heavy rainfall (deep red and pink colors), cloud-free areas (moats) in between the inner and outer cloud bands of Hurricane Irma and cloud top heights averaging around 9 to 10 miles (15 to 16 kilometers). Lower values of reflectivity (areas of green and blue) denote smaller-sized ice and water particle sizes typically located at the top of a storm system (in the anvil area). The Cloud Profiling Radar loses signal at around 3 miles (5 kilometers) in height (in the melting layer) due to water (ice) particles larger than 0.12 inches (3 millimeters) in diameter. Moderate to heavy rainfall occurs in these areas where signal weakening is detectable. Smaller cumulus and cumulonimbus cloud types are evident as CloudSat moves farther south, beneath the thick cirrus canopy. An animation is available at https://photojournal.jpl.nasa.gov/catalog/PIA21947

n/a

NASA Image and Video Library

1988-08-08

A recent Hubble Space Telescope (HST) view reveals Uranus surrounded by its 4 major rings and 10 of its 17 known satellites. This false color image was generated by Erich Karoschka using data taken with Hubble's Near Infrared Camera and Multi-Object Spectrometer. The HST recently found about 20 clouds. The colors in the image indicate altitude. The green and blue regions show where the atmosphere is clear and can be penetrated by sunlight. In yellow and grey regions, the sunlight reflects from a higher haze or cloud layer. The orange and red colors indicate very high clouds, such as cirrus clouds on Earth.

Efficacy of Cloud-Radiative Perturbations in Deep Open- and Closed-Cell Stratocumulus Clouds due to Aerosol Perturbations

NASA Astrophysics Data System (ADS)

Possner, A.; Wang, H.; Caldeira, K.; Wood, R.; Ackerman, T. P.

2017-12-01

Aerosol-cloud interactions (ACIs) in marine stratocumulus remain a significant source of uncertainty in constraining the cloud-radiative effect in a changing climate. Ship tracks are undoubted manifestations of ACIs embedded within stratocumulus cloud decks and have proven to be a useful framework to study the effect of aerosol perturbations on cloud morphology, macrophysical, microphyiscal and cloud-radiative properties. However, so far most observational (Christensen et al. 2012, Chen et al. 2015) and numerical studies (Wang et al. 2011, Possner et al. 2015, Berner et al. 2015) have concentrated on ship tracks in shallow boundary layers of depths between 300 - 800 m, while most stratocumulus decks form in significantly deeper boundary layers (Muhlbauer et al. 2014). In this study we investigate the efficacy of aerosol perturbations in deep open and closed cell stratocumulus. Multi-day idealised cloud-resolving simulations are performed for the RF06 flight of the VOCALS-Rex field campaign (Wood et al. 2011). During this flight pockets of deep open and closed cells were observed in a 1410 m deep boundary layer. The efficacy of aerosol perturbations of varied concentration and spatial gradients in altering the cloud micro- and macrophysical state and cloud-radiative effect is determined in both cloud regimes. Our simulations show that a continued point source emission flux of 1.16*1011 particles m-2 s-1 applied within a 300x300 m2 gridbox induces pronounced cloud cover changes in approximately a third of the simulated 80x80 km2 domain, a weakening of the diurnal cycle in the open-cell regime and a resulting increase in domain-mean cloud albedo of 0.2. Furthermore, we contrast the efficacy of equal strength near-surface or above-cloud aerosol perturbations in altering the cloud state.

Improving Scene Classifications with Combined Active/Passive Measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Rodier, S.; Vaughan, M.; McGill, M.

The uncertainties in cloud and aerosol physical properties derived from passive instruments such as MODIS are not insignificant And the uncertainty increases when the optical depths decrease Lidar observations do much better for the thin clouds and aerosols Unfortunately space-based lidar measurements such as the one onboard CALIPSO satellites are limited to nadir view only and thus have limited spatial coverage To produce climatologically meaningful thin cloud and aerosol data products it is necessary to combine the spatial coverage of MODIS with the highly sensitive CALIPSO lidar measurements Can we improving the quality of cloud and aerosol remote sensing data products by extending the knowledge about thin clouds and aerosols learned from CALIPSO-type of lidar measurements to a larger portion of the off-nadir MODIS-like multi-spectral pixels To answer the question we studied the collocated Cloud Physics Lidar CPL with Modis-Airborne-Simulation MAS observations and established an effective data fusion technique that will be applied in the combined CALIPSO MODIS cloud aerosol product algorithms This technique performs k-mean and Kohonen self-organized map cluster analysis on the entire swath of MAS data as well as on the combined CPL MAS data at the nadir track Interestingly the clusters generated from the two approaches are almost identical It indicates that the MAS multi-spectral data may have already captured most of the cloud and aerosol scene types such as cloud ice water phase multi-layer information aerosols

Radiative transfer model for aerosols at infrared wavelengths for passive remote sensing applications: revisited.

PubMed

Ben-David, Avishai; Davidson, Charles E; Embury, Janon F

2008-11-01

We introduced a two-dimensional radiative transfer model for aerosols in the thermal infrared [Appl. Opt.45, 6860-6875 (2006)APOPAI0003-693510.1364/AO.45.006860]. In that paper we superimposed two orthogonal plane-parallel layers to compute the radiance due to a two-dimensional (2D) rectangular aerosol cloud. In this paper we revisit the model and correct an error in the interaction of the two layers. We derive new expressions relating to the signal content of the radiance from an aerosol cloud based on the concept of five directional thermal contrasts: four for the 2D diffuse radiance and one for direct radiance along the line of sight. The new expressions give additional insight on the radiative transfer processes within the cloud. Simulations for Bacillus subtilis var. niger (BG) bioaerosol and dustlike kaolin aerosol clouds are compared and contrasted for two geometries: an airborne sensor looking down and a ground-based sensor looking up. Simulation results suggest that aerosol cloud detection from an airborne platform may be more challenging than for a ground-based sensor and that the detection of an aerosol cloud in emission mode (negative direct thermal contrast) is not the same as the detection of an aerosol cloud in absorption mode (positive direct thermal contrast).

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.

Radiative Impacts of Cloud Heterogeneity and Overlap in an Atmospheric General Circulation Model

NASA Technical Reports Server (NTRS)

Oreopoulos, L.; Lee, D.; Sud, Y. C.; Suarez, M. J.

2012-01-01

The radiative impacts of introducing horizontal heterogeneity of layer cloud condensate, and vertical overlap of condensate and cloud fraction are examined with the aid of a new radiation package operating in the GEOS-5 Atmospheric General Circulation Model. The impacts are examined in terms of diagnostic top-of-the-atmosphere shortwave (SW) and longwave (LW) cloud radiative effect (CRE) calculations for a range of assumptions and parameter specifications about the overlap. The investigation is conducted for two distinct cloud schemes, the one that comes with the standard GEOS-5 distribution, and another which has been recently used experimentally for its enhanced GEOS-5 distribution, and another which has been recently used experimentally for its enhanced cloud microphysical capabilities; both are coupled to a cloud generator allowing arbitrary cloud overlap specification. We find that cloud overlap radiative impacts are significantly stronger for the operational cloud scheme for which a change of cloud fraction overlap from maximum-random to generalized results to global changes of SW and LW CRE of approximately 4 Watts per square meter, and zonal changes of up to approximately 10 Watts per square meter. This is because of fewer occurrences compared to the other scheme of large layer cloud fractions and of multi-layer situations with large numbers of atmospheric being simultaneously cloudy, conditions that make overlap details more important. The impact on CRE of the details of condensate distribution overlap is much weaker. Once generalized overlap is adopted, both cloud schemes are only modestly sensitive to the exact values of the overlap parameters. We also find that if one of the CRE components is overestimated and the other underestimated, both cannot be driven towards observed values by adjustments to cloud condensate heterogeneity and overlap alone.

Study of atmospheric parameters measurements using MM-wave radar in synergy with LITE-2

NASA Technical Reports Server (NTRS)

Andrawis, Madeleine Y.

1994-01-01

The Lidar In-Space Technology Experiment, (LITE), has been developed, designed, and built by NASA Langley Research Center, to be flown on the space shuttle 'Discovery' on September 9, 1994. Lidar, which stands for light detecting and ranging, is a radar system that uses short pulses of laser light instead of radio waves in the case of the common radar. This space-based lidar offers atmospheric measurements of stratospheric and tropospheric aerosols, the planetary boundary layer, cloud top heights, and atmospheric temperature and density in the 10-40 km altitude range. A study is being done on the use, advantages, and limitations of a millimeterwave radar to be utilized in synergy with the Lidar system, for the LITE-2 experiment to be flown on a future space shuttle mission. The lower atmospheric attenuation, compared to infrared and optical frequencies, permits the millimeter-wave signals to penetrate through the clouds and measure multi-layered clouds, cloud thickness, and cloud-base height. These measurements would provide a useful input to radiation computations used in the operational numerical weather prediction models, and for forecasting. High power levels, optimum modulation, data processing, and high antenna gain are used to increase the operating range, while space environment, radar tradeoffs, and power availability are considered. Preliminary, numerical calculations are made, using the specifications of an experimental system constructed at Georgia Tech. The noncoherent 94 GHz millimeter-wave radar system has a pulsed output with peak value of 1 kW. The backscatter cross section of the particles to be measured, that are present in the volume covered by the beam footprint, is also studied.

MISR Stereo-heights of Grassland Fire Smoke Plumes in Australia

NASA Astrophysics Data System (ADS)

Mims, S. R.; Kahn, R. A.; Moroney, C. M.; Gaitley, B. J.; Nelson, D. L.; Garay, M. J.

2008-12-01

Plume heights from wildfires are used in climate modeling to predict and understand trends in aerosol transport. This study examines whether smoke from grassland fires in the desert region of Western and central Australia ever rises above the relatively stable atmospheric boundary layer and accumulates in higher layers of relative atmospheric stability. Several methods for deriving plume heights from the Multi-angle Imaging SpectroRadiometer (MISR) instrument are examined for fire events during the summer 2000 and 2002 burning seasons. Using MISR's multi-angle stereo-imagery from its three near-nadir-viewing cameras, an automatic algorithm routinely derives the stereo-heights above the geoid of the level-of-maximum-contrast for the entire global data set, which often correspond to the heights of clouds and aerosol plumes. Most of the fires that occur in the cases studied here are small, diffuse, and difficult to detect. To increase the signal from these thin hazes, the MISR enhanced stereo product that computes stereo heights from the most steeply viewing MISR cameras is used. For some cases, a third approach to retrieving plume heights from MISR stereo imaging observations, the MISR Interactive Explorer (MINX) tool, is employed to help differentiate between smoke and cloud. To provide context and to search for correlative factors, stereo-heights are combined with data providing fire strength from the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, atmospheric structure from the NCEP/NCAR Reanalysis Project, surface cover from the Australia National Vegetation Information System, and forward and backward trajectories from the NOAA HYSPLIT model. Although most smoke plumes concentrate in the near-surface boundary layer, as expected, some appear to rise higher. These findings suggest that a closer examination of grassland fire energetics may be warranted.

An Integrated Cloud-Aerosol-Radiation Product Using CERES, MODIS, CALIPSO and CloudSat Data

NASA Astrophysics Data System (ADS)

Sun-Mack, S.; Gibson, S.; Chen, Y.; Wielicki, B.; Minnis, P.

2006-12-01

The goal of this paper is to provide the first integrated data set of global vertical profiles of aerosols, clouds, and radiation using the combined NASA A-Train data from Aqua CERES and MODIS, CALIPSO, and CloudSat. All of these instruments are flying in formation as part of the Aqua Train, or A-Train. This paper will present the preliminary results of merging aerosol and cloud data from the CALIPSO active lidar, cloud data from CloudSat, integrated column aerosol and cloud data from the MODIS CERES analyses, and surface and top-of-atmosphere broadband radiation fluxes from CERES. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Nearly a Decade of CALIPSO Observations of Asian and Saharan Dust Properties Near Source and Transport Regions

NASA Technical Reports Server (NTRS)

Omar, Ali H.; Liu, Z.; Tackett, J.; Vaughan, M.; Trepte, C.; Winker, D.; H. Yu,

2015-01-01

The lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, makes robust measurements of dust and has generated a length of record that is significant both seasonally and inter-annually. We exploit this record to determine a multi-year climatology of the properties of Asian and Saharan dust, in particular seasonal optical depths, layer frequencies, and layer heights of dust gridded in accordance with the Level 3 data products protocol, between 2006-2015. The data are screened using standard CALIPSO quality assurance flags, cloud aerosol discrimination (CAD) scores, overlying features and layer properties. To evaluate the effects of transport on the morphology, vertical extent and size of the dust layers, we compare probability distribution functions of the layer integrated volume depolarization ratios, geometric depths and integrated attenuated color ratios near the source to the same distributions in the far field or transport region. CALIPSO is collaboration between NASA and Centre National D'études Spatiales (CNES), was launched in April 2006 to provide vertically resolved measurements of cloud and aerosol distributions. The primary instrument on the CALIPSO satellite is the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a near-nadir viewing two-wavelength polarization-sensitive instrument. The unique nature of CALIOP measurements make it quite challenging to validate backscatter profiles, aerosol type, and cloud phase, all of which are used to retrieve extinction and optical depth. To evaluate the uncertainty in the lidar ratios, we compare the values computed from dust layers overlying opaque water clouds, considered nominal, with the constant lidar ratio value used in the CALIOP algorithms for dust. We also explore the effects of noise on the CALIOP retrievals at daytime by comparing the distributions of the properties at daytime to the nighttime distributions.

Lidar Measurements of Ozone, Aerosols, and Clouds Observed in the Tropics Near Central America During TC4-Costa Rica

NASA Astrophysics Data System (ADS)

Hair, J. W.; Browell, E.; Butler, C.; Fenn, M.; Notari, A.; Simpson, S.; Ismail, S.; Avery, M.

2007-12-01

Large-scale measurements of ozone and aerosol distributions were made from the NASA DC-8 aircraft during the TC4 (Tropical Composition, Cloud, and Climate Coupling) field experiment conducted from June 28 - August 10, 2007 based in San Jose, Costa Rica. Remote measurements were made with an airborne lidar to provide ozone and multiple-wavelength aerosol and cloud backscatter profiles from near the surface to above the tropopause along the flight track. Aerosol depolarization measurements were also made for the detection of nonspherical aerosols, such as mineral dust, biomass burning, and recent emissions from South American volcanoes. Long-range transport of Saharan dust with depolarizing aerosols was frequently observed in the lower troposphere both over the Caribbean Sea and Pacific Ocean and within the marine boundary layer. In addition, visible and sub-visible cirrus clouds were observed with the multi-wavelength backscatter and depolarization measurements. Initial distributions of ozone, aerosol, and cloud are presented which will be used to interpret large-scale atmospheric processes. In situ measurements of ozone and aerosols made onboard the DC-8 will be compared to the remote lidar measurements. This paper provides a first look at the characteristics of ozone, aerosol, and cloud distributions that were encountered during this field experiment and provide a unique dataset that will be further related through satellite data, backward trajectories, and chemical transport models (CTM) to sources and sinks of ozone, aerosols, and clouds and to dynamical, chemical, and radiative processes.

Automatic Cloud Detection from Multi-Temporal Satellite Images: Towards the Use of PLÉIADES Time Series

NASA Astrophysics Data System (ADS)

Champion, N.

2012-08-01

Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images) and is based on a region-growing procedure. Seeds (corresponding to clouds) are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images). Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011). In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Four-dimensional distribution of the 2010 Eyjafjallajökull volcanic cloud over Europe observed by EARLINET

NASA Astrophysics Data System (ADS)

Pappalardo, G.; Mona, L.; D'Amico, G.; Wandinger, U.; Adam, M.; Amodeo, A.; Ansmann, A.; Apituley, A.; Alados Arboledas, L.; Balis, D.; Boselli, A.; Bravo-Aranda, J. A.; Chaikovsky, A.; Comeron, A.; Cuesta, J.; De Tomasi, F.; Freudenthaler, V.; Gausa, M.; Giannakaki, E.; Giehl, H.; Giunta, A.; Grigorov, I.; Groß, S.; Haeffelin, M.; Hiebsch, A.; Iarlori, M.; Lange, D.; Linné, H.; Madonna, F.; Mattis, I.; Mamouri, R.-E.; McAuliffe, M. A. P.; Mitev, V.; Molero, F.; Navas-Guzman, F.; Nicolae, D.; Papayannis, A.; Perrone, M. R.; Pietras, C.; Pietruczuk, A.; Pisani, G.; Preißler, J.; Pujadas, M.; Rizi, V.; Ruth, A. A.; Schmidt, J.; Schnell, F.; Seifert, P.; Serikov, I.; Sicard, M.; Simeonov, V.; Spinelli, N.; Stebel, K.; Tesche, M.; Trickl, T.; Wang, X.; Wagner, F.; Wiegner, M.; Wilson, K. M.

2013-04-01

The eruption of the Icelandic volcano Eyjafjallajökull in April-May 2010 represents a "natural experiment" to study the impact of volcanic emissions on a continental scale. For the first time, quantitative data about the presence, altitude, and layering of the volcanic cloud, in conjunction with optical information, are available for most parts of Europe derived from the observations by the European Aerosol Research Lidar NETwork (EARLINET). Based on multi-wavelength Raman lidar systems, EARLINET is the only instrument worldwide that is able to provide dense time series of high-quality optical data to be used for aerosol typing and for the retrieval of particle microphysical properties as a function of altitude. In this work we show the four-dimensional (4-D) distribution of the Eyjafjallajökull volcanic cloud in the troposphere over Europe as observed by EARLINET during the entire volcanic event (15 April-26 May 2010). All optical properties directly measured (backscatter, extinction, and particle linear depolarization ratio) are stored in the EARLINET database available at http://www.earlinet.org. A specific relational database providing the volcanic mask over Europe, realized ad hoc for this specific event, has been developed and is available on request at http://www.earlinet.org. During the first days after the eruption, volcanic particles were detected over Central Europe within a wide range of altitudes, from the upper troposphere down to the local planetary boundary layer (PBL). After 19 April 2010, volcanic particles were detected over southern and south-eastern Europe. During the first half of May (5-15 May), material emitted by the Eyjafjallajökull volcano was detected over Spain and Portugal and then over the Mediterranean and the Balkans. The last observations of the event were recorded until 25 May in Central Europe and in the Eastern Mediterranean area. The 4-D distribution of volcanic aerosol layering and optical properties on European scale reported here provides an unprecedented data set for evaluating satellite data and aerosol dispersion models for this kind of volcanic events.

Invisible Cirrus Clouds

NASA Technical Reports Server (NTRS)

2002-01-01

The Moderate-resolution Imaging Spectroradiometer's (MODIS') cloud detection capability is so sensitive that it can detect clouds that would be indistinguishable to the human eye. This pair of images highlights MODIS' ability to detect what scientists call 'sub-visible cirrus.' The image on top shows the scene using data collected in the visible part of the electromagnetic spectrum-the part our eyes can see. Clouds are apparent in the center and lower right of the image, while the rest of the image appears to be relatively clear. However, data collected at 1.38um (lower image) show that a thick layer of previously undetected cirrus clouds obscures the entire scene. These kinds of cirrus are called 'sub-visible' because they can't be detected using only visible light. MODIS' 1.38um channel detects electromagnetic radiation in the infrared region of the spectrum. These images were made from data collected on April 4, 2000. Image courtesy Mark Gray, MODIS Atmosphere Team

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.

RACORO continental boundary layer cloud investigations. 2. Large-eddy simulations of cumulus clouds and evaluation with in-situ and ground-based observations

DOE PAGES

Endo, Satoshi; Fridlind, Ann M.; Lin, Wuyin; ...

2015-06-19

A 60-hour case study of continental boundary layer cumulus clouds is examined using two large-eddy simulation (LES) models. The case is based on observations obtained 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 site. The LES models are driven by continuous large-scale and surface forcings, and are constrained by multi-modal and temporally varying aerosol number size distribution profiles derived from aircraft observations. We compare simulated cloud macrophysical and microphysical properties with ground-based remote sensing and aircraft observations.more » The LES simulations capture the observed transitions of the evolving cumulus-topped boundary layers during the three daytime periods, and generally reproduce variations of droplet number concentration with liquid water content (LWC), corresponding to the gradient between the cloud centers and cloud edges at given heights. The observed LWC values fall within the range of simulated values; the observed droplet number concentrations are commonly higher than simulated, but differences remain on par with potential estimation errors in the aircraft measurements. Sensitivity studies examine the influences of bin microphysics versus bulk microphysics, aerosol advection, supersaturation treatment, and aerosol hygroscopicity. Simulated macrophysical cloud properties are found to be insensitive in this non-precipitating case, but microphysical properties are especially sensitive to bulk microphysics supersaturation treatment and aerosol hygroscopicity.« less

Snow precipitation on Mars driven by cloud-induced night-time convection

NASA Astrophysics Data System (ADS)

Spiga, Aymeric; Hinson, David P.; Madeleine, Jean-Baptiste; Navarro, Thomas; Millour, Ehouarn; Forget, François; Montmessin, Franck

2017-09-01

Although it contains less water vapour than Earth's atmosphere, the Martian atmosphere hosts clouds. These clouds, composed of water-ice particles, influence the global transport of water vapour and the seasonal variations of ice deposits. However, the influence of water-ice clouds on local weather is unclear: it is thought that Martian clouds are devoid of moist convective motions, and snow precipitation occurs only by the slow sedimentation of individual particles. Here we present numerical simulations of the meteorology in Martian cloudy regions that demonstrate that localized convective snowstorms can occur on Mars. We show that such snowstorms--or ice microbursts--can explain deep night-time mixing layers detected from orbit and precipitation signatures detected below water-ice clouds by the Phoenix lander. In our simulations, convective snowstorms occur only during the Martian night, and result from atmospheric instability due to radiative cooling of water-ice cloud particles. This triggers strong convective plumes within and below clouds, with fast snow precipitation resulting from the vigorous descending currents. Night-time convection in Martian water-ice clouds and the associated snow precipitation lead to transport of water both above and below the mixing layers, and thus would affect Mars' water cycle past and present, especially under the high-obliquity conditions associated with a more intense water cycle.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Overview of MPLNET Version 3 Cloud Detection

NASA Technical Reports Server (NTRS)

Lewis, Jasper R.; Campbell, James; Welton, Ellsworth J.; Stewart, Sebastian A.; Haftings, Phillip

2016-01-01

The National Aeronautics and Space Administration Micro Pulse Lidar Network, version 3, cloud detection algorithm is described and differences relative to the previous version are highlighted. Clouds are identified from normalized level 1 signal profiles using two complementary methods. The first method considers vertical signal derivatives for detecting low-level clouds. The second method, which detects high-level clouds like cirrus, is based on signal uncertainties necessitated by the relatively low signal-to-noise ratio exhibited in the upper troposphere by eye-safe network instruments, especially during daytime. Furthermore, a multitemporal averaging scheme is used to improve cloud detection under conditions of a weak signal-to-noise ratio. Diurnal and seasonal cycles of cloud occurrence frequency based on one year of measurements at the Goddard Space Flight Center (Greenbelt, Maryland) site are compared for the new and previous versions. The largest differences, and perceived improvement, in detection occurs for high clouds (above 5 km, above MSL), which increase in occurrence by over 5%. There is also an increase in the detection of multilayered cloud profiles from 9% to 19%. Macrophysical properties and estimates of cloud optical depth are presented for a transparent cirrus dataset. However, the limit to which the cirrus cloud optical depth could be reliably estimated occurs between 0.5 and 0.8. A comparison using collocated CALIPSO measurements at the Goddard Space Flight Center and Singapore Micro Pulse Lidar Network (MPLNET) sites indicates improvements in cloud occurrence frequencies and layer heights.

Detecting Distributed SQL Injection Attacks in a Eucalyptus Cloud Environment

NASA Technical Reports Server (NTRS)

Kebert, Alan; Barnejee, Bikramjit; Solano, Juan; Solano, Wanda

2013-01-01

The cloud computing environment offers malicious users the ability to spawn multiple instances of cloud nodes that are similar to virtual machines, except that they can have separate external IP addresses. In this paper we demonstrate how this ability can be exploited by an attacker to distribute his/her attack, in particular SQL injection attacks, in such a way that an intrusion detection system (IDS) could fail to identify this attack. To demonstrate this, we set up a small private cloud, established a vulnerable website in one instance, and placed an IDS within the cloud to monitor the network traffic. We found that an attacker could quite easily defeat the IDS by periodically altering its IP address. To detect such an attacker, we propose to use multi-agent plan recognition, where the multiple source IPs are considered as different agents who are mounting a collaborative attack. We show that such a formulation of this problem yields a more sophisticated approach to detecting SQL injection attacks within a cloud computing environment.

A Lidar Point Cloud Based Procedure for Vertical Canopy Structure Analysis And 3D Single Tree Modelling in Forest

PubMed Central

Wang, Yunsheng; Weinacker, Holger; Koch, Barbara

2008-01-01

A procedure for both vertical canopy structure analysis and 3D single tree modelling based on Lidar point cloud is presented in this paper. The whole area of research is segmented into small study cells by a raster net. For each cell, a normalized point cloud whose point heights represent the absolute heights of the ground objects is generated from the original Lidar raw point cloud. The main tree canopy layers and the height ranges of the layers are detected according to a statistical analysis of the height distribution probability of the normalized raw points. For the 3D modelling of individual trees, individual trees are detected and delineated not only from the top canopy layer but also from the sub canopy layer. The normalized points are resampled into a local voxel space. A series of horizontal 2D projection images at the different height levels are then generated respect to the voxel space. Tree crown regions are detected from the projection images. Individual trees are then extracted by means of a pre-order forest traversal process through all the tree crown regions at the different height levels. Finally, 3D tree crown models of the extracted individual trees are reconstructed. With further analyses on the 3D models of individual tree crowns, important parameters such as crown height range, crown volume and crown contours at the different height levels can be derived. PMID:27879916

Exploiting Cloud Radar Doppler Spectra of Mixed-Phase Clouds during ACCEPT Field Experiment to Identify Microphysical Processes

NASA Astrophysics Data System (ADS)

Kalesse, H.; Myagkov, A.; Seifert, P.; Buehl, J.

2015-12-01

Cloud radar Doppler spectra offer much information about cloud processes. By analyzing millimeter radar Doppler spectra from cloud-top to -base in mixed-phase clouds in which super-cooled liquid-layers are present we try to tell the microphysical evolution story of particles that are present by disentangling the contributions of the solid and liquid particles to the total radar returns. Instead of considering vertical profiles, dynamical effects are taken into account by following the particle population evolution along slanted paths which are caused by horizontal advection of the cloud. The goal is to identify regions in which different microphysical processes such as new particle formation (nucleation), water vapor deposition, aggregation, riming, or sublimation occurr. Cloud radar measurements are supplemented by Doppler lidar and Raman lidar observations as well as observations with MWR, wind profiler, and radio sondes. The presence of super-cooled liquid layers is identified by positive liquid water paths in MWR measurements, the vertical location of liquid layers (in non-raining systems and below lidar extinction) is derived from regions of high-backscatter and low depolarization in Raman lidar observations. In collocated cloud radar measurements, we try to identify cloud phase in the cloud radar Doppler spectrum via location of the Doppler peak(s), the existence of multi-modalities or the spectral skewness. Additionally, within the super-cooled liquid layers, the radar-identified liquid droplets are used as air motion tracer to correct the radar Doppler spectrum for vertical air motion w. These radar-derived estimates of w are validated by independent estimates of w from collocated Doppler lidar measurements. A 35 GHz vertically pointing cloud Doppler radar (METEK MIRA-35) in linear depolarization (LDR) mode is used. Data is from the deployment of the Leipzig Aerosol and Cloud Remote Observations System (LACROS) during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) field experiment in Cabauw, Netherlands in Fall 2014. There, another MIRA-35 was operated in simultaneous transmission and simultaneous reception (STSR) mode for obtaining measurements of differential reflectivity (ZDR) and correlation coefficient ρhv.

Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

NASA Technical Reports Server (NTRS)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny

2015-01-01

To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

Application of Polypyrrole Multi-Walled Carbon Nanotube Composite Layer for Detection of Mercury, Lead and Iron Ions Using Surface Plasmon Resonance Technique

PubMed Central

Sadrolhosseini, Amir Reza; Noor, A. S. M.; Bahrami, Afarin; Lim, H. N.; Talib, Zainal Abidin; Mahdi, Mohd. Adzir

2014-01-01

Polypyrrole multi-walled carbon nanotube composite layers were used to modify the gold layer to measure heavy metal ions using the surface plasmon resonance technique. The new sensor was fabricated to detect trace amounts of mercury (Hg), lead (Pb), and iron (Fe) ions. In the present research, the sensitivity of a polypyrrole multi-walled carbon nanotube composite layer and a polypyrrole layer were compared. The application of polypyrrole multi-walled carbon nanotubes enhanced the sensitivity and accuracy of the sensor for detecting ions in an aqueous solution due to the binding of mercury, lead, and iron ions to the sensing layer. The Hg ion bonded to the sensing layer more strongly than did the Pb and Fe ions. The limitation of the sensor was calculated to be about 0.1 ppm, which produced an angle shift in the region of 0.3° to 0.6°. PMID:24733263

Probability Density Functions for the CALIPSO Lidar Version 4 Cloud-Aerosol Discrimination (CAD) Algorithm

NASA Astrophysics Data System (ADS)

Liu, Z.; Kar, J.; Zeng, S.; Tackett, J. L.; Vaughan, M.; Trepte, C. R.; Omar, A. H.; Hu, Y.; Winker, D. M.

2017-12-01

In the CALIPSO retrieval algorithm, detection layers in the lidar measurements is followed by their classification as a "cloud" or "aerosol" using 5-dimensional probability density functions (PDFs). The five dimensions are the mean attenuated backscatter at 532 nm, the layer integrated total attenuated color ratio, the mid-layer altitude, integrated volume depolarization ratio and latitude. The new version 4 (V4) level 2 (L2) data products, released in November 2016, are the first major revision to the L2 product suite since May 2010. Significant calibration changes in the V4 level 1 data necessitated substantial revisions to the V4 L2 CAD algorithm. Accordingly, a new set of PDFs was generated to derive the V4 L2 data products. The V4 CAD algorithm is now applied to layers detected in the stratosphere, where volcanic layers and occasional cloud and smoke layers are observed. Previously, these layers were designated as `stratospheric', and not further classified. The V4 CAD algorithm is also applied to all layers detected at single shot (333 m) resolution. In prior data releases, single shot detections were uniformly classified as clouds. The CAD PDFs used in the earlier releases were generated using a full year (2008) of CALIPSO measurements. Because the CAD algorithm was not applied to stratospheric features, the properties of these layers were not incorporated into the PDFs. When building the V4 PDFs, the 2008 data were augmented with additional data from June 2011, and all stratospheric features were included. The Nabro and Puyehue-Cordon volcanos erupted in June 2011, and volcanic aerosol layers were observed in the upper troposphere and lower stratosphere in both the northern and southern hemispheres. The June 2011 data thus provides the stratospheric aerosol properties needed for comprehensive PDF generation. In contrast to earlier versions of the PDFs, which were generated based solely on observed distributions, construction of the V4 PDFs considered the typical optical and physical properties of feature subtypes, and thus provide a more comprehensive physical basis for discrimination. As a result of the changes made, the V4 CAD provides better performance and more reliable confidence levels. We describe the generation of V4 PDFs and present characterization and performance of the new CAD algorithm.

SGP and TWP (Manus) Ice Cloud Vertical Velocities

DOE Data Explorer

Kalesse, Heike

2013-06-27

Daily netcdf-files of ice-cloud dynamics observed at the ARM sites at SGP (Jan1997-Dec2010) and Manus (Jul1999-Dec2010). The files include variables at different time resolution (10s, 20min, 1hr). Profiles of radar reflectivity factor (dbz), Doppler velocity (vel) as well as retrieved vertical air motion (V_air) and reflectivity-weighted particle terminal fall velocity (V_ter) are given at 10s, 20min and 1hr resolution. Retrieved V_air and V_ter follow radar notation, so positive values indicate downward motion. Lower level clouds are removed, however a multi-layer flag is included.

Sound field measurement in a double layer cavitation cluster by rugged miniature needle hydrophones.

PubMed

Koch, Christian

2016-03-01

During multi-bubble cavitation the bubbles tend to organize themselves into clusters and thus the understanding of properties and dynamics of clustering is essential for controlling technical applications of cavitation. Sound field measurements are a potential technique to provide valuable experimental information about the status of cavitation clouds. Using purpose-made, rugged, wide band, and small-sized needle hydrophones, sound field measurements in bubble clusters were performed and time-dependent sound pressure waveforms were acquired and analyzed in the frequency domain up to 20 MHz. The cavitation clusters were synchronously observed by an electron multiplying charge-coupled device (EMCCD) camera and the relation between the sound field measurements and cluster behaviour was investigated. Depending on the driving power, three ranges could be identified and characteristic properties were assigned. At low power settings no transient and no or very low stable cavitation activity can be observed. The medium range is characterized by strong pressure peaks and various bubble cluster forms. At high power a stable double layer was observed which grew with further increasing power and became quite dynamic. The sound field was irregular and the fundamental at driving frequency decreased. Between the bubble clouds completely different sound field properties were found in comparison to those in the cloud where the cavitation activity is high. In between the sound field pressure amplitude was quite small and no collapses were detected. Copyright © 2015. Published by Elsevier B.V.

RACORO continental boundary layer cloud investigations. Part I: Case study development and ensemble large-scale forcings

DOE PAGES

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; ...

2015-06-19

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60-hour case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in-situ measurements from the RACORO field campaign and remote-sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functionsmore » for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be ~0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing datasets are derived from the ARM variational analysis, ECMWF forecasts, and a multi-scale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in 'trial' large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.« less

An Evaluation of Northern Hemisphere Merged Cloud Analyses from the United States Air Force Cloud Depiction Forecasting System II

DTIC Science & Technology

2013-03-01

layering and typing to provide a vertical stratification of the cloud-filled pixels detected in Level 2. Level 3 output is remapped to the standard AFWA...analyses are compared to one another to see if the most recent analysis also has the lowest estimated error. Optimum interpolation (OI) occurs when...NORTHERN HEMISPHERE MERGED CLOUD ANALYSES FROM THE UNITED STATES AIR FORCE CLOUD DEPICTION FORECASTING SYSTEM II by Chandra M. Pasillas March

Development of Multi-Field of view-Multiple-Scattering-Polarization Lidar ： analysis of angular resolved backscattered signals

NASA Astrophysics Data System (ADS)

Makino, T.; Okamoto, H.; Sato, K.; Tanaka, K.; Nishizawa, T.; Sugimoto, N.; Matsui, I.; Jin, Y.; Uchiyama, A.; Kudo, R.

2014-12-01

We have developed a new type of ground-based lidar, Multi-Field of view-Multiple-Scattering-Polarization Lidar (MFMSPL), to analyze multiple scattering contribution due to low-level clouds. One issue of the ground based lidar is the limitation of optical thickness of about 3 due to the strong attenuation in the lidar signals so that only the cloud bottom part can be observed. In order to overcome the problem, we have proposed the MFMSPL that has been designed to observe similar degree of multiple scattering contribution expected from space-borne lidar CALIOP on CALIPSO satellite. The system consists of eight detectors; four telescopes for parallel channels and four for perpendicular channels. The four pairs of telescope have been mounted with four different off-beam angles, ranging from -5 to 35mrad, where the angle is defined as the one between the direction of laser beam and the direction of telescope. Consequently, similar large foot print (100m) as CALIOP can be achieved in the MFMSPL observations when the altitude of clouds is located at about 1km. The use of multi-field of views enables to measure depolarization ratio from optically thick clouds. The outer receivers attached with larger angles generally detect backscattered signals from clouds located at upper altitudes due to the enhanced multiple scattering compared with the inner receiver that detects signals only from cloud bottom portions. Therefore the information of cloud microphysics from optically thicker regions is expected by the MFMSPL observations compared with the conventional lidar with small FOV. The MFMSPL have been continuously operated in Tsukuba, Japan since June 2014.Initial analyses have indicated expected performances from the theoretical estimation by backward Monte-Carlo simulations. The depolarization ratio from deeper part of the clouds detected by the receiver with large off-beam angle showed much larger values than those from the one with small angle. The calibration procedures and summary of initial observations will be presented. The observed data obtained by the MFMSPL will be used to develop and evaluate the retrieval algorithms for cloud microphysics applied to the CALIOP data.

3D Cloud Tomography, Followed by Mean Optical and Microphysical Properties, with Multi-Angle/Multi-Pixel Data

NASA Astrophysics Data System (ADS)

Davis, A. B.; von Allmen, P. A.; Marshak, A.; Bal, G.

2010-12-01

The geometrical assumption in all operational cloud remote sensing algorithms is that clouds are plane-parallel slabs, which applies relatively well to the most uniform stratus layers. Its benefit is to justify using classic 1D radiative transfer (RT) theory, where angular details (solar, viewing, azimuthal) are fully accounted for and precise phase functions can be used, to generate the look-up tables used in the retrievals. Unsurprisingly, these algorithms catastrophically fail when applied to cumulus-type clouds, which are highly 3D. This is unfortunate for the cloud-process modeling community that may thrive on in situ airborne data, but would very much like to use satellite data for more than illustrations in their presentations and publications. So, how can we obtain quantitative information from space-based observations of finite aspect ratio clouds? Cloud base/top heights, vertically projected area, mean liquid water content (LWC), and volume-averaged droplet size would be a good start. Motivated by this science need, we present a new approach suitable for sparse cumulus fields where we turn the tables on the standard procedure in cloud remote sensing. We make no a priori assumption about cloud shape, save an approximately flat base, but use brutal approximations about the RT that is necessarily 3D. Indeed, the first order of business is to roughly determine the cloud's outer shape in one of two ways, which we will frame as competing initial guesses for the next phase of shape refinement and volume-averaged microphysical parameter estimation. Both steps use multi-pixel/multi-angle techniques amenable to MISR data, the latter adding a bi-spectral dimension using collocated MODIS data. One approach to rough cloud shape determination is to fit the multi-pixel/multi-angle data with a geometric primitive such as a scalene hemi-ellipsoid with 7 parameters (translation in 3D space, 3 semi-axes, 1 azimuthal orientation); for the radiometry, a simple radiosity-type model is used where the cloud surface "emits" either reflected (sunny-side) or transmitted (shady-side) light at different levels. As it turns out, the reflected/transmitted light ratio yields an approximate cloud optical thickness. Another approach is to invoke tomography techniques to define the volume occupied by the cloud using, as it were, cloud masks for each direction of observation. In the shape and opacity refinement phase, initial guesses along with solar and viewing geometry information are used to predict radiance in each pixel using a fast diffusion model for the 3D RT in MISR's non-absorbing red channel (275 m resolution). Refinement is constrained and stopped when optimal resolution is reached. Finally, multi-pixel/mono-angle MODIS data for the same cloud (at comparable 250 m resolution) reveals the desired droplet size information, hence the volume-averaged LWC. This is an ambitious remote sensing science project drawing on cross-disciplinary expertise gained in medical imaging using both X-ray and near-IR sources and detectors. It is high risk but with potentially high returns not only for the cloud modeling community but also aerosol and surface characterization in the presence of broken 3D clouds.

multi-dimensional Cloud-aERosol Exploratory Study using RPAS (mCERES): Bottom-up and top-down closure of aerosol-cloud interactions

NASA Astrophysics Data System (ADS)

Roberts, Greg; Calmer, Radiance; Sanchez, Kevin; Cayez, Grégoire; Nicoll, Kerianne; Hashimshoni, Eyal; Rosenfeld, Daniel; Ansmann, Albert; Sciare, Jean; Ovadneite, Jurgita; Bronz, Murat; Hattenberger, Gautier; Preissler, Jana; Buehl, Johannes; Ceburnis, Darius; O'Dowd, Colin

2016-04-01

Clouds are omnipresent in earth's atmosphere and constitute an important role in regulating the radiative budget of the planet. However, the response of clouds to climate change remains uncertain, in particular, with respect to aerosol-cloud interactions and feedback mechanisms between the biosphere and atmosphere. Aerosol-cloud interactions and their feedbacks are the main themes of the European project FP7 BACCHUS (Impact of Biogenic versus Anthropogenic Emissions on Clouds and Climate: towards a Holistic Understanding). The National Center for Meteorological Research (CNRM-GAME, Toulouse, France) conducted airborne experiments in Cyprus and Ireland in March and August 2015 respectively to link ground-based and satellite observations. Multiple RPAS (remotely piloted aircraft systems) were instrumented for a specific scientific focus to characterize the vertical distribution of aerosol, cloud microphysical properties, radiative fluxes, 3D wind vectors and meteorological state parameters. Flights below and within clouds were coordinated with satellite overpasses to perform 'top-down' closure of cloud micro-physical properties. Measurements of cloud condensation nuclei spectra at the ground-based site have been used to determine cloud microphyical properties using wind vectors and meteorological parameters measured by the RPAS at cloud base. These derived cloud properties have been validated by in-situ RPAS measurements in the cloud and compared to those derived by the Suomi-NPP satellite. In addition, RPAS profiles in Cyprus observed the layers of dust originating from the Arabian Peninsula and the Sahara Desert. These profiles generally show a well-mixed boundary layer and compare well with ground-based LIDAR observations.

Properties of CIRRUS Overlapping Clouds as Deduced from the GOES-12 Imagery Data

NASA Technical Reports Server (NTRS)

Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny; Khaiyer, Mandana

2006-01-01

Understanding the impact of cirrus clouds on modifying both the solar reflected and terrestrial emitted radiations is crucial for climate studies. Unlike most boundary layer stratus and stratocumulus clouds that have a net cooling effect on the climate, high-level thin cirrus clouds can have a warming effect on our climate. Many research efforts have been devoted to retrieving cirrus cloud properties due to their ubiquitous presence. However, using satellite observations to detect and/or retrieve cirrus cloud properties faces two major challenges. First, they are often semitransparent at visible to infrared wavelengths; and secondly, they often occur over a lower cloud system. The overlapping of high-level cirrus and low-level stratus cloud poses a difficulty in determining the individual cloud top altitudes and optical properties, especially when the signals from cirrus clouds are overwhelmed by the signals of stratus clouds. Moreover, the operational satellite retrieval algorithms, which often assume only single layer cloud in the development of cloud retrieval techniques, cannot resolve the cloud overlapping situation properly. The new geostationary satellites, starting with the Twelfth Geostationary Operational Environmental Satellite (GOES-12), are providing a new suite of imager bands that have replaced the conventional 12-micron channel with a 13.3-micron CO2 absorption channel. The replacement of the 13.3-micron channel allows for the application of a CO2-slicing retrieval technique (Chahine et al. 1974; Smith and Platt 1978), which is one of the important passive satellite methods for remote sensing the altitudes of mid to high-level clouds. Using the CO2- slicing technique is more effective in detecting semitransparent cirrus clouds than using the conventional infrared-window method.

Architecture Design of Healthcare Software-as-a-Service Platform for Cloud-Based Clinical Decision Support Service.

PubMed

Oh, Sungyoung; Cha, Jieun; Ji, Myungkyu; Kang, Hyekyung; Kim, Seok; Heo, Eunyoung; Han, Jong Soo; Kang, Hyunggoo; Chae, Hoseok; Hwang, Hee; Yoo, Sooyoung

2015-04-01

To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft's Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) was used. The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. We expect that cloud-based HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs.

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

Impact of Resolution on Simulation of Closed Mesoscale Cellular Convection Identified by Dynamically Guided Watershed Segmentation

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

Martini, Matus N.; Gustafson, William I.; Yang, Qing

2014-11-18

Organized mesoscale cellular convection (MCC) is a common feature of marine stratocumulus that forms in response to a balance between mesoscale dynamics and smaller scale processes such as cloud radiative cooling and microphysics. We use the Weather Research and Forecasting model with chemistry (WRF-Chem) and fully coupled cloud-aerosol interactions to simulate marine low clouds during the VOCALS-REx campaign over the southeast Pacific. A suite of experiments with 3- and 9-km grid spacing indicates resolution-dependent behavior. The simulations with finer grid spacing have smaller liquid water paths and cloud fractions, while cloud tops are higher. The observed diurnal cycle is reasonablymore » well simulated. To isolate organized MCC characteristics we develop a new automated method, which uses a variation of the watershed segmentation technique that combines the detection of cloud boundaries with a test for coincident vertical velocity characteristics. This ensures that the detected cloud fields are dynamically consistent for closed MCC, the most common MCC type over the VOCALS-REx region. We demonstrate that the 3-km simulation is able to reproduce the scaling between horizontal cell size and boundary layer height seen in satellite observations. However, the 9-km simulation is unable to resolve smaller circulations corresponding to shallower boundary layers, instead producing invariant MCC horizontal scale for all simulated boundary layers depths. The results imply that climate models with grid spacing of roughly 3 km or smaller may be needed to properly simulate the MCC structure in the marine stratocumulus regions.« less

CATS Cloud and Aerosol Level 2 Heritage Edition Data Products.

NASA Astrophysics Data System (ADS)

Rodier, S. D.; Vaughan, M.; Yorks, J. E.; Palm, S. P.; Selmer, P. A.; Hlavka, D. L.; McGill, M. J.; Trepte, C. R.

2017-12-01

The Cloud-Aerosol Transport System (CATS) instrument was developed at NASA's Goddard Space Flight Center (GSFC) and deployed to the International Space Station (ISS) in January 2015. The CATS elastic backscatter lidars have been operating continuously in one of two science modes since February 2015. One of the primary science objectives of CATS is to continue the CALIPSO aerosol and cloud profile data record to provide continuity of lidar climate observations during the transition from CALIPSO to EarthCARE. To accomplish this, the CATS project at NASA's Goddard Space Flight Center (GSFC) and the CALIPSO project at NASA's Langley Research Center (LaRC) closely collaborated to develop and deliver a full suite of CALIPSO-like level 2 data products using the latest version of the CALIPSO level 2 Version 4 algorithms for the CATS data acquired while operating in science mode 1 (Multi-beam backscatter detection at 1064 and 532 nm, with depolarization measurement at both wavelengths). In this work, we present the current status of the CATS Heritage (i.e. CALIPSO-like) level 2 data products derived from the recent released CATS Level 1B V2-08 data. Extensive comparisons are performed between the three data sets (CALIPSO V4.10 Level 2, CATS Level 2 Operational V2-00 and CATS Heritage V1.00) for cloud and aerosol measurements (e.g., cloud-top height cloud-phase, cloud-layer occurrence frequency and cloud-aerosol discrimination) along the ISS path. In addition, global comparisons (between 52°S and 52°N) of aerosol extinction profiles derived from the CATS Level 2 Operational products and CALIOP V4 Level 2 products are presented. Comparisons of aerosol optical depths retrieved from active sensors (CATS and CALIOP) and passive sensors (MODIS) will provide context for the extinction profile comparisons.

Aerosol and cloud sensing with the Lidar In-space Technology Experiment (LITE)

NASA Technical Reports Server (NTRS)

Winker, D. M.; McCormick, M. P.

1994-01-01

The Lidar In-space Technology Experiment (LITE) is a multi-wavelength backscatter lidar developed by NASA Langley Research Center to fly on the Space Shuttle. The LITE instrument is built around a three-wavelength ND:YAG laser and a 1-meter diameter telescope. The laser operates at 10 Hz and produces about 500 mJ per pulse at 1064 nm and 532 nm, and 150 mJ per pulse at 355 nm. The objective of the LITE program is to develop the engineering processes required for space lidar and to demonstrate applications of space-based lidar to remote sensing of the atmosphere. The LITE instrument was designed to study a wide range of cloud and aerosol phenomena. To this end, a comprehensive program of scientific investigations has been planned for the upcoming mission. Simulations of on-orbit performance show the instrument has sufficient sensitivity to detect even thin cirrus on a single-shot basis. Signal averaging provides the capability of measuring the height and structure of the planetary boundary layer, aerosols in the free troposphere, the stratospheric aerosol layer, and density profiles to an altitude of 40 km. The instrument has successfully completed a ground-test phase and is scheduled to fly on the Space Shuttle Discovery for a 9-day mission in September 1994.

Remote sensing of low visibility over otopeni airport

NASA Astrophysics Data System (ADS)

Buzdugan, Livius; Urlea, Denisa; Bugeac, Paul; Stefan, Sabina

2018-04-01

The paper is focused on the study of atmospheric conditions determining low vertical visibility over Henri Coanda airport. A network of ceilometers and a Sodar were used to detect fog and low level cloud layers. In our study, vertical visibility from ceilometers and acoustic reflectivity from Sodar for November 2016 were used to estimate fog depth and top of fog layers, respectively. The correlation between fog and low cloud occurrence and the wind direction and speed is also investigated.

An integrated multi-sensors approach for volcanic cloud retrievals and source characterization

NASA Astrophysics Data System (ADS)

Corradini, Stefano; Merucci, Luca

2017-04-01

Volcanic eruptions are one the most important sources of natural pollution. In particular the volcanic clouds represent a severe threat for aviation safety. Worldwide the volcanic activity is monitored by using satellite and ground-based instruments working at different spectral ranges, with different spatial resolutions and sensitivities. Here the complementarity between geostationary and polar satellites and ground based measurements is exploited, in order to significantly improve the volcanic cloud detection and retrievals and to fully characterize the eruption source. The integration procedure named MACE (Multi-platform volcanic Ash Cloud Estimation), has been developed during the EU-FP7 APhoRISM project aimed to develop innovative products to support the management and mitigation of the volcanic and the seismic crisis. The proposed method integrates in a novel manner the volcanic ash retrievals at the space-time scale of typical geostationary observations using both the polar satellite estimations and in-situ measurements. On MACE the typical volcanic cloud retrievals in the thermal infrared are integrated by using a wider spectral range from visible to microwave. Moreover the volcanic cloud detection is extended in case of cloudy atmosphere or steam plumes. As example, the integrated approach is tested on different recent eruptions, occurred on Etna (Italy) in 2013 and 2015 and on Calbuco (Chile) in 2015.

Detecting Inspection Objects of Power Line from Cable Inspection Robot LiDAR Data.

PubMed

Qin, Xinyan; Wu, Gongping; Lei, Jin; Fan, Fei; Ye, Xuhui

2018-04-22

Power lines are extending to complex environments (e.g., lakes and forests), and the distribution of power lines in a tower is becoming complicated (e.g., multi-loop and multi-bundle). Additionally, power line inspection is becoming heavier and more difficult. Advanced LiDAR technology is increasingly being used to solve these difficulties. Based on precise cable inspection robot (CIR) LiDAR data and the distinctive position and orientation system (POS) data, we propose a novel methodology to detect inspection objects surrounding power lines. The proposed method mainly includes four steps: firstly, the original point cloud is divided into single-span data as a processing unit; secondly, the optimal elevation threshold is constructed to remove ground points without the existing filtering algorithm, improving data processing efficiency and extraction accuracy; thirdly, a single power line and its surrounding data can be respectively extracted by a structured partition based on a POS data (SPPD) algorithm from "layer" to "block" according to power line distribution; finally, a partition recognition method is proposed based on the distribution characteristics of inspection objects, highlighting the feature information and improving the recognition effect. The local neighborhood statistics and the 3D region growing method are used to recognize different inspection objects surrounding power lines in a partition. Three datasets were collected by two CIR LIDAR systems in our study. The experimental results demonstrate that an average 90.6% accuracy and average 98.2% precision at the point cloud level can be achieved. The successful extraction indicates that the proposed method is feasible and promising. Our study can be used to obtain precise dimensions of fittings for modeling, as well as automatic detection and location of security risks, so as to improve the intelligence level of power line inspection.

Reconstruction of 3D Shapes of Opaque Cumulus Clouds from Airborne Multiangle Imaging: A Proof-of-Concept

NASA Astrophysics Data System (ADS)

Davis, A. B.; Bal, G.; Chen, J.

2015-12-01

Operational remote sensing of microphysical and optical cloud properties is invariably predicated on the assumption of plane-parallel slab geometry for the targeted cloud. The sole benefit of this often-questionable assumption about the cloud is that it leads to one-dimensional (1D) radiative transfer (RT)---a textbook, computationally tractable model. We present new results as evidence that, thanks to converging advances in 3D RT, inverse problem theory, algorithm implementation, and computer hardware, we are at the dawn of a new era in cloud remote sensing where we can finally go beyond the plane-parallel paradigm. Granted, the plane-parallel/1D RT assumption is reasonable for spatially extended stratiform cloud layers, as well as the smoothly distributed background aerosol layers. However, these 1D RT-friendly scenarios exclude cases that are critically important for climate physics. 1D RT---whence operational cloud remote sensing---fails catastrophically for cumuliform clouds that have fully 3D outer shapes and internal structures driven by shallow or deep convection. For these situations, the first order of business in a robust characterization by remote sensing is to abandon the slab geometry framework and determine the 3D geometry of the cloud, as a first step toward bone fide 3D cloud tomography. With this specific goal in mind, we deliver a proof-of-concept for an entirely new kind of remote sensing applicable to 3D clouds. It is based on highly simplified 3D RT and exploits multi-angular suites of cloud images at high spatial resolution. Airborne sensors like AirMSPI readily acquire such data. The key element of the reconstruction algorithm is a sophisticated solution of the nonlinear inverse problem via linearization of the forward model and an iteration scheme supported, where necessary, by adaptive regularization. Currently, the demo uses a 2D setting to show how either vertical profiles or horizontal slices of the cloud can be accurately reconstructed. Extension to 3D volumes is straightforward but the next challenge is to accommodate images at lower spatial resolution, e.g., from MISR/Terra. G. Bal, J. Chen, and A.B. Davis (2015). Reconstruction of cloud geometry from multi-angle images, Inverse Problems in Imaging (submitted).

Using long-term ARM observations to evaluate Arctic mixed-phased cloud representation in the GISS ModelE GCM

NASA Astrophysics Data System (ADS)

Lamer, K.; Fridlind, A. M.; Luke, E. P.; Tselioudis, G.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.

2016-12-01

The presence of supercooled liquid in clouds affects surface radiative and hydrological budgets, especially at high latitudes. Capturing these effects is crucial to properly quantifying climate sensitivity. Currently, a number of CGMs disagree on the distribution of cloud phase. Adding to the challenge is a general lack of observations on the continuum of clouds, from high to low-level and from warm to cold. In the current study, continuous observations from 2011 to 2014 are used to evaluate all clouds produced by the GISS ModelE GCM over the ARM North Slope of Alaska site. The International Satellite Cloud Climatology Project (ISCCP) Global Weather State (GWS) approach reveals that fair-weather (GWS 7, 32% occurrence rate), as well as mid-level storm related (GWS 5, 28%) and polar (GWS 4, 14%) clouds, dominate the large-scale cloud patterns at this high latitude site. At higher spatial and temporal resolutions, ground-based cloud radar observations reveal a majority of single layer cloud vertical structures (CVS). While clear sky and low-level clouds dominate (each with 30% occurrence rate) a fair amount of shallow ( 10%) to deep ( 5%) convection are observed. Cloud radar Doppler spectra are used along with depolarization lidar observations in a neural network approach to detect the presence, layering and inhomogeneity of supercooled liquid layers. Preliminary analyses indicate that most of the low-level clouds sampled contain one or more supercooled liquid layers. Furthermore, the relationship between CVS and the presence of supercooled liquid is established, as is the relationship between the presence of supercool liquid and precipitation susceptibility. Two approaches are explored to bridge the gap between large footprint GCM simulations and high-resolution ground-based observations. The first approach consists of comparing model output and ground-based observations that exhibit the same column CVS type (i.e. same cloud depth, height and layering). Alternatively, the second approach consists of comparing model output and ground-based observations that exhibit the same large-scale GWS type (i.e. same cloud top pressure and optical depth patterns) where ground-based observations are associated to large-scale GWS every 3 hours using the closest satellite overpass.

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.

Delay-based virtual congestion control in multi-tenant datacenters

NASA Astrophysics Data System (ADS)

Liu, Yuxin; Zhu, Danhong; Zhang, Dong

2018-03-01

With the evolution of cloud computing and virtualization, the congestion control of virtual datacenters has become the basic issue for multi-tenant datacenters transmission. Regarding to the friendly conflict of heterogeneous congestion control among multi-tenant, this paper proposes a delay-based virtual congestion control, which translates the multi-tenant heterogeneous congestion control into delay-based feedback uniformly by setting the hypervisor translation layer, modifying three-way handshake of explicit feedback and packet loss feedback and throttling receive window. The simulation results show that the delay-based virtual congestion control can effectively solve the unfairness of heterogeneous feedback congestion control algorithms.

Comparasion of Cloud Cover restituted by POLDER and MODIS

NASA Astrophysics Data System (ADS)

Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.

2009-04-01

PARASOL and AQUA are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and MODIS provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and MODIS level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and MODIS. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, MODIS can better detect the fractional clouds thus explaining as one part of a positive bias in any latitude and in any viewing angle with an order of 10% between the POLDER cloud amount and the so-called MODIS "combined" cloud amount. Nevertheless it is worthy to note that a negative bias of about 10% is obtained between the POLDER cloud amount and the MODIS "day-mean" cloud amount. Main differences between the two MODIS cloud amount values are known to be due to the filtering of remaining aerosols or cloud edges. due to both this high spatial resolution of MODIS and the fact that "combined" cloud amount filters cloud edges, we can also explain why appear the high positive bias regions over subtropical ocean in south hemisphere and over east Africa in summer. Thanks to several channels in the thermal infrared spectral domain, MODIS detects probably much better the thin cirrus especially over land, thus causing a general negative bias for ice clouds. The multi-spectral capability of MODIS also allows for a better detection of low clouds over snow or ice, Hence the (POLDER-MODIS) cloud amount difference is often negative over Greenland, Antarctica, and over the continents at middle-high latitudes in spring and autumn associated to the snow coverage. The multi-spectral capability of MODIS also makes the discrimination possible between the biomass burning aerosols and the fractional clouds over the continents. Thus a positive bias appears in central Africa in summer and autumn associated to important biomass burning events. Over transition region between desert and non-desert, the presence of large negative bias (POLDER-MODIS) of cloud amount maybe partly due to MODIS pixel falsely labeled the desert as cloudy, where MODIS algorithm uses static desert mask. This is clearly highlighted in south of Sahara in spring and summer where we find a bias negative with an order of -0.1. What is more, thanks to its multi-angular capability, POLDER can discriminate the sun-glint region thus minimizing the dependence of cloud amount on view angle. It makes the detection of high clouds easier over a black surface thanks to its polarization character.

Analysis of reflectance spectra of UV-absorbing aerosol scenes measured by SCIAMACHY

NASA Astrophysics Data System (ADS)

de Graaf, M.; Stammes, P.; Aben, E. A. A.

2007-01-01

Reflectance spectra from 280-1750 nm of typical desert dust aerosol (DDA) and biomass burning aerosol (BBA) scenes over oceans are presented, measured by the space-borne spectrometer Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). DDA and BBA are both UV-absorbing aerosols, but their effect on the top-of-atmosphere (TOA) reflectance is different due to differences in the way mineral aerosols and smoke reflect and absorb radiation. Mineral aerosols are typically large, inert particles, found in warm, dry continental air. Smoke particles, on the other hand, are usually small particles, although often clustered, chemically very active and highly variable in composition. Moreover, BBA are hygroscopic and over oceans BBA were invariably found in cloudy scenes. TOA reflectance spectra of typical DDA and BBA scenes were analyzed, using radiative transfer simulations, and compared. The DDA spectrum was successfully simulated using a layer with a bimodal size distribution of mineral aerosols in a clear sky. The spectrum of the BBA scene, however, was determined by the interaction between cloud droplets and smoke particles, as is shown by simulations with a model of separate aerosol and cloud layers and models with internally and externally mixed aerosol/cloud layers. The occurrence of clouds in smoke scenes when sufficient water vapor is present usually prevents the detection of optical properties of these aerosol plumes using space-borne sensors. However, the Absorbing Aerosol Index (AAI), a UV color index, is not sensitive to scattering aerosols and clouds and can be used to detect these otherwise obscured aerosol plumes over clouds. The amount of absorption of radiation can be expressed using the absorption optical thickness. The absorption optical thickness in the DDA case was 0.42 (340 nm) and 0.14 (550 nm) for an aerosol layer of optical thickness 1.74 (550 nm). In the BBA case the absorption optical thickness was 0.18 (340 nm) and 0.10 (550 nm) for an aerosol/cloud layer of optical thickness 20.0 (550 nm). However, this reduced the cloud albedo by about 0.2 (340 nm) and 0.15 (550 nm). This method can be an important tool to estimate the global impact of absorption of shortwave radiation by smoke and industrial aerosols inside clouds.

Retrievals of Cloud Droplet Size from the RSP Data: Validation Using in Situ Measurements

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail D.; Cairns, Brian; Sinclair, Kenneth; Wasilewski, Andrzej P.; Ziemba, Luke; Crosbie, Ewan; Hair, John; Hu, Yongxiang; Hostetler, Chris; Stamnes, Snorre

2016-01-01

We present comparisons of cloud droplet size distributions retrieved from the Research Scanning Polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). This field experiment was based at St. Johns airport, Newfoundland, Canada with the latest deployment in May - June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring polarized and total reflectances in9 spectral channels. Its unique high angular resolution allows for characterization of liquid water droplet size using the rainbow structure observed in the polarized reflectances in the scattering angle range between 135 and 165 degrees. A parametric fitting algorithm applied to the polarized reflectances provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution (DSD) itself. The latter is important in the case of clouds with complex structure, which results in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparison of remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was at the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons show generally good agreement with deviations explainable by the position of the aircraft within cloud and by presence of additional cloud layers in RSP view that do not contribute to the in situ DSDs. In the latter case the distributions retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The comparison results provide a rare validation of polarimetric droplet size retrieval techniques, which can be used for analysis of satellite data on global scale.

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

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

DOE PAGES

Prather, M. J.

2015-08-14

A new approach for modeling photolysis rates ( J values) in atmospheres with fractional cloud cover has been developed and is implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observations of the vertical correlation of cloud layers, Cloud-J 7.3c 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 by four quadrature atmospheres produces mean J values in an atmospheric column with root mean square (rms) errors of 4 % or less compared with 10–20 %more » errors using simpler approximations. 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

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.

Use of Probability Distribution Functions for Discriminating Between Cloud and Aerosol in Lidar Backscatter Data

NASA Technical Reports Server (NTRS)

Liu, Zhaoyan; Vaughan, Mark A.; Winker, Davd M.; Hostetler, Chris A.; Poole, Lamont R.; Hlavka, Dennis; Hart, William; McGill, Mathew

2004-01-01

In this paper we describe the algorithm hat will be used during the upcoming Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission for discriminating between clouds and aerosols detected in two wavelength backscatter lidar profiles. We first analyze single-test and multiple-test classification approaches based on one-dimensional and multiple-dimensional probability density functions (PDFs) in the context of a two-class feature identification scheme. From these studies we derive an operational algorithm based on a set of 3-dimensional probability distribution functions characteristic of clouds and aerosols. A dataset acquired by the Cloud Physics Lidar (CPL) is used to test the algorithm. Comparisons are conducted between the CALIPSO algorithm results and the CPL data product. The results obtained show generally good agreement between the two methods. However, of a total of 228,264 layers analyzed, approximately 5.7% are classified as different types by the CALIPSO and CPL algorithm. This disparity is shown to be due largely to the misclassification of clouds as aerosols by the CPL algorithm. The use of 3-dimensional PDFs in the CALIPSO algorithm is found to significantly reduce this type of error. Dust presents a special case. Because the intrinsic scattering properties of dust layers can be very similar to those of clouds, additional algorithm testing was performed using an optically dense layer of Saharan dust measured during the Lidar In-space Technology Experiment (LITE). In general, the method is shown to distinguish reliably between dust layers and clouds. The relatively few erroneous classifications occurred most often in the LITE data, in those regions of the Saharan dust layer where the optical thickness was the highest.

Multi-year ground-based observations of aerosol-cloud interactions in the Mid-Atlantic of the United States

NASA Astrophysics Data System (ADS)

Li, Siwei; Joseph, Everette; Min, Qilong; Yin, Bangsheng

2017-02-01

The U.S. Mid-Atlantic region experiences a wide variability of aerosol loading and frequent episodes of elevated anthropogenic aerosol loading associated with urban pollution conditions during summer months. In this study, multi-year ground-based observations (2006 to 2010) of aerosol and cloud properties from passive, active and in situ measurements at an atmospheric measurement field station in the Baltimore-Washington corridor operated by Howard University were analyzed to examine aerosol indirect effect on single-layer warm clouds including cloud optical depth (COD), liquid water path (LWP), cloud droplet effective radius (Re) and cloud droplet number concentration (Nd) in this region. A greater occurrence of polluted episodes and cloud cases with smaller Re (<7 μm) were found during the polluted year summers (2006, 2007 and 2008) than the clean year summers (2009 and 2010). The measurements of aerosol particulate matter with aerodynamic diameter≤2.5 μm (PM2.5) were used to represent the aerosol loading under cloudy conditions. Significant negative relationships between cloud droplet Re and PM2.5 were observed. Cloud cases were separated into clean and polluted groups based on the value of PM2.5. The cloud droplet Re was found proportional to LWP under clean conditions but weakly dependent on LWP under polluted conditions. The Nd was proportional to LWP under polluted condition but weakly dependent on LWP under clean conditions. Moreover, the effects of increasing fine aerosol particles on modifying cloud microphysical properties were found more significant under large LWP than small LWP in this region.

Improvements to the CATS Cloud-Aerosol Data Products and Implications for the Space-Based Lidar Data Record

NASA Astrophysics Data System (ADS)

Yorks, J. E.; McGill, M. J.; Nowottnick, E. P.; Palm, S. P.; Hlavka, D. L.; Selmer, P. A.; Rodier, S. D.; Vaughan, M.; Pauly, R.

2017-12-01

The Cloud-Aerosol Transport System (CATS) is an elastic backscatter lidar that has generated over 175 billion laser pulses on-orbit from the International Space Station (ISS) since February 2015. The CATS instrument was designed to demonstrate new in-space technologies for future Earth Science missions while also providing properties of clouds and aerosols such as: layer height/thickness, backscatter, optical depth, extinction, and feature type. Despite the "tech demo" nature of CATS and the lack of a funded science team, the research community is increasingly embracing CATS data. New CATS data products, the most acurrate yet, were released in the summer of 2017. The major algorithm changes made in L1B Version 2-08 (V2-08) focused on the backscatter calibration and the inclusion of a new flag to notify users of granules with depolarization ratio values of poor quality. Several changes were made to the molecular folding correction factor and calibration algorithms that result in favorable comparisons between CATS, CALIPSO, and modeled Rayleigh 1064 nm backscatter profiles. Given that the 1064 nm attenuated total backscatter and depolarization ratio are used to retrieve nearly all L2O data products, the accuracy of the L2O products has also improved. Several changes were made in CATS L2O Version 2-00 data products to improve cloud and aerosol detection. The CATS L2O data now includes layer detection at both 5 and 60 km horizontal resolutions to increase daytime detection of thin cirrus and aerosol layers over land. Horizontal persistence tests prevent superficial "striping" that was visible in vertical feature mask images for horizontally homogeneous cloud and aerosol layers. Also, the absolute uncertainties for all the L2O parameters are now reported in the CATS data products. Given the uncertain status of continued CALIPSO operations, these updated CATS data products may be the only space-based lidar data record that continues into the 2018 timeframe.

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

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

Integrated Cloud-Aerosol-Radiation Product using CERES, MODIS, CALIPSO and CloudSat Data

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave

2007-01-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3- dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave; Stephens, Graeme; Partain, Philip

2007-10-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Using OMI Observations to Measure Aerosol Absorption of Biomass Burning Aerosols Above Clouds

NASA Technical Reports Server (NTRS)

Torres, Omar; Bhartia, P. K.; Jethva, Hiren

2011-01-01

The presence of absorbing aerosol layers above clouds is unambiguously detected by the TOMS/OMI UV Aerosol Index (AI) that uses satellite observations at two near-UV channels. A sensitivity study using radiative transfer calculations shows that the AI signal of resulting from the presence of aerosols above clouds is mainly driven by the aerosol absorption optical depth and the optical depth of the underlying cloud. Based on these results, an inversion algorithm has been developed to retrieve the aerosol optical depth (AOD) of aerosol layers above clouds. In this presentation we will discuss the sensitivity analysis, describe the retrieval approach, and present results of applications of the retrieval method to OMI observations over the South Atlantic Ocean. Preliminary error analyses, to be discussed, indicate that the AOD can be underestimated (up to -30%) or overestimated (up to 60%) depending on algorithmic assumptions.

Architecture Design of Healthcare Software-as-a-Service Platform for Cloud-Based Clinical Decision Support Service

PubMed Central

Oh, Sungyoung; Cha, Jieun; Ji, Myungkyu; Kang, Hyekyung; Kim, Seok; Heo, Eunyoung; Han, Jong Soo; Kang, Hyunggoo; Chae, Hoseok; Hwang, Hee

2015-01-01

Objectives To design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability. Methods We analyzed the architecture requirements of an HSP, including the interface, business services, cloud SaaS, quality attributes, privacy and security, and multi-lingual capacity. For cloud-based SaaS services, we focused on Clinical Decision Service (CDS) content services, basic functional services, and mobile services. Microsoft's Azure cloud computing for Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) was used. Results The functional and software views of an HSP were designed in a layered architecture. External systems can be interfaced with the HSP using SOAP and REST/JSON. The multi-tenancy model of the HSP was designed as a shared database, with a separate schema for each tenant through a single application, although healthcare data can be physically located on a cloud or in a hospital, depending on regulations. The CDS services were categorized into rule-based services for medications, alert registration services, and knowledge services. Conclusions We expect that cloud-based HSPs will allow small and mid-sized hospitals, in addition to large-sized hospitals, to adopt information infrastructures and health information technology with low system operation and maintenance costs. PMID:25995962

Marine Layer Clouds off the California Coast

NASA Image and Video Library

2017-12-08

NASA image acquired September 27, 2012 On September 27, 2012, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite captured this nighttime view of low-lying marine layer clouds along the coast of California. The image was captured by the VIIRS “day-night band,” which detects light in a range of wavelengths from green to near-infrared and uses filtering techniques to observe signals such as gas flares, auroras, wildfires, city lights, and reflected moonlight. An irregularly-shaped patch of high clouds hovers off the coast of California, and moonlight caused the high clouds to cast distinct shadows on the marine layer clouds below. VIIRS acquired the image when the Moon was in its waxing gibbous phase, meaning it was more than half-lit, but less than full. Low clouds pose serious hazards for air and ship traffic, but satellites have had difficulty detecting them in the past. To illustrate this, the second image shows the same scene in thermal infrared, the band that meteorologists generally use to monitor clouds at night. Only high clouds are visible; the low clouds do not show up at all because they are roughly the same temperature as the ground. NASA Earth Observatory image by Jesse Allen and Robert Simmon, using VIIRS Day-Night Band data from the Suomi National Polar-orbiting Partnership. Suomi NPP is the result of a partnership between NASA, the National Oceanic and Atmospheric Administration, and the Department of Defense. Caption by Adam Voiland. Instrument: Suomi NPP - VIIRS Credit: NASA Earth Observatory Click here to view all of the Earth at Night 2012 images Click here to read more about this image NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

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.

All-sky photogrammetry techniques to georeference a cloud field

NASA Astrophysics Data System (ADS)

Crispel, Pierre; Roberts, Gregory

2018-01-01

In this study, we present a novel method of identifying and geolocalizing cloud field elements from a portable all-sky camera stereo network based on the ground and oriented towards zenith. The methodology is mainly based on stereophotogrammetry which is a 3-D reconstruction technique based on triangulation from corresponding stereo pixels in rectified images. In cases where clouds are horizontally separated, identifying individual positions is performed with segmentation techniques based on hue filtering and contour detection algorithms. Macroscopic cloud field characteristics such as cloud layer base heights and velocity fields are also deduced. In addition, the methodology is fitted to the context of measurement campaigns which impose simplicity of implementation, auto-calibration, and portability. Camera internal geometry models are achieved a priori in the laboratory and validated to ensure a certain accuracy in the peripheral parts of the all-sky image. Then, stereophotogrammetry with dense 3-D reconstruction is applied with cameras spaced 150 m apart for two validation cases. The first validation case is carried out with cumulus clouds having a cloud base height at 1500 m a.g.l. The second validation case is carried out with two cloud layers: a cumulus fractus layer with a base height at 1000 m a.g.l. and an altocumulus stratiformis layer with a base height of 2300 m a.g.l. Velocity fields at cloud base are computed by tracking image rectangular patterns through successive shots. The height uncertainty is estimated by comparison with a Vaisala CL31 ceilometer located on the site. The uncertainty on the horizontal coordinates and on the velocity field are theoretically quantified by using the experimental uncertainties of the cloud base height and camera orientation. In the first cumulus case, segmentation of the image is performed to identify individuals clouds in the cloud field and determine the horizontal positions of the cloud centers.

Further developments in cloud statistics for computer simulations

NASA Technical Reports Server (NTRS)

Chang, D. T.; Willand, J. H.

1972-01-01

This study is a part of NASA's continued program to provide global statistics of cloud parameters for computer simulation. The primary emphasis was on the development of the data bank of the global statistical distributions of cloud types and cloud layers and their applications in the simulation of the vertical distributions of in-cloud parameters such as liquid water content. These statistics were compiled from actual surface observations as recorded in Standard WBAN forms. Data for a total of 19 stations were obtained and reduced. These stations were selected to be representative of the 19 primary cloud climatological regions defined in previous studies of cloud statistics. Using the data compiled in this study, a limited study was conducted of the hemogeneity of cloud regions, the latitudinal dependence of cloud-type distributions, the dependence of these statistics on sample size, and other factors in the statistics which are of significance to the problem of simulation. The application of the statistics in cloud simulation was investigated. In particular, the inclusion of the new statistics in an expanded multi-step Monte Carlo simulation scheme is suggested and briefly outlined.

A cloud masking algorithm for EARLINET lidar systems

NASA Astrophysics Data System (ADS)

Binietoglou, Ioannis; Baars, Holger; D'Amico, Giuseppe; Nicolae, Doina

2015-04-01

Cloud masking is an important first step in any aerosol lidar processing chain as most data processing algorithms can only be applied on cloud free observations. Up to now, the selection of a cloud-free time interval for data processing is typically performed manually, and this is one of the outstanding problems for automatic processing of lidar data in networks such as EARLINET. In this contribution we present initial developments of a cloud masking algorithm that permits the selection of the appropriate time intervals for lidar data processing based on uncalibrated lidar signals. The algorithm is based on a signal normalization procedure using the range of observed values of lidar returns, designed to work with different lidar systems with minimal user input. This normalization procedure can be applied to measurement periods of only few hours, even if no suitable cloud-free interval exists, and thus can be used even when only a short period of lidar measurements is available. Clouds are detected based on a combination of criteria including the magnitude of the normalized lidar signal and time-space edge detection performed using the Sobel operator. In this way the algorithm avoids misclassification of strong aerosol layers as clouds. Cloud detection is performed using the highest available time and vertical resolution of the lidar signals, allowing the effective detection of low-level clouds (e.g. cumulus humilis). Special attention is given to suppress false cloud detection due to signal noise that can affect the algorithm's performance, especially during day-time. In this contribution we present the details of algorithm, the effect of lidar characteristics (space-time resolution, available wavelengths, signal-to-noise ratio) to detection performance, and highlight the current strengths and limitations of the algorithm using lidar scenes from different lidar systems in different locations across Europe.

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.

Overview of 3D-TRACE, a NASA Initiative in Three-Dimensional Tomography of the Aerosol-Cloud Environment

NASA Astrophysics Data System (ADS)

Davis, Anthony; Diner, David; Yanovsky, Igor; Garay, Michael; Xu, Feng; Bal, Guillaume; Schechner, Yoav; Aides, Amit; Qu, Zheng; Emde, Claudia

2013-04-01

Remote sensing is a key tool for sorting cloud ensembles by dynamical state, aerosol environments by source region, and establishing causal relationships between aerosol amounts, type, and cloud microphysics-the so-called indirect aerosol climate impacts, and one of the main sources of uncertainty in current climate models. Current satellite imagers use data processing approaches that invariably start with cloud detection/masking to isolate aerosol air-masses from clouds, and then rely on one-dimensional (1D) radiative transfer (RT) to interpret the aerosol and cloud measurements in isolation. Not only does this lead to well-documented biases for the estimates of aerosol radiative forcing and cloud optical depths in current missions, but it is fundamentally inadequate for future missions such as EarthCARE where capturing the complex, three-dimensional (3D) interactions between clouds and aerosols is a primary objective. In order to advance the state of the art, the next generation of satellite information processing systems must incorporate technologies that will enable the treatment of the atmosphere as a fully 3D environment, represented more realistically as a continuum. At one end, there is an optically thin background dominated by aerosols and molecular scattering that is strongly stratified and relatively homogeneous in the horizontal. At the other end, there are optically thick embedded elements, clouds and aerosol plumes, which can be more or less uniform and quasi-planar or else highly 3D with boundaries in all directions; in both cases, strong internal variability may be present. To make this paradigm shift possible, we propose to combine the standard models for satellite signal prediction physically grounded in 1D and 3D RT, both scalar and vector, with technologies adapted from biomedical imaging, digital image processing, and computer vision. This will enable us to demonstrate how the 3D distribution of atmospheric constituents, and their associated microphysical properties, can be reconstructed from multi-angle/multi-spectral imaging radiometry and, more and more, polarimetry. Specific technologies of interest are computed tomography (reconstruction from projections), optical tomography (using cross-pixel radiation transport in the diffusion limit), stereoscopy (depth/height retrievals), blind source and scale separation (signal unmixing), and disocclusion (information recovery in the presence of obstructions). Later on, these potentially powerful inverse problem solutions will be fully integrated in a versatile satellite data analysis toolbox. At present, we can report substantial progress at the component level. Specifically, we will focus on the most elementary problems in atmospheric tomography with an emphasis on the vastly under-exploited class of multi-pixel techniques. One basic problem is to infer the outer shape and mean opacity of 3D clouds, along with a bulk measure of cloud particle size. Another is to separate high and low cloud layers based on their characteristically different spatial textures. Yet another is to reconstruct the 3D spatial distribution of aerosol density based on passive imaging. This suite of independent feasibility studies amounts to a compelling proofof- concept for the ambitious 3D-Tomographic Reconstruction of the Aerosol-Cloud Environment (3D-TRACE) project as a whole.

Ground-based microwave radar and optical lidar signatures of volcanic ash plumes: models, observations and retrievals

NASA Astrophysics Data System (ADS)

Mereu, Luigi; Marzano, Frank; Mori, Saverio; Montopoli, Mario; Cimini, Domenico; Martucci, Giovanni

2013-04-01

The detection and quantitative retrieval of volcanic ash clouds is of significant interest due to its environmental, climatic and socio-economic effects. Real-time monitoring of such phenomena is crucial, also for the initialization of dispersion models. Satellite visible-infrared radiometric observations from geostationary platforms are usually exploited for long-range trajectory tracking and for measuring low level eruptions. Their imagery is available every 15-30 minutes and suffers from a relatively poor spatial resolution. Moreover, the field-of-view of geostationary radiometric measurements may be blocked by water and ice clouds at higher levels and their overall utility is reduced at night. Ground-based microwave radars may represent an important tool to detect and, to a certain extent, mitigate the hazard from the ash clouds. Ground-based weather radar systems can provide data for determining the ash volume, total mass and height of eruption clouds. Methodological studies have recently investigated the possibility of using ground-based single-polarization and dual-polarization radar system for the remote sensing of volcanic ash cloud. A microphysical characterization of volcanic ash was carried out in terms of dielectric properties, size distribution and terminal fall speed, assuming spherically-shaped particles. A prototype of volcanic ash radar retrieval (VARR) algorithm for single-polarization systems was proposed and applied to S-band and C-band weather radar data. The sensitivity of the ground-based radar measurements decreases as the ash cloud is farther so that for distances greater than about 50 kilometers fine ash might be not detected anymore by microwave radars. In this respect, radar observations can be complementary to satellite, lidar and aircraft observations. Active remote sensing retrieval from ground, in terms of detection, estimation and sensitivity, of volcanic ash plumes is not only dependent on the sensor specifications, but also on the range and ash cloud distribution. The minimum detectable signal can be increased, for a given system and ash plume scenario, by decreasing the observation range and increasing the operational frequency using a multi-sensor approach, but also exploiting possible polarimetric capabilities. In particular, multi-wavelengths lidars can be complementary systems useful to integrate radar-based ash particle measurement. This work, starting from the results of a previous study and from above mentioned issues, is aimed at quantitatively assessing the optimal choices for microwave and millimeter-wave radar systems with a dual-polarization capability for real-time ash cloud remote sensing to be used in combination with an optical lidar. The physical-electromagnetic model of ash particle distributions is systematically reviewed and extended to include non-spherical particle shapes, vesicular composition, silicate content and orientation phenomena. The radar and lidar scattering and absorption response is simulated and analyzed in terms of self-consistent polarimetric signatures for ash classification purposes and correlation with ash concentration and mean diameter for quantitative retrieval aims. A sensitivity analysis to ash concentration, as a function of sensor specifications, range and ash category, is carried out trying to assess the expected multi-sensor multi-spectral system performances and limitations. The multi-sensor multi-wavelength polarimetric model-based approach can be used within a particle classification and estimation scheme, based on the VARR Bayesian metrics. As an application, the ground-based observation of the Eyjafjallajökull volcanic ash plume on 15-16 May 2010, carried out at the Atmospheric Research Station at Mace Head, Carna (Ireland) with MIRA36 35-GHz Ka-Band Doppler cloud radar and CHM15K lidar/ceilometer at 1064-nm wavelength, has been considered. Results are discussed in terms of retrievals and intercomparison with other ground-based and satellite-based sensors.

Use of Field Observations for Understanding Controls of Polar Low Cloud Microphysical Properties

NASA Astrophysics Data System (ADS)

McFarquhar, G. M.

2016-12-01

Although arctic clouds have a net warming effect on the Arctic surface, their radiative effect is sensitive to cloud microphysical properties, namely the sizes, phases and shapes of cloud particles. Such cloud properties are influenced by the numbers, compositions and sizes of aerosols, meteorological conditions, and surface characteristics. Uncertainty in representing cloud-aerosol interactions in varying environmental conditions and associated feedbacks is a major cause in our lack of understanding of why the Arctic is warming faster than the rest of the Earth. Here, the understanding of cloud-aerosol interactions gained from past arctic field experiments is reviewed. Such studies have characterized the structure of single-layer mixed phase clouds that are ubiquitous in the Arctic and investigated different aerosol indirect effect mechanisms acting in these clouds. But, it is still unknown what controls the amount of supercooled water in arctic clouds (especially in complex frequently occurring multi-layer clouds), how probability distributions of cloud properties and radiative heating and their subsequent impact on temperature profiles and underlying snow and sea ice cover vary with aerosol loading and composition in different surface and meteorological conditions, how the composition and concentration of arctic aerosols and cloud microphysical properties vary annually and interannually, and how cloud-aerosol-radiative interactions can be better represented in models with varying temporal and spatial scales. These needs can be addressed in two ways. First, there is a need for comprehensive and routine aircraft, UAV and tethered balloon measurements in the presence of ground, air or space-based remote sensors over a variety of surface and meteorological conditions. Second, planned observational campaigns (the Measurements of Aerosols Radiation and Clouds over the Southern Oceans MARCUS and the Southern Oceans Cloud Radiation Transport Experimental Study SOCRATES) should provide cloud, aerosol, radiative and precipitation observations over the pristine and continually cloudy Southern Oceans that are remote from natural and continental anthropogenic aerosol sources should provide a process-oriented understanding of cloud-aerosol interactions in liquid and ice clouds.

Seasonal Differences in Tropical Western Pacific Cloud Ice, Water Vapor and Aerosols Observed From Space During ATTREX-III and POSIDON

NASA Astrophysics Data System (ADS)

Avery, M. A.; Rosenlof, K. H.; Vaughan, M.; Getzewich, B. J.; Thornberry, T. D.; Gao, R. S.; Rollins, A. W.; Woods, S.; Yorks, J. E.; Jensen, E. J.

2017-12-01

Recent aircraft missions sampling the tropical tropopause layer (TTL) in the tropical Western Pacific have provided a wealth of detailed cloud microphysical and associated aerosol, water vapor and temperature data for understanding processes that regulate stratospheric composition and hydration. This presentation seeks to provide a regional context for these measurements by comparing and contrasting active space-based observations from these time periods (Feb-Mar 2014 for ATTREX-III and Oct 2016 for POSIDON), primarily from the Clouds and Aerosol Lidar with Orthogonal Polarization (CALIOP), with the addition of Cloud Profiling Radar (CPR) and the Cloud-Aerosol Transport System (CATS) where these data sets are available. While the ATTREX III and POSIDON aircraft field missions both took place from Guam in the Western Pacific, there were striking differences between the amount, geographical distribution and properties of cirrus clouds and aerosols in the Tropical TTL. In addition to cloud and aerosol amount and location, we present geometric properties, including cloud top heights, transparent cloud and aerosol layer thicknesses and location of the 532 nm backscatter centroid, which is roughly equivalent to the layer vertical center of mass. We also present differences in the distribution of cirrus cloud extinction coefficients and ice water content, and aerosol optical depths, as detected from space, and compare these with in situ measurements and with temperature and water vapor distributions from the Microwave Limb Sounder (MLS). We find that there is more intense convection reaching the tropical tropopause during the POSIDON mission, and consequently more associated cloud ice observed during POSIDON than during ATTREX-III.

Casting Light and Shadows on a Saharan Dust Storm

NASA Technical Reports Server (NTRS)

2003-01-01

On March 2, 2003, near-surface winds carried a large amount of Saharan dust aloft and transported the material westward over the Atlantic Ocean. These observations from the Multi-angle Imaging SpectroRadiometer (MISR) aboard NASA's Terra satellite depict an area near the Cape Verde Islands (situated about 700 kilometers off of Africa's western coast) and provide images of the dust plume along with measurements of its height and motion. Tracking the three-dimensional extent and motion of air masses containing dust or other types of aerosols provides data that can be used to verify and improve computer simulations of particulate transport over large distances, with application to enhancing our understanding of the effects of such particles on meteorology, ocean biological productivity, and human health.

MISR images the Earth by measuring the spatial patterns of reflected sunlight. In the upper panel of the still image pair, the observations are displayed as a natural-color snapshot from MISR's vertical-viewing (nadir) camera. High-altitude cirrus clouds cast shadows on the underlying ocean and dust layer, which are visible in shades of blue and tan, respectively. In the lower panel, heights derived from automated stereoscopic processing of MISR's multi-angle imagery show the cirrus clouds (yellow areas) to be situated about 12 kilometers above sea level. The distinctive spatial patterns of these clouds provide the necessary contrast to enable automated feature matching between images acquired at different view angles. For most of the dust layer, which is spatially much more homogeneous, the stereoscopic approach was unable to retrieve elevation data. However, the edges of shadows cast by the cirrus clouds onto the dust (indicated by blue and cyan pixels) provide sufficient spatial contrast for a retrieval of the dust layer's height, and indicate that the top of layer is only about 2.5 kilometers above sea level.

Motion of the dust and clouds is directly observable with the assistance of the multi-angle 'fly-over' animation (Below). The frames of the animation consist of data acquired by the 70-degree, 60-degree, 46-degree and 26-degree forward-viewing cameras in sequence, followed by the images from the nadir camera and each of the four backward-viewing cameras, ending with 70-degree backward image. Much of the south-to-north shift in the position of the clouds is due to geometric parallax between the nine view angles (rather than true motion), whereas the west-to-east motion is due to actual motion of the clouds over the seven minutes during which all nine cameras observed the scene. MISR's automated data processing retrieved a primarily westerly (eastward) motion of these clouds with speeds of 30-40 meters per second. Note that there is much less geometric parallax for the cloud shadows owing to the relatively low altitude of the dust layer upon which the shadows are cast (the amount of parallax is proportional to elevation and a feature at the surface would have no geometric parallax at all); however, the westerly motion of the shadows matches the actual motion of the clouds. The automated processing was not able to resolve a velocity for the dust plume, but by manually tracking dust features within the plume images that comprise the animation sequence we can derive an easterly (westward) speed of about 16 meters per second. These analyses and visualizations of the MISR data demonstrate that not only are the cirrus clouds and dust separated significantly in elevation, but they exist in completely different wind regimes, with the clouds moving toward the east and the dust moving toward the west.

[figure removed for brevity, see original site]

(Click on image above for high resolution version)

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17040. The panels cover an area of about 312 kilometers x 242 kilometers, and use data from blocks 74 to 77 within World Reference System-2 path 207.

MISR was built and is managed by NASA's Jet Propulsion Laboratory,Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Current Status of Aerosol Retrievals from TOMS

NASA Technical Reports Server (NTRS)

Torres, O.; Herman, J. R.; Bhartia, P. K.; Ginoux, P.

1999-01-01

Properties of atmospheric aerosols over all land and water surfaces are retrieved from TOMS measurements of backscattered radiances. The TOMS technique, uses observations at two wavelengths. In the near ultraviolet (330-380 nm) range, where the effects of gaseous absorption are negligible. The retrieved properties are optical depth and a measure of aerosol absorptivity, generally expressed as single scattering albedo. The main sources of error of the TOMS aerosol products are sub-pixel cloud contamination and uncertainty on the height above the surface of UV-absorbing aerosol layers. The first error source is related to the large footprint (50 x 50 km at nadir) of the sensor, and the lack of detection capability of sub-pixel size clouds. The uncertainty associated with the height of the absorbing aerosol layers, on the other hand, is related to the pressure dependence of the molecular scattering process, which is the basis of the near-UV method of absorbing aerosol detection. The detection of non-absorbing aerosols is not sensitive to aerosol layer height. We will report on the ongoing work to overcome both of these difficulties. Coincident measurements of high spatial resolution thermal infrared radiances are used to address the cloud contamination issue. Mostly clear scenes for aerosol retrieval are selected by examining the spatial homogeneity of the IR radiance measurements within a TOMS pixel. The approach to reduce the uncertainty associated with the height of the aerosol layer by making use of a chemical transport model will also be discussed.

A cloud detection algorithm using the downwelling infrared radiance measured by an infrared pyrometer of the ground-based microwave radiometer

DOE PAGES

Ahn, M. H.; Han, D.; Won, H. Y.; ...

2015-02-03

For better utilization of the ground-based microwave radiometer, it is important to detect the cloud presence in the measured data. Here, we introduce a simple and fast cloud detection algorithm by using the optical characteristics of the clouds in the infrared atmospheric window region. The new algorithm utilizes the brightness temperature (Tb) measured by an infrared radiometer installed on top of a microwave radiometer. The two-step algorithm consists of a spectral test followed by a temporal test. The measured Tb is first compared with a predicted clear-sky Tb obtained by an empirical formula as a function of surface air temperaturemore » and water vapor pressure. For the temporal test, the temporal variability of the measured Tb during one minute compares with a dynamic threshold value, representing the variability of clear-sky conditions. It is designated as cloud-free data only when both the spectral and temporal tests confirm cloud-free data. Overall, most of the thick and uniform clouds are successfully detected by the spectral test, while the broken and fast-varying clouds are detected by the temporal test. The algorithm is validated by comparison with the collocated ceilometer data for six months, from January to June 2013. The overall proportion of correctness is about 88.3% and the probability of detection is 90.8%, which are comparable with or better than those of previous similar approaches. Two thirds of discrepancies occur when the new algorithm detects clouds while the ceilometer does not, resulting in different values of the probability of detection with different cloud-base altitude, 93.8, 90.3, and 82.8% for low, mid, and high clouds, respectively. Finally, due to the characteristics of the spectral range, the new algorithm is found to be insensitive to the presence of inversion layers.« less

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

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

Wood, Robert; Wyant, Matthew; Bretherton, Christopher S.

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21 month (April 2009-December 2010) comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulusmore » and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1- 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from at Graciosa are being compared with short-range forecasts made a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.« less

Clouds, aerosol, and precipitation in the Marine Boundary Layer: An ARM mobile facility deployment

DOE PAGES

Wood, Robert; Luke, Ed; Wyant, Matthew; ...

2014-04-27

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009-December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulusmore » and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1-11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging.The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.« less

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

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

Wood, Robert; Wyant, Matthew; Bretherton, Christopher S.

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) 38 deployment at Graciosa Island in the Azores generated a 21 month (April 2009-December 2010) 39 comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric 40 Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is 41 to gain improved understanding of the interactions of clouds, aerosols and precipitation in the 42 marine boundary layer. 43 Graciosa Island straddles the boundary between the subtropics and midlatitudes in the 44 Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and 45 cloudiness conditions. Lowmore » clouds are the dominant cloud type, with stratocumulus and cumulus 46 occurring regularly. Approximately half of all clouds contained precipitation detectable as radar 47 echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1-48 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide 49 range of aerosol conditions was sampled during the deployment consistent with the diversity of 50 sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way 51 interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation 52 and cloud radiative properties while being controlled in part by precipitation scavenging. 53 The data from at Graciosa are being compared with short-range forecasts made a variety 54 of models. A pilot analysis with two climate and two weather forecast models shows that they 55 reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, 56 but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to 57 be a long-term ARM site that became operational in October 2013.« less

Numerical simulations of Jupiter’s moist convection layer: Structure and dynamics in statistically steady states

NASA Astrophysics Data System (ADS)

Sugiyama, K.; Nakajima, K.; Odaka, M.; Kuramoto, K.; Hayashi, Y.-Y.

2014-02-01

A series of long-term numerical simulations of moist convection in Jupiter’s atmosphere is performed in order to investigate the idealized characteristics of the vertical structure of multi-composition clouds and the convective motions associated with them, varying the deep abundances of condensable gases and the autoconversion time scale, the latter being one of the most questionable parameters in cloud microphysical parameterization. The simulations are conducted using a two-dimensional cloud resolving model that explicitly represents the convective motion and microphysics of the three cloud components, H2O, NH3, and NH4SH imposing a body cooling that substitutes the net radiative cooling. The results are qualitatively similar to those reported in Sugiyama et al. (Sugiyama, K. et al. [2011]. Intermittent cumulonimbus activity breaking the three-layer cloud structure of Jupiter. Geophys. Res. Lett. 38, L13201. doi:10.1029/2011GL047878): stable layers associated with condensation and chemical reaction act as effective dynamical and compositional boundaries, intense cumulonimbus clouds develop with distinct temporal intermittency, and the active transport associated with these clouds results in the establishment of mean vertical profiles of condensates and condensable gases that are distinctly different from the hitherto accepted three-layered structure (e.g., Atreya, S.K., Romani, P.N. [1985]. Photochemistry and clouds of Jupiter, Saturn and Uranus. In: Recent Advances in Planetary Meteorology. Cambridge Univ. Press, London, pp. 17-68). Our results also demonstrate that the period of intermittent cloud activity is roughly proportional to the deep abundance of H2O gas. The autoconversion time scale does not strongly affect the results, except for the vertical profiles of the condensates. Changing the autoconversion time scale by a factor of 100 changes the intermittency period by a factor of less than two, although it causes a dramatic increase in the amount of condensates in the upper troposphere. The moist convection layer becomes potentially unstable with respect to an air parcel rising from below the H2O lifting condensation level (LCL) well before the development of cumulonimbus clouds. The instability accumulates until an appropriate trigger is provided by the H2O condensate that falls down through the H2O LCL; the H2O condensate drives a downward flow below the H2O LCL as a result of the latent cooling associated with the re-evaporation of the condensate, and the returning updrafts carry moist air from below to the moist convection layer. Active cloud development is terminated when the instability is completely exhausted. The period of intermittency is roughly equal to the time obtained by dividing the mean temperature increase, which is caused by active cumulonimbus development, by the body cooling rate.

Evaluation of large-eddy simulations forced with mesoscale model output for a multi-week period during a measurement campaign

NASA Astrophysics Data System (ADS)

Heinze, Rieke; Moseley, Christopher; Böske, Lennart Nils; Muppa, Shravan Kumar; Maurer, Vera; Raasch, Siegfried; Stevens, Bjorn

2017-06-01

Large-eddy simulations (LESs) of a multi-week period during the HD(CP)2 (High-Definition Clouds and Precipitation for advancing Climate Prediction) Observational Prototype Experiment (HOPE) conducted in Germany are evaluated with respect to mean boundary layer quantities and turbulence statistics. Two LES models are used in a semi-idealized setup through forcing with mesoscale model output to account for the synoptic-scale conditions. Evaluation is performed based on the HOPE observations. The mean boundary layer characteristics like the boundary layer depth are in a principal agreement with observations. Simulating shallow-cumulus layers in agreement with the measurements poses a challenge for both LES models. Variance profiles agree satisfactorily with lidar measurements. The results depend on how the forcing data stemming from mesoscale model output are constructed. The mean boundary layer characteristics become less sensitive if the averaging domain for the forcing is large enough to filter out mesoscale fluctuations.

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

NASA Astrophysics Data System (ADS)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2006-12-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

NASA Astrophysics Data System (ADS)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2005-05-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Point Cloud Classification of Tesserae from Terrestrial Laser Data Combined with Dense Image Matching for Archaeological Information Extraction

NASA Astrophysics Data System (ADS)

Poux, F.; Neuville, R.; Billen, R.

2017-08-01

Reasoning from information extraction given by point cloud data mining allows contextual adaptation and fast decision making. However, to achieve this perceptive level, a point cloud must be semantically rich, retaining relevant information for the end user. This paper presents an automatic knowledge-based method for pre-processing multi-sensory data and classifying a hybrid point cloud from both terrestrial laser scanning and dense image matching. Using 18 features including sensor's biased data, each tessera in the high-density point cloud from the 3D captured complex mosaics of Germigny-des-prés (France) is segmented via a colour multi-scale abstraction-based featuring extracting connectivity. A 2D surface and outline polygon of each tessera is generated by a RANSAC plane extraction and convex hull fitting. Knowledge is then used to classify every tesserae based on their size, surface, shape, material properties and their neighbour's class. The detection and semantic enrichment method shows promising results of 94% correct semantization, a first step toward the creation of an archaeological smart point cloud.

Modeling marine boundary-layer clouds with a two-layer model: A one-dimensional simulation

NASA Technical Reports Server (NTRS)

Wang, Shouping

1993-01-01

A two-layer model of the marine boundary layer is described. The model is used to simulate both stratocumulus and shallow cumulus clouds in downstream simulations. Over cold sea surfaces, the model predicts a relatively uniform structure in the boundary layer with 90%-100% cloud fraction. Over warm sea surfaces, the model predicts a relatively strong decoupled and conditionally unstable structure with a cloud fraction between 30% and 60%. A strong large-scale divergence considerably limits the height of the boundary layer and decreases relative humidity in the upper part of the cloud layer; thus, a low cloud fraction results. The efffects of drizzle on the boundary-layer structure and cloud fraction are also studied with downstream simulations. It is found that drizzle dries and stabilizes the cloud layer and tends to decouple the cloud from the subcloud layer. Consequently, solid stratocumulus clouds may break up and the cloud fraction may decrease because of drizzle.

Concept, Simulation, and Instrumentation for Radiometric Inflight Icing Detection

NASA Technical Reports Server (NTRS)

Ryerson, Charles; Koenig, George G.; Reehorst, Andrew L.; Scott, Forrest R.

2009-01-01

The multi-agency Flight in Icing Remote Sensing Team (FIRST), a consortium of the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), the National Center for Atmospheric Research (NCAR), the National Oceanographic and Atmospheric Administration (NOAA), and the Army Corps of Engineers (USACE), has developed technologies for remotely detecting hazardous inflight icing conditions. The USACE Cold Regions Research and Engineering Laboratory (CRREL) assessed the potential of onboard passive microwave radiometers for remotely detecting icing conditions ahead of aircraft. The dual wavelength system differences the brightness temperature of Space and clouds, with greater differences potentially indicating closer and higher magnitude cloud liquid water content (LWC). The Air Force RADiative TRANsfer model (RADTRAN) was enhanced to assess the flight track sensing concept, and a 'flying' RADTRAN was developed to simulate a radiometer system flying through simulated clouds. Neural network techniques were developed to invert brightness temperatures and obtain integrated cloud liquid water. In addition, a dual wavelength Direct-Detection Polarimeter Radiometer (DDPR) system was built for detecting hazardous drizzle drops. This paper reviews technology development to date and addresses initial polarimeter performance.

Exploring Venus Interior Structure by Detection of Infrasonic Waves

NASA Astrophysics Data System (ADS)

Mimoun, D.; Cutts, J.; Stevenson, D.; Garcia, R. F.

2015-04-01

Knowledge of the interior structure of Venus is currently impeded by the limited time that a seismometer can survive in the atmosphere of Venus. We propose to remotely detect quakes by infrasonic measurements at the top of the cloud layer.

Cloud and aerosol studies using combined CPL and MAS data

NASA Astrophysics Data System (ADS)

Vaughan, Mark A.; Rodier, Sharon; Hu, Yongxiang; McGill, Matthew J.; Holz, Robert E.

2004-11-01

Current uncertainties in the role of aerosols and clouds in the Earth's climate system limit our abilities to model the climate system and predict climate change. These limitations are due primarily to difficulties of adequately measuring aerosols and clouds on a global scale. The A-train satellites (Aqua, CALIPSO, CloudSat, PARASOL, and Aura) will provide an unprecedented opportunity to address these uncertainties. The various active and passive sensors of the A-train will use a variety of measurement techniques to provide comprehensive observations of the multi-dimensional properties of clouds and aerosols. However, to fully achieve the potential of this ensemble requires a robust data analysis framework to optimally and efficiently map these individual measurements into a comprehensive set of cloud and aerosol physical properties. In this work we introduce the Multi-Instrument Data Analysis and Synthesis (MIDAS) project, whose goal is to develop a suite of physically sound and computationally efficient algorithms that will combine active and passive remote sensing data in order to produce improved assessments of aerosol and cloud radiative and microphysical properties. These algorithms include (a) the development of an intelligent feature detection algorithm that combines inputs from both active and passive sensors, and (b) identifying recognizable multi-instrument signatures related to aerosol and cloud type derived from clusters of image pixels and the associated vertical profile information. Classification of these signatures will lead to the automated identification of aerosol and cloud types. Testing of these new algorithms is done using currently existing and readily available active and passive measurements from the Cloud Physics Lidar and the MODIS Airborne Simulator, which simulate, respectively, the CALIPSO and MODIS A-train instruments.

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.

A Method for the Automatic Detection of Insect Clutter in Doppler-Radar Returns.

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

Luke,E.; Kollias, P.; Johnson, K.

2006-06-12

The accurate detection and removal of insect clutter from millimeter wavelength cloud radar (MMCR) returns is of high importance to boundary layer cloud research (e.g., Geerts et al., 2005). When only radar Doppler moments are available, it is difficult to produce a reliable screening of insect clutter from cloud returns because their distributions overlap. Hence, screening of MMCR insect clutter has historically involved a laborious manual process of cross-referencing radar moments against measurements from other collocated instruments, such as lidar. Our study looks beyond traditional radar moments to ask whether analysis of recorded Doppler spectra can serve as the basismore » for reliable, automatic insect clutter screening. We focus on the MMCR operated by the Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) program at its Southern Great Plains (SGP) facility in Oklahoma. Here, archiving of full Doppler spectra began in September 2003, and during the warmer months, a pronounced insect presence regularly introduces clutter into boundary layer returns.« less

The Community Cloud retrieval for CLimate (CC4CL) - Part 1: A framework applied to multiple satellite imaging sensors

NASA Astrophysics Data System (ADS)

Sus, Oliver; Stengel, Martin; Stapelberg, Stefan; McGarragh, Gregory; Poulsen, Caroline; Povey, Adam C.; Schlundt, Cornelia; Thomas, Gareth; Christensen, Matthew; Proud, Simon; Jerg, Matthias; Grainger, Roy; Hollmann, Rainer

2018-06-01

We present here the key features of the Community Cloud retrieval for CLimate (CC4CL) processing algorithm. We focus on the novel features of the framework: the optimal estimation approach in general, explicit uncertainty quantification through rigorous propagation of all known error sources into the final product, and the consistency of our long-term, multi-platform time series provided at various resolutions, from 0.5 to 0.02°. By describing all key input data and processing steps, we aim to inform the user about important features of this new retrieval framework and its potential applicability to climate studies. We provide an overview of the retrieved and derived output variables. These are analysed for four, partly very challenging, scenes collocated with CALIOP (Cloud-Aerosol lidar with Orthogonal Polarization) observations in the high latitudes and over the Gulf of Guinea-West Africa. The results show that CC4CL provides very realistic estimates of cloud top height and cover for optically thick clouds but, where optically thin clouds overlap, returns a height between the two layers. CC4CL is a unique, coherent, multi-instrument cloud property retrieval framework applicable to passive sensor data of several EO missions. Through its flexibility, CC4CL offers the opportunity for combining a variety of historic and current EO missions into one dataset, which, compared to single sensor retrievals, is improved in terms of accuracy and temporal sampling.

Liquid Water Cloud Properties During the Polarimeter Definition Experiment (PODEX)

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail D.; Cairns, Brian; Wasilewski, Andrzei P.; Ackerman, Andrew S.; McGill, Matthew J.; Yorks, John E.; Hlavka, Dennis L.; Platnick, Steven; Arnold, George; Van Diedenhoven, Bastiaan;

Cloud layer thicknesses from a combination of surface and upper-air observations

NASA Technical Reports Server (NTRS)

Poore, Kirk D.; Wang, Junhong; Rossow, William B.

1995-01-01

Cloud layer thicknesses are derived from base and top altitudes by combining 14 years (1975-1988) of surface and upper-air observations at 63 sites in the Northern Hemisphere. Rawinsonde observations are employed to determine the locations of cloud-layer top and base by testing for dewpoint temperature depressions below some threshold value. Surface observations serve as quality checks on the rawinsonde-determined cloud properties and provide cloud amount and cloud-type information. The dataset provides layer-cloud amount, cloud type, high, middle, or low height classes, cloud-top heights, base heights and layer thicknesses, covering a range of latitudes from 0 deg to 80 deg N. All data comes from land sites: 34 are located in continental interiors, 14 are near coasts, and 15 are on islands. The uncertainties in the derived cloud properties are discussed. For clouds classified by low-, mid-, and high-top altitudes, there are strong latitudinal and seasonal variations in the layer thickness only for high clouds. High-cloud layer thickness increases with latitude and exhibits different seasonal variations in different latitude zones: in summer, high-cloud layer thickness is a maximum in the Tropics but a minimum at high latitudes. For clouds classified into three types by base altitude or into six standard morphological types, latitudinal and seasonal variations in layer thickness are very small. The thickness of the clear surface layer decreases with latitude and reaches a summer minimum in the Tropics and summer maximum at higher latitudes over land, but does not vary much over the ocean. Tropical clouds occur in three base-altitude groups and the layer thickness of each group increases linearly with top altitude. Extratropical clouds exhibit two groups, one with layer thickness proportional to their cloud-top altitude and one with small (less than or equal to 1000 m) layer thickness independent of cloud-top altitude.

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.

Atmospheric boundary layer CO2 remote sensing with a direct detection LIDAR instrument based on a widely tunable optical parametric source.

PubMed

Cadiou, Erwan; Mammez, Dominique; Dherbecourt, Jean-Baptiste; Gorju, Guillaume; Pelon, Jacques; Melkonian, Jean-Michel; Godard, Antoine; Raybaut, Myriam

2017-10-15

We report on the capability of a direct detection differential absorption lidar (DIAL) for range resolved and integrated path (IPDIAL) remote sensing of CO 2 in the atmospheric boundary layer (ABL). The laser source is an amplified nested cavity optical parametric oscillator (NesCOPO) emitting approximately 8 mJ at the two measurement wavelengths selected near 2050 nm. Direct detection atmospheric measurements are taken from the ground using a 30 Hz frequency switching between emitted wavelengths. Results show that comparable precision measurements are achieved in DIAL and IPDIAL modes (not better than a few ppm) on high SNR targets such as near range ABL aerosol and clouds, respectively. Instrumental limitations are analyzed and degradation due to cloud scattering variability is discussed to explain observed DIAL and IPDIAL limitations.

Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Korkin, S.; Wang, Y.; Quayle, B.; Laszlo, I.

2012-01-01

The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.

Impact of aerosol intrusions on sea-ice melting rates and the structure Arctic boundary layer clouds

NASA Astrophysics Data System (ADS)

Cotton, W.; Carrio, G.; Jiang, H.

2003-04-01

The Los Alamos National Laboratory sea-ice model (LANL CICE) was implemented into the real-time and research versions of the Colorado State University-Regional Atmospheric Modeling System (RAMS@CSU). The original version of CICE was modified in its structure to allow module communication in an interactive multigrid framework. In addition, some improvements have been made in the routines involved in the coupling, among them, the inclusion of iterative methods that consider variable roughness lengths for snow-covered ice thickness categories. This version of the model also includes more complex microphysics that considers the nucleation of cloud droplets, allowing the prediction of mixing ratios and number concentrations for all condensed water species. The real-time version of RAMS@CSU automatically processes the NASA Team SSMI F13 25km sea-ice coverage data; the data are objectively analyzed and mapped to the model grid configuration. We performed two types of cloud resolving simulations to assess the impact of the entrainment of aerosols from above the inversion on Arctic boundary layer clouds. The first series of numerical experiments corresponds to a case observed on May 4 1998 during the FIRE-ACE/SHEBA field experiment. Results indicate a significant impact on the microstructure of the simulated clouds. When assuming polluted initial profiles above the inversion, the liquid water fraction of the cloud monotonically decreases, the total condensate paths increases and downward IR tends to increase due to a significant increase in the ice water path. The second set of cloud resolving simulations focused on the evaluation of the potential effect of aerosol concentration above the inversion on melting rates during spring-summer period. For these multi-month simulations, the IFN and CCN profiles were also initialized assuming the 4 May profiles as benchmarks. Results suggest that increasing the aerosol concentrations above the boundary layer increases sea-ice melting rates when mixed phase clouds are present.

Method and Apparatus for Monitoring the Integrity of a Geomembrane Liner using time Domain Reflectometry

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

Morris, John L.

1998-11-09

Leaks are detected in a multi-layered geomembrane liner by a two-dimensional time domain reflectometry (TDR) technique. The TDR geomembrane liner is constructed with an electrically conductive detection layer positioned between two electrically non-conductive dielectric layers, which are each positioned between the detection layer and an electrically conductive reference layer. The integrity of the TDR geomembrane liner is determined by generating electrical pulses within the detection layer and measuring the time delay for any reflected electrical energy caused by absorption of moisture by a dielectric layer.

Method and apparatus for monitoring the integrity of a geomembrane liner using time domain reflectometry

DOEpatents

Morrison, John L [Idaho Falls, ID

2001-04-24

Leaks are detected in a multi-layered geomembrane liner by a two-dimensional time domain reflectometry (TDR) technique. The TDR geomembrane liner is constructed with an electrically conductive detection layer positioned between two electrically non-conductive dielectric layers, which are each positioned between the detection layer and an electrically conductive reference layer. The integrity of the TDR geomembrane liner is determined by generating electrical pulses within the detection layer and measuring the time delay for any reflected electrical energy caused by absorption of moisture by a dielectric layer.

Long Term Stratospheric Aerosol Lidar Measurements in Kyushu

NASA Technical Reports Server (NTRS)

Fujiwara, Motowo

1992-01-01

Lidar soundings of the stratospheric aerosols have been made since 1972 at Fukuoka, Kyushu Island of Japan. Volcanic clouds from eruptions of La Soufriere, Sierra Negra, St. Helens, Uluwan, Alaid, unknown volcano, and El Chichon were detected one after another in only three years from 1979 to 1982. In july 1991 strong scattering layers which were originated from the serious eruptions of Pinatubo in June and were almost comparable to the El Chichon clouds were detected. Volcanic clouds from pinatubo and other volcanos mentioned are examined and carefully compared to each other and to the wind and temperature which was measured by Fukuoka Meteorological Observatory almost at the same time as the lidar observation was made.

Mystery #14

Atmospheric Science Data Center

2013-04-22

... play geographical detective! This natural-color image from the Multi-angle Imaging SpectroRadiometer (MISR) instrument on the Terra ... type of clouds pictured here are often associated with lightning and sustained rainstorms lasting several hours or more. 5. ...

Day-time identification of summer hailstorm cells from MSG data

NASA Astrophysics Data System (ADS)

Merino, A.; López, L.; Sánchez, J. L.; García-Ortega, E.; Cattani, E.; Levizzani, V.

2013-10-01

Identifying deep convection is of paramount importance, as it may be associated with extreme weather that has significant impact on the environment, property and the population. A new method, the Hail Detection Tool (HDT), is described for identifying hail-bearing storms using multi-spectral Meteosat Second Generation (MSG) data. HDT was conceived as a two-phase method, in which the first step is the Convective Mask (CM) algorithm devised for detection of deep convection, and the second a Hail Detection algorithm (HD) for the identification of hail-bearing clouds among cumulonimbus systems detected by CM. Both CM and HD are based on logistic regression models trained with multi-spectral MSG data-sets comprised of summer convective events in the middle Ebro Valley between 2006-2010, and detected by the RGB visualization technique (CM) or C-band weather radar system of the University of León. By means of the logistic regression approach, the probability of identifying a cumulonimbus event with CM or a hail event with HD are computed by exploiting a proper selection of MSG wavelengths or their combination. A number of cloud physical properties (liquid water path, optical thickness and effective cloud drop radius) were used to physically interpret results of statistical models from a meteorological perspective, using a method based on these "ingredients." Finally, the HDT was applied to a new validation sample consisting of events during summer 2011. The overall Probability of Detection (POD) was 76.9% and False Alarm Ratio 16.7%.

Development of module for neural network identification of attacks on applications and services in multi-cloud platforms

NASA Astrophysics Data System (ADS)

Parfenov, D. I.; Bolodurina, I. P.

2018-05-01

The article presents the results of developing an approach to detecting and protecting against network attacks on the corporate infrastructure deployed on the multi-cloud platform. The proposed approach is based on the combination of two technologies: a softwareconfigurable network and virtualization of network functions. The approach for searching for anomalous traffic is to use a hybrid neural network consisting of a self-organizing Kohonen network and a multilayer perceptron. The study of the work of the prototype of the system for detecting attacks, the method of forming a learning sample, and the course of experiments are described. The study showed that using the proposed approach makes it possible to increase the effectiveness of the obfuscation of various types of attacks and at the same time does not reduce the performance of the network

A multi-layer steganographic method based on audio time domain segmented and network steganography

NASA Astrophysics Data System (ADS)

Xue, Pengfei; Liu, Hanlin; Hu, Jingsong; Hu, Ronggui

2018-05-01

Both audio steganography and network steganography are belong to modern steganography. Audio steganography has a large capacity. Network steganography is difficult to detect or track. In this paper, a multi-layer steganographic method based on the collaboration of them (MLS-ATDSS&NS) is proposed. MLS-ATDSS&NS is realized in two covert layers (audio steganography layer and network steganography layer) by two steps. A new audio time domain segmented steganography (ATDSS) method is proposed in step 1, and the collaboration method of ATDSS and NS is proposed in step 2. The experimental results showed that the advantage of MLS-ATDSS&NS over others is better trade-off between capacity, anti-detectability and robustness, that means higher steganographic capacity, better anti-detectability and stronger robustness.

A lower limit on the top of Jupiter's haze layer

NASA Technical Reports Server (NTRS)

Cook, A. F., II; Duxbury, T. C.; Hunt, G. E.

1979-01-01

Remote sensing observations of the Jovian atmosphere at wavelengths ranging from UV to the IR are affected by the presence of haze layers above the visible clouds. These layers are difficult to detect as they generally contain submicron particles. In the present paper, a sequence of Voyager images of high-latitude haze, which extends through the Jovian stratosphere into the mesosphere is presented and discussed.

Detecting the building blocks of aromatics

NASA Astrophysics Data System (ADS)

Joblin, Christine; Cernicharo, José

2018-01-01

Interstellar clouds are sites of active organic chemistry (1). Many small, gasphase molecules are found in the dark parts of the clouds that are protected from ultraviolet (UV) photons, but these molecules photodissociate in the external layers of the cloud that are exposed to stellar radiation (see the photo). These irradiated regions are populated by large polycyclic aromatic hydrocarbons (PAHs) with characteristic infrared (IR) emission features. These large aromatics are expected to form from benzene (C6H6), which is, however, difficult to detect because it does not have a permanent dipole moment and can only be detected via its IR absorption transitions against a strong background source (2). On page 202 of this issue, McGuire et al. (3) report the detection of benzonitrile (c-C6H5CN) with radio telescopes. Benzonitrile likely forms in the reaction of CN with benzene; from its observation, it is therefore possible to estimate the abundance of benzene itself.

Clouds, Aerosol, and Precipitation in the Marine Boundary Layer: An ARM Mobile Facility Deployment

NASA Technical Reports Server (NTRS)

Wood, Robert; Wyant, Matthew; Bretherton, Christopher S.; Remillard, Jasmine; Kollias, Pavlos; Fletcher, Jennifer; Stemmler, Jayson; de Szoeke, Simone; Yuter, Sandra; Miller, Matthew;

[Construction and analysis of a monitoring system with remote real-time multiple physiological parameters based on cloud computing].

PubMed

Zhu, Lingyun; Li, Lianjie; Meng, Chunyan

2014-12-01

There have been problems in the existing multiple physiological parameter real-time monitoring system, such as insufficient server capacity for physiological data storage and analysis so that data consistency can not be guaranteed, poor performance in real-time, and other issues caused by the growing scale of data. We therefore pro posed a new solution which was with multiple physiological parameters and could calculate clustered background data storage and processing based on cloud computing. Through our studies, a batch processing for longitudinal analysis of patients' historical data was introduced. The process included the resource virtualization of IaaS layer for cloud platform, the construction of real-time computing platform of PaaS layer, the reception and analysis of data stream of SaaS layer, and the bottleneck problem of multi-parameter data transmission, etc. The results were to achieve in real-time physiological information transmission, storage and analysis of a large amount of data. The simulation test results showed that the remote multiple physiological parameter monitoring system based on cloud platform had obvious advantages in processing time and load balancing over the traditional server model. This architecture solved the problems including long turnaround time, poor performance of real-time analysis, lack of extensibility and other issues, which exist in the traditional remote medical services. Technical support was provided in order to facilitate a "wearable wireless sensor plus mobile wireless transmission plus cloud computing service" mode moving towards home health monitoring for multiple physiological parameter wireless monitoring.

G-band atmospheric radars: new frontiers in cloud physics

NASA Astrophysics Data System (ADS)

Battaglia, A.; Westbrook, C. D.; Kneifel, S.; Kollias, P.; Humpage, N.; Löhnert, U.; Tyynelä, J.; Petty, G. W.

2014-01-01

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud-scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G-band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G-band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

G band atmospheric radars: new frontiers in cloud physics

NASA Astrophysics Data System (ADS)

Battaglia, A.; Westbrook, C. D.; Kneifel, S.; Kollias, P.; Humpage, N.; Löhnert, U.; Tyynelä, J.; Petty, G. W.

2014-06-01

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

Detecting Water Bodies in LANDSAT8 Oli Image Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, W.; He, G.; Long, T.; Ni, Y.

2018-04-01

Water body identifying is critical to climate change, water resources, ecosystem service and hydrological cycle. Multi-layer perceptron(MLP) is the popular and classic method under deep learning framework to detect target and classify image. Therefore, this study adopts this method to identify the water body of Landsat8. To compare the performance of classification, the maximum likelihood and water index are employed for each study area. The classification results are evaluated from accuracy indices and local comparison. Evaluation result shows that multi-layer perceptron(MLP) can achieve better performance than the other two methods. Moreover, the thin water also can be clearly identified by the multi-layer perceptron. The proposed method has the application potential in mapping global scale surface water with multi-source medium-high resolution satellite data.

Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results

NASA Astrophysics Data System (ADS)

Eichmann, Kai-Uwe; Lelli, Luca; von Savigny, Christian; Sembhi, Harjinder; Burrows, John P.

2016-03-01

Cloud top heights (CTHs) are retrieved for the period 1 January 2003 to 7 April 2012 using height-resolved limb spectra measured with the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) on board ENVISAT (ENVIronmental SATellite). In this study, we present the retrieval code SCODA (SCIAMACHY cloud detection algorithm) based on a colour index method and test the accuracy of the retrieved CTHs in comparison to other methods. Sensitivity studies using the radiative transfer model SCIATRAN show that the method is capable of detecting cloud tops down to about 5 km and very thin cirrus clouds up to the tropopause. Volcanic particles can be detected that occasionally reach the lower stratosphere. Upper tropospheric ice clouds are observable for a nadir cloud optical thickness (COT) ≥ 0.01, which is in the subvisual range. This detection sensitivity decreases towards the lowermost troposphere. The COT detection limit for a water cloud top height of 5 km is roughly 0.1. This value is much lower than thresholds reported for passive cloud detection methods in nadir-viewing direction. Low clouds at 2 to 3 km can only be retrieved under very clean atmospheric conditions, as light scattering of aerosol particles interferes with the cloud particle scattering. We compare co-located SCIAMACHY limb and nadir cloud parameters that are retrieved with the Semi-Analytical CloUd Retrieval Algorithm (SACURA). Only opaque clouds (τN,c > 5) are detected with the nadir passive retrieval technique in the UV-visible and infrared wavelength ranges. Thus, due to the frequent occurrence of thin clouds and subvisual cirrus clouds in the tropics, larger CTH deviations are detected between both viewing geometries. Zonal mean CTH differences can be as high as 4 km in the tropics. The agreement in global cloud fields is sufficiently good. However, the land-sea contrast, as seen in nadir cloud occurrence frequency distributions, is not observed in limb geometry. Co-located cloud top height measurements of the limb-viewing Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on ENVISAT are compared for the period from January 2008 to March 2012. The global CTH agreement of about 1 km is observed, which is smaller than the vertical field of view of both instruments. Lower stratospheric aerosols from volcanic eruptions occasionally interfere with the cloud retrieval and inhibit the detection of tropospheric clouds. The aerosol impact on cloud retrievals was studied for the volcanoes Kasatochi (August 2008), Sarychev Peak (June 2009), and Nabro (June 2011). Long-lasting aerosol scattering is detected after these events in the Northern Hemisphere for heights above 12.5 km in tropical and polar latitudes. Aerosol top heights up to about 22 km are found in 2009 and the enhanced lower stratospheric aerosol layer persisted for about 7 months. In August 2009 about 82 % of the lower stratosphere between 30 and 70° N was filled with scattering particles and nearly 50 % in October 2008.

The Venus SAGE Atmospheric Structure Investigation

NASA Technical Reports Server (NTRS)

Colaprete, Anthony; Crisp, Dave; LaBaw, Clayton; Morse, Stephanie

2005-01-01

Experiment goals and objectives are: a) To accurately define the state properties as a function of altitude from below the 10(exp -4) mb level (approx.150 km) to 92 bars (surface); b) To measure the stability of the atmosphere, and identify convective layers and stable layers, where they exist; c) To detect cloud levels from changes in the lapse rate at their boundaries; d) To provide state properties within the cloud levels, and thus provide supplementary information on cloud composition; e) To search for and characterize wave structure within the atmosphere; f) To search for and measure the intensity and scale of turbulence; g) To measure descent and surface wind speed and direction; h) To provide Lander altitude and attitude during decent for descent imaging analysis; and i) To provide a back-up landing sensor.

Orientation of airborne laser scanning point clouds with multi-view, multi-scale image blocks.

PubMed

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters.

Orientation of Airborne Laser Scanning Point Clouds with Multi-View, Multi-Scale Image Blocks

PubMed Central

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters. PMID:22454569

DOE ASR Final Report on “Use of ARM Observations to Investigate the Role of Tropical Radiative Processes and Cloud Radiative Effects in Climate Simulations”

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

Fu, Qiang; Comstock, Jennifer

The overall objective of this ASR funded project is to investigate the role of cloud radiative effects, especially those associated with tropical thin cirrus clouds in the tropical tropopause layer, by analyzing the ARM observations combined with numerical models. In particular, we have processed and analyzed the observations from the Raman lidar at the ARM SGP and TWP sites. In the tenure of the project (8/15/2013 – 8/14/2016 and with a no-cost extension to 8/14/2017), we have been concentrating on (i) developing an automated feature detection scheme of clouds and aerosols for the ARM Raman lidar; (ii) developing an automatedmore » retrieval of cloud and aerosol extinctions for the ARM Raman lidar; (iii) investigating cloud radiative effects based on the observations on the simulated temperatures in the tropical tropopause layer using a radiative-convective model; and (iv) examining the effect of changes of atmospheric composition on the tropical lower-stratospheric temperatures. In addition, we have examined the biases in the CALIPSO-inferred aerosol direct radiative effects using ground-based Raman lidars at the ARM SGP and TWP sites, and estimated the impact of lidar detection sensitivity on assessing global aerosol direct radiative effects. We have also investigated the diurnal cycle of clouds and precipitation at the ARM site using the cloud radar observations along with simulations from the multiscale modeling framework. The main results of our research efforts are reported in the six referred journal publications that acknowledge the DOE Grant DE-SC0010557.« less

Layer stacking: A novel algorithm for individual forest tree segmentation from LiDAR point clouds

Treesearch

Elias Ayrey; Shawn Fraver; John A. Kershaw; Laura S. Kenefic; Daniel Hayes; Aaron R. Weiskittel; Brian E. Roth

2017-01-01

As light detection and ranging (LiDAR) technology advances, it has become common for datasets to be acquired at a point density high enough to capture structural information from individual trees. To process these data, an automatic method of isolating individual trees from a LiDAR point cloud is required. Traditional methods for segmenting trees attempt to isolate...

Operational Exploitation of Satellite-Based Sounding Data and Numerical Weather Prediction Models for Directed Energy Applications

DTIC Science & Technology

2015-12-01

Verification Tool for Laser Environmental Effects Definition and Reference (LEEDR) Development ................................... 45 3.5 Gap Filling with NWP... effective cloud cover for all cloud layers within the AIRS field-of-view. ......................................... 59 Figure 37. Average wind...IR Infrared JPL Jet Propulsion Lab LEEDR Laser Environmental Effects Definition and Reference LIDAR Light Detection and Ranging MODIS Moderate

Secure and robust cloud computing for high-throughput forensic microsatellite sequence analysis and databasing.

PubMed

Bailey, Sarah F; Scheible, Melissa K; Williams, Christopher; Silva, Deborah S B S; Hoggan, Marina; Eichman, Christopher; Faith, Seth A

2017-11-01

Next-generation Sequencing (NGS) is a rapidly evolving technology with demonstrated benefits for forensic genetic applications, and the strategies to analyze and manage the massive NGS datasets are currently in development. Here, the computing, data storage, connectivity, and security resources of the Cloud were evaluated as a model for forensic laboratory systems that produce NGS data. A complete front-to-end Cloud system was developed to upload, process, and interpret raw NGS data using a web browser dashboard. The system was extensible, demonstrating analysis capabilities of autosomal and Y-STRs from a variety of NGS instrumentation (Illumina MiniSeq and MiSeq, and Oxford Nanopore MinION). NGS data for STRs were concordant with standard reference materials previously characterized with capillary electrophoresis and Sanger sequencing. The computing power of the Cloud was implemented with on-demand auto-scaling to allow multiple file analysis in tandem. The system was designed to store resulting data in a relational database, amenable to downstream sample interpretations and databasing applications following the most recent guidelines in nomenclature for sequenced alleles. Lastly, a multi-layered Cloud security architecture was tested and showed that industry standards for securing data and computing resources were readily applied to the NGS system without disadvantageous effects for bioinformatic analysis, connectivity or data storage/retrieval. The results of this study demonstrate the feasibility of using Cloud-based systems for secured NGS data analysis, storage, databasing, and multi-user distributed connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrated Change Detection and Classification in Urban Areas Based on Airborne Laser Scanning Point Clouds.

PubMed

Tran, Thi Huong Giang; Ressl, Camillo; Pfeifer, Norbert

2018-02-03

This paper suggests a new approach for change detection (CD) in 3D point clouds. It combines classification and CD in one step using machine learning. The point cloud data of both epochs are merged for computing features of four types: features describing the point distribution, a feature relating to relative terrain elevation, features specific for the multi-target capability of laser scanning, and features combining the point clouds of both epochs to identify the change. All these features are merged in the points and then training samples are acquired to create the model for supervised classification, which is then applied to the whole study area. The final results reach an overall accuracy of over 90% for both epochs of eight classes: lost tree, new tree, lost building, new building, changed ground, unchanged building, unchanged tree, and unchanged ground.

A hierarchical methodology for urban facade parsing from TLS point clouds

NASA Astrophysics Data System (ADS)

Li, Zhuqiang; Zhang, Liqiang; Mathiopoulos, P. Takis; Liu, Fangyu; Zhang, Liang; Li, Shuaipeng; Liu, Hao

2017-01-01

The effective and automated parsing of building facades from terrestrial laser scanning (TLS) point clouds of urban environments is an important research topic in the GIS and remote sensing fields. It is also challenging because of the complexity and great variety of the available 3D building facade layouts as well as the noise and data missing of the input TLS point clouds. In this paper, we introduce a novel methodology for the accurate and computationally efficient parsing of urban building facades from TLS point clouds. The main novelty of the proposed methodology is that it is a systematic and hierarchical approach that considers, in an adaptive way, the semantic and underlying structures of the urban facades for segmentation and subsequent accurate modeling. Firstly, the available input point cloud is decomposed into depth planes based on a data-driven method; such layer decomposition enables similarity detection in each depth plane layer. Secondly, the labeling of the facade elements is performed using the SVM classifier in combination with our proposed BieS-ScSPM algorithm. The labeling outcome is then augmented with weak architectural knowledge. Thirdly, least-squares fitted normalized gray accumulative curves are applied to detect regular structures, and a binarization dilation extraction algorithm is used to partition facade elements. A dynamic line-by-line division is further applied to extract the boundaries of the elements. The 3D geometrical façade models are then reconstructed by optimizing facade elements across depth plane layers. We have evaluated the performance of the proposed method using several TLS facade datasets. Qualitative and quantitative performance comparisons with several other state-of-the-art methods dealing with the same facade parsing problem have demonstrated its superiority in performance and its effectiveness in improving segmentation accuracy.

A Search for Binary Systems in the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Brown, Cody; Nidever, David L.

2018-06-01

The Large and Small Magellanic Clouds are two of the closest dwarf galaxies to our Milky Way and offer an excellent laboratory to study the evolution of galaxies. The close proximity of these galaxies provide a chance to study individual stars in detail and learn about stellar properties and galactic formation of the Clouds. The Apache Point Observatory Galactic Evolution Experiment (APOGEE), part of the SDSS-IV, has gathered high quality, multi-epoch, spectroscopic data on a multitude of stars in the Magellanic Clouds. The time-series data can be used to detect and characterize binary stars and make the first spectroscopic measurements of the field binary fraction of the Clouds. I will present preliminary results from this project.

Sahara Dust Cloud

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site] Dust Particles Click on the image for Quicktime movie from 7/15-7/24

A continent-sized cloud of hot air and dust originating from the Sahara Desert crossed the Atlantic Ocean and headed towards Florida and the Caribbean. A Saharan Air Layer, or SAL, forms when dry air and dust rise from Africa's west coast and ride the trade winds above the Atlantic Ocean.

These dust clouds are not uncommon, especially during the months of July and August. They start when weather patterns called tropical waves pick up dust from the desert in North Africa, carry it a couple of miles into the atmosphere and drift westward.

In a sequence of images created by data acquired by the Earth-orbiting Atmospheric Infrared Sounder ranging from July 15 through July 24, we see the distribution of the cloud in the atmosphere as it swirls off of Africa and heads across the ocean to the west. Using the unique silicate spectral signatures of dust in the thermal infrared, AIRS can detect the presence of dust in the atmosphere day or night. This detection works best if there are no clouds present on top of the dust; when clouds are present, they can interfere with the signal, making it much harder to detect dust as in the case of July 24, 2005.

In the Quicktime movie, the scale at the bottom of the images shows +1 for dust definitely detected, and ranges down to -1 for no dust detected. The plots are averaged over a number of AIRS observations falling within grid boxes, and so it is possible to obtain fractional numbers. [figure removed for brevity, see original site] Total Water Vapor in the Atmosphere Around the Dust Cloud Click on the image for Quicktime movie

The dust cloud is contained within a dry adiabatic layer which originates over the Sahara Desert. This Saharan Air Layer (SAL) advances Westward over the Atlantic Ocean, overriding the cool, moist air nearer the surface. This burst of very dry air is visible in the AIRS retrieved total water vapor product as a region of depressed water vapor (brown in the images) migrating slowly Westward toward the Caribbean. The SAL phenomenon inhibits the formation of tropical cyclones and thus has given the West Indies and the East Coast of the US a respite from hurricanes.

The Atmospheric Infrared Sounder Experiment, with its visible, infrared, and microwave detectors, provides a three-dimensional look at Earth's weather. Working in tandem, the three instruments can make simultaneous observations all the way down to the Earth's surface, even in the presence of heavy clouds. With more than 2,000 channels sensing different regions of the atmosphere, the system creates a global, 3-D map of atmospheric temperature and humidity and provides information on clouds, greenhouse gases, and many other atmospheric phenomena. The AIRS Infrared Sounder Experiment flies onboard NASA's Aqua spacecraft and is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., under contract to NASA. JPL is a division of the California Institute of Technology in Pasadena.

Comparison between SAGE II and ISCCP high-level clouds. 1: Global and zonal mean cloud amounts

NASA Technical Reports Server (NTRS)

Liao, Xiaohan; Rossow, William B.; Rind, David

1995-01-01

Global high-level clouds identified in Stratospheric Aerosol and Gas Experiment II (SAGE II) occultation measurements for January and July in the period 1985 to 1990 are compared with near-nadir-looking observations from the International Satellite Cloud Climatology Project (ISCCP). Global and zonal mean high-level cloud amounts from the two data sets agree very well, if clouds with layer extinction coefficients of less than 0.008/km at 1.02 micrometers wavelength are removed from the SAGE II results and all detected clouds are interpreted to have an average horizontal size of about 75 km along the 200 km transimission path length of the SAGE II observations. The SAGE II results are much more sensitive to variations of assumed cloud size than to variations of detection threshold. The geographical distribution of cloud fractions shows good agreement, but systematic regional differences also indicate that the average cloud size varies somewhat among different climate regimes. The more sensitive SAGE II results show that about one third of all high-level clouds are missed by ISCCP but that these clouds have very low optical thicknesses (less than 0.1 at 0.6 micrometers wavelength). SAGE II sampling error in monthly zonal cloud fraction is shown to produce no bias, to be less than the intraseasonal natural variability, but to be comparable with the natural variability at longer time scales.

Deformation analysis of a sinkhole in Thuringia using multi-temporal multi-view stereo 3D reconstruction data

NASA Astrophysics Data System (ADS)

Petschko, Helene; Goetz, Jason; Schmidt, Sven

2017-04-01

Sinkholes are a serious threat on life, personal property and infrastructure in large parts of Thuringia. Over 9000 sinkholes have been documented by the Geological Survey of Thuringia, which are caused by collapsing hollows which formed due to solution processes within the local bedrock material. However, little is known about surface processes and their dynamics at the flanks of the sinkhole once the sinkhole has shaped. These processes are of high interest as they might lead to dangerous situations at or within the vicinity of the sinkhole. Our objective was the analysis of these deformations over time in 3D by applying terrestrial photogrammetry with a simple DSLR camera. Within this study, we performed an analysis of deformations within a sinkhole close to Bad Frankenhausen (Thuringia) using terrestrial photogrammetry and multi-view stereo 3D reconstruction to obtain a 3D point cloud describing the morphology of the sinkhole. This was performed for multiple data collection campaigns over a 6-month period. The photos of the sinkhole were taken with a Nikon D3000 SLR Camera. For the comparison of the point clouds the Multiscale Model to Model Comparison (M3C2) plugin of the software CloudCompare was used. It allows to apply advanced methods of point cloud difference calculation which considers the co-registration error between two point clouds for assessing the significance of the calculated difference (given in meters). Three Styrofoam cuboids of known dimensions (16 cm wide/29 cm high/11.5 cm deep) were placed within the sinkhole to test the accuracy of the point cloud difference calculation. The multi-view stereo 3D reconstruction was performed with Agisoft Photoscan. Preliminary analysis indicates that about 26% of the sinkhole showed changes exceeding the co-registration error of the point clouds. The areas of change can mainly be detected on the flanks of the sinkhole and on an earth pillar that formed in the center of the sinkhole. These changes describe toppling (positive change of a few centimeters at the earth pillar) and a few erosion processes along the flanks (negative change of a few centimeters) compared to the first date of data acquisition. Additionally, the Styrofoam cuboids have successfully been detected with an observed depth change of 10 cm. However, the limitations of this approach related to the co-registration of the point clouds and data acquisition (windy conditions) have to be analyzed in more detail.

RACORO Extended-Term Aircraft Observations of Boundary-Layer Clouds

NASA Technical Reports Server (NTRS)

Vogelmann, Andrew M.; McFarquhar, Greg M.; Ogren, John A.; Turner, David D.; Comstock, Jennifer M.; Feingold, Graham; Long, Charles N.; Jonsson, Haflidi H.; Bucholtz, Anthony; Collins, Don R.;

Wonders in the Antarctic Sea and Sky

NASA Image and Video Library

2017-12-08

Wonders in the Antarctic Sea and Sky NASA aircraft and scientists have returned to the United States after a short ice-surveying mission to #Antarctica. Despite having only a week of flying time, the team returned with crucial scientific data and a trove of spectacular aerial photographs. The flights over Antarctica were part of Operation #IceBridge, a multi-year mission to monitor conditions in Antarctica and the Arctic until a new ice-monitoring satellite, ICESat-2, launches in 2016. ICESat-1 was decommissioned in 2009, and IceBridge aircraft have been flying ever since. Laser altimeter and radar data are the primary products of the mission, but IceBridge project scientist Michael Studinger almost always has his digital camera ready as well. On November 24, 2013, he took this photograph of a multi-layered lenticular cloud hovering near Mount Discovery, a volcano about 70 kilometers (44 miles) southwest of McMurdo. Lenticular #clouds are a type of wave cloud. They usually form when a layer of air near the surface encounters a topographic barrier, gets pushed upward, and flows over it as a series of atmospheric gravity waves. Lenticular clouds form at the crest of the waves, where the air is coolest and water vapor is most likely to condense into cloud droplets. The bulging sea ice in the foreground is a pressure ridge, which formed when separate ice floes collided and piled up on each other. Read more: 1.usa.gov/18lXIQS Photograph courtesy of Michael Studinger. Caption by Adam Voiland of NASA's Earth Observatory. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Analysis of aerosol effects on warm clouds over the Yangtze River Delta from multi-sensor satellite observations

NASA Astrophysics Data System (ADS)

Liu, Yuqin; de Leeuw, Gerrit; Kerminen, Veli-Matti; Zhang, Jiahua; Zhou, Putian; Nie, Wei; Qi, Ximeng; Hong, Juan; Wang, Yonghong; Ding, Aijun; Guo, Huadong; Krüger, Olaf; Kulmala, Markku; Petäjä, Tuukka

2017-05-01

Aerosol effects on low warm clouds over the Yangtze River Delta (YRD, eastern China) are examined using co-located MODIS, CALIOP and CloudSat observations. By taking the vertical locations of aerosol and cloud layers into account, we use simultaneously observed aerosol and cloud data to investigate relationships between cloud properties and the amount of aerosol particles (using aerosol optical depth, AOD, as a proxy). Also, we investigate the impact of aerosol types on the variation of cloud properties with AOD. Finally, we explore how meteorological conditions affect these relationships using ERA-Interim reanalysis data. This study shows that the relation between cloud properties and AOD depends on the aerosol abundance, with a different behaviour for low and high AOD (i.e. AOD < 0.35 and AOD > 0.35). This applies to cloud droplet effective radius (CDR) and cloud fraction (CF), but not to cloud optical thickness (COT) and cloud top pressure (CTP). COT is found to decrease when AOD increases, which may be due to radiative effects and retrieval artefacts caused by absorbing aerosol. Conversely, CTP tends to increase with elevated AOD, indicating that the aerosol is not always prone to expand the vertical extension. It also shows that the COT-CDR and CWP (cloud liquid water path)-CDR relationships are not unique, but affected by atmospheric aerosol loading. Furthermore, separation of cases with either polluted dust or smoke aerosol shows that aerosol-cloud interaction (ACI) is stronger for clouds mixed with smoke aerosol than for clouds mixed with dust, which is ascribed to the higher absorption efficiency of smoke than dust. The variation of cloud properties with AOD is analysed for various relative humidity and boundary layer thermodynamic and dynamic conditions, showing that high relative humidity favours larger cloud droplet particles and increases cloud formation, irrespective of vertical or horizontal level. Stable atmospheric conditions enhance cloud cover horizontally. However, unstable atmospheric conditions favour thicker and higher clouds. Dynamically, upward motion of air parcels can also facilitate the formation of thicker and higher clouds. Overall, the present study provides an understanding of the impact of aerosols on cloud properties over the YRD. In addition to the amount of aerosol particles (or AOD), evidence is provided that aerosol types and ambient environmental conditions need to be considered to understand the observed relationships between cloud properties and AOD.

Multilayered Clouds Identification and Retrieval for CERES Using MODIS

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung

2006-01-01

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

Cold Water Vapor in the Barnard 5 Molecular Cloud

NASA Technical Reports Server (NTRS)

Wirstrom, E. S.; Charnley, S. B.; Persson, C. M.; Buckle, J. V.; Cordiner, M. A.; Takakuwa, S.

2014-01-01

After more than 30 yr of investigations, the nature of gas-grain interactions at low temperatures remains an unresolved issue in astrochemistry. Water ice is the dominant ice found in cold molecular clouds; however, there is only one region where cold ((is) approximately 10 K) water vapor has been detected-L1544. This study aims to shed light on ice desorption mechanisms under cold cloud conditions by expanding the sample. The clumpy distribution of methanol in dark clouds testifies to transient desorption processes at work-likely to also disrupt water ice mantles. Therefore, the Herschel HIFI instrument was used to search for cold water in a small sample of prominent methanol emission peaks. We report detections of the ground-state transition of o-H2O (J = 110-101) at 556.9360 GHz toward two positions in the cold molecular cloud, Barnard 5. The relative abundances of methanol and water gas support a desorption mechanism which disrupts the outer ice mantle layers, rather than causing complete mantle removal.

Adaptive Weibull Multiplicative Model and Multilayer Perceptron Neural Networks for Dark-Spot Detection from SAR Imagery

PubMed Central

Taravat, Alireza; Oppelt, Natascha

2014-01-01

Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR), as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM) and MultiLayer Perceptron (MLP) neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN) model generates poor accuracies. PMID:25474376

Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds.

PubMed

Hamraz, Hamid; Contreras, Marco A; Zhang, Jun

2017-07-28

Airborne laser scanning (LiDAR) point clouds over large forested areas can be processed to segment individual trees and subsequently extract tree-level information. Existing segmentation procedures typically detect more than 90% of overstory trees, yet they barely detect 60% of understory trees because of the occlusion effect of higher canopy layers. Although understory trees provide limited financial value, they are an essential component of ecosystem functioning by offering habitat for numerous wildlife species and influencing stand development. Here we model the occlusion effect in terms of point density. We estimate the fractions of points representing different canopy layers (one overstory and multiple understory) and also pinpoint the required density for reasonable tree segmentation (where accuracy plateaus). We show that at a density of ~170 pt/m² understory trees can likely be segmented as accurately as overstory trees. Given the advancements of LiDAR sensor technology, point clouds will affordably reach this required density. Using modern computational approaches for big data, the denser point clouds can efficiently be processed to ultimately allow accurate remote quantification of forest resources. The methodology can also be adopted for other similar remote sensing or advanced imaging applications such as geological subsurface modelling or biomedical tissue analysis.

An empirical method to correct for temperature-dependent variations in the overlap function of CHM15k ceilometers

NASA Astrophysics Data System (ADS)

Hervo, Maxime; Poltera, Yann; Haefele, Alexander

2016-07-01

Imperfections in a lidar's overlap function lead to artefacts in the background, range and overlap-corrected lidar signals. These artefacts can erroneously be interpreted as an aerosol gradient or, in extreme cases, as a cloud base leading to false cloud detection. A correct specification of the overlap function is hence crucial in the use of automatic elastic lidars (ceilometers) for the detection of the planetary boundary layer or of low cloud. In this study, an algorithm is presented to correct such artefacts. It is based on the assumption of a homogeneous boundary layer and a correct specification of the overlap function down to a minimum range, which must be situated within the boundary layer. The strength of the algorithm lies in a sophisticated quality-check scheme which allows the reliable identification of favourable atmospheric conditions. The algorithm was applied to 2 years of data from a CHM15k ceilometer from the company Lufft. Backscatter signals corrected for background, range and overlap were compared using the overlap function provided by the manufacturer and the one corrected with the presented algorithm. Differences between corrected and uncorrected signals reached up to 45 % in the first 300 m above ground. The amplitude of the correction turned out to be temperature dependent and was larger for higher temperatures. A linear model of the correction as a function of the instrument's internal temperature was derived from the experimental data. Case studies and a statistical analysis of the strongest gradient derived from corrected signals reveal that the temperature model is capable of a high-quality correction of overlap artefacts, in particular those due to diurnal variations. The presented correction method has the potential to significantly improve the detection of the boundary layer with gradient-based methods because it removes false candidates and hence simplifies the attribution of the detected gradients to the planetary boundary layer. A particularly significant benefit can be expected for the detection of shallow stable layers typical of night-time situations. The algorithm is completely automatic and does not require any on-site intervention but requires the definition of an adequate instrument-specific configuration. It is therefore suited for use in large ceilometer networks.

Probability theory for 3-layer remote sensing radiative transfer model: univariate case.

PubMed

Ben-David, Avishai; Davidson, Charles E

2012-04-23

A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model. From the Johnson family we use the SU distribution that can address a wide range of skewness and kurtosis values (in addition to addressing the first two moments, mean and variance). In the limit, SU can also describe lognormal and normal distributions. With the probability model one can evaluate the potential for detecting a target (vapor cloud layer), the probability of observing thermal contrast, and evaluate performance (receiver operating characteristics curves) in clutter-noise limited scenarios. This is (to our knowledge) the first probability model for the 3-layer remote sensing geometry that treats all parameters as random variables and includes higher-order statistics. © 2012 Optical Society of America

Understanding the Spatiotemporal Structures in Atmosphere-Land Surface Exchange at the Jülich Observatory for Cloud Evolution

NASA Astrophysics Data System (ADS)

Marke, T.; Crewell, S.; Loehnert, U.; Rascher, U.; Schween, J. H.

2015-12-01

This study aims at identifying spatial and temporal patterns of surface-atmosphere exchange parameters from highly-resolved and long-term observations. For this purpose, a combination of continuous ground-based measurements and dedicated aircraft campaigns using state-of-the-art remote sensing instrumentation at the Jülich Observatory for Cloud Evolution (JOYCE) is available. JOYCE provides a constantly growing multi-year data set for detailed insight into boundary layer processes and patterns related to surface conditions since 2011. The JOYCE site is embedded in a rural environment with different crop types. The availability of a scanning microwave radiometer and cloud radar is a unique component of JOYCE. The hemispheric scans of the ground-based radiometer allow the identification and quantification of horizontal gradients in water vapor and liquid water path measurements. How these gradients are connected to near-surface fluxes and the topography depending on the mean wind flow and surface fluxes is investigated by exploring the long-term data set. Additionally, situations with strong coupling to the surface can be identified by observing the atmospheric turbulence and stability within the boundary layer, using different lidar systems. Furthermore, the influence of thin liquid water clouds, which are typical for the boundary layer development, on the radiation field and the interaction with the vegetation is examined. Applying a synergistic statistical retrieval approach, using passive microwave and infrared observations, shows an improvement in retrieving thin liquid cloud microphysical properties. The role of vegetation is assessed by exploiting the time series of the sun-induced chlorophyll fluorescence (SIF) signal measured at the ground level using automated measurements. For selected case studies, a comparison to maps of hyperspectral reflectance and SIF obtained from an airborne high-resolution imaging spectrometer is realized.

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.

A multiscale modeling framework model (superparameterized CAM5) with a higher-order turbulence closure: Model description and low-cloud simulations

DOE PAGES

Wang, Minghuai; Larson, Vincent E.; Ghan, Steven; ...

2015-04-18

In this study, a higher-order turbulence closure scheme, called Cloud Layers Unified by Binormals (CLUBB), is implemented into a Multi-scale Modeling Framework (MMF) model to improve low cloud simulations. The performance of CLUBB in MMF simulations with two different microphysics configurations (one-moment cloud microphysics without aerosol treatment and two-moment cloud microphysics coupled with aerosol treatment) is evaluated against observations and further compared with results from the Community Atmosphere Model, Version 5 (CAM5) with conventional cloud parameterizations. CLUBB is found to improve low cloud simulations in the MMF, and the improvement is particularly evident in the stratocumulus-to-cumulus transition regions. Compared tomore » the single-moment cloud microphysics, CLUBB with two-moment microphysics produces clouds that are closer to the coast, and agrees better with observations. In the stratocumulus-to cumulus transition regions, CLUBB with two-moment cloud microphysics produces shortwave cloud forcing in better agreement with observations, while CLUBB with single moment cloud microphysics overestimates shortwave cloud forcing. CLUBB is further found to produce quantitatively similar improvements in the MMF and CAM5, with slightly better performance in the MMF simulations (e.g., MMF with CLUBB generally produces low clouds that are closer to the coast than CAM5 with CLUBB). As a result, improved low cloud simulations in MMF make it an even more attractive tool for studying aerosol-cloud-precipitation interactions.« less

Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Preliminary Science Plan

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

Varble, Adam; Nesbitt, Steve; Salio, Paola

General circulation models and downscaled regional models exhibit persistent biases in deep convective initiation location and timing, cloud top height, stratiform area and precipitation fraction, and anvil coverage. Despite important impacts on the distribution of atmospheric heating, moistening, and momentum, nearly all climate models fail to represent convective organization, while system evolution is not represented at all. Improving representation of convective systems in models requires characterization of their predictability as a function of environmental conditions, and this characterization depends on observing many cases of convective initiation, non-initiation, organization, and non-organization. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) experiment inmore » the Sierras de Córdoba mountain range of north-central Argentina is designed to improve understanding of cloud life cycle and organization in relation to environmental conditions so that cumulus, microphysics, and aerosol parameterizations in multi-scale models can be improved. The Sierras de Córdoba range has a high frequency of orographic boundary-layer clouds, many reaching congestus depths, many initiating into deep convection, and some organizing into mesoscale systems uniquely observable from a single fixed site. Some systems even grow upscale to become among the deepest, largest, and longest-lived in the world. These systems likely contribute to an observed regional trend of increasing extreme rainfall, and poor prediction of them likely contributes to a warm, dry bias in climate models downstream of the Sierras de Córdoba range in a key agricultural region. Many environmental factors influence the convective lifecycle in this region including orographic, low-level jet, and frontal circulations, surface fluxes, synoptic vertical motions influenced by the Andes, cloud detrainment, and aerosol properties. Local and long-range transport of smoke resulting from biomass burning as well as blowing dust are common in the austral spring, while changes in land surface properties as the wet season progresses impact surface fluxes and boundary layer evolution on daily and seasonal time scales that feed back to cloud and rainfall generation. This range of environmental conditions and cloud properties coupled with a high frequency of events makes this an ideal location for improving our understanding of cloud-environment interactions. The following primary science questions will be addressed through coordinated first ARM Mobile Facility (AMF1), mobile C-band Scanning ARM Precipitation Radar (C-SAPR2), guest instrumentation, and potential ARM Aerial Facility (AAF) Gulfstream-1 (G-1) observations: 1. How are the properties and lifecycles of orographically generated cumulus humulis, mediocris, and congestus clouds affected by environmental kinematics, thermodynamics, aerosols, and surface properties? How do these cloud types alter these environmental conditions? 2. How do environmental kinematics, thermodynamics, and aerosols impact deep convective initiation, upscale growth, and mesoscale organization? How are soil moisture, surface fluxes, and aerosol properties altered by deep convective precipitation events and seasonal accumulation of precipitation? This multi-faceted experiment involves a long term 8.5-month Extended Observing Period (EOP, 15 August, 2018-30 April, 2019) as well as a 6-week Intensive Observation Period (IOP, 1 November-15 December) that will coincide with the international multi-agency RELAMPAGO field campaign.« less

Domain-averaged, Shallow Precipitation Measurements During the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA)

NASA Astrophysics Data System (ADS)

Lamer, K.; Luke, E. P.; Kollias, P.; Oue, M.; Wang, J.

2017-12-01

The Atmospheric Radiation Measurement (ARM) Climate Research Facility operates a fixed observatory in the Eastern North Atlantic (ENA) on Graciosa Island in the Azores. Straddling the tropics and extratropics, the Azores receive air transported from North America, the Arctic and sometimes Europe. At the ARM ENA site, marine boundary layer clouds are frequently observed all year round. Estimates of drizzle mass flux from the surface to cloud base height are documented using a combination of high sensitivity profiling 35-GHz radar and ceilometer observations. Three years of drizzle mass flux retrievals reveal that statistically, directly over the ENA site, marine boundary layer cloud drizzle rates tend to be weak with few heavy drizzle events. In the summer of 2017, this site hosted the first phase of the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign, which is motivated by the need for comprehensive in situ characterization of boundary layer structure, low clouds and aerosols. During this phase, the 35-GHz scanning ARM cloud radar was operated as a surveillance radar, providing regional context for the profiling observations. While less sensitive, the scanning radar measurements document a larger number of heavier drizzle events and provide domain-representative estimates of shallow precipitation. A best estimate, domain averaged, shallow precipitation rate for the region around the ARM ENA site is presented. The methodology optimally combines the ability of the profiling observations to detect the weak but frequently occurring drizzle events with the scanning cloud radar's ability to capture the less frequent heavier drizzle events. The technique is also evaluated using high resolution model output and a sophisticated forward radar operator.

New single-aircraft integrated atmospheric observation capabilities

NASA Astrophysics Data System (ADS)

Wang, Z.

2011-12-01

Improving current weather and climate model capabilities requires better understandings of many atmospheric processes. Thus, advancing atmospheric observation capabilities has been regarded as the highest imperatives to advance the atmospheric science in the 21st century. Under the NSF CAREER support, we focus on developing new airborne observation capabilities through the developments of new instrumentations and the single-aircraft integration of multiple remote sensors with in situ probes. Two compact Wyoming cloud lidars were built to work together with a 183 GHz microwave radiometer, a multi-beam Wyoming cloud radar and in situ probes for cloud studies. The synergy of these remote sensor measurements allows us to better resolve the vertical structure of cloud microphysical properties and cloud scale dynamics. Together with detailed in situ data for aerosol, cloud, water vapor and dynamics, we developed the most advanced observational capability to study cloud-scale properties and processes from a single aircraft (Fig. 1). A compact Raman lidar was also built to work together with in situ sampling to characterize boundary layer aerosol and water vapor distributions for many important atmospheric processes studies, such as, air-sea interaction and convective initialization. Case studies will be presented to illustrate these new observation capabilities.

Trends and solar cycle effects in mesospheric ice clouds

NASA Astrophysics Data System (ADS)

Lübken, Franz-Josef; Berger, Uwe; Fiedler, Jens; Baumgarten, Gerd; Gerding, Michael

Lidar observations of mesospheric ice layers (noctilucent clouds, NLC) are now available since 12 years which allows to study solar cycle effects on NLC parameters such as altitudes, bright-ness, and occurrence rates. We present observations from our lidar stations in Kuehlungsborn (54N) and ALOMAR (69N). Different from general expectations the mean layer characteris-tics at ALOMAR do not show a persistent anti-correlation with solar cycle. Although a nice anti-correlation of Ly-alpha and occurrence rates is detected in the first half of the solar cycle, occurrence rates decreased with decreasing solar activity thereafter. Interestingly, in summer 2009 record high NLC parameters were detected as expected in solar minimum conditions. The morphology of NLC suggests that other processes except solar radiation may affect NLC. We have recently applied our LIMA model to study in detail the solar cycle effects on tempera-tures and water vapor concentration the middle atmosphere and its subsequent influence on mesospheric ice clouds. Furthermore, lower atmosphere effects are implicitly included because LIMA nudges to the conditions in the troposphere and lower stratosphere. We compare LIMA results regarding solar cycle effects on temperatures and ice layers with observations at ALO-MAR as well as satellite borne measurements. We will also present LIMA results regarding the latitude variation of solar cycle and trends, including a comparison of northern and southern hemisphere. We have adapted the observation conditions from SBUV (wavelength and scatter-ing angle) in LIMA for a detailed comparison with long term observations of ice clouds from satellites.

Validation of the Two-Layer Model for Correcting Clear Sky Reflectance Near Clouds

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Evans, K. Frank; Vamal, Tamas

2014-01-01

A two-layer model was developed in our earlier studies to estimate the clear sky reflectance enhancement near clouds. This simple model accounts for the radiative interaction between boundary layer clouds and molecular layer above, the major contribution to the reflectance enhancement near clouds for short wavelengths. We use LES/SHDOM simulated 3D radiation fields to valid the two-layer model for reflectance enhancement at 0.47 micrometer. We find: (a) The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; and (b) The magnitude of the 2-layer modeled enhancement agree reasonably well with the "truth" with some expected underestimation. We further extend our model to include cloud-surface interaction using the Poisson model for broken clouds. We found that including cloud-surface interaction improves the correction, though it can introduced some over corrections for large cloud albedo, large cloud optical depth, large cloud fraction, large cloud aspect ratio. This over correction can be reduced by excluding scenes (10 km x 10km) with large cloud fraction for which the Poisson model is not designed for. Further research is underway to account for the contribution of cloud-aerosol radiative interaction to the enhancement.

Observed aerosol effects on marine cloud nucleation and supersaturation

NASA Astrophysics Data System (ADS)

Russell, Lynn M.; Sorooshian, Armin; Seinfeld, John H.; Albrecht, Bruce A.; Nenes, Athanasios; Leaitch, W. Richard; Macdonald, Anne Marie; Ahlm, Lars; Chen, Yi-Chun; Coggon, Matthew; Corrigan, Ashley; Craven, Jill S.; Flagan, Richard C.; Frossard, Amanda A.; Hawkins, Lelia N.; Jonsson, Haflidi; Jung, Eunsil; Lin, Jack J.; Metcalf, Andrew R.; Modini, Robin; Mülmenstädt, Johannes; Roberts, Greg C.; Shingler, Taylor; Song, Siwon; Wang, Zhen; Wonaschütz, Anna

2013-05-01

Aerosol particles in the marine boundary layer include primary organic and salt particles from sea spray and combustion-derived particles from ships and coastal cities. These particle types serve as nuclei for marine cloud droplet activation, although the particles that activate depend on the particle size and composition as well as the supersaturation that results from cloud updraft velocities. The Eastern Pacific Emitted Aerosol Cloud Experiment (EPEACE) 2011 was a targeted aircraft campaign to assess how different particle types nucleate cloud droplets. As part of E-PEACE 2011, we studied the role of marine particles as cloud droplet nuclei and used emitted particle sources to separate particle-induced feedbacks from dynamical variability. The emitted particle sources included shipboard smoke-generated particles with 0.05-1 μm diameters (which produced tracks measured by satellite and had drop composition characteristic of organic smoke) and combustion particles from container ships with 0.05-0.2 μm diameters (which were measured in a variety of conditions with droplets containing both organic and sulfate components) [1]. Three central aspects of the collaborative E-PEACE results are: (1) the size and chemical composition of the emitted smoke particles compared to ship-track-forming cargo ship emissions as well as background marine particles, with particular attention to the role of organic particles, (2) the characteristics of cloud track formation for smoke and cargo ships, as well as the role of multi-layered low clouds, and (3) the implications of these findings for quantifying aerosol indirect effects. For comparison with the E-PEACE results, the preliminary results of the Stratocumulus Observations of Los-Angeles Emissions Derived Aerosol-Droplets (SOLEDAD) 2012 provided evidence of the cloud-nucleating roles of both marine organic particles and coastal urban pollution, with simultaneous measurements of the effective supersaturations of the clouds in the California coastal region.

Gravity Waves Ripple over Marine Stratocumulus Clouds

NASA Technical Reports Server (NTRS)

2004-01-01

In this natural-color image from the Multi-angle Imaging SpectroRadiometer (MISR), a fingerprint-like gravity wave feature occurs over a deck of marine stratocumulus clouds. Similar to the ripples that occur when a pebble is thrown into a still pond, such 'gravity waves' sometimes appear when the relatively stable and stratified air masses associated with stratocumulus cloud layers are disturbed by a vertical trigger from the underlying terrain, or by a thunderstorm updraft or some other vertical wind shear. The stratocumulus cellular clouds that underlie the wave feature are associated with sinking air that is strongly cooled at the level of the cloud-tops -- such clouds are common over mid-latitude oceans when the air is unperturbed by cyclonic or frontal activity. This image is centered over the Indian Ocean (at about 38.9o South, 80.6o East), and was acquired on October 29, 2003.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82o north and 82o south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 20545. The image covers an area of 245 kilometers x 378 kilometers, and uses data from blocks 121 to 122 within World Reference System-2 path 134.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Optical cloud detection from a disposable airborne sensor

NASA Astrophysics Data System (ADS)

Nicoll, Keri; Harrison, R. Giles; Brus, David

2016-04-01

In-situ measurement of cloud droplet microphysical properties is most commonly made from manned aircraft platforms due to the size and weight of the instrumentation, which is both costly and typically limited to sampling only a few clouds. This work describes the development of a small, lightweight (<200g), disposable, optical cloud sensor which is designed for use on routine radiosonde balloon flights and also small unmanned aerial vehicle (UAV) platforms. The sensor employs the backscatter principle, using an ultra-bright LED as the illumination source, with a photodiode detector. Scattering of the LED light by cloud droplets generates a small optical signal which is separated from background light fluctuations using a lock-in technique. The signal to noise obtained permits cloud detection using the scattered LED light, even in daytime. During recent field tests in Pallas, Finland, the retrieved optical sensor signal has been compared with the DMT Cloud and Aerosol Spectrometer (CAS) which measures cloud droplets in the size range from 0.5 to 50 microns. Both sensors were installed at the hill top observatory of Sammaltunturi during a field campaign in October and November 2015, which experienced long periods of immersion inside cloud. Preliminary analysis shows very good agreement between the CAPS and the disposable cloud sensor for cloud droplets >5micron effective diameter. Such data and calibration of the sensor will be discussed here, as will simultaneous balloon launches of the optical cloud sensor through the same cloud layers.

A 19-Month Climatology of Marine Aerosol-Cloud-Radiation Properties Derived From DOE ARM AMF Deployment at the Azores: Part I: Cloud Fraction and Single-Layered MBL Cloud Properties

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Xi, Baike; Kennedy, Aaron; Minnis, Patrick; Wood, Robert

2013-01-01

A 19-month record of total, and single-layered low (0-3 km), middle (3-6 km), and high (> 6 km) cloud fractions (CFs), and the single-layered marine boundary layer (MBL) cloud macrophysical and microphysical properties has been generated from ground-based measurements taken at the ARM Azores site between June 2009 and December 2010. It documents the most comprehensive and longest dataset on marine cloud fraction and MBL cloud properties to date. The annual means of total CF, and single-layered low, middle, and high CFs derived from ARM radar-lidar observations are 0.702, 0.271, 0.01 and 0.106, respectively. More total and single-layered high CFs occurred during winter, while single-layered low CFs were greatest during summer. The diurnal cycles for both total and low CFs are stronger during summer than during winter. The CFs are bimodally distributed in the vertical with a lower peak at approx. 1 km and higher one between 8 and 11 km during all seasons, except summer, when only the low peak occurs. The persistent high pressure and dry conditions produce more single-layered MBL clouds and fewer total clouds during summer, while the low pressure and moist air masses during winter generate more total and multilayered-clouds, and deep frontal clouds associated with midlatitude cyclones.

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.

Climatic Implications of the Observed Temperature Dependence of the Liquid Water Path of Low Clouds in the Southern Great Plains

NASA Technical Reports Server (NTRS)

DelGenio, Anthony

1999-01-01

Satellite observations of low-level clouds have challenged the assumption that adiabatic liquid water content combined with constant physical thickness will lead to a negative cloud optics feedback in a decadal climate change. We explore the reasons for the satellite results using four years of surface remote sensing data from the Atmospheric Radiation Measurement Program Cloud and Radiation Testbed site in the Southern Great Plains of the United States. We find that low cloud liquid water path is approximately invariant with temperature in winter but decreases strongly with temperature in summer, consistent with the satellite inferences at this latitude. This behavior occurs because liquid water content shows no detectable temperature dependence while cloud physical thickness decreases with warming. Thinning of clouds with warming is observed on seasonal, synoptic, and diurnal time scales; it is most obvious in the warm sectors of baroclinic waves. Although cloud top is observed to slightly descend with warming, the primary cause of thinning, is the ascent of cloud base due to the reduction in surface relative humidity and the concomitant increase in the lifting condensation level of surface air. Low cloud liquid water path is not observed to be a continuous function of temperature. Rather, the behavior we observe is best explained as a transition in the frequency of occurrence of different boundary layer types. At cold temperatures, a mixture of stratified and convective boundary layers is observed, leading to a broad distribution of liquid water path values, while at warm temperatures, only convective boundary layers with small liquid water paths, some of them decoupled, are observed. Our results, combined with the earlier satellite inferences, imply that the commonly quoted 1.5C lower limit for the equilibrium global climate sensitivity to a doubling of CO2 which is based on models with near-adiabatic liquid water behavior and constant physical thickness, should be revised upward.

Climatic Implications of the Observed Temperature Dependence of the Liquid Water Path of Low Clouds in the Southern Great Plains

NASA Technical Reports Server (NTRS)

DelGenio, Anthony D.; Wolf, Audrey B.

1999-01-01

Satellite observations of low-level clouds have challenged the assumption that adiabatic liquid water content combined with constant physical thickness will lead to a negative cloud optics feedback in a decadal climate change. We explore the reasons for the satellite results using four years of surface remote sensing data from the Atmospheric Radiation Measurement Program Cloud and Radiation Testbed site in the Southern Great Plains of the United States. We find that low cloud liquid water path is approximately invariant with temperature in winter but decreases strongly with temperature in summer, consistent with the satellite inferences at this latitude. This behavior occurs because liquid water content shows no detectable temperature dependence while cloud physical thickness decreases with warming. Thinning of clouds with warming is observed on seasonal, synoptic, and diurnal time scales; it is most obvious in the warm sectors of baroclinic waves. Although cloud top is observed to slightly descend with warming, the primary cause of thinning is the ascent of cloud base due to the reduction in surface relative humidity and the concomitant increase in the lifting condensation level of surface air. Low cloud liquid water path is not observed to be a continuous function of temperature. Rather, the behavior we observe is best explained as a transition in the frequency of occurrence of different boundary layer types: At cold temperatures, a mixture of stratified and convective boundary layers is observed, leading to a broad distribution of liquid water path values, while at warm temperatures, only convective boundary layers with small liquid water paths, some of them decoupled, are observed. Our results, combined with the earlier satellite inferences, imply that the commonly quoted 1.50 C lower limit for the equilibrium global climate sensitivity to a doubling of CO2, which is based on models with near-adiabatic liquid water behavior and constant physical thickness, should be revised upward.

Coastal Observations of Weather Features in Senegal during the AMMA SOP-3 Period

NASA Technical Reports Server (NTRS)

Jenkins, G.; Kucera, P.; Joseph, E.; Fuentes, J.; Gaye, A.; Gerlach, J.; Roux, F.; Viltard, N.; Papazzoni, M.; Protat, A.;

SST Variation Due to Interactive Convective-Radiative Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shie, C.-L.; Johnson, D.; Simpson, J.; Li, X.; Sui, C.-H.

2000-01-01

The recent linking of Cloud-Resolving Models (CRMs) to Ocean-Mixed Layer (OML) models has provided a powerful new means of quantifying the role of cloud systems in ocean-atmosphere coupling. This is due to the fact that the CRM can better resolve clouds and cloud systems and allow for explicit cloud-radiation interaction. For example, Anderson (1997) applied an atmospheric forcing associated with a CRM simulated squall line to a 3-D OML model (one way or passive interaction). His results suggested that the spatial variability resulting from the squall forcing can last at least 24 hours when forced with otherwise spatially uniform fluxes. In addition, the sea surface salinity (SSS) variability continuously decreased following the forcing, while some of the SST variability remained when a diurnal mixed layer capped off the surface structure. The forcing used in the OML model, however, focused on shorter time (8 h) and smaller spatial scales (100-120 km). In this study, the 3-D Goddard Cumulus Ensemble Model (GCE; 512 x 512 x 23 cu km, 2-km horizontal resolution) is used to simulate convective active episodes occurring in the Western Pacific warm pool and Eastern Atlantic regions. The model is integrated for seven days, and the simulated results are coupled to an OML model to better understand the impact of precipitation and changes in the planetary boundary layer upon SST variation. We will specifically examine and compare the results of linking the OML model with various spatially-averaged outputs from GCE simulations (i.e., 2 km vs. 10-50 km horizontal resolutions), in order to help understand the SST sensitivity to multi-scale influences. This will allow us to assess the importance of explicitly simulated deep and shallow clouds, as well as the subgrid-scale effects (in coarse-model runs) upon SST variation. Results using both 1-D and 2-D OML models will be evaluated to assess the effects of horizontal advection.

Hot Jupiter with Hidden Water (Artist Concept)

NASA Image and Video Library

2016-06-08

Hot Jupiters, exoplanets around the same size as Jupiter that orbit very closely to their stars, often have cloud or haze layers in their atmospheres. This may prevent space telescopes from detecting atmospheric water that lies beneath the clouds, according to a study in the Astrophysical Journal. As much as half of the water in the atmospheres of these exoplanets may be blocked by these clouds or hazes, research suggests. The study, led by researchers at NASA's Jet Propulsion Laboratory, Pasadena, California, examined hot Jupiters that had been observed with the Hubble Space Telescope. http://photojournal.jpl.nasa.gov/catalog/PIA20687

Images from Galileo of the Venus cloud deck

USGS Publications Warehouse

Belton, M.J.S.; Gierasch, P.J.; Smith, M.D.; Helfenstein, P.; Schinder, P.J.; Pollack, James B.; Rages, K.A.; Ingersoll, A.P.; Klaasen, K.P.; Veverka, J.; Anger, C.D.; Carr, M.H.; Chapman, C.R.; Davies, M.E.; Fanale, F.P.; Greeley, R.; Greenberg, R.; Head, J. W.; Morrison, D.; Neukum, G.; Pilcher, C.B.

1991-01-01

Images of Venus taken at 418 (violet) and 986 [near-infrared (NIR)] nanometers show that the morphology and motions of large-scale features change with depth in the cloud deck. Poleward meridional velocities, seen in both spectral regions, are much reduced in the NIR. In the south polar region the markings in the two wavelength bands are strongly anticorrelated. The images follow the changing state of the upper cloud layer downwind of the subsolar point, and the zonal flow field shows a longitudinal periodicity that may be coupled to the formation of large-scale planetary waves. No optical lightning was detected.

Ceramic Electron Multiplier

DOE PAGES

Comby, G.

1996-10-01

The Ceramic Electron Multipliers (CEM) is a compact, robust, linear and fast multi-channel electron multiplier. The Multi Layer Ceramic Technique (MLCT) allows to build metallic dynodes inside a compact ceramic block. The activation of the metallic dynodes enhances their secondary electron emission (SEE). The CEM can be used in multi-channel photomultipliers, multi-channel light intensifiers, ion detection, spectroscopy, analysis of time of flight events, particle detection or Cherenkov imaging detectors. (auth)

Characteristics of cloud occurrence using ceilometer measurements and its relationship to precipitation over Seoul

NASA Astrophysics Data System (ADS)

Lee, Sanghee; Hwang, Seung-On; Kim, Jhoon; Ahn, Myoung-Hwan

2018-03-01

Clouds are an important component of the atmosphere that affects both climate and weather, however, their contributions can be very difficult to determine. Ceilometer measurements can provide high resolution information on atmospheric conditions such as cloud base height (CBH) and vertical frequency of cloud occurrence (CVF). This study presents the first comprehensive analysis of CBH and CVF derived using Vaisala CL51 ceilometers at two urban stations in Seoul, Korea, during a three-year period from January 2014 to December 2016. The average frequency of cloud occurrence detected by the ceilometers is 54.3%. It is found that the CL51 is better able to capture CBH as compared to another ceilometer CL31 at a nearby meteorological station because it could detect high clouds more accurately. Frequency distributions for CBH up to 13,000 m providing detailed vertical features with 500-m interval show 55% of CBHs below 2 km for aggregated CBHs. A bimodal frequency distribution was observed for three-layers CBHs. A monthly variation of CVF reveals that frequency concentration of lower clouds is found in summer and winter, and higher clouds more often detected in spring and autumn. Monthly distribution features of cloud occurrence and precipitation are depending on seasons and it might be easy to define their relationship due to higher degree of variability of precipitation than cloud occurrence. However, a fluctuation of cloud occurrence frequency in summer is similar to precipitation in trend, whereas clouds in winter are relatively frequent but precipitation is not accompanied. In addition, recent decrease of summer precipitation could be mostly explained by a decrease of cloud occurrence. Anomalous precipitation recorded sometimes is considerably related to corresponding cloud occurrence. The diurnal and daily variations of CBH and CVF from ceilometer observations and the analysis of microwave radiometer measurements for two typical cloudiness cases are also reviewed in parallel. This analysis in finer temporal scale exhibits that utilization of ground-based observations together could help to analyze the cloud behaviors.

Comparative Study of Aerosol and Cloud Detected by CALIPSO and OMI

NASA Technical Reports Server (NTRS)

Chen, Zhong; Torres, Omar; McCormick, M. Patrick; Smith, William; Ahn, Changwoo

2012-01-01

The Ozone Monitoring Instrument (OMI) on the Aura Satellite detects the presence of desert dust and smoke particles (also known as aerosols) in terms of a parameter known as the UV Aerosol Index (UV AI). The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission measures the vertical distribution of aerosols and clouds. Aerosols and clouds play important roles in the atmosphere and climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a very important task. This paper presents a comparative analysis of the CALIPSO Version 2 Vertical Feature Mask (VFM) product with the (OMI) UV Aerosol Index (UV AI) and reflectivity datasets for a full year of 2007. The comparison is done at regional and global scales. Based on CALIPSO arid OMI observations, the vertical and horizontal extent of clouds and aerosols are determined and the effects of aerosol type selection, load, cloud fraction on aerosol identification are discussed. It was found that the spatial-temporal correlation found between CALIPSO and OMI observations, is strongly dependent on aerosol types and cloud contamination. CALIPSO is more sensitivity to cloud and often misidentifies desert dust aerosols as cloud, while some small scale aerosol layers as well as some pollution aerosols are unidentified by OMI UV AI. Large differences in aerosol distribution patterns between CALIPSO and OMI are observed, especially for the smoke and pollution aerosol dominated areas. In addition, the results found a significant correlation between CALIPSO lidar 1064 nm backscatter and the OMI UV AI over the study regions.

A Sample of What We Have Learned from A-Train Cloud Measurements

NASA Technical Reports Server (NTRS)

Joiner, Joanna; Vasilkov, Alexander; Ziemke, Jerry; Chandra, Sushil; Spurr, Robert; Bhartia, P. K.; Krotkov, Nick; Sneep, Maarten; Menzel, Paul; Platnick, Steve;

D Building FAÇADE Reconstruction Using Handheld Laser Scanning Data

NASA Astrophysics Data System (ADS)

Sadeghi, F.; Arefi, H.; Fallah, A.; Hahn, M.

2015-12-01

3D The three dimensional building modelling has been an interesting topic of research for decades and it seems that photogrammetry methods provide the only economic means to acquire truly 3D city data. According to the enormous developments of 3D building reconstruction with several applications such as navigation system, location based services and urban planning, the need to consider the semantic features (such as windows and doors) becomes more essential than ever, and therefore, a 3D model of buildings as block is not any more sufficient. To reconstruct the façade elements completely, we employed the high density point cloud data that obtained from the handheld laser scanner. The advantage of the handheld laser scanner with capability of direct acquisition of very dense 3D point clouds is that there is no need to derive three dimensional data from multi images using structure from motion techniques. This paper presents a grammar-based algorithm for façade reconstruction using handheld laser scanner data. The proposed method is a combination of bottom-up (data driven) and top-down (model driven) methods in which, at first the façade basic elements are extracted in a bottom-up way and then they are served as pre-knowledge for further processing to complete models especially in occluded and incomplete areas. The first step of data driven modelling is using the conditional RANSAC (RANdom SAmple Consensus) algorithm to detect façade plane in point cloud data and remove noisy objects like trees, pedestrians, traffic signs and poles. Then, the façade planes are divided into three depth layers to detect protrusion, indentation and wall points using density histogram. Due to an inappropriate reflection of laser beams from glasses, the windows appear like holes in point cloud data and therefore, can be distinguished and extracted easily from point cloud comparing to the other façade elements. Next step, is rasterizing the indentation layer that holds the windows and doors information. After rasterization process, the morphological operators are applied in order to remove small irrelevant objects. Next, the horizontal splitting lines are employed to determine floors and vertical splitting lines are employed to detect walls, windows, and doors. The windows, doors and walls elements which are named as terminals are clustered during classification process. Each terminal contains a special property as width. Among terminals, windows and doors are named the geometry tiles in definition of the vocabularies of grammar rules. Higher order structures that inferred by grouping the tiles resulted in the production rules. The rules with three dimensional modelled façade elements constitute formal grammar that is named façade grammar. This grammar holds all the information that is necessary to reconstruct façades in the style of the given building. Thus, it can be used to improve and complete façade reconstruction in areas with no or limited sensor data. Finally, a 3D reconstructed façade model is generated that the accuracy of its geometry size and geometry position depends on the density of the raw point cloud.

Towards an e-Health Cloud Solution for Remote Regions at Bahia-Brazil.

PubMed

Sarinho, V T; Mota, A O; Silva, E P

2017-12-19

This paper presents CloudMedic, an e-Health Cloud solution that manages health care services in remote regions of Bahia-Brazil. For that, six main modules: Clinic, Hospital, Supply, Administrative, Billing and Health Business Intelligence, were developed to control the health flow among health actors at health institutions. They provided database model and procedures for health business rules, a standard gateway for data maintenance between web views and database layer, and a multi-front-end framework based on web views and web commands configurations. These resources were used by 2042 health actors in 261 health posts covering health demands from 118 municipalities at Bahia state. They also managed approximately 2.4 million health service 'orders and approximately 13.5 million health exams for more than 1.3 million registered patients. As a result, a collection of health functionalities available in a cloud infrastructure was successfully developed, deployed and validated in more than 28% of Bahia municipalities. A viable e-Health Cloud solution that, despite municipality limitations in remote regions, decentralized and improved the access to health care services at Bahia state.

Boundary-layer cumulus over heterogeneous landscapes: A subgrid GCM parameterization. Final report, December 1991--November 1995

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

Stull, R.B.; Tripoli, G.

1996-01-08

The authors developed single-column parameterizations for subgrid boundary-layer cumulus clouds. These give cloud onset time, cloud coverage, and ensemble distributions of cloud-base altitudes, cloud-top altitudes, cloud thickness, and the characteristics of cloudy and clear updrafts. They tested and refined the parameterizations against archived data from Spring and Summer 1994 and 1995 intensive operation periods (IOPs) at the Southern Great Plains (SGP) ARM CART site near Lamont, Oklahoma. The authors also found that: cloud-base altitudes are not uniform over a heterogeneous surface; tops of some cumulus clouds can be below the base-altitudes of other cumulus clouds; there is an overlap regionmore » near cloud base where clear and cloudy updrafts exist simultaneously; and the lognormal distribution of cloud sizes scales to the JFD of surface layer air and to the shape of the temperature profile above the boundary layer.« less

Remote Sensing of Supercooled Cloud Layers in Cold Climate Using Ground Based Integrated Sensors System and Comparison with Pilot Reports and model forecasts

NASA Astrophysics Data System (ADS)

Boudala, Faisal; Wu, Di; Gultepe, Ismail; Anderson, Martha; turcotte, marie-france

2017-04-01

In-flight aircraft icing is one of the major weather hazards to aviation . It occurs when an aircraft passes through a cloud layer containing supercooled drops (SD). The SD in contact with the airframe freezes on the surface which degrades the performance of the aircraft.. Prediction of in-flight icing requires accurate prediction of SD sizes, liquid water content (LWC), and temperature. The current numerical weather predicting (NWP) models are not capable of making accurate prediction of SD sizes and associated LWC. Aircraft icing environment is normally studied by flying research aircraft, which is quite expensive. Thus, developing a ground based remote sensing system for detection of supercooled liquid clouds and characterization of their impact on severity of aircraft icing one of the important tasks for improving the NWPs based predictions and validations. In this respect, Environment and Climate Change Canada (ECCC) in cooperation with the Department of National Defense (DND) installed a number of specialized ground based remote sensing platforms and present weather sensors at Cold Lake, Alberta that includes a multi-channel microwave radiometer (MWR), K-band Micro Rain radar (MRR), Ceilometer, Parsivel distrometer and Vaisala PWD22 present weather sensor. In this study, a number of pilot reports confirming icing events and freezing precipitation that occurred at Cold Lake during the 2014-2016 winter periods and associated observation data for the same period are examined. The icing events are also examined using aircraft icing intensity estimated using ice accumulation model which is based on a cylindrical shape approximation of airfoil and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predicted LWC, median volume diameter and temperature. The results related to vertical atmospheric profiling conditions, surface observations, and the Canadian High Resolution Regional Deterministic Prediction System (HRDPS) model predictions are given. Preliminary results suggest that remote sensing and present weather sensors based observations of cloud SD regions can be used to describe micro and macro physical characteristics of the icing conditions. The model based icing intensity prediction reasonably agreed with the PIREPs and MWR observations.

A comparison between CloudSat and aircraft data for a multilayer, mixed phase cloud system during the Canadian CloudSat-CALIPSO Validation Project

NASA Astrophysics Data System (ADS)

Barker, H. W.; Korolev, A. V.; Hudak, D. R.; Strapp, J. W.; Strawbridge, K. B.; Wolde, M.

2008-04-01

Reflectivities recorded by the W-band Cloud Profiling Radar (CPR) aboard NASA's CloudSat satellite and some of CloudSat's retrieval products are compared to Ka-band radar reflectivities and in situ cloud properties gathered by instrumentation on the NRC's Convair-580 aircraft. On 20 February 2007, the Convair flew several transects along a 60 nautical mile stretch of CloudSat's afternoon ground track over southern Quebec. On one of the transects it was well within CloudSat's radar's footprint while in situ sampling a mixed phase boundary layer cloud. A cirrus cloud was also sampled before and after overpass. Air temperature and humidity profiles from ECMWF reanalyses, as employed in CloudSat's retrieval stream, agree very well with those measured by the Convair. The boundary layer cloud was clearly visible, to the eye and lidar, and dominated the region's solar radiation budget. It was, however, often below or near the Ka-band's distance-dependent minimum detectable signal. In situ samples at overpass revealed it to be composed primarily of small, supercooled droplets at the south end and increasingly intermixed with ice northward. Convair and CloudSat CPR reflectivities for the low cloud agree well, but while CloudSat properly ascribed it as overcast, mixed phase, and mostly liquid near the south end, its estimates of liquid water content LWC (and visible extinction coefficient κ) and droplet effective radii are too small and large, respectively. The cirrus consisted largely of irregular crystals with typical effective radii ˜150 μm. While both CPR reflectivities agree nicely, CloudSat's estimates of crystal number concentrations are too large by a factor of 5. Nevertheless, distributions of ice water content and κ deduced from in situ data agree quite well with values retrieved from CloudSat algorithms.

DISCRIMINATING BETWEEN CLOUDY, HAZY, AND CLEAR SKY EXOPLANETS USING REFRACTION

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

Misra, Amit K.; Meadows, Victoria S.

2014-11-01

We propose a method to distinguish between cloudy, hazy, and clear sky (free of clouds and hazes) exoplanet atmospheres that could be applicable to upcoming large aperture space- and ground-based telescopes such as the James Webb Space Telescope (JWST) and the European Extremely Large Telescope (E-ELT). These facilities will be powerful tools for characterizing transiting exoplanets, but only after a considerable amount of telescope time is devoted to a single planet. A technique that could provide a relatively rapid means of identifying haze-free targets (which may be more valuable targets for characterization) could potentially increase the science return for thesemore » telescopes. Our proposed method utilizes broadband observations of refracted light in the out-of-transit spectrum. Light refracted through an exoplanet atmosphere can lead to an increase of flux prior to ingress and subsequent to egress. Because this light is transmitted at pressures greater than those for typical cloud and haze layers, the detection of refracted light could indicate a cloud- or haze-free atmosphere. A detection of refracted light could be accomplished in <10 hr for Jovian exoplanets with JWST and <5 hr for super-Earths/mini-Neptunes with E-ELT. We find that this technique is most effective for planets with equilibrium temperatures between 200 and 500 K, which may include potentially habitable planets. A detection of refracted light for a potentially habitable planet would strongly suggest the planet was free of a global cloud or haze layer, and therefore a promising candidate for follow-up observations.« less

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.

Quantified Objectives for Assessing the Contribution of Low Clouds to Climate Sensitivity and Variability

NASA Astrophysics Data System (ADS)

Del Genio, A. D.; Platnick, S. E.; Bennartz, R.; Klein, S. A.; Marchand, R.; Oreopoulos, L.; Pincus, R.; Wood, R.

2016-12-01

Low clouds are central to leading-order questions in climate and subseasonal weather predictability, and are key to the NRC panel report's goals "to understand the signals of the Earth system under a changing climate" and "for improved models and model projections." To achieve both goals requires a mix of continuity observations to document the components of the changing climate and improvements in retrievals of low cloud and boundary layer dynamical/thermodynamic properties to ensure process-oriented observations that constrain the parameterized physics of the models. We discuss four climate/weather objectives that depend sensitively on understanding the behavior of low clouds: 1. Reduce uncertainty in GCM-inferred climate sensitivity by 50% by constraining subtropical low cloud feedbacks. 2. Eliminate the GCM Southern Ocean shortwave flux bias and its effect on cloud feedback and the position of the midlatitude storm track. 3. Eliminate the double Intertropical Convergence Zone bias in GCMs and its potential effects on tropical precipitation over land and the simulation and prediction of El Niño. 4. Increase the subseasonal predictability of tropical warm pool precipitation from 20 to 30 days. We envision advances in three categories of observations that would be highly beneficial for reaching these goals: 1. More accurate observations will facilitate more thorough evaluation of clouds in GCMs. 2. Better observations of the links between cloud properties and the environmental state will be used as the foundation for parameterization improvements. 3. Sufficiently long and higher quality records of cloud properties and environmental state will constrain low cloud feedback purely observationally. To accomplish this, the greatest need is to replace A-Train instruments, which are nearing end-of-life, with enhanced versions. The requirements are sufficient horizontal and vertical resolution to capture boundary layer cloud and thermodynamic spatial structure; more accurate determination of cloud condensate profiles and optical properties; near-coincident observations to permit multi-instrument retrievals and association with dynamic and thermodynamic structure; global coverage; and, for long-term monitoring, measurement and orbit stability and sufficient mission duration.

Cloud Type Classification (cldtype) Value-Added Product

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

Flynn, Donna; Shi, Yan; Lim, K-S

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

Inhomogeneities in frontal cirrus clouds

NASA Astrophysics Data System (ADS)

Neis, Patrick; Krämer, Martina; Hoor, Peter; Reutter, Philipp; Spichtinger, Peter

2013-04-01

Frontal cirrus clouds have a scientifically proven effect on the Earth's radiation budget and thereby an influence on the weather and climate change in regional scale. The formation processes and structures of frontal cirrus clouds are still not fully understood. For a close investigation of typical frontal cirrus clouds, we use in situ measurements from the CIRRUS-III campaign over Germany and Northern Europe in November 2006. Besides water vapour, cloud ice water content, ice particle size distributions, condensation nuclei, and reactive nitrogen were measured during 6 flights. In this work the data of the 24th November flight is used to detect and to analyze warm frontal cirrus clouds in the mid latitudes on small temporal and spatial scale. Further, these results are compared with large-scale meteorological analyses from ECMWF and satellite data. Combining these data, the formation and evolution of inhomogeneities in the cirrus cloud structure are investigated. One important result is a qualitative agreement between the occurrence of cirrus clouds and the 'sharpness' of the Tropopause Inversion Layer (TIL).

Cloud condensation nuclei near marine cumulus

NASA Technical Reports Server (NTRS)

Hudson, James G.

1993-01-01

Extensive airborne measurements of cloud condensation nucleus (CCN) spectra and condensation nuclei below, in, between, and above the cumulus clouds near Hawaii point to important aerosol-cloud interactions. Consistent particle concentrations of 200/cu cm were found above the marine boundary layer and within the noncloudy marine boundary layer. Lower and more variable CCN concentrations within the cloudy boundary layer, especially very close to the clouds, appear to be a result of cloud scavenging processes. Gravitational coagulation of cloud droplets may be the principal cause of this difference in the vertical distribution of CCN. The results suggest a reservoir of CCN in the free troposphere which can act as a source for the marine boundary layer.

DEVELOPING ATMOSPHERIC RETRIEVAL METHODS FOR DIRECT IMAGING SPECTROSCOPY OF GAS GIANTS IN REFLECTED LIGHT. I. METHANE ABUNDANCES AND BASIC CLOUD PROPERTIES

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

Lupu, Roxana E.; Marley, Mark S.; Zahnle, Kevin

Upcoming space-based coronagraphic instruments in the next decade will perform reflected light spectroscopy and photometry of cool directly imaged extrasolar giant planets. We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs a geometric albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler ( emcee ) and a multimodal nested sampling algorithm ( MultiNest ) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model andmore » highlights possible discrepancies in the likelihood maps. As a proof of concept, our current atmospheric model contains one or two cloud layers, methane as a major absorber, and a H{sub 2}–He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise ratio in the presence of spectral noise correlations. After internal validation, the method is applied to realistic spectra of Jupiter, Saturn, and HD 99492c, a model observing target. We find that the presence or absence of clouds and methane can be determined with high confidence, while parameter uncertainties are model dependent and correlated. Such general methods will also be applicable to the interpretation of direct imaging spectra of cloudy terrestrial planets.« less

Developing Atmospheric Retrieval Methods for Direct Imaging Spectroscopy of Gas Giants in Reflected Light I: Methane Abundances and Basic Cloud Properties

NASA Technical Reports Server (NTRS)

Lupu, R. E.; Marley, M. S.; Lewis, N.; Line, M.; Traub, W.; Zahnle, K.

2016-01-01

Reflected light spectroscopy and photometry of cool, directly imaged extrasolar giant planets are expected to be performed in the next decade by space-based telescopes equipped with optical wavelength coronagraphs and integral field spectrographs, such as the Wide-Field Infrared Survey Telescope (WFIRST). We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs an albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler (emcee) and a multimodal nested sampling algorithm (MultiNest) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model, and highlights possible discrepancies in the likelihood maps. Here we apply this methodology to simulated spectra of cool giant planets. As a proof-of-concept, our current atmospheric model contains 1 or 2 cloud layers, methane as a major absorber, and a H2-He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise, in the presence of spectral noise correlations. After internal validation, the method is applied to realistic reflected-light spectra of Jupiter, Saturn, and HD 99492 c, a likely observing target. We find that the presence or absence of clouds and methane can be determined with high accuracy, while parameters uncertainties are model-dependent.

GOT C+ Survey of [CII] 158 Micrometer Emission: Atomic to Molecular Cloud Transitions in the Inner Galaxy

NASA Technical Reports Server (NTRS)

Velusamy, T.; Langer, W. D.; Willacy, K.; Pineda, J. L.; Goldsmith, P. F.

2012-01-01

We present the results of the distribution of CO-dark H2 gas in a sample of 2200 interstellar clouds in the inner Galaxy (l = 90 deg to +57 deg) detected in the velocity resolved [CII] spectra observed in the GOT C+ survey using the Herschel HIFI. We analyze the [CII] intensities along with the ancillary HI, (12)CO and (13)CO data for each cloud to determine their evolutionary state and to derive the H2 column densities in the C(+) and C(+)/CO transition layers in the cloud. We discuss the overall Galactic distribution of the [CII] clouds and their properties as a function Galactic radius. GOT C+ results on the global distribution of [CII] clouds and CO-dark H2 gas traces the FUV and star formation rates in the Galactic disk.

GOT C+ Survey of [CII] 158 μm Emission: Atomic to Molecular Cloud Transitions in the Inner Galaxy

NASA Astrophysics Data System (ADS)

Velusamy, T.; Langer, W. D.; Willacy, K.; Pineda, J. L.; Goldsmith, P. F.

2013-03-01

We present the results of the distribution of CO-dark H2 gas in a sample of 2223 interstellar clouds in the inner Galaxy (l=-90° to +57°) detected in the velocity resolved [CII] spectra observed in the GOT C+ survey using the Herschel HIFI. We analyze the [CII] intensities along with the ancillary HI, 12CO and 13CO data for each cloud to determine their evolutionary state and to derive the H2 column densities in the C+ and C+/CO transition layers in the cloud. We discuss the overall Galactic distribution of the [CII] clouds and their properties as a function Galactic radius. GOT C+ results on the global distribution of [CII] clouds and CO-dark H2 gas traces the FUV intensity and star formation rate in the Galactic disk.

Cirrus Cloud Retrieval Using Infrared Sounding Data: Multilevel Cloud Errors.

NASA Astrophysics Data System (ADS)

Baum, Bryan A.; Wielicki, Bruce A.

1994-01-01

In this study we perform an error analysis for cloud-top pressure retrieval using the High-Resolution Infrared Radiometric Sounder (HIRS/2) 15-µm CO2 channels for the two-layer case of transmissive cirrus overlying an overcast, opaque stratiform cloud. This analysis includes standard deviation and bias error due to instrument noise and the presence of two cloud layers, the lower of which is opaque. Instantaneous cloud pressure retrieval errors are determined for a range of cloud amounts (0.1 1.0) and cloud-top pressures (850250 mb). Large cloud-top pressure retrieval errors are found to occur when a lower opaque layer is present underneath an upper transmissive cloud layer in the satellite field of view (FOV). Errors tend to increase with decreasing upper-cloud elective cloud amount and with decreasing cloud height (increasing pressure). Errors in retrieved upper-cloud pressure result in corresponding errors in derived effective cloud amount. For the case in which a HIRS FOV has two distinct cloud layers, the difference between the retrieved and actual cloud-top pressure is positive in all casts, meaning that the retrieved upper-cloud height is lower than the actual upper-cloud height. In addition, errors in retrieved cloud pressure are found to depend upon the lapse rate between the low-level cloud top and the surface. We examined which sounder channel combinations would minimize the total errors in derived cirrus cloud height caused by instrument noise and by the presence of a lower-level cloud. We find that while the sounding channels that peak between 700 and 1000 mb minimize random errors, the sounding channels that peak at 300—500 mb minimize bias errors. For a cloud climatology, the bias errors are most critical.

Development of Waterfall Cliff Face: An Implication from Multitemporal High-definition Topographic Data

NASA Astrophysics Data System (ADS)

Hayakawa, Y. S.; Obanawa, H.

2015-12-01

Bedrock knickpoints (waterfalls) often act as erosional front in bedrock rivers, whose geomorphological processes are various. In waterfalls with vertical cliffs, both fluvial erosion and mass movement are feasible to form the landscape. Although morphological changes of such steep cliffs are sometimes visually observed, quantitative and precise measurements of their spatiotemporal distribution have been limited due to poor accessibility to such cliffs. For the clarification of geomorphological processes in such cliffs, multi-temporal mapping of the cliff face at a high resolution can be advantaged by short-range remote sensing approaches. Here we carry out multi-temporal terrestrial laser scanning (TLS), as well as structure-from-motion multi-view stereo (SfM-MVS) photogrammetry based on unmanned aerial system (UAS) for accurate topographic mapping of cliffs around a waterfall. The study site is Kegon Falls in central Japan, having a vertical drop of surface water from top of its overhanging cliff and groundwater outflows from its lower portions. The bedrock consists of alternate layers of jointed andesite lava and conglomerates. The latest major rockfall in 1986 caused approximately 8-m recession of the waterfall lip. Three-dimensional changes of the rock surface were detected by multi-temporal measurements by TLS over years, showing the portions of small rockfalls and surface lowering in the bedrock. Erosion was frequently observed in relatively weak the conglomerates layer, whereas small rockfalls were often found in the andesite layers. Wider areas of the waterfall and cliff were also measured by UAS-based SfM-MVS photogrammetry, improving the mapping quality of the cliff morphology. Point clouds are also projected on a vertical plane to generate a digital elevation model (DEM), and cross-sectional profiles extracted from the DEM indicate the presence of a distinct, 5-10-m deep depression in the cliff face. This appears to have been formed by freeze-thaw and/or wet-dry weathering following the recession in 1986. The long-term development of the waterfall cliff face is then discussed comprising various processes of rockfalls, water pressure and weathering.

A robust multi-frequency mixing algorithm for suppression of rivet signal in GMR inspection of riveted structures

NASA Astrophysics Data System (ADS)

Safdernejad, Morteza S.; Karpenko, Oleksii; Ye, Chaofeng; Udpa, Lalita; Udpa, Satish

2016-02-01

The advent of Giant Magneto-Resistive (GMR) technology permits development of novel highly sensitive array probes for Eddy Current (EC) inspection of multi-layer riveted structures. Multi-frequency GMR measurements with different EC pene-tration depths show promise for detection of bottom layer notches at fastener sites. However, the distortion of the induced magnetic field due to flaws is dominated by the strong fastener signal, which makes defect detection and classification a challenging prob-lem. This issue is more pronounced for ferromagnetic fasteners that concentrate most of the magnetic flux. In the present work, a novel multi-frequency mixing algorithm is proposed to suppress rivet signal response and enhance defect detection capability of the GMR array probe. The algorithm is baseline-free and does not require any assumptions about the sample geometry being inspected. Fastener signal suppression is based upon the random sample consensus (RANSAC) method, which iteratively estimates parameters of a mathematical model from a set of observed data with outliers. Bottom layer defects at fastener site are simulated as EDM notches of different length. Performance of the proposed multi-frequency mixing approach is evaluated on finite element data and experimental GMR measurements obtained with unidirectional planar current excitation. Initial results are promising demonstrating the feasibility of the approach.

Long-term Studies of Marine Halogen Release

NASA Astrophysics Data System (ADS)

Tschritter, J.; Holla, R.; Frieß, U.; Platt, U.

2009-04-01

Institute of Enviromental Physics, Heidelberg, Germany. Long term measurements of atmospheric trace gases using multi-axis DOAS instruments are pursued at the new SOLAS observatory on the island of Sao Vicente, (Cape Verde). This research is part of the SOPRAN (Surface Ocean Processes in the ANthropocene) project (Fördernummer:03F0462F). Reactive halogen species (RHS) such as bromine- and iodine- containing species play major roles in the chemistry of ozone in both the troposphere and lower stratosphere and thus possibly influence the ozone budget on a global scale. In addition iodine-species emitted from the ocean surface have been shown to be responsible for the production of new atmospheric particles in the marine boundary layer. This may have an effect on cloud formation and radiation transfer on local and global scales. Long term measurements of RHS abundances will help to identify their key regions and processes for formation. A new long term Multi-MAX-DOAS instrument has been installed at the SOLAS observatory on the island of Sao Vicente, (Cape Verde). The main focus of these unique measurements is the investigation of reactive halogen chemistry in the subtropical marine boundary layer based on measurements of BrO, IO, and possibly OIO. Because of its wide spectral range also the use for O4-retrievals to gain aerosol profiles is possible. IO has been detected with mixing ratios up to 1.3 ppt. For BrO an upper limit of 2 ppt could be determined.

Roles of drizzle in a one-dimensional third-order turbulence closure model of the nocturnal stratus-topped marine boundary layer

NASA Technical Reports Server (NTRS)

Wang, Shouping; Wang, Qing

1994-01-01

This study focuses on the effects of drizzle in a one-dimensional third-order turbulence closure model of the nocturnal stratus-topped marine boundary layer. When the simulated drizzle rate is relatively small (maximum approximately equal to 0.6 mm/day), steady-state solutions are obtained. The boundary layer stabilizes essentially because drizzle causes evaporative cooling of the subcloud layer. This stabilization considerably reduces the buoyancy flux and turbulence kinetic energy below the stratus cloud. Thus, drizzle tends to decouple the cloud from the subcloud layer in the model, as suggested by many observational studies. In addition, the evaporation of drizzle in the subcloud layer creates small scattered clouds, which are likely to represent cumulus clouds, below the solid stratus cloud in the model. The sensitivity experiments show that these scattered clouds help maintain a coupled boundary layer. When the drizzle rate is relatively large (maximum approximately equal to 0.9 mm/day), the response of the model becomes transient with bursts in turbulent fluxes. This phenomenon is related to the formation of the scattered cloud layer below the solid stratus cloud. It appears that the model is inadequate to represent the heat and moisture transport by strong updrafts covering a small fractional area in cumulus convection.

Building Facade Modeling Under Line Feature Constraint Based on Close-Range Images

NASA Astrophysics Data System (ADS)

Liang, Y.; Sheng, Y. H.

2018-04-01

To solve existing problems in modeling facade of building merely with point feature based on close-range images , a new method for modeling building facade under line feature constraint is proposed in this paper. Firstly, Camera parameters and sparse spatial point clouds data were restored using the SFM , and 3D dense point clouds were generated with MVS; Secondly, the line features were detected based on the gradient direction , those detected line features were fit considering directions and lengths , then line features were matched under multiple types of constraints and extracted from multi-image sequence. At last, final facade mesh of a building was triangulated with point cloud and line features. The experiment shows that this method can effectively reconstruct the geometric facade of buildings using the advantages of combining point and line features of the close - range image sequence, especially in restoring the contour information of the facade of buildings.

Merging of OMI and AIRS Ozone Data

NASA Technical Reports Server (NTRS)

Labow, Gordon J.; Fisher, Bradford; Susskind, Joel

2014-01-01

The OMI Instrument measures ozone using the backscattered light in the UV part of the spectrum. In polar night there are no OMI measurements so we hope to incorporate the AIRS ozone data to fill in these missing regions. AIRS is on the Aqua platform and has been operating since May 2002. AIRS is a multi-detector array grating spectrometer containing 2378 IR channels between 650 per centimeter and 2760 per centimeter which measures atmospheric temperature, precipitable water, water vapor, CO, CH4, CO2 and ozone profiles and column amount. It can also measure effective cloud fraction and cloud top pressure for up to two cloud layers and sea-land skin temperature. Since 2008, OMI has had part of its aperture occulted with a piece of the thermal blanket resulting in several scan positions being unusable. We hope to use the AIRS data to fill in the missing ozone values for those missing scan positions.

a Global Registration Algorithm of the Single-Closed Ring Multi-Stations Point Cloud

NASA Astrophysics Data System (ADS)

Yang, R.; Pan, L.; Xiang, Z.; Zeng, H.

2018-04-01

Aimed at the global registration problem of the single-closed ring multi-stations point cloud, a formula in order to calculate the error of rotation matrix was constructed according to the definition of error. The global registration algorithm of multi-station point cloud was derived to minimize the error of rotation matrix. And fast-computing formulas of transformation matrix with whose implementation steps and simulation experiment scheme was given. Compared three different processing schemes of multi-station point cloud, the experimental results showed that the effectiveness of the new global registration method was verified, and it could effectively complete the global registration of point cloud.

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

NASA Astrophysics Data System (ADS)

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

2003-12-01

Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each resolution. Results are compared with the radar reflectivity techniques employed by the NOAA ETL MMCR and the PARSL 94 GHz radars located at the CRYSTAL-FACE Eastern & Western Ground Sites, respectively. This technique is most likely to yield improvements for low and midlevel layer clouds that have little thermal variability in cloud height.

Venus' Spectral Signatures and the Potential for Life in the Clouds.

PubMed

Limaye, Sanjay S; Mogul, Rakesh; Smith, David J; Ansari, Arif H; Słowik, Grzegorz P; Vaishampayan, Parag

2018-03-30

The lower cloud layer of Venus (47.5-50.5 km) is an exceptional target for exploration due to the favorable conditions for microbial life, including moderate temperatures and pressures (∼60°C and 1 atm), and the presence of micron-sized sulfuric acid aerosols. Nearly a century after the ultraviolet (UV) contrasts of Venus' cloud layer were discovered with Earth-based photographs, the substances and mechanisms responsible for the changes in Venus' contrasts and albedo are still unknown. While current models include sulfur dioxide and iron chloride as the UV absorbers, the temporal and spatial changes in contrasts, and albedo, between 330 and 500 nm, remain to be fully explained. Within this context, we present a discussion regarding the potential for microorganisms to survive in Venus' lower clouds and contribute to the observed bulk spectra. In this article, we provide an overview of relevant Venus observations, compare the spectral and physical properties of Venus' clouds to terrestrial biological materials, review the potential for an iron- and sulfur-centered metabolism in the clouds, discuss conceivable mechanisms of transport from the surface toward a more habitable zone in the clouds, and identify spectral and biological experiments that could measure the habitability of Venus' clouds and terrestrial analogues. Together, our lines of reasoning suggest that particles in Venus' lower clouds contain sufficient mass balance to harbor microorganisms, water, and solutes, and potentially sufficient biomass to be detected by optical methods. As such, the comparisons presented in this article warrant further investigations into the prospect of biosignatures in Venus' clouds. Key Words: Venus-Clouds-Life-Habitability-Microorganism-Albedo-Spectroscopy-Biosignatures-Aerosol-Sulfuric Acid. Astrobiology 18, xxx-xxx.

Lidar Cloud Detection with Fully Convolutional Networks

NASA Astrophysics Data System (ADS)

Cromwell, E.; Flynn, D.

2017-12-01

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

Aviation response to a widely dispersed volcanic ash and gas cloud from the August 2008 eruption of Kasatochi, Alaska, USA

USGS Publications Warehouse

Guffanti, Marianne; Schneider, David J.; Wallace, Kristi L.; Hall, Tony; Bensimon, Dov R.; Salinas, Leonard J.

2010-01-01

The extensive volcanic cloud from Kasatochi's 2008 eruption caused widespread disruptions to aviation operations along Pacific oceanic, Canadian, and U.S. air routes. Based on aviation hazard warnings issued by the National Oceanic and Atmospheric Administration, U.S. Geological Survey, the Federal Aviation Administration, and Meteorological Service of Canada, air carriers largely avoided the volcanic cloud over a 5 day period by route modifications and flight cancellations. Comparison of time coincident GOES thermal infrared (TIR) data for ash detection with Ozone Monitoring Instrument (OMI) ultraviolet data for SO2 detection shows congruent areas of ash and gas in the volcanic cloud in the 2 days following onset of ash production. After about 2.5 days, the area of SO2 detected by OMI was more extensive than the area of ash indicated by TIR data, indicating significant ash depletion by fall out had occurred. Pilot reports of visible haze at cruise altitudes over Canada and the northern United States suggested that SO2 gas had converted to sulfate aerosols. Uncertain about the hazard potential of the aging cloud, airlines coped by flying over, under, or around the observed haze layer. Samples from a nondamaging aircraft encounter with Kasatochi's nearly 3 day old cloud contained volcanic silicate particles, confirming that some fine ash is present in predominantly gas clouds. The aircraft's exposure to ash was insufficient to cause engine damage; however, slightly damaging encounters with volcanic clouds from eruptions of Reventador in 2002 and Hekla in 2000 indicate the possibility of lingering hazards associated with old and/or diffuse volcanic clouds.

Improved cloud parameterization for Arctic climate simulations based on satellite data

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Rheticus Displacement: an Automatic Geo-Information Service Platform for Ground Instabilities Detection and Monitoring

NASA Astrophysics Data System (ADS)

Chiaradia, M. T.; Samarelli, S.; Agrimano, L.; Lorusso, A. P.; Nutricato, R.; Nitti, D. O.; Morea, A.; Tijani, K.

2016-12-01

Rheticus® is an innovative cloud-based data and services hub able to deliver Earth Observation added-value products through automatic complex processes and a minimum interaction with human operators. This target is achieved by means of programmable components working as different software layers in a modern enterprise system which relies on SOA (service-oriented-architecture) model. Due to its architecture, where every functionality is well defined and encapsulated in a standalone component, Rheticus is potentially highly scalable and distributable allowing different configurations depending on the user needs. Rheticus offers a portfolio of services, ranging from the detection and monitoring of geohazards and infrastructural instabilities, to marine water quality monitoring, wildfires detection or land cover monitoring. In this work, we outline the overall cloud-based platform and focus on the "Rheticus Displacement" service, aimed at providing accurate information to monitor movements occurring across landslide features or structural instabilities that could affect buildings or infrastructures. Using Sentinel-1 (S1) open data images and Multi-Temporal SAR Interferometry techniques (i.e., SPINUA), the service is complementary to traditional survey methods, providing a long-term solution to slope instability monitoring. Rheticus automatically browses and accesses (on a weekly basis) the products of the rolling archive of ESA S1 Scientific Data Hub; S1 data are then handled by a mature running processing chain, which is responsible of producing displacement maps immediately usable to measure with sub-centimetric precision movements of coherent points. Examples are provided, concerning the automatic displacement map generation process, as well as the integration of point and distributed scatterers, the integration of multi-sensors displacement maps (e.g., Sentinel-1 IW and COSMO-SkyMed HIMAGE), the combination of displacement rate maps acquired along both ascending and descending passes. ACK: Study carried out in the framework of the FAST4MAP project and co-funded by the Italian Space Agency (Contract n. 2015-020-R.0). Sentinel-1A products provided by ESA. CSK® Products, ASI, provided by ASI under a license to use. Rheticus® is a registered trademark of Planetek Italia srl.

Multi-layer Clouds Over the South Indian Ocean

NASA Technical Reports Server (NTRS)

2003-01-01

The complex structure and beauty of polar clouds are highlighted by these images acquired by the Multi-angle Imaging SpectroRadiometer (MISR) on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean, to the north of Enderbyland, East Antarctica.

The image at left was created by overlying a natural-color view from MISR's downward-pointing (nadir) camera with a color-coded stereo height field. MISR retrieves heights by a pattern recognition algorithm that utilizes multiple view angles to derive cloud height and motion. The opacity of the height field was then reduced until the field appears as a translucent wash over the natural-color image. The resulting purple, cyan and green hues of this aesthetic display indicate low, medium or high altitudes, respectively, with heights ranging from less than 2 kilometers (purple) to about 8 kilometers (green). In the lower right corner, the edge of the Antarctic coastline and some sea ice can be seen through some thin, high cirrus clouds.

The right-hand panel is a natural-color image from MISR's 70-degree backward viewing camera. This camera looks backwards along the path of Terra's flight, and in the southern hemisphere the Sun is in front of this camera. This perspective causes the cloud-tops to be brightly outlined by the sun behind them, and enhances the shadows cast by clouds with significant vertical structure. An oblique observation angle also enhances the reflection of light by atmospheric particles, and accentuates the appearance of polar clouds. The dark ocean and sea ice that were apparent through the cirrus clouds at the bottom right corner of the nadir image are overwhelmed by the brightness of these clouds at the oblique view.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17794. The panels cover an area of 335 kilometers x 605 kilometers, and utilize data from blocks 142 to 145 within World Reference System-2 path 155.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Aircraft-based investigation of Dynamics-Aerosol-Chemistry-Cloud Interactions in Southern West Africa

NASA Astrophysics Data System (ADS)

Flamant, Cyrille

2017-04-01

The EU-funded project DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa, http://www.dacciwa.eu) is investigating the relationship between weather, climate and air pollution in southern West Africa. The air over the coastal region of West Africa is a unique mixture of natural and anthropogenic gases, liquids and particles, emitted in an environment, in which multi-layer cloud decks frequently form. These exert a large influence on the local weather and climate, mainly due to their impact on radiation, the surface energy balance and thus the diurnal cycle of the atmospheric boundary layer. The main objective for the aircraft detachment was to build robust statistics of cloud properties in southern West Africa in different chemical landscapes to investigate the physical processes involved in their life cycle in such a complex chemical environment. As part of the DACCIWA field campaigns, three European aircraft (the German DLR Falcon 20, the French SAFIRE ATR 42 and the British BAS Twin Otter) conducted a total of 50 research flights across Ivory Coast, Ghana, Togo, and Benin from 27 June to 16 July 2016 for a total of 155 flight hours, including hours sponsored through 3 EUFAR projects. The aircraft were used in different ways based on their strengths, but all three had comparable instrumentation with the the capability to do gas-phase chemistry, aerosol and clouds, thereby generating a rich dataset of atmospheric conditions across the region. Eight types of flight objectives were conducted to achieve the goals of the DACCIWA: (i) Stratus clouds, (ii) Land-sea breeze clouds, (iii) Mid-level clouds, (iv) Biogenic emission, (v) City emissions, (vi) Flaring and ship emissions, (vii) Dust and biomass burning aerosols, and (viii) air-sea interactions. An overview of the DACCIWA aircraft campaign as well as first highlights from the airborne observations will be presented.

An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB

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

Song, Hua; Zhang, Zhibo; Ma, Po-Lun

This paper presents a two-step evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmospheric Model (version 5.3, CAM5) simulations, one based on the CAM5 standard parameterization schemes (CAM5-Base), and the other on the Cloud Layers Unified By Binormals (CLUBB) scheme (CAM5-CLUBB). In the first step, we compare the cloud properties directly from model outputs between the two simulations. We find that the CAM5-CLUBB run produces more MBL clouds in the tropical and subtropical large-scale descending regions. Moreover, the stratocumulus (Sc) to cumulus (Cu) cloud regime transition is much smoother in CAM5-CLUBB than in CAM5-Base. In addition,more » in CAM5-Base we find some grid cells with very small low cloud fraction (<20%) to have very high in-cloud water content (mixing ratio up to 400mg/kg). We find no such grid cells in the CAM5-CLUBB run. However, we also note that both simulations, especially CAM5-CLUBB, produce a significant amount of “empty” low cloud cells with significant cloud fraction (up to 70%) and near-zero in-cloud water content. In the second step, we use satellite observations from CERES, MODIS and CloudSat to evaluate the simulated MBL cloud properties by employing the COSP satellite simulators. We note that a feature of the COSP-MODIS simulator to mimic the minimum detection threshold of MODIS cloud masking removes much more low clouds from CAM5-CLUBB than it does from CAM5-Base. This leads to a surprising result — in the large-scale descending regions CAM5-CLUBB has a smaller COSP-MODIS cloud fraction and weaker shortwave cloud radiative forcing than CAM5-Base. A sensitivity study suggests that this is because CAM5-CLUBB suffers more from the above-mentioned “empty” clouds issue than CAM5-Base. The COSP-MODIS cloud droplet effective radius in CAM5-CLUBB shows a spatial increase from coastal St toward Cu, which is in qualitative agreement with MODIS observations. In contrast, COSP-MODIS cloud droplet effective radius in CAM5-Base almost remains a constant. In comparison with CloudSat observations, the histogram of the radar reflectivity from modeled MBL clouds is too narrow without a distinct separation between cloud and drizzle modes. Moreover, the probability of drizzle in both simulations is almost twice as high as the observation. Future studies are needed to understand the causes of these differences and their potential connection with the “empty” cloud issues in the model.« less

Retrieval of Aerosol Absorption Properties from Satellite Observations

NASA Technical Reports Server (NTRS)

Torres, Omar; Bhartia, Pawan K.; Jethva, H.; Ahn, Chang-Woo

2012-01-01

The Angstrom Absorption Exponent (AAE) is a parameter commonly used to characterize the wavelength-dependence of aerosol absorption optical depth (AAOD). It is closely related to aerosol composition. Black carbon (BC) containing aerosols yield AAE values near unity whereas Organic carbon (OC) aerosol particles are associated with values larger than 2. Even larger AAE values have been reported for desert dust aerosol particles. Knowledge of spectral AAOD is necessary for the calculation of direct radiative forcing effect of aerosols and for inferring aerosol composition. We have developed a satellitebased method of determining the spectral AAOD of absorbing aerosols. The technique uses multi-spectral measurements of upwelling radiation from scenes where absorbing aerosols lie above clouds as indicated by the UV Aerosol Index. For those conditions, the satellite measurement can be explained, using an approximations of Beer's Law (BL), as the upwelling reflectance at the cloud top attenuated by the absorption effects of the overlying aerosol layer. The upwelling reflectance at the cloud-top in an aerosol-free atmospheric column is mainly a function of cloud optical depth (COD). In the proposed method of AAE derivation, the first step is determining COD which is retrieved using a previously developed color-ratio based approach. In the second step, corrections for molecular scattering effects are applied to both the observed ad the calculated cloud reflectance terms, and the spectral AAOD is then derived by an inversion of the BL approximation. The proposed technique will be discussed in detail and application results making use of OMI multi-spectral measurements in the UV-Vis. will be presented.

MC-GenomeKey: a multicloud system for the detection and annotation of genomic variants.

PubMed

Elshazly, Hatem; Souilmi, Yassine; Tonellato, Peter J; Wall, Dennis P; Abouelhoda, Mohamed

2017-01-20

Next Generation Genome sequencing techniques became affordable for massive sequencing efforts devoted to clinical characterization of human diseases. However, the cost of providing cloud-based data analysis of the mounting datasets remains a concerning bottleneck for providing cost-effective clinical services. To address this computational problem, it is important to optimize the variant analysis workflow and the used analysis tools to reduce the overall computational processing time, and concomitantly reduce the processing cost. Furthermore, it is important to capitalize on the use of the recent development in the cloud computing market, which have witnessed more providers competing in terms of products and prices. In this paper, we present a new package called MC-GenomeKey (Multi-Cloud GenomeKey) that efficiently executes the variant analysis workflow for detecting and annotating mutations using cloud resources from different commercial cloud providers. Our package supports Amazon, Google, and Azure clouds, as well as, any other cloud platform based on OpenStack. Our package allows different scenarios of execution with different levels of sophistication, up to the one where a workflow can be executed using a cluster whose nodes come from different clouds. MC-GenomeKey also supports scenarios to exploit the spot instance model of Amazon in combination with the use of other cloud platforms to provide significant cost reduction. To the best of our knowledge, this is the first solution that optimizes the execution of the workflow using computational resources from different cloud providers. MC-GenomeKey provides an efficient multicloud based solution to detect and annotate mutations. The package can run in different commercial cloud platforms, which enables the user to seize the best offers. The package also provides a reliable means to make use of the low-cost spot instance model of Amazon, as it provides an efficient solution to the sudden termination of spot machines as a result of a sudden price increase. The package has a web-interface and it is available for free for academic use.

Multi-Dimensional Optimization for Cloud Based Multi-Tier Applications

ERIC Educational Resources Information Center

Jung, Gueyoung

2010-01-01

Emerging trends toward cloud computing and virtualization have been opening new avenues to meet enormous demands of space, resource utilization, and energy efficiency in modern data centers. By being allowed to host many multi-tier applications in consolidated environments, cloud infrastructure providers enable resources to be shared among these…

Arctic PBL Cloud Height and Motion Retrievals from MISR and MINX

NASA Technical Reports Server (NTRS)

Wu, Dong L.

2012-01-01

How Arctic clouds respond and feedback to sea ice loss is key to understanding of the rapid climate change seen in the polar region. As more open water becomes available in the Arctic Ocean, cold air outbreaks (aka. off-ice flow from polar lows) produce a vast sheet of roll clouds in the planetary boundary layer (PBl). The cold air temperature and wind velocity are the critical parameters to determine and understand the PBl structure formed under these roll clouds. It has been challenging for nadir visible/IR sensors to detect Arctic clouds due to lack of contrast between clouds and snowy/icy surfaces. In addition) PBl temperature inversion creates a further problem for IR sensors to relate cloud top temperature to cloud top height. Here we explore a new method with the Multiangle Imaging Spectro-Radiometer (MISR) instrument to measure cloud height and motion over the Arctic Ocean. Employing a stereoscopic-technique, MISR is able to measure cloud top height accurately and distinguish between clouds and snowy/icy surfaces with the measured height. We will use the MISR INteractive eXplorer (MINX) to quantify roll cloud dynamics during cold-air outbreak events and characterize PBl structures over water and over sea ice.

Multi-Dimensional Damage Detection

NASA Technical Reports Server (NTRS)

Gibson, Tracy L. (Inventor); Williams, Martha K. (Inventor); Roberson, Luke B. (Inventor); Lewis, Mark E. (Inventor); Snyder, Sarah J. (Inventor); Medelius, Pedro J. (Inventor)

2016-01-01

Methods and systems may provide for a structure having a plurality of interconnected panels, wherein each panel has a plurality of detection layers separated from one another by one or more non-detection layers. The plurality of detection layers may form a grid of conductive traces. Additionally, a monitor may be coupled to each grid of conductive traces, wherein the monitor is configured to detect damage to the plurality of interconnected panels in response to an electrical property change with respect to one or more of the conductive traces. In one example, the structure is part of an inflatable space platform such as a spacecraft or habitat.

Lidar and radar measurements of the melting layer: observations of dark and bright band phenomena

NASA Astrophysics Data System (ADS)

Di Girolamo, P.; Summa, D.; Cacciani, M.; Norton, E. G.; Peters, G.; Dufournet, Y.

2012-05-01

Multi-wavelength lidar measurements in the melting layer revealing the presence of dark and bright bands have been performed by the University of BASILicata Raman lidar system (BASIL) during a stratiform rain event. Simultaneously radar measurements have been also performed from the same site by the University of Hamburg cloud radar MIRA 36 (35.5 GHz), the University of Hamburg dual-polarization micro rain radar (24.15 GHz) and the University of Manchester UHF wind profiler (1.29 GHz). Measurements from BASIL and the radars are illustrated and discussed in this paper for a specific case study on 23 July 2007 during the Convective and Orographically-induced Precipitation Study (COPS). Simulations of the lidar dark and bright band based on the application of concentric/eccentric sphere Lorentz-Mie codes and a melting layer model are also provided. Lidar and radar measurements and model results are also compared with measurements from a disdrometer on ground and a two-dimensional cloud (2DC) probe on-board the ATR42 SAFIRE. Measurements and model results are found to confirm and support the conceptual microphysical/scattering model elaborated by Sassen et al. (2005).

Initial studies of middle and upper tropospheric stratiform clouds

NASA Technical Reports Server (NTRS)

Cox, S. K.

1982-01-01

The spatial and temporal occurrence of cloud layers, the development of a physical-numerical model to simulate the life cycles of tropospheric cloud layers, and the design of an observational program to study the properties of these layers are described.

Further Research on the Electrification of Pyrocumulus Clouds

NASA Technical Reports Server (NTRS)

Lang, Timothy J.; Laroche, Kendell; Baum, Bryan; Bateman, Monte; Mach, Douglas

2015-01-01

Past research on pyrocumulus electrification has demonstrated that a variety of lightning types can occur, including cloud-to-ground (CG) flashes, sometimes of dominant positive polarity, as well as small intra-cloud (IC) discharges in the upper levels of the pyro-cloud. In Colorado during summer 2012, the first combined polarimetric radar, multi-Doppler radar, and three-dimensional lightning mapping array (LMA) observations of lightning-producing pyrocumulus were obtained. These observations suggested that the National Lightning Detection Network (NLDN) was not sensitive enough to detect the small IC flashes that appear to be the dominant mode of lightning in these clouds. However, after an upgrade to the network in late 2012, the NLDN began detecting some of this pyrocumulus lightning. Multiple pyrocumulus clouds documented by the University of Wisconsin for various fires in 2013 and 2014 (including over the Rim, West Fork Complex, Yarnell Hill, Hardluck, and several other incidents) are examined and reported on here. This study exploits the increased-sensitivity NLDN as well as the new nationwide U.S. network of polarimetric Next-generation Radars (NEXRADs). These observations document the common occurrence of a polarimetric "dirty ice" signature - modest reflectivities (20-40+ dBZ), near-zero differential reflectivity, and reduced correlation coefficient (less than 0.9) - prior to the production of lightning. This signature is indicative of a mixture of ash and ice particles in the upper levels of the pyro-cloud (less than -20 C), with the ice interpreted as being necessary for pyro-cloud electrification. Pseudo-Geostationary Lightning Mapper (GLM) data will be produced from the 2012 LMA observations, and the ability of GLM to detect small pyrocumulus ICs will be assessed. The utility of lightning and polarimetric radar for documenting rapid wildfire growth, as well as for documenting pyrocumulus impacts on the composition of the upper troposphere/lower stratosphere (UTLS), will be discussed.

AN INFRARED VIEW OF SATURN

NASA Technical Reports Server (NTRS)

2002-01-01

In honor of NASA Hubble Space Telescope's eighth anniversary, we have GIFt wrapped Saturn in vivid colors. Actually, this image is courtesy of the new Near Infrared Camera and Multi-Object Spectrometer (NICMOS), which has taken its first peek at Saturn. The false-color image - taken Jan. 4, 1998 - shows the planet's reflected infrared light. This view provides detailed information on the clouds and hazes in Saturn's atmosphere. The blue colors indicate a clear atmosphere down to a main cloud layer. Different shadings of blue indicate variations in the cloud particles, in size or chemical composition. The cloud particles are believed to be ammonia ice crystals. Most of the northern hemisphere that is visible above the rings is relatively clear. The dark region around the south pole at the bottom indicates a big hole in the main cloud layer. The green and yellow colors indicate a haze above the main cloud layer. The haze is thin where the colors are green but thick where they are yellow. Most of the southern hemisphere (the lower part of Saturn) is quite hazy. These layers are aligned with latitude lines, due to Saturn's east-west winds. The red and orange colors indicate clouds reaching up high into the atmosphere. Red clouds are even higher than orange clouds. The densest regions of two storms near Saturn's equator appear white. On Earth, the storms with the highest clouds are also found in tropical latitudes. The smaller storm on the left is about as large as the Earth, and larger storms have been recorded on Saturn in 1990 and 1994. The rings, made up of chunks of ice, are as white as images of ice taken in visible light. However, in the infrared, water absorption causes various colorations. The most obvious is the brown color of the innermost ring. The rings cast their shadow onto Saturn. The bright line seen within this shadow is sunlight shining through the Cassini Division, the separation between the two bright rings. It is best observed on the left side, just above the rings. This view is possible due to a rare geometry during the observation. The next time this is observable from Earth will be in 2006. An accurate investigation of the ring's shadow also shows sunlight shining through the Encke Gap, a thin division very close to the outer edge of the ring system. Two of Saturn's satellites were recorded, Dione on the lower left and Tethys on the upper right. Tethys is just ending its transit across the disk of Saturn. They appear in different colors, yellow and green, indicating different conditions on their icy surfaces. Wavelengths: A color image consists of three exposures (or three film layers). For visible true-color images, the wavelengths of these three exposures are 0.4, 0.5, and 0.6 micrometers for blue, green, and red light, respectively. This Saturn image was taken at longer infrared wavelengths of 1.0, 1.8, and 2.1 micrometers, displayed as blue, green, and red. Reflected sunlight is seen at all these wavelengths, since Saturn's own heat glows only at wavelengths above 4 micrometers. Image credit: Erich Karkoschka (University of Arizona), and NASA

Forest Biomass Mapping from Stereo Imagery and Radar Data

NASA Astrophysics Data System (ADS)

Sun, G.; Ni, W.; Zhang, Z.

2013-12-01

Both InSAR and lidar data provide critical information on forest vertical structure, which are critical for regional mapping of biomass. However, the regional application of these data is limited by the availability and acquisition costs. Some researchers have demonstrated potentials of stereo imagery in the estimation of forest height. Most of these researches were conducted on aerial images or spaceborne images with very high resolutions (~0.5m). Space-born stereo imagers with global coverage such as ALOS/PRISM have coarser spatial resolutions (2-3m) to achieve wider swath. The features of stereo images are directly affected by resolutions and the approaches use by most of researchers need to be adjusted for stereo imagery with lower resolutions. This study concentrated on analyzing the features of point clouds synthesized from multi-view stereo imagery over forested areas. The small footprint lidar and lidar waveform data were used as references. The triplets of ALOS/PRISM data form three pairs (forward/nadir, backward/nadir and forward/backward) of stereo images. Each pair of the stereo images can be used to generate points (pixels) with 3D coordinates. By carefully co-register these points from three pairs of stereo images, a point cloud data was generated. The height of each point above ground surface was then calculated using DEM from National Elevation Dataset, USGS as the ground surface elevation. The height data were gridded into pixel of different sizes and the histograms of the points within a pixel were analyzed. The average height of the points within a pixel was used as the height of the pixel to generate a canopy height map. The results showed that the synergy of point clouds from different views were necessary, which increased the point density so the point cloud could detect the vertical structure of sparse and unclosed forests. The top layer of multi-layered forest could be captured but the dense forest prevented the stereo imagery to see through. The canopy height map exhibited spatial patterns of roads, forest edges and patches. The linear regression showed that the canopy height map had a good correlation with RH50 of LVIS data at 30m pixel size with a gain of 1.04, bias of 4.3m and R2 of 0.74 (Fig. 1). The canopy height map from PRISM and dual-pol PALSAR data were used together to map biomass in our study area near Howland, Maine, and the results were evaluated using biomass map generated from LVIS waveform data independently. The results showed that adding CHM from PRISM significantly improved biomass accuracy and raised the biomass saturation level of L-band SAR data in forest biomass mapping.

Biologically inspired multi-layered synthetic skin for tactile feedback in prosthetic limbs.

PubMed

Osborn, Luke; Nguyen, Harrison; Betthauser, Joseph; Kaliki, Rahul; Thakor, Nitish

2016-08-01

The human body offers a template for many state-of-the-art prosthetic devices and sensors. In this work, we present a novel, sensorized synthetic skin that mimics the natural multi-layered nature of mechanoreceptors found in healthy glabrous skin to provide tactile information. The multi-layered sensor is made up of flexible piezoresistive textiles that act as force sensitive resistors (FSRs) to convey tactile information, which are embedded within a silicone rubber to resemble the compliant nature of human skin. The top layer of the synthetic skin is capable of detecting small loads less than 5 N whereas the bottom sensing layer responds reliably to loads over 7 N. Finite element analysis (FEA) of a simplified human fingertip and the synthetic skin was performed. Results suggest similarities in behavior during loading. A natural tactile event is simulated by loading the synthetic skin on a prosthetic limb. Results show the sensors' ability to detect applied loads as well as the ability to simulate neural spiking activity based on the derivative and temporal differences of the sensor response. During the tactile loading, the top sensing layer responded 0.24 s faster than the bottom sensing layer. A synthetic biologically-inspired skin such as this will be useful for enhancing the functionality of prosthetic limbs through tactile feedback.

Boundary Layer Thermodynamics and Cloud Microphysics for a Mixed Stratocumulus and Cumulus Cloud Field Observed during ACE-ENA

NASA Astrophysics Data System (ADS)

Jensen, M. P.; Miller, M. A.; Wang, J.

2017-12-01

The first Intensive Observation Period of the DOE Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) took place from 21 June through 20 July 2017 involving the deployment of the ARM Gulfstream-159 (G-1) aircraft with a suite of in situ cloud and aerosol instrumentation in the vicinity of the ARM Climate Research Facility Eastern North Atlantic (ENA) site on Graciosa Island, Azores. Here we present preliminary analysis of the thermodynamic characteristics of the marine boundary layer and the variability of cloud properties for a mixed cloud field including both stratiform cloud layers and deeper cumulus elements. Analysis combines in situ atmospheric state observations from the G-1 with radiosonde profiles and surface meteorology from the ENA site in order to characterize the thermodynamic structure of the marine boundary layer including the coupling state and stability. Cloud/drizzle droplet size distributions measured in situ are combined with remote sensing observations from a scanning cloud radar, and vertically pointing cloud radar and lidar provide quantification of the macrophysical and microphysical properties of the mixed cloud field.

Application of Deep Learning to Detect Precursors of Tropical Cyclone

NASA Astrophysics Data System (ADS)

Matsuoka, D.; Nakano, M.; Sugiyama, D.; Uchida, S.

2017-12-01

Tropical cyclones (TCs) affect significant damage to human society. Predicting TC generation as soon as possible is important issue in both academic and social perspectives. In the present work, we investigate the probability of predicting TCs seven days prior using deep neural networks. The training data is produced from 30-year cloud resolving global atmospheric simulation (NICAM) with 14 km horizontal resolution (Kodama et al., 2015). We employed a TCs tracking algorithm (Sugi et al., 2002; Nakano et al., 2015) to NICAM simulation data in order to generate supervised cloud images (horizontal sizes are 800-1,000km). We generate approximately one million images of "TCs (include their precursors)" and "not TCs (low pressure clouds)". We generate ten types of image classifier based on 2-dimensional convolutional neural network, includes four convolutional layers, three pooling layers and two fully connected layers. The final predicted results are obtained by these ensemble mean values. Generated classifiers are applied to untrained global simulation data (four million test images). As a result, we succeeded in predicting the precursors of TCs seven and five days before their formation with a Recall of 88.6% and 89.6% (Precision is 11.4%), respectively.

Test study on the performance of shielding configuration with stuffed layer under hypervelocity impact

NASA Astrophysics Data System (ADS)

Ke, Fa-wei; Huang, Jie; Wen, Xue-zhong; Ma, Zhao-xia; Liu, Sen

2016-10-01

In order to study the cracking and intercepting mechanism of stuffed layer configuration on the debris cloud and to develop stuffed layer configuration with better performance, the hypervelocity impact tests on shielding configurations with stuffed layer were carried out. Firstly, the hypervelocity impact tests on the shielding configuration with stuffed layer of 3 layer ceramic fibre and 3 layer aramid fibre were finished, the study results showed that the debris cloud generated by the aluminum sphere impacting bumper at the velocity of about 6.2 km/s would be racked and intercepted by the stuffed layer configuration efficiently when the ceramic fibre layers and aramid fibre layers were jointed together, however, the shielding performance would be declined when the ceramic fibre layers and aramid fibre layers were divided by some distance. The mechanism of stuffed layer racking and intercepting the debris cloud was analyzed according to the above test results. Secondly, based on the mechanism of the stuffed layer cracking and intercepint debirs cloud the hypervelocity impact tests on the following three stuffed layer structures with the equivalent areal density to the 1 mm-thick aluminum plate were also carried out to compare their performance of cracking and intercepting debris cloud. The mechanisms of stuffed layer racking and intercepting the debris cloud were validated by the test result. Thirdly, the influence of the stuffed layer position on the shielding performance was studied by the test, too. The test results would provide reference for the design of better performance shielding configuration with stuffed layer.

Relation of Cloud Occurrence Frequency, Overlap, and Effective Thickness Derived from CALIPSO and CloudSat Merged Cloud Vertical Profiles

NASA Technical Reports Server (NTRS)

Kato, Seiji; Sun-Mack, Sunny; Miller, Walter F.; Rose, Fred G.; Chen, Yan; Minnis, Patrick; Wielicki, Bruce A.

2009-01-01

A cloud frequency of occurrence matrix is generated using merged cloud vertical profile derived from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR). The matrix contains vertical profiles of cloud occurrence frequency as a function of the uppermost cloud top. It is shown that the cloud fraction and uppermost cloud top vertical pro les can be related by a set of equations when the correlation distance of cloud occurrence, which is interpreted as an effective cloud thickness, is introduced. The underlying assumption in establishing the above relation is that cloud overlap approaches the random overlap with increasing distance separating cloud layers and that the probability of deviating from the random overlap decreases exponentially with distance. One month of CALIPSO and CloudSat data support these assumptions. However, the correlation distance sometimes becomes large, which might be an indication of precipitation. The cloud correlation distance is equivalent to the de-correlation distance introduced by Hogan and Illingworth [2000] when cloud fractions of both layers in a two-cloud layer system are the same.

Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements

NASA Technical Reports Server (NTRS)

Vaughan, Mark A.; Powell, Kathleen A.; Kuehn, Ralph E.; Young, Stuart A.; Winker, David M.; Hostetler, Chris A.; Hunt, William H.; Liu, Zhaoyan; McGill, Matthew J.; Getzewich, Brian J.

2009-01-01

Accurate knowledge of the vertical and horizontal extent of clouds and aerosols in the earth s atmosphere is critical in assessing the planet s radiation budget and for advancing human understanding of climate change issues. To retrieve this fundamental information from the elastic backscatter lidar data acquired during the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a selective, iterated boundary location (SIBYL) algorithm has been developed and deployed. SIBYL accomplishes its goals by integrating an adaptive context-sensitive profile scanner into an iterated multiresolution spatial averaging scheme. This paper provides an in-depth overview of the architecture and performance of the SIBYL algorithm. It begins with a brief review of the theory of target detection in noise-contaminated signals, and an enumeration of the practical constraints levied on the retrieval scheme by the design of the lidar hardware, the geometry of a space-based remote sensing platform, and the spatial variability of the measurement targets. Detailed descriptions are then provided for both the adaptive threshold algorithm used to detect features of interest within individual lidar profiles and the fully automated multiresolution averaging engine within which this profile scanner functions. The resulting fusion of profile scanner and averaging engine is specifically designed to optimize the trade-offs between the widely varying signal-to-noise ratio of the measurements and the disparate spatial resolutions of the detection targets. Throughout the paper, specific algorithm performance details are illustrated using examples drawn from the existing CALIPSO dataset. Overall performance is established by comparisons to existing layer height distributions obtained by other airborne and space-based lidars.

Cloud and Aerosol Retrieval for the 2001 GLAS Satellite Lidar Mission

NASA Technical Reports Server (NTRS)

Hart, William D.; Palm, Stephen P.; Spinhirne, James D.

2000-01-01

The Geoscience Laser Altimeter System (GLAS) is scheduled for launch in July of 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESAT). In addition to being a precision altimeter for mapping the height of the Earth's icesheets, GLAS will be an atmospheric lidar, sensitive enough to detect gaseous, aerosol, and cloud backscatter signals, at horizontal and vertical resolutions of 175 and 75m, respectively. GLAS will be the first lidar to produce temporally continuous atmospheric backscatter profiles with nearly global coverage (94-degree orbital inclination). With a projected operational lifetime of five years, GLAS will collect approximately six billion lidar return profiles. The large volume of data dictates that operational analysis algorithms, which need to keep pace with the data yield of the instrument, must be efficient. So, we need to evaluate the ability of operational algorithms to detect atmospheric constituents that affect global climate. We have to quantify, in a statistical manner, the accuracy and precision of GLAS cloud and aerosol observations. Our poster presentation will show the results of modeling studies that are designed to reveal the effectiveness and sensitivity of GLAS in detecting various atmospheric cloud and aerosol features. The studies consist of analyzing simulated lidar returns. Simulation cases are constructed either from idealized renditions of atmospheric cloud and aerosol layers or from data obtained by the NASA ER-2 Cloud Lidar System (CLS). The fabricated renditions permit quantitative evaluations of operational algorithms to retrieve cloud and aerosol parameters. The use of observational data permits the evaluations of performance for actual atmospheric conditions. The intended outcome of the presentation is that climatology community will be able to use the results of these studies to evaluate and quantify the impact of GLAS data upon atmospheric modeling efforts.

Monte Carlo model of light transport in multi-layered tubular organs

NASA Astrophysics Data System (ADS)

Zhang, Yunyao; Zhu, Jingping; Zhang, Ning

2017-02-01

We present a Monte Carlo static light migration model (Endo-MCML) to simulate endoscopic optical spectroscopy for tubular organs such as esophagus and colon. The model employs multi-layered hollow cylinder which emitting and receiving light both from the inner boundary to meet the conditions of endoscopy. Inhomogeneous sphere can be added in tissue layers to model cancer or other abnormal changes. The 3D light distribution and exit angle would be recorded as results. The accuracy of the model has been verified by Multi-layered Monte Carlo(MCML) method and NIRFAST. This model can be used for the forward modeling of light transport during endoscopically diffuse optical spectroscopy, light scattering spectroscopy, reflectance spectroscopy and other static optical detection or imaging technologies.

Towards PACE Atmospheric Correction, Aerosol and Cloud Products: Making Use of Expanded Spectral, Angular and Polarimetric Information.

NASA Astrophysics Data System (ADS)

Remer, L. A.; Boss, E.; Ahmad, Z.; Cairns, B.; Chowdhary, J.; Coddington, O.; Davis, A. B.; Dierssen, H. M.; Diner, D. J.; Franz, B. A.; Frouin, R.; Gao, B. C.; Garay, M. J.; Heidinger, A.; Ibrahim, A.; Kalashnikova, O. V.; Knobelspiesse, K. D.; Levy, R. C.; Omar, A. H.; Meyer, K.; Platnick, S. E.; Seidel, F. C.; van Diedenhoven, B.; Werdell, J.; Xu, F.; Zhai, P.; Zhang, Z.

2017-12-01

NASA's Science Team for the Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission is concluding three years of study exploring the science potential of expanded spectral, angular and polarization capability for space-based retrievals of water leaving radiance, aerosols and clouds. The work anticipates future development of retrievals to be applied to the PACE Ocean Color Instrument (OCI) and/or possibly a PACE Multi-Angle Polarimeter (MAP). In this presentation we will report on the Science Team's accomplishments associated with the atmosphere (significant efforts are also directed by the ST towards the ocean). Included in the presentation will be sensitivity studies that explore new OCI capabilities for aerosol and cloud layer height, aerosol absorption characterization, cloud property retrievals, and how we intend to move from heritage atmospheric correction algorithms to make use of and adjust to OCI's hyperspectral and UV wavelengths. We will then address how capabilities will improve with the PACE MAP, how these capabilities from both OCI and MAP correspond to specific societal benefits from the PACE mission, and what is still needed to close the gaps in our understanding before the PACE mission can realize its full potential.

Provider-Independent Use of the Cloud

NASA Astrophysics Data System (ADS)

Harmer, Terence; Wright, Peter; Cunningham, Christina; Perrott, Ron

Utility computing offers researchers and businesses the potential of significant cost-savings, making it possible for them to match the cost of their computing and storage to their demand for such resources. A utility compute provider enables the purchase of compute infrastructures on-demand; when a user requires computing resources a provider will provision a resource for them and charge them only for their period of use of that resource. There has been a significant growth in the number of cloud computing resource providers and each has a different resource usage model, application process and application programming interface (API)-developing generic multi-resource provider applications is thus difficult and time consuming. We have developed an abstraction layer that provides a single resource usage model, user authentication model and API for compute providers that enables cloud-provider neutral applications to be developed. In this paper we outline the issues in using external resource providers, give examples of using a number of the most popular cloud providers and provide examples of developing provider neutral applications. In addition, we discuss the development of the API to create a generic provisioning model based on a common architecture for cloud computing providers.

Cloud-Resolving Model Simulations of Aerosol-Cloud Interactions Triggered by Strong Aerosol Emissions in the Arctic

NASA Astrophysics Data System (ADS)

Wang, H.; Kravitz, B.; Rasch, P. J.; Morrison, H.; Solomon, A.

2014-12-01

Previous process-oriented modeling studies have highlighted the dependence of effectiveness of cloud brightening by aerosols on cloud regimes in warm marine boundary layer. Cloud microphysical processes in clouds that contain ice, and hence the mechanisms that drive aerosol-cloud interactions, are more complicated than in warm clouds. Interactions between ice particles and liquid drops add additional levels of complexity to aerosol effects. A cloud-resolving model is used to study aerosol-cloud interactions in the Arctic triggered by strong aerosol emissions, through either geoengineering injection or concentrated sources such as shipping and fires. An updated cloud microphysical scheme with prognostic aerosol and cloud particle numbers is employed. Model simulations are performed in pure super-cooled liquid and mixed-phase clouds, separately, with or without an injection of aerosols into either a clean or a more polluted Arctic boundary layer. Vertical mixing and cloud scavenging of particles injected from the surface is still quite efficient in the less turbulent cold environment. Overall, the injection of aerosols into the Arctic boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. The pure liquid clouds are more susceptible to the increase in aerosol number concentration than the mixed-phase clouds. Rain production processes are more effectively suppressed by aerosol injection, whereas ice precipitation (snow) is affected less; thus the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. Aerosol injection into a clean boundary layer results in a greater cloud albedo increase than injection into a polluted one, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, the impact of dynamical feedback due to precipitation changes is small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering/shipping could have substantial local radiative effects, but is unlikely to be effective as the sole means of counterbalancing warming due to climate change.

From large-eddy simulation to multi-UAVs sampling of shallow cumulus clouds

NASA Astrophysics Data System (ADS)

Lamraoui, Fayçal; Roberts, Greg; Burnet, Frédéric

2016-04-01

In-situ sampling of clouds that can provide simultaneous measurements at satisfying spatio-temporal resolutions to capture 3D small scale physical processes continues to present challenges. This project (SKYSCANNER) aims at bringing together cloud sampling strategies using a swarm of unmanned aerial vehicles (UAVs) based on Large-eddy simulation (LES). The multi-UAV-based field campaigns with a personalized sampling strategy for individual clouds and cloud fields will significantly improve the understanding of the unresolved cloud physical processes. An extensive set of LES experiments for case studies from ARM-SGP site have been performed using MesoNH model at high resolutions down to 10 m. The carried out simulations led to establishing a macroscopic model that quantifies the interrelationship between micro- and macrophysical properties of shallow convective clouds. Both the geometry and evolution of individual clouds are critical to multi-UAV cloud sampling and path planning. The preliminary findings of the current project reveal several linear relationships that associate many cloud geometric parameters to cloud related meteorological variables. In addition, the horizontal wind speed indicates a proportional impact on cloud number concentration as well as triggering and prolonging the occurrence of cumulus clouds. In the framework of the joint collaboration that involves a Multidisciplinary Team (including institutes specializing in aviation, robotics and atmospheric science), this model will be a reference point for multi-UAVs sampling strategies and path planning.

Simulations of arctic mixed-phase clouds in forecasts with CAM3 and AM2 for M-PACE

DOE PAGES

Xie, Shaocheng; Boyle, James; Klein, Stephen A.; ...

2008-02-27

[1] Simulations of mixed-phase clouds in forecasts with the NCAR Atmosphere Model version 3 (CAM3) and the GFDL Atmospheric Model version 2 (AM2) for the Mixed-Phase Arctic Cloud Experiment (M-PACE) are performed using analysis data from numerical weather prediction centers. CAM3 significantly underestimates the observed boundary layer mixed-phase cloud fraction and cannot realistically simulate the variations of liquid water fraction with temperature and cloud height due to its oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer cloud fraction while its clouds contain much less cloud condensate than CAM3 and the observations. The simulation of themore » boundary layer mixed-phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used (CAM3LIU). The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes. Sensitivity tests show that these results are not sensitive to the analysis data used for model initialization. Increasing model horizontal resolution helps capture the subgrid-scale features in Arctic frontal clouds but does not help improve the simulation of the single-layer boundary layer clouds. AM2 simulated cloud fraction and LWP are sensitive to the change in cloud ice number concentrations used in the Wegener-Bergeron-Findeisen process while CAM3LIU only shows moderate sensitivity in its cloud fields to this change. Furthermore, this paper shows that the Wegener-Bergeron-Findeisen process is important for these models to correctly simulate the observed features of mixed-phase clouds.« less

Simulations of Arctic mixed-phase clouds in forecasts with CAM3 and AM2 for M-PACE

NASA Astrophysics Data System (ADS)

Xie, Shaocheng; Boyle, James; Klein, Stephen A.; Liu, Xiaohong; Ghan, Steven

2008-02-01

Simulations of mixed-phase clouds in forecasts with the NCAR Atmosphere Model version 3 (CAM3) and the GFDL Atmospheric Model version 2 (AM2) for the Mixed-Phase Arctic Cloud Experiment (M-PACE) are performed using analysis data from numerical weather prediction centers. CAM3 significantly underestimates the observed boundary layer mixed-phase cloud fraction and cannot realistically simulate the variations of liquid water fraction with temperature and cloud height due to its oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer cloud fraction while its clouds contain much less cloud condensate than CAM3 and the observations. The simulation of the boundary layer mixed-phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used (CAM3LIU). The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes. Sensitivity tests show that these results are not sensitive to the analysis data used for model initialization. Increasing model horizontal resolution helps capture the subgrid-scale features in Arctic frontal clouds but does not help improve the simulation of the single-layer boundary layer clouds. AM2 simulated cloud fraction and LWP are sensitive to the change in cloud ice number concentrations used in the Wegener-Bergeron-Findeisen process while CAM3LIU only shows moderate sensitivity in its cloud fields to this change. This paper shows that the Wegener-Bergeron-Findeisen process is important for these models to correctly simulate the observed features of mixed-phase clouds.

A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.

PubMed

Wu, Guanlin; Bao, Weidong; Zhu, Xiaomin; Zhang, Xiongtao

2018-05-23

The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.

Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

NASA Astrophysics Data System (ADS)

Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-07-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms.Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (M{O/Y}D04). The M{O/Y}D04 product is of course normally produced from M{O/Y}D021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a M{O/Y}D021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source.We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

NASA Technical Reports Server (NTRS)

Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-01-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Development of Eddy Current Techniques for Detection of Deep Fatigue Cracks in Multi-Layer Airframe Components

NASA Technical Reports Server (NTRS)

Wincheski, Russell A.

2008-01-01

Thick, multi-layer aluminum structure has been widely used in aircraft design in critical wing splice areas. The multi-layer structure generally consists of three or four aluminum layers with different geometry and varying thickness, which are held together with fasteners. The detection of cracks under fasteners with ultrasonic techniques in subsurface layers away from the skin is impeded primarily by interlayer bonds and faying sealant condition. Further, assessment of such sealant condition is extremely challenging in terms of complexity of structure, limited access, and inspection cost. Although Eddy current techniques can be applied on in-service aircraft from the exterior of the skin without knowing sealant condition, the current eddy current techniques are not able to detect defects with wanted sensitivity. In this work a series of low frequency eddy current probes have been designed, fabricated and tested for this application. A probe design incorporating a shielded magnetic field sensor concentrically located in the interior of a drive coil has been employed to enable a localized deep diffusion of the electromagnetic field into the part under test. Due to the required low frequency inspections, probes have been testing using a variety of magnetic field sensors (pickup coil, giant magneto-resistive, anisotropic magneto-resistive, and spin-dependent tunneling). The probe designs as well as capabilities based upon a target inspection for sub-layer cracking in an airframe wing spar joint is presented.

The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

NASA Astrophysics Data System (ADS)

Kuçak, R. A.; Özdemir, E.; Erol, S.

2017-05-01

Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

Experimental measurements of the ground cloud effluents and cloud growth for the May 20, 1975, Titan 3C launch at Air Force Eastern Test Range, Florida

NASA Technical Reports Server (NTRS)

Gregory, G. L.; Storey, R. W., Jr.

1977-01-01

The experiment included surface level and airborne in situ cloud measurements of the exhaust effluents from the Titan IIIC solid rocket boosters. Simultaneous visible spectrum photographic pictures of the ground cloud as well as infrared imaging of the cloud were obtained to study the cloud rise, growth, and direction of travel within the earth's surface mixing layer. The NASA multilayer diffusion model predictions of cloud growth, direction of travel, and expected surface level effluent concentrations were made prior to launch and after launch using measured meteorological conditions. Prelaunch predictions were used to position the effluent monitoring instruments, and the postlaunch predictions were compared with the measured data. Measurement results showed that surface level effluent values were low, often below the detection limits of the instrumentation. The maximum surface level hydrogen chloride concentration measured 50 parts per billion at about 8 km from the launch pad. The maximum observed in-cloud (airborne measurement) hydrogen chloride concentration was 7 per million.

Impact of Arctic sea-ice retreat on the recent change in cloud-base height during autumn

NASA Astrophysics Data System (ADS)

Sato, K.; Inoue, J.; Kodama, Y.; Overland, J. E.

2012-12-01

Cloud-base observations over the ice-free Chukchi and Beaufort Seas in autumn were conducted using a shipboard ceilometer and radiosondes during the 1999-2010 cruises of the Japanese R/V Mirai. To understand the recent change in cloud base height over the Arctic Ocean, these cloud-base height data were compared with the observation data under ice-covered situation during SHEBA (the Surface Heat Budget of the Arctic Ocean project in 1998). Our ice-free results showed a 30 % decrease (increase) in the frequency of low clouds with a ceiling below (above) 500 m. Temperature profiles revealed that the boundary layer was well developed over the ice-free ocean in the 2000s, whereas a stable layer dominated during the ice-covered period in 1998. The change in surface boundary conditions likely resulted in the difference in cloud-base height, although it had little impact on air temperatures in the mid- and upper troposphere. Data from the 2010 R/V Mirai cruise were investigated in detail in terms of air-sea temperature difference. This suggests that stratus cloud over the sea ice has been replaced as stratocumulus clouds with low cloud fraction due to the decrease in static stability induced by the sea-ice retreat. The relationship between cloud-base height and air-sea temperature difference (SST-Ts) was analyzed in detail using special section data during 2010 cruise data. Stratus clouds near the sea surface were predominant under a warm advection situation, whereas stratocumulus clouds with a cloud-free layer were significant under a cold advection situation. The threshold temperature difference between sea surface and air temperatures for distinguishing the dominant cloud types was 3 K. Anomalous upward turbulent heat fluxes associated with the sea-ice retreat have likely contributed to warming of the lower troposphere. Frequency distribution of the cloud-base height (km) detected by a ceilometer/lidar (black bars) and radiosondes (gray bars), and profiles of potential temperature (K) for (a) ice-free cases (R/V Mirai during September) and (b) ice-covered case (SHEBA during September 1998). (c) Vertical profiles of air temperature from 1000 hPa to 150 hPa (solid lines: observations north of 75°N, and dashed lines: the ERA-Interim reanalysis over 75-82.5°N, 150-170°W). Green, blue, and red lines denote profiles derived from observations by NP stations (the 1980s), SHEBA (1998), and the R/V Mirai (the 2000s), respectively. (d) Temperature trend calculated by the ERA-Interim reanalysis over the area.

Remote detection and recognition of bio-aerosols by laser-induced fluorescense lidar: practical implementation and field tests

NASA Astrophysics Data System (ADS)

Boreysho, Anatoly; Savin, Andrey; Morozov, Alexey; Konyaev, Maxim; Konovalov, Konstantin

2007-06-01

Recognition of aerosol clouds material at some significant distance is now a key requirement for the wide range of applications. The elastic backscatter lidar have demonstrated high capabilities in aerosol remote detection, cloud real-time mapping at very long distances for low-concentration natural aerosols as well as artificial ones [1]. However, recognition ability is required to make them more relevant. Laser-induced fluorescence (LIF) looks very promising with respect to the recognition problem. New approach based on mobile lidar complex [2] equipped by spectrally-and range-resolved LIF-sensor is described as well as some results of field tests. The LIF-sensor consists of four-harmonics Nd:YAG laser equipped by an output expander to provide final beam divergence <1 mrad, 500-mm aspheric Cassegrain-type multi-wavelength receiving telescope, set of single-element receivers for measurement of the elastic backscatter radiation, and multi-element receiver with monochromator for spectrally-resolved LIF measurements. The system is equipped by 2-axis scanning mirror and variable-FOV video-camera collimated with the lidar scanning direction. The LIF-lidar is mounted on a truck-based platform (20-feet container) as a part of multi-purpose mobile lidar complex and adjusted for field conditions.

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds.

PubMed

Sorooshian, Armin; MacDonald, Alexander B; Dadashazar, Hossein; Bates, Kelvin H; Coggon, Matthew M; Craven, Jill S; Crosbie, Ewan; Hersey, Scott P; Hodas, Natasha; Lin, Jack J; Negrón Marty, Arnaldo; Maudlin, Lindsay C; Metcalf, Andrew R; Murphy, Shane M; Padró, Luz T; Prabhakar, Gouri; Rissman, Tracey A; Shingler, Taylor; Varutbangkul, Varuntida; Wang, Zhen; Woods, Roy K; Chuang, Patrick Y; Nenes, Athanasios; Jonsson, Haflidi H; Flagan, Richard C; Seinfeld, John H

2018-02-27

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing.

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds

PubMed Central

Sorooshian, Armin; MacDonald, Alexander B.; Dadashazar, Hossein; Bates, Kelvin H.; Coggon, Matthew M.; Craven, Jill S.; Crosbie, Ewan; Hersey, Scott P.; Hodas, Natasha; Lin, Jack J.; Negrón Marty, Arnaldo; Maudlin, Lindsay C.; Metcalf, Andrew R.; Murphy, Shane M.; Padró, Luz T.; Prabhakar, Gouri; Rissman, Tracey A.; Shingler, Taylor; Varutbangkul, Varuntida; Wang, Zhen; Woods, Roy K.; Chuang, Patrick Y.; Nenes, Athanasios; Jonsson, Haflidi H.; Flagan, Richard C.; Seinfeld, John H.

2018-01-01

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing. PMID:29485627

A multi-year data set on aerosol-cloud-precipitation-meteorology interactions for marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Sorooshian, Armin; MacDonald, Alexander B.; Dadashazar, Hossein; Bates, Kelvin H.; Coggon, Matthew M.; Craven, Jill S.; Crosbie, Ewan; Hersey, Scott P.; Hodas, Natasha; Lin, Jack J.; Negrón Marty, Arnaldo; Maudlin, Lindsay C.; Metcalf, Andrew R.; Murphy, Shane M.; Padró, Luz T.; Prabhakar, Gouri; Rissman, Tracey A.; Shingler, Taylor; Varutbangkul, Varuntida; Wang, Zhen; Woods, Roy K.; Chuang, Patrick Y.; Nenes, Athanasios; Jonsson, Haflidi H.; Flagan, Richard C.; Seinfeld, John H.

2018-02-01

Airborne measurements of meteorological, aerosol, and stratocumulus cloud properties have been harmonized from six field campaigns during July-August months between 2005 and 2016 off the California coast. A consistent set of core instruments was deployed on the Center for Interdisciplinary Remotely-Piloted Aircraft Studies Twin Otter for 113 flight days, amounting to 514 flight hours. A unique aspect of the compiled data set is detailed measurements of aerosol microphysical properties (size distribution, composition, bioaerosol detection, hygroscopicity, optical), cloud water composition, and different sampling inlets to distinguish between clear air aerosol, interstitial in-cloud aerosol, and droplet residual particles in cloud. Measurements and data analysis follow documented methods for quality assurance. The data set is suitable for studies associated with aerosol-cloud-precipitation-meteorology-radiation interactions, especially owing to sharp aerosol perturbations from ship traffic and biomass burning. The data set can be used for model initialization and synergistic application with meteorological models and remote sensing data to improve understanding of the very interactions that comprise the largest uncertainty in the effect of anthropogenic emissions on radiative forcing.

Detection of gene communities in multi-networks reveals cancer drivers

NASA Astrophysics Data System (ADS)

Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

2015-12-01

We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.

The evolution of nocturnal boundary-layer clouds in southern West Africa - a case study from DACCIWA

NASA Astrophysics Data System (ADS)

Adler, Bianca; Kalthoff, Norbert; Babić, Karmen; Lohou, Fabienne; Dione, Cheikh; Lothon, Marie; Pedruzo-Bagazgoitia, Xabier

2017-04-01

During the monsoon season, the atmospheric boundary layer in southern West Africa is characterised by various kinds of low-level clouds which experience a distinct diurnal cycle. During the night, extensive low-level stratiform clouds frequently form with a cloud base often less than few hundred metres above ground. After sunrise the cloud base slowly starts rising and eventually a transition to convective clouds occurs. While the existence of the clouds is documented in satellite images and synoptic observations, little is known about the mechanisms controlling their evolution. To provide observational evidence, a field campaign was conducted in southern West Africa in June and July 2016 within the framework of the Dynamics-aerosol-chemistry-cloud interactions in West Africa (DACCIWA) project. Comprehensive ground-based in situ and remote sensing measurements were performed at three different supersites in Ghana, Benin and Nigeria. In this contribution, we present the diurnal cycle of boundary-layer clouds for a typical day using data from a supersite at Savè in Benin. Due to the synergy of various instruments, we are able to obtain detailed information on the evolution of the clouds as well as on the boundary-layer structure with high temporal and vertical resolution. By combining ceilometer, cloud radar and microwave radiometer data we determined the cloud base, -depth and -density. The clouds form in the same layer as a nocturnal low-level jet (NLLJ), which we probe by sodar and UHF profiler. There is evidence for a strong link between the height and strength of the NLLJ and the density of the nocturnal clouds.

Material optimization of multi-layered enhanced nanostructures

NASA Astrophysics Data System (ADS)

Strobbia, Pietro

The employment of surface enhanced Raman scattering (SERS)-based sensing in real-world scenarios will offer numerous advantages over current optical sensors. Examples of these advantages are the intrinsic and simultaneous detection of multiple analytes, among many others. To achieve such a goal, SERS substrates with throughput and reproducibility comparable to commonly used fluorescence sensors have to be developed. To this end, our lab has discovered a multi-layer geometry, based on alternating films of a metal and a dielectric, that amplifies the SERS signal (multi-layer enhancement). The advantage of these multi-layered structures is to amplify the SERS signal exploiting layer-to-layer interactions in the volume of the structures, rather than on its surface. This strategy permits an amplification of the signal without modifying the surface characteristics of a substrate, and therefore conserving its reproducibility. Multi-layered structures can therefore be used to amplify the sensitivity and throughput of potentially any previously developed SERS sensor. In this thesis, these multi-layered structures were optimized and applied to different SERS substrates. The role of the dielectric spacer layer in the multi-layer enhancement was elucidated by fabricating spacers with different characteristics and studying their effect on the overall enhancement. Thickness, surface coverage and physical properties of the spacer were studied. Additionally, the multi-layered structures were applied to commercial SERS substrates and to isolated SERS probes. Studies on the dependence of the multi-layer enhancement on the thickness of the spacer demonstrated that the enhancement increases as a function of surface coverage at sub-monolayer thicknesses, due to the increasing multi-layer nature of the substrates. For fully coalescent spacers the enhancement decreases as a function of thickness, due to the loss of interaction between proximal metallic films. The influence of the physical properties of the spacer on the multi-layer enhancement were also studied. The trends in Schottky barrier height, interfacial potential and dielectric constant were isolated by using different materials as spacers (i.e., TiO2, HfO2, Ag 2O and Al2O3). The results show that the bulk dielectric constant of the material can be used to predict the relative magnitude of the multi-layer enhancement, with low dielectric constant materials performing more efficiently as spacers. Optimal spacer layers were found to be ultrathin coalescent films (ideally a monolayer) of low dielectric constant materials. Finally, multi-layered structures were observed to be employable to amplify SERS in drastically different substrate geometries. The multi-layered structures were applied to disposable commercial SERS substrates (i.e., Klarite). This project involved the regeneration of the used substrates, by stripping and redepositing the gold coating layer, and their amplification, by using the multi-layer geometry. The latter was observed to amplify the sensitivity of the substrates. Additionally, the multi-layered structures were applied to probes dispersed in solution. Such probes were observed to yield stronger SERS signal when optically trapped and to reduce the background signal. The application of the multi-layered structures on trapped probes, not only further amplified the SERS signal, but also increased the maximum number of applicable layers for the structures.

Evaluation of long-term surface-retrieved cloud droplet number concentration with in situ aircraft observations: ARM Cloud Droplet Number Concentration

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

Lim, Kyo-Sun Sunny; Riihimaki, Laura; Comstock, Jennifer M.

A new cloud-droplet number concentration (NDROP) value added product (VAP) has been produced at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for the 13 years from January 1998 to January 2011. The retrieval is based on surface radiometer measurements of cloud optical depth from the multi-filter rotating shadow-band radiometer (MFRSR) and liquid water path from the microwave radiometer (MWR). It is only applicable for single-layered warm clouds. Validation with in situ aircraft measurements during the extended-term aircraft field campaign, Routine ARM Aerial Facility (AAF) CLOWD Optical Radiative Observations (RACORO), shows that the NDROP VAP robustly reproduces themore » primary mode of the in situ measured probability density function (PDF), but produces a too wide distribution, primarily caused by frequent high cloud-droplet number concentration. Our analysis shows that the error in the MWR retrievals at low liquid water paths is one possible reason for this deficiency. Modification through the diagnosed liquid water path from the coordinate solution improves not only the PDF of the NDROP VAP but also the relationship between the cloud-droplet number concentration and cloud-droplet effective radius. Consideration of entrainment effects rather than assuming an adiabatic cloud improves the values of the NDROP retrieval by reducing the magnitude of cloud-droplet number concentration. Aircraft measurements and retrieval comparisons suggest that retrieving the vertical distribution of cloud-droplet number concentration and effective radius is feasible with an improvement of the parameter representing the mixing effects between environment and clouds and with a better understanding of the effect of mixing degree on cloud properties.« less

Multi-Dimensional Damage Detection for Surfaces and Structures

NASA Technical Reports Server (NTRS)

Williams, Martha; Lewis, Mark; Roberson, Luke; Medelius, Pedro; Gibson, Tracy; Parks, Steen; Snyder, Sarah

2013-01-01

Current designs for inflatable or semi-rigidized structures for habitats and space applications use a multiple-layer construction, alternating thin layers with thicker, stronger layers, which produces a layered composite structure that is much better at resisting damage. Even though such composite structures or layered systems are robust, they can still be susceptible to penetration damage. The ability to detect damage to surfaces of inflatable or semi-rigid habitat structures is of great interest to NASA. Damage caused by impacts of foreign objects such as micrometeorites can rupture the shell of these structures, causing loss of critical hardware and/or the life of the crew. While not all impacts will have a catastrophic result, it will be very important to identify and locate areas of the exterior shell that have been damaged by impacts so that repairs (or other provisions) can be made to reduce the probability of shell wall rupture. This disclosure describes a system that will provide real-time data regarding the health of the inflatable shell or rigidized structures, and information related to the location and depth of impact damage. The innovation described here is a method of determining the size, location, and direction of damage in a multilayered structure. In the multi-dimensional damage detection system, layers of two-dimensional thin film detection layers are used to form a layered composite, with non-detection layers separating the detection layers. The non-detection layers may be either thicker or thinner than the detection layers. The thin-film damage detection layers are thin films of materials with a conductive grid or striped pattern. The conductive pattern may be applied by several methods, including printing, plating, sputtering, photolithography, and etching, and can include as many detection layers that are necessary for the structure construction or to afford the detection detail level required. The damage is detected using a detector or sensory system, which may include a time domain reflectometer, resistivity monitoring hardware, or other resistance-based systems. To begin, a layered composite consisting of thin-film damage detection layers separated by non-damage detection layers is fabricated. The damage detection layers are attached to a detector that provides details regarding the physical health of each detection layer individually. If damage occurs to any of the detection layers, a change in the electrical properties of the detection layers damaged occurs, and a response is generated. Real-time analysis of these responses will provide details regarding the depth, location, and size estimation of the damage. Multiple damages can be detected, and the extent (depth) of the damage can be used to generate prognostic information related to the expected lifetime of the layered composite system. The detection system can be fabricated very easily using off-the-shelf equipment, and the detection algorithms can be written and updated (as needed) to provide the level of detail needed based on the system being monitored. Connecting to the thin film detection layers is very easy as well. The truly unique feature of the system is its flexibility; the system can be designed to gather as much (or as little) information as the end user feels necessary. Individual detection layers can be turned on or off as necessary, and algorithms can be used to optimize performance. The system can be used to generate both diagnostic and prognostic information related to the health of layer composite structures, which will be essential if such systems are utilized for space exploration. The technology is also applicable to other in-situ health monitoring systems for structure integrity.

CATS Cloud-Aerosol Products and Near Real Time Capabilities

NASA Astrophysics Data System (ADS)

Nowottnick, E. P.; Yorks, J. E.; McGill, M. J.; Palm, S. P.; Hlavka, D. L.; Selmer, P. A.; Rodier, S. D.; Vaughan, M. A.

2016-12-01

The Cloud-Aerosol Transport System (CATS) is a backscatter lidar that is designed to demonstrate technologies in space for future Earth Science missions. CATS is located on the International Space Station (ISS), where it has been operating semi-continuously since February 2015. CATS provides observations of cloud and aerosol vertical profiles similar to CALIPSO, but with more comprehensive coverage of the tropics and mid-latitudes due to the ISS orbit properties. Additionally, the ISS orbit permits the study of diurnal variability of clouds and aerosols. CATS data has applications for identifying of cloud phase and aerosol types. Analysis of recent Level 2 data yield several biases in cloud and aerosol layer detection and identification, as well as retrievals of optical properties that will be improved for the next version to be released in late 2016. With data latency of less than 6 hours, CATS data is also being used for forecasting of volcanic plume transport, experimental data assimilation into aerosol transport models (GEOS-5, NAAPS), and field campaign flight planning (KORUS-AQ, ORACLES).

Geometric identification and damage detection of structural elements by terrestrial laser scanner

NASA Astrophysics Data System (ADS)

Hou, Tsung-Chin; Liu, Yu-Wei; Su, Yu-Min

2016-04-01

In recent years, three-dimensional (3D) terrestrial laser scanning technologies with higher precision and higher capability are developing rapidly. The growing maturity of laser scanning has gradually approached the required precision as those have been provided by traditional structural monitoring technologies. Together with widely available fast computation for massive point cloud data processing, 3D laser scanning can serve as an efficient structural monitoring alternative for civil engineering communities. Currently most research efforts have focused on integrating/calculating the measured multi-station point cloud data, as well as modeling/establishing the 3D meshes of the scanned objects. Very little attention has been spent on extracting the information related to health conditions and mechanical states of structures. In this study, an automated numerical approach that integrates various existing algorithms for geometric identification and damage detection of structural elements were established. Specifically, adaptive meshes were employed for classifying the point cloud data of the structural elements, and detecting the associated damages from the calculated eigenvalues in each area of the structural element. Furthermore, kd-tree was used to enhance the searching efficiency of plane fitting which were later used for identifying the boundaries of structural elements. The results of geometric identification were compared with M3C2 algorithm provided by CloudCompare, as well as validated by LVDT measurements of full-scale reinforced concrete beams tested in laboratory. It shows that 3D laser scanning, through the established processing approaches of the point cloud data, can offer a rapid, nondestructive, remote, and accurate solution for geometric identification and damage detection of structural elements.

A Case Study of Ship Track Formation in a Polluted Marine Boundary Layer.

NASA Astrophysics Data System (ADS)

Noone, Kevin J.; Johnson, Doug W.; Taylor, Jonathan P.; Ferek, Ronald J.; Garrett, Tim; Hobbs, Peter V.; Durkee, Philip A.; Nielsen, Kurt; Öström, Elisabeth; O'Dowd, Colin; Smith, Michael H.; Russell, Lynn M.; Flagan, Richard C.; Seinfeld, John H.; de Bock, Lieve; van Grieken, René E.; Hudson, James G.; Brooks, Ian;  Gasparovic, Richard F.;  Pockalny, Robert A.

2000-08-01

A case study of the effects of ship emissions on the microphysical, radiative, and chemical properties of polluted marine boundary layer clouds is presented. Two ship tracks are discussed in detail. In situ measurements of cloud drop size distributions, liquid water content, and cloud radiative properties, as well as aerosol size distributions (outside-cloud, interstitial, and cloud droplet residual particles) and aerosol chemistry, are presented. These are related to remotely sensed measurements of cloud radiative properties.The authors examine the processes behind ship track formation in a polluted marine boundary layer as an example of the effects of anthropogenic particulate pollution on the albedo of marine stratiform clouds.

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei--Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2010-01-01

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Seasonally Transported Aerosol Layers Over Southeast Atlantic are Closer to Underlying Clouds than Previously Reported

NASA Technical Reports Server (NTRS)

Rajapakshe, Chamara; Zhang, Zhibo; Yorks, John E.; Yu, Hongbin; Tan, Qian; Meyer, Kerry; Platnick, Steven; Winker, David M.

2017-01-01

From June to October, low-level clouds in the southeast (SE) Atlantic often underlie seasonal aerosol layers transported from African continent. Previously, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) 532 nm lidar observations have been used to estimate the relative vertical location of the above-cloud aerosols (ACA) to the underlying clouds. Here we show new observations from NASA's Cloud-Aerosol Transport System (CATS) lidar. Two seasons of CATS 1064 nm observations reveal that the bottom of the ACA layer is much lower than previously estimated based on CALIPSO 532 nm observations. For about 60% of CATS nighttime ACA scenes, the aerosol layer base is within 360 m distance to the top of the underlying cloud. Our results are important for future studies of the microphysical indirect and semidirect effects of ACA in the SE Atlantic region.

Particle Size of CO2 Condensates in Mars Atmosphere Revealed by Climate Sounder and Laser Ranging Observations

NASA Astrophysics Data System (ADS)

Hu, Renyu

Current-generation Mars Climate Sounder (MCS) onboard the Mars Reconnaissance Orbiter (MRO) offers extensive coverage of the latitudinal and seasonal distribution of CO_2 condensation in Mars’s atmosphere. The atmospheric temperature profiles measured by MCS reveal that the thickness of CO_2 condensation layer reaches a maximum of 10-15 km (north) or ˜20 km (south) during the middle of winter. There is a shrinking of the CO_2 condensation layer from L_S ˜270(°) to ˜300(°) in 2007, probably related to a planet-encircling dust storm. We integrate the condensation area and the condensation occurrence rate synthesized from the MCS observations to estimate cumulative masses of CO2 condensates deposited onto the northern and southern seasonal polar caps. The mass loading of CO_2 condensate particles, when condensation occurs, can be independently inferred from the detections of reflective clouds by the Mars Orbiter Laser Altimetry (MOLA) onboard the Mars Global Surveyor (MGS). Therefore, we approximate the precipitation flux by the particle settling flux, which is estimated using the impulse responses of MOLA filter channels. With our approach, the total atmospheric condensation mass can be estimated from these observational data sets, with average particle size as the only free parameter. By comparison with the seasonal polar cap masses inferred from the time-varying gravity of Mars, our estimates indicate that the average condensate particle radius is 8 - 22 mum in the northern hemisphere and 4 - 13 mum in the southern hemisphere. This multi-instrument data analysis provides new constraints on modeling the microphysics of CO_2 clouds on Mars.

Observations of temporal change of nighttime cloud cover from Himawari 8 and ground-based sky camera over Chiba, Japan

NASA Astrophysics Data System (ADS)

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

2017-12-01

Detection of nighttime cloud from Himawari 8 is implemented using the difference of digital numbers from bands 13 (10.4µm) and 7 (3.9µm). The digital number difference of -1.39x104 can be used as a threshold to separate clouds from clear sky conditions. To look at observations from the ground over Chiba, a digital camera (Canon Powershot A2300) is used to take images of the sky every 5 minutes at an exposure time of 5s at the Center for Environmental Remote Sensing, Chiba University. From these images, cloud cover values are obtained using threshold algorithm (Gacal, et al, 2016). Ten minute nighttime cloud cover values from these two datasets are compared and analyzed from 29 May to 05 June 2017 (20:00-03:00 JST). When compared with lidar data, the camera can detect thick high level clouds up to 10km. The results show that during clear sky conditions (02-03 June), both camera and satellite cloud cover values show 0% cloud cover. During cloudy conditions (05-06 June), the camera shows almost 100% cloud cover while satellite cloud cover values range from 60 to 100%. These low values can be attributed to the presence of low-level thin clouds ( 2km above the ground) as observed from National Institute for Environmental Studies lidar located inside Chiba University. This difference of cloud cover values shows that the camera can produce accurate cloud cover values of low level clouds that are sometimes not detected by satellites. The opposite occurs when high level clouds are present (01-02 June). Derived satellite cloud cover shows almost 100% during the whole night while ground-based camera shows cloud cover values that range from 10 to 100% during the same time interval. The fluctuating values can be attributed to the presence of thin clouds located at around 6km from the ground and the presence of low level clouds ( 1km). Since the camera relies on the reflected city lights, it is possible that the high level thin clouds are not observed by the camera but is observed by the satellite. Also, this condition constitutes layers of clouds that are not observed by each camera. The results of this study show that one instrument can be used to correct each other to provide better cloud cover values. These corrections is dependent on the height and thickness of the clouds. No correction is necessary when the sky is clear.

Modification of the Atmospheric Boundary Layer by a Small Island: Observations from Nauru

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

Matthews, Stuart; Hacker, Jorg M.; Cole, Jason N.

2007-03-01

Nauru, a small island in the tropical pacific, generates plumes of clouds that may grow to several hundred km length. This study uses observations to examine the mesoscale disturbance of the marine atmospheric boundary layer by the island that produces these cloud streets. Observations of the surface layer were made from two ships in the vicinity of Nauru and from instruments on the island. The structure of the atmospheric boundary layer over the island was investigated using aircraft flights. Cloud production over Nauru was examined using remote sensing instruments. During the day the island surface layer was warmer than themore » marine surface layer and wind speed was lower than over the ocean. Surface heating forced the growth of a thermal internal boundary layer, above which a street of cumulus clouds formed. The production of clouds resulted in reduced downwelling shortwave irradiance at the island surface. A plume of warm-dry air was observed over the island which extended 15 – 20 km downwind.« less

Cassini limb images of hazes in Saturn’s northern hemisphere

NASA Astrophysics Data System (ADS)

Sanchez-Lavega, Agustin M.; Garcia, Daniel; del Rio-Gaztelurrutia, Teresa; Garcia-Muñoz, Antonio; Perez-Hoyos, Santiago; Hueso, Ricardo

2017-10-01

We have used high resolution Cassini ISS images of the limb of Saturn to study the vertical distribution, altitude location, thickness and optical properties of the haze layers in the northern hemisphere (1°S to 82°N) in 2013 and 2015. The images cover an ample spectral range from the ultraviolet (UV1 filter, 264 nm) to the near infrared (CB3 filter, 938 nm) including methane absorption bands at 619 nm, 724 nm and 890 nm. Spatial resolution ranges from 1.6 to 13 km/pixel depending on wavelength and latitude. Three latitude bands were selected for the analysis according to the background zonal wind profile measured at cloud level and known dynamical activity: (a) North Polar Region encompassing the Hexagon latitude (74°N) (b) Mid-latitudes (45°N-52°N), and (3) Equator (1°N-3°S). The best defined haze structures and most extended haze layers were found at the latitude of the Hexagon. Up to 6-8 haze layers extending up to 400 km in altitude above clouds (in the pressure range from about 0.7 bar to 0.1 mbar) were detected. The vertical thickness of the layers is in the range 3-15 km compared to the scale height which is about 40 km. The spectral reflectivity is relatively uniform between the layers in the blue and red continuum wavelengths coming from the backward light scattering from the haze particles, while the brightness in the methane bands (relative to red continuum) and in the ultraviolet shows the effects of methane absorption and Rayleigh scattering by the gas, respectively. At mid-latitudes 3-4 haze layers are found spanning up to altitudes 200 km above the clouds. At the Equator 5-6 layers are found extending up to altitudes 250 km above the clouds (up to 2 mbar in pressure level) in a region of great dynamical interest because of the particular structure of the zonal winds and their known oscillations. We comment on the possible nature of the haze layers on the basis of condensing species and photochemistry.

APhoRISM FP7 project: the Multi-platform volcanic Ash Cloud Estimation (MACE) infrastructure

NASA Astrophysics Data System (ADS)

Merucci, Luca; Corradini, Stefano; Bignami, Christian; Stramondo, Salvatore

2014-05-01

APHORISM is an FP7 project that aims to develop innovative products to support the management and mitigation of the volcanic and the seismic crisis. Satellite and ground measurements will be managed in a novel manner to provide new and improved products in terms of accuracy and quality of information. The Multi-platform volcanic Ash Cloud Estimation (MACE) infrastructure will exploit the complementarity between geostationary, and polar satellite sensors and ground measurements to improve the ash detection and retrieval and to fully characterize the volcanic ash clouds from source to the atmosphere. The basic idea behind the proposed method consists to manage in a novel manner, the volcanic ash retrievals at the space-time scale of typical geostationary observations using both the polar satellite estimations and in-situ measurements. The typical ash thermal infrared (TIR) retrieval will be integrated by using a wider spectral range from visible (VIS) to microwave (MW) and the ash detection will be extended also in case of cloudy atmosphere or steam plumes. All the MACE ash products will be tested on three recent eruptions representative of different eruption styles in different clear or cloudy atmospheric conditions: Eyjafjallajokull (Iceland) 2010, Grimsvotn (Iceland) 2011 and Etna (Italy) 2011-2012. The MACE infrastructure will be suitable to be implemented in the next generation of ESA Sentinels satellite missions.

A Fast Infrared Radiative Transfer Model for Overlapping Clouds

NASA Technical Reports Server (NTRS)

Niu, Jianguo; Yang, Ping; Huang, Huang-Lung; Davies, James E.; Li, Jun; Baum, Bryan A.; Hu, Yong X.

2006-01-01

A fast infrared radiative transfer model (FIRTM2) appropriate for application to both single-layered and overlapping cloud situations is developed for simulating the outgoing infrared spectral radiance at the top of the atmosphere (TOA). In FIRTM2 a pre-computed library of cloud reflectance and transmittance values is employed to account for one or two cloud layers, whereas the background atmospheric optical thickness due to gaseous absorption can be computed from a clear-sky radiative transfer model. FIRTM2 is applicable to three atmospheric conditions: 1) clear-sky, 2) single-layered ice or water cloud, and 3) two simultaneous cloud layers in a column (e.g., ice cloud overlying water cloud). Moreover, FIRTM2 outputs the derivatives (i.e., Jacobians) of the TOA brightness temperature with respect to cloud optical thickness and effective particle size. Sensitivity analyses have been carried out to assess the performance of FIRTM2 for two spectral regions, namely the longwave (LW) band (587.3 - 1179.5/cm) and the short-to-medium wave (SMW) band (1180.1 - 2228.9/cm). The assessment is carried out in terms of brightness temperature differences (BTD) between FIRTM2 and the well-known discrete ordinates radiative transfer model (DISORT), henceforth referred to as BTD (F-D). The BTD (F-D) values for single-layered clouds are generally less than 0.8 K. For the case of two cloud layers (specifically ice cloud over water cloud), the BTD(F-D) values are also generally less than 0.8 K except for the SMW band for the case of a very high altitude (>15 km) cloud comprised of small ice particles. Note that for clear-sky atmospheres, FIRTM2 reduces to the clear-sky radiative transfer model that is incorporated into FIRTM2, and the errors in this case are essentially those of the clear-sky radiative transfer model.

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

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.

Vertical Structure of Ice Cloud Layers From CloudSat and CALIPSO Measurements and Comparison to NICAM Simulations

NASA Technical Reports Server (NTRS)

Ham, Seung-Hee; Sohn, Byung-Ju; Kato, Seiji; Satoh, Masaki

2013-01-01

The shape of the vertical profile of ice cloud layers is examined using 4 months of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) global measurements taken on January, April, July, and October 2007. Ice clouds are selected using temperature profiles when the cloud base is located above the 253K temperature level. The obtained ice water content (IWC), effective radius, or extinction coefficient profiles are normalized by their layer mean values and are expressed in the normalized vertical coordinate, which is defined as 0 and 1 at the cloud base and top heights, respectively. Both CloudSat and CALIPSO observations show that the maximum in the IWC and extinction profiles shifts toward the cloud bottom, as the cloud depth increases. In addition, clouds with a base reaching the surface in a high-latitude region show that the maximum peak of the IWC and extinction profiles occurs near the surface, which is presumably due to snow precipitation. CloudSat measurements show that the seasonal difference in normalized cloud vertical profiles is not significant, whereas the normalized cloud vertical profile significantly varies depending on the cloud type and the presence of precipitation. It is further examined if the 7 day Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulation results from 25 December 2006 to 1 January 2007 generate similar cloud profile shapes. NICAM IWC profiles also show maximum peaks near the cloud bottom for thick cloud layers and maximum peaks at the cloud bottom for low-level clouds near the surface. It is inferred that oversized snow particles in the NICAM cloud scheme produce a more vertically inhomogeneous IWC profile than observations due to quick sedimentation.

Topoclimatological and snowhydrological survey of Switzerland

NASA Technical Reports Server (NTRS)

Winiger, M. (Principal Investigator)

1979-01-01

The author has identified the following significant results. The chosen time of overflight of HCMM seems to be ideal for the study of basic climatological events. Nocturnal temperature inversion zones are easily detectable and their dependency on the relief is clearly seen. Especially the alpine valleys show a very differentiated pattern of cold lakes, separated by warmer zones as a consequence of rock and forrest barriers or changes in the valley profile. Wet areas are usually colder than dry parts under comparable topographic conditions. Even very small topographic obstacles are able to block up the flow of cold air masses (or ground water flow). Urban areas are clearly detectable. Differences to the surface temperatures of surrounding rural land are much more significant during day-time (mainly during the summer months). Fog layers are clearly defined in the visible channel (day-time), but much more difficult to identify in the IR (mainly during the night). There is not a fundamental difference to NOAA-analysis of cloud systems. The most important advantage is the better detectability of convective cloud systems (small cumulus clouds).

A High Resolution Hydrometer Phase Classifier Based on Analysis of Cloud Radar Doppler Spectra.

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

Luke,E.; Kollias, P.

2007-08-06

The lifecycle and radiative properties of clouds are highly sensitive to the phase of their hydrometeors (i.e., liquid or ice). Knowledge of cloud phase is essential for specifying the optical properties of clouds, or else, large errors can be introduced in the calculation of the cloud radiative fluxes. Current parameterizations of cloud water partition in liquid and ice based on temperature are characterized by large uncertainty (Curry et al., 1996; Hobbs and Rangno, 1998; Intriery et al., 2002). This is particularly important in high geographical latitudes and temperature ranges where both liquid droplets and ice crystal phases can exist (mixed-phasemore » cloud). The mixture of phases has a large effect on cloud radiative properties, and the parameterization of mixed-phase clouds has a large impact on climate simulations (e.g., Gregory and Morris, 1996). Furthermore, the presence of both ice and liquid affects the macroscopic properties of clouds, including their propensity to precipitate. Despite their importance, mixed-phase clouds are severely understudied compared to the arguably simpler single-phase clouds. In-situ measurements in mixed-phase clouds are hindered due to aircraft icing, difficulties distinguishing hydrometeor phase, and discrepancies in methods for deriving physical quantities (Wendisch et al. 1996, Lawson et al. 2001). Satellite-based retrievals of cloud phase in high latitudes are often hindered by the highly reflecting ice-covered ground and persistent temperature inversions. From the ground, the retrieval of mixed-phase cloud properties has been the subject of extensive research over the past 20 years using polarization lidars (e.g., Sassen et al. 1990), dual radar wavelengths (e.g., Gosset and Sauvageot 1992; Sekelsky and McIntosh, 1996), and recently radar Doppler spectra (Shupe et al. 2004). Millimeter-wavelength radars have substantially improved our ability to observe non-precipitating clouds (Kollias et al., 2007) due to their excellent sensitivity that enables the detection of thin cloud layers and their ability to penetrate several non-precipitating cloud layers. However, in mixed-phase clouds conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to identify the cloud phase. This limits our ability to identify the spatial distribution of cloud phase and our ability to identify the conditions under which mixed-phase clouds form.« less

An experimental study of the role of particle diffusive convection on the residence time of volcanic ash clouds

NASA Astrophysics Data System (ADS)

Deal, E.; Carazzo, G.; Jellinek, M.

2013-12-01

The longevity of volcanic ash clouds generated by explosive volcanic plumes is difficult to predict. Diffusive convective instabilities leading to the production of internal layering are known to affect the stability and longevity of these clouds, but the detailed mechanisms controlling particle dynamics and sedimentation are poorly understood. We present results from a series of analog experiments reproducing diffusive convection in a 2D (Hele-Shaw) geometry, which allow us to constrain conditions for layer formation, sedimentation regime and cloud residence time as a function of only the source conditions. We inject a turbulent particle-laden jet sideways into a tank containing a basal layer of salt water and an upper layer of fresh water, which ultimately spreads as a gravity current. After the injection is stopped, particles in suspension settle through the cloud to form particle boundary layers (PBL) at the cloud base. We vary the initial particle concentration of the plume and the injection velocity over a wide range of conditions to identify and characterize distinct regimes of sedimentation. Our experiments show that convective instabilities driven as a result of differing diffusivities of salt and particles lead to periodic layering over a wide range of conditions expected in nature. The flux of particles from layered clouds and the thicknesses of the layers are understood using classical theory for double diffusive convection adjusted for the hydrodynamic diffusion of particles. Although diffusive convection increases sedimentation rates for the smallest particles (<30 μm) its overall effect is to extend the cloud residence time to several hours by maintaining larger particles in suspension within the layers, which is several orders of magnitude longer than expected when considering individual settling rates.

A modeling study of marine boundary layer clouds

NASA Technical Reports Server (NTRS)

Wang, Shouping; Fitzjarrald, Daniel E.

1993-01-01

Marine boundary layer (MBL) clouds are important components of the earth's climate system. These clouds drastically reduce the amount of solar radiation absorbed by the earth, but have little effect on the emitted infrared radiation on top of the atmosphere. In addition, these clouds are intimately involved in regulating boundary layer turbulent fluxes. For these reasons, it is important that general circulation models used for climate studies must realistically simulate the global distribution of the MBL. While the importance of these cloud systems is well recognized, many physical processes involved in these clouds are poorly understood and their representation in large-scale models remains an unresolved problem. The present research aims at the development and improvement of the parameterization of these cloud systems and an understanding of physical processes involved. This goal is addressed in two ways. One is to use regional modeling approach to validate and evaluate two-layer marine boundary layer models using satellite and ground-truth observations; the other is to combine this simple model with a high-order turbulence closure model to study the transition processes from stratocumulus to shallow cumulus clouds. Progress made in this effort is presented.

Evaluating stratiform cloud base charge remotely

NASA Astrophysics Data System (ADS)

Harrison, R. Giles; Nicoll, Keri A.; Aplin, Karen L.

2017-06-01

Stratiform clouds acquire charge at their upper and lower horizontal boundaries due to vertical current flow in the global electric circuit. Cloud charge is expected to influence microphysical processes, but understanding is restricted by the infrequent in situ measurements available. For stratiform cloud bases below 1 km in altitude, the cloud base charge modifies the surface electric field beneath, allowing a new method of remote determination. Combining continuous cloud height data during 2015-2016 from a laser ceilometer with electric field mill data, cloud base charge is derived using a horizontal charged disk model. The median daily cloud base charge density found was -0.86 nC m-2 from 43 days' data. This is consistent with a uniformly charged region 40 m thick at the cloud base, now confirming that negative cloud base charge is a common feature of terrestrial layer clouds. This technique can also be applied to planetary atmospheres and volcanic plumes.